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Inference Isn’t Just the Data (Notes from Sep 2 to Sep 8, 2019) October 14, 2019

Posted by Anthony in Automation, Blockchain, Digital, experience, finance, Founders, global, Leadership, marketing, questions, social, Strategy, Uncategorized.
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Internet has enabled more data, but that’s not necessarily a good thing for most. I’ve seen this for all ages – somehow, this deluge of information provides a glut where, instead of doing more research (because more is available), we seem to do less. There’s a laziness that has arisen, where the least amount of work is done because the sources are abundant. And this is problematic. And emblematic for what has transpired over the last decade with the web 2.0.

I say that it is problematic, but I do suspect it’s actually created a ton of wealth. The opportunity of doing a small amount of extra effort to sift through or provide a more nuanced/researched view in order to extract a ton more value from a wider audience is awesome. That’s never before been more evident or available to a wider group of individuals. Especially when, with nearly the world online, communities that would normally (past) not have had markets, all of a sudden have vast reach – internet enabled the connection across many neighborhoods/cities/regions/countries/continents. A magical thing for those that wish to do the research, put in a bit more work, and most importantly here, share the work for the public, at the cost of potential exposure to those that disagree or have reached a different conclusion.

I, for one, am all for this abundance. A sharing of differing opinions and agreement or stories of anecdotes allow us to bring more data into the fold. That should enhance any inference/analysis on the information brought to the table – and real applications, at that. However, like many good things, there will be a small portion of people that are bad actors or looking to just ruin the good derived from a community or topic. Also, may see plagiarism or curation that doesn’t really add anything – worse, monetizing the curation of something where the value isn’t created. For 100 people, 1 bad actor would still be 99% good. 99.9% of 10,000 people is 10 bad. That’s a fair amount, but when you have a commonality among the people where some join for the purpose of providing poor information, or unproductive data or ruin the experience for the rest, it can tear it apart. And that’s becoming harder to gauge, I’d imagine (rise of community managers and insertion of social data and other related ‘checks’ inserted).

So that I can get off this little soapbox, I wanted to bring attention to those that have so far only consumed information – please share and try to bring some new insights. It will hopefully bring in a new person that sees it – refreshing eyes can be useful on new information- we all have different experiences. And for the bad actors, hopefully there’s an end goal that does provide some value – it’s tough early on but the right communities invite opposing views to allow others to draw conclusions. Inferences aren’t merely opinion on the shallowest, easiest data to gather, but rather a collection and reflection on a set that may agree or collectively provide information to allow a deeper understanding.

Enjoy the notes I had from this week! I do suggest going through the a16z podcast 16Min on the News (for news from the week).

  • Apple Card, BEC Scams Fed (16 Minutes on the News #7, 8/25/19)
    • Became available this week – partnering with Goldman Sachs and Mastercard coated white and titanium
      • Apple moving into financial services, no typical sign-up fees or late / overdraft fees
    • Apple as reinventing existing categories repeatedly, so even changing basic stuff like making the transparency feature
      • Reminder of SMS and Innovator’s Dilemma (making money in core with new business on horizon because you’d cannibalize yourself to enter)
      • B2b2c as incentivized to grow – GS not a big consumer lending (Marcus last 2 years), but can drive growth
    • Offering 3% cash back when purchasing from Apple, 2% with Apple Pay, 1% from card – incentivizing payment mechanism
      • Interchange fee is expensive but if they become default payment mechanism, they can pivot
      • Money as emotionally driven vs functional and product – making sense in rational isn’t the move
      • Nobody wants to budget just as nobody wants to diet – instead, automate small financial decisions to help achieve better outcome
        • Self-driving money: not having to make the decisions to optimize your financial life (too high friction or don’t know about them)
    • GS with $350 to acquire customers – traditionally, credit cards have been onerous
      • Future: everyone should have access to payments via unsecuritized debt without great credit
        • People that are creditworthy with great credit scores but those that never pay bills and have bad credit
        • Overly negative in a different sense (ones that are almost wealthy that end up getting in trouble)
    • BEC scams – business email compromise
      • More than doubling each year – big deal on security
      • Sending email messages to send money – better technical systems are now just asking individuals (social eng as most effective form)
  • Ben Lorica, Chief Data Scientist at O’Reilly (Big Data Beard 8/13/19)
    268x0w

    • Future of Big Data with O’Reilly’s
    • Would take handle “5g” or something related for the future
    • Collecting, aggregating and normalizing big data now – business intelligence reports, simple averages or trends
      • What else can we do? Improve or automate processes/workflows or extract higher revenue from systems
      • Natural evolution and what are the bottlenecks for the AI / ML processes (are you early stages, models in production?)
    • Quintessential marketing for hype but developing a use case for the application
      • Tools for labeling data, data programming
      • Mentioned how to do ML with demo and user cases for interacting by Product Managers – SF O’Reilly conf
    • RPA with proper use case and proper implementation (close to the task)
      • Successful organizations have figured out how to bridge that gap – technologists with communication/collab on business side
    • On open source side, TensorFlow and PyTorch as top 2
      • Data science side – announcements about internal data science platforms to work together (share pipelines / features / models) openly
      • DataBricks, one company that he advises, also works on delivering enterprise data science platforms – IBM, cloud vendors
    • MLFlow as DataBricks’ for managing and tracking ML development life cycle
      • Monitoring alerts for retrain model, feature drift, deploy model against live data (simulating on live data but not production)
      • Model governance as tools that excite him – highly regulated industries like banking, financial services – what models and metadata
        • When was it last touched, trained, on what data, etc…
    • Managed services based on open source – managed Spark, for instance – minimal log in
      • If I have a better model but worse data, the better data should win, and that’s what drives competitive advantage
    • Big push toward hardware space – training at the edge or even model training in general – specialized hardware for accelerating DL / ML
      • More researchers working on data cleaning and data repair
      • Snorkl from Stanford researchers – easier for more people to use the product
      • Reinforcement learning – he’s most interested in UC Berkeley’s RISE Club’s REY (sp?) – distributed computation platform in C++ low latency
        • Building on top of REY as Odin – can cover 80% of Pandas, faster and other libraries
  • Frank, Chief Business Officer at Edge Sports/Analytics (Wharton XM)
  • Becky Miller, co-founder & CEO at Tinyhood (Wharton XM)
    858aeebd82f3bb14afd339eda1db

    • Wanting to connect with other supermoms and doing a community
    • Deciding to do parenting classes online and helping subscriptions
  • Josh Phifer, co-founder at Barn Owl (Wharton XM)
    barn20owl2020rgb20_stagexchange_intro20pic

    • From Wyoming / Nebraska ranching, went to Wharton
    • Starting with water sensors but wasn’t quite working or gaining traction, thought drones would work initially
    • Pivoting as they were running out of money to find a product – camera with satellite / cell connection from China sourcing
      • Bootstrapping about $175k from friends and family
    • Camera use case – all kinds of agriculture applications for checking – can send picture via app, timed or on certain amount of times
      • Solar and battery powered
    • Obsession over the problem, not marriage to a solution – feed the need
    • Initial app created with Bubble.io, introduced at Wharton – low code solution with logic programming
      • Hired on an employee – electrical systems who could help with building out full app and logistics
  • Mark Nathan, CEO of Zapari (Mastering Innovation / Wharton XM)
    • Discussion of moving from engineering, building stuff to the medicine / insurance field
    • Not necessarily working on analytics, but collecting and informing consumers and other stakeholders
    • Doesn’t foresee regulation as a hindrance, since what they’re doing isn’t predicated on that
    • Primarily started with SoCal, Medicare and getting adoption from pharmacies – assisting nurses on customer service end with their call center, ex
      • Not set up to deal with pharmacists or customers, can alleviate this and help with people fulfilling prescriptions
  • JD Long, VP of Risk Management for Renaissance Reinsurance (Data Framed #37, 8/27/18)
    renaissancere-grey

    • Starting in R stackoverflow asking questions / answers and building the community with Mark Driscoll
    • Graduated in undergrad, starting masters and asked where PhD’s were going (of Agri Econ): answers AMEX
      • Due to SAS and mainframes, UNIX, R-Cran hadn’t started
      • AMEX was explicitly recruiting in 1996 for these economists because of modeling, coding messy data, crop insurance, regression (econometrics)
    • History of cultural agricultural yields, weather and prices from before 1996 – which was agricultural crop insurance start
    • Simulate and stochastically getting a bunch of results that give you an idea of the distribution of the model
      • He does very little predicting of what may happen next year – looks at shape of distribution for the following year
      • Looking at improbable 1 in 1000 results that may be possible in that distribution
      • Book: “How to Measure Anything” – what’s the highest and lowest estimate
    • Risk vs uncertainty: Risk is understanding underlying distribution but not sure what you’ll get; Uncertainty is not knowing the distribution
      • Flipping a coin has risk – can model the probabilities if you know the coin, but uncertainty would be not knowing if the coin is loaded / biased
      • Auto insurance is type of product that is mostly risk, less uncertainty – predictable patterns, historical distributions and tail events
        • Terror events – historical categorization of events but no reason to see world events as drawing from the distribution of that
          • Unstable random geopolitical events, component of risk vs higher uncertainty
    • Reinsurance with risks that can be correlated based on underlying physical relationships, such as homeowners insurance in NYC should be correlated
      • Hurricane Sandy would be something that hits everything there
      • P&C companies with casualty claim could be connected among multiple companies
      • Legal change in framework could cause claims to increase 15% – have to understand the correlation when aggregating data
      • 2 distributions can be added or correlations using copula – artifact of some other process
        • Model data should be containing it already but this is only way to insert
    • In 3000 BCE, Babylonians had disaster contingency – loans didn’t have to be repaid if losses happened for certain events
      • Edmond Haley (Haley’s comet) created modern-style mortality table in 1693
      • Lloyd’s coffee house emerged for shipping news and buy shipping insurance (turned into Lloyds of London – marketplace now)
      • 1992 – Hurricane Andrew recharged after ripping Florida and hit Alabama and Louisiana – big catastrophe for reinsurance companies
        • Hurricane reinsurance was a gentlemen’s game – big contraction of market after Andrew, filled by crop of reinsurers in Bermuda
        • Became a quantitative analysis market after this – turning point of reinsurance, reasonable proximity for US and capital-free
    • Heuristics that make certain assumptions for the modeling of both finance, insurance
      • More effective models for sharing and coming together with actuaries, risks and methodology
      • Data science examples, actuaries methodology that would be working together (GLM combined with understanding on actuary side)
    • If asker of question made it easier on the question answerer (on example for Stack Overflow)
      • Incomplete code or maybe not syntactically right so the answerer cannot answer it properly
      • Empathy for the receivers of your opinion or problem or otherwise
      • If doing analysis to equip underwriter for a deal – what information does the underwriter need to be well-equipped for negotiating their deal
        • Influences and drives thinking of how to serve that analysis / information
    • “Hacking empathy”: from Agile development method would be User Stories
      • Hugo is a data scientist who is trying to understand X. He needs this tool to do Y so he can understand X.
        • Forces the person to do this to think about that user or other person
        • Think about who is consuming it to give nudges or reminding someone – doesn’t think that way
      • At DataCamp, how active or users or learning profiles that they are aimed at
        • Designing for average, you design for no one from podcast “99% Invisible”
        • Give target audience a name to relate to them; multidimensional space for ‘tyranny of mean’
          • If you have 3 dimensions of human body (leg length, height, hand size, arm length, etc..)
            any 3 with a small margin of error will be merely 6% of pop
    • Where is market opportunity? Met with a headhunter in space.
      • Deep learning and AI for media and ink spill – interesting and have potential for revolutionary changes.
      • Former guest Jenny Bryan who talked of attempting to get people out of Excel – massive movement there, he believes
    • If we don’t ask “Does our analysis change the outcome?”, we can do infinite analysis since it’s all that we don’t know
      • Never drive organization. Leaders should have candid conversations about if the research is going to change the answer of the decisions.
        • If it’s a no – why put resources toward it?
        • What’s the next best simplest alternative? Not comparing to doing nothing.
          • Deploying a complicated model should be compared to old forecasting method or cheaper, faster one. Is the added complexity worth it?
      • Hugo tells them to deploy basic baseline model, do 20 min of EDA and try to make own prediction. Then test the models against that.
        • In public policy, effectiveness isn’t against doing nothing, it’s the next best. Benchmarks are too often done at base.
        • “Plot your damn data”
  • Matt Lieber, cofounder & President of Gimlet Media (20min VC FF030 1/15/16)
    gimlet-and-spotify

    • Produced radio shows Fair Game and On Point, worked as a management consultant at BCG
    • Radio producer was his lifelong dream after being a radio head growing up
    • Met Alex Bloomberg after his MBA and consulting, who is the cofounder – left to go learn business side
      • Distribution to big audience, too many gatekeepers, market-by-market he had to go to program directors to pick up the show
      • Exciting thing, creative, ambitious work was happening there
    • Constraint breeding creativity – raising a series A
      • Had launched 3 or 4 shows in first year, scaling to some audiences and had worked
      • Revenue from start, ads in the beginning – VCs didn’t want to hear about those
      • Believed they could self-fund through profits, growth with revenues – don’t need to dilute, maintain control
        • Would need to build up the company after building some shows
    • Keeping small culture – fairly strong but not explicitly communicating it yet
      • Behavior of leadership and design of signs – started Gimlet Guides around 25 employees for onboarding
        • Gimlet Guides are the mentors for establishing new employee onboarding – lunch once a month, questions
    • Wanted to get a partner for VC who was aligned with the vision, experience investing in media for different return timelines and dynamics
      • Sea of change of how a whole generation will consume radio and shows
      • Simplest, direct way for market – size of radio ($18bn+ in US in advertising alone) – digital for mobile media market
        • Consumption shifting to mobile – advertisement doesn’t work (Gimlet is ~80% mobile)
    • Deciding how to make new shows? Question from someone
      • Mentioned “Surprisingly Awesome” – people want to be entertained and learn something, recent ep was interest rates and economy
      • Teamed up with Adam McKay and Adam Davidson for it
      • Learning, listen and come away with some understanding, a host to connect with and is there a narrative
    • Mystery Show, Reply All, Startup and Surprisingly Awesome are all the biggest shows
    • Favorite book: Great Plains by Ian Frasier, didn’t have an emulator
    • Challenging aspect of creating it: scaling editorial where you create a system to grow and teach editorial material
    • Most excited about the next shows – this case, a podcast about podcasts called Sampler
    • Best advice: Be nice.
  • Abhinav Asthana, Founder of Postman (Wharton XM)
    postman

    • Talking about why he loved building more than what he had done previously
    • Community for that
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Fostering a Community (Notes from Aug 26 – Sep 1, 2019) September 23, 2019

Posted by Anthony in Blockchain, Digital, experience, finance, Founders, global, Hiring, Leadership, questions, social, Strategy, training, Uncategorized, WomenInWork.
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What a crazy couple of weeks! And it’s not likely to slow – I’ll give some more information behind that very shortly. Exciting new things on the horizon, though – and ones I’ll be proud to announce when I can. August provided a lot of clarity in direction – good because it wasn’t exactly restful.

I mentioned it in last week’s post, as well, but I’ve been hyper-aware of the people around me interacting, enjoying and laughing over commonalities. It’s at every level, though I peruse coffee shops far more often than other places. Interesting stories are almost expected. If you refer to my reading list, you’ll notice a new one, Dignity. As part of a book club, I was hesitant and unsure when it took the lead because of the topic – primarily drugs/poverty/downtrodden/unlucky collection as reported, but halfway through I’ve been pleasantly surprised at how much perspective Chris provides. I can’t help but draw that fixture of everyone has their own experiences that provide the lens through which we draw conclusions on everything else. Endless and it’s very tough to remove ourselves or step back – especially with things we’re unfamiliar with.

Ultimately, though, everyone wants to share their experiences with others – whether it’s some depth of despair, depression or building a community, religion, or hiring employees to work with or spending time for fun and adventure. We’re human. We spend time with other humans. There’s a reason we’ve survived this long in groups and why the solo artists end up in peril – this is completely generalized but in MY experience, I’d say I see a truth in this.

Kate Shillo, Director at Galvanize, mentioned her journey for Martha Stewart’s media company to Galvanize where they help businesses grow with their people. Morgan Dunbar, at Bendigo Partners, discussed his involvement in AIR – summit and conference for sharing ideas/businesses for financial services to hopefully rise all boats, as they say. Mike Vernal, at Sequoia Capital, went through how Facebook’s earlier years helped him with approaching problems and the finality of decisions – what they’ve fostered for the boards he is now a member of. He tries to understand the start-up and the founders view of the problem after a quick determination of if they know the idea enough. Others, which I only caught pieces of, had similar views.

I hope your community, whatever that may be, is productive and positive – helping you gain what you’d prefer from it.

  • Kate Shillo (@kshillo), Director at Galvanize Ventures (20min VC 1/13/16)
    gavalize-logo

    • Investing in hardware and future of IoT
    • Got an interview with Martha Stewart’s Omni Media and she was temping for her – living in NYC 2007
      • Would have an idea in her company – create, build & continue w/ mini incubators
      • She wishes Marthapedia was made – hasn’t done it yet
    • Wasn’t quite stimulated enough in 2007, she quit and bought a surfboard – 6 months later she was back in NYC
      • Had met Kenny Lerer (around in interviews) – met before Martha with an internet newspaper (Huff Post)
      • Took a huge pay cut to do some research on other startups as Kenny was on the chair for Huffington Post (~30 employees)
        • He was chair at Betaworks at that time, too
      • She was the human tester for Betaworks (only other one to test)
      • Helped launch Ken Lerer Ventures (Lerer Hippeau Ventures) as formalizing process for his angel investing
    • Help of having Huffington Post (sold in 2011) as starting propelled them into NYC market – unheard of at the time
      • Market down, nobody investing in seed – writing small checks at Lerer “Go by Betaworks and Lerer Ventures is there”
      • First content investment was Food 52
      • Consumer tech pics – paperless post, Warby Parker, Bottle Bar, BarkBox
    • Galvanize (continuous learning – helping businesses and their business grow – new archetype in higher ed)
      • Galvanize Ventures with 3 partners – all of elements to provide their startups
      • Early stage – small, idea from pre-seed to series A (seed process), reserving for follow-ons
      • Small markets like ATX, PHX, SLC to get in – coaching co’s along the way
    • 48 investments in 2 years
      • Consumer mobile-heavy so far, her excitement in hardware – starting in 2014 was IoT hotbed
    • Crowdfunding as a bit of advertising, validating customer interaction and capital as gravy – her opinion
      • Shipping product is usually a hurdle – many people don’t want to invest without seeing this
      • Reflecting on Lerer investments – seeing market share of her old portfolio companies
    • Size of fund is $10.2 mln, $100k checks for pre-seed, seed and series A – get priced out for series A
    • Favorite book: God of Small Things, misconception for VC: that it’s easy (no control for company sometimes but exciting when it works)
      • Sourcing vs existing portfolio co’s helping
    • Favorite apps: Moment app, Twodots (betaworks), Slash, Sunrise calendar, Pant, Wildcard and Venmo at the time
    • Recent investment: msg.ai empowering brands for messaging platforms ecommerce
  • Morgan Dunbar, partner at Bendigo Partners (FYI 8/5/19)
    86aeb71777442ba0eadc52ed226d20ee

    • Capital Market Space within FinTech as principal investors
    • Was mostly on sell-side for analytics on portfolio construction – with Citi Group in Tokyo in 2009 running Japanese equities
    • Bendigo – early stage fintech companies with bias on capital markets, retail, middle and back office
      • Advisor practice with institutional, private equity, large enterprise in capital marketers
      • Transaction advisory, operational consulting and strategy around fintech ecosystem
    • Bill Stevenson partner on AIR Summit – 2013 creation for invitation-only for senior buy/sell-side pros to discuss high-level themes
      • Alpha Innovation Required (AIR) – invite ~20 emerging fintech cos to speak to a use case for front office (alpha generative)
    • Traditional VCs have a fundamental lack of operational understanding in capital markets
      • Secondly, long sales cycle in businesses – thousands at enterprise level vs millions in consumer
      • Regulatory that can be scary without expertise
    • Artificial Intelligence as just replicating a process (as opposed to intelligent)
      • AIR focusing on people, organization, talent and cultural alpha
      • Tradition, trust, not new – center for innovation and trying to do something, be empowered for innovation and development
    • Google pushing into asset management other than cloud, data and analytics
      • Asset managers may start looking at Google like Bloomberg – help build portfolios, vendors to tap for alpha
    • If buy-side problem, then sell-side has a problem, fee compression (growth of passive) – active vs passive (value for performance)
      • Robos (whether or not they’re worth valuations) validated demographics looking for low-cost access with simple UI and intuitive
  • Mike Vernal (@mvernal), Partner at Sequoia Capital (20min VC 8/26/19)
    sequoia

    • Citizen, rideOS, Rockset, Threads & Houseparty board
    • Spent 8 years at Facebook as VP of Product
    • Sequoia – Brian, led A to join board for his roommate’s company and his former PM at Microsoft started a co in 2009 and Brian joined
      • Joined Scouts program early on
      • Had first child a week prior to 8 years at Facebook, took paternity leave to reflect
    • Really enjoyed Facebook first few years – tremendous energy and optimism to create something from nothing
      • Early stage founders in a garage for idealism and irrational energy, switched to Sequoia (been there 3 years)
    • Entrepreneurs that can explain entirety of business in 3-5 min, rest of meeting is the details of the pitch
      • Feedback cycle for great and enduring company – decision-making is a short or longer memo and reading through them
      • For his mistakes, thinking and writing and playing out future – each case was instinctually being interested but not trusting instincts
        • Try to be rational and analysis-driven
      • More importantly, internal conviction on a company, founding team and working on
      • If not at Sequoia, would he go work for that company?
    • Terminal and non-terminal decisions – once you’ve made it, you can’t make it again
      • Do something, if wrong, do it again – try to hire, realize mistake, hire again
        • Pick one, roll out to some, figure if it’s working or not, and iterating
      • Venture – most important is decisions – if you pass a round, you’re done maybe until next round
      • In operations, tempo and learning for decision-making
    • Bundling vs Unbundling – past 10 years will be unbundling of SaaS and best in breed
      • SaaS that are more niche – features as something larger, $1 or $2 / ee / mo
      • Thinks there will be a consolidation of the apps, incumbents that will integrate and put them all-in-one (Notion)
      • Meta-SaaS apps that will put them together as the market matures
      • SaaS as software, business software (maybe banks that are on-premise)
    • Book: 100 years of Solitude, almost every startup underprices their product
    • Time management is the challenge – constant battle, reading quickly and get the ones he finds most interesting
    • Verkada as most recent investment – can build a great experience
  • Kash Mathur (@kashmathur), COO of Chewse (Wharton XM)
    chewse-open-graph-e1559782200236

    • Tracy and cofounders starting it in LA originally, in 2011 before bringing it to SF for 500 Startups
    • Attracting Kash in 2016 as they were figuring out SF before relaunching LA
    • Corporate culture, enterprise dealing and owning the customer service – blended marketplace
      • Starting each executive, strategy board with a “One thing most people don’t know about me is…”
      • Connecting between people
    • Why they have connected Hosts for each enterprise – owning the location, service and whole process
      • Important value and differentiator from other catering companies
  • Linda Crawford, CEO of Helpshift (Wharton XM)
    helpshift-logo

    • Being named top 50 SaaS CEO of 2018, joining HelpShift after Salesforce
    • CCO (customer) at Optimizely, as well as Board Member at Demandwise
  • Rob Farmer, Independent Advisor Study and assets at Schwab (Wharton XM)
    • Talking about participants and customers

Your Experience is Your Own, Only (Notes from Aug 19 to Aug 25, 2019) September 10, 2019

Posted by Anthony in Automation, Blockchain, Digital, experience, finance, Founders, global, gym, Hiring, Leadership, marketing, NLP, social, Strategy, training, Uncategorized, WomenInWork.
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I’ve been considering more and more about how my experiences are only mine. Especially when I feel like I don’t share them often. Working so much but not always discussing it with people outside of work (re: almost never). I was reminded of this while I met with a family member who I see roughly once a month or so. When she asks how work is or I mention I’m busy on days when she wants to meet, it often came with a “busy with a meeting at X but can do Y”. Never more. And almost always, I ask how her work is, and she divulges. So when we sat down for dinner and she point blank asked “I have 2 things: 1. Can you help me with something on my new phone? and 2. What is it actually that you do?” I chuckled because generally I don’t care to share that information – I really enjoy valuing start-ups and learning about the space / tech / finance / education changes, but other than high level stuff, rarely does anyone want to hear me talk extensively a la a podcast episode deep-dive or something. They don’t see the relevance, other than it being exciting for me. Same with when I was advising, same since launching the fund and all while working on project deployment in data science for others.

I strongly suggest reading through Colson Whitehead’s essay here about his version of New York City. How it’s interpreted. essay here

Another thing I read through today was Farnam Street’s blog post on asking seemingly simple questions that may be defined or determined by our experiences with those concepts. An example he uses: “What is a horse?” Try to think how we may answer this.
Power questions

 

  • AI in the Past, Present and Future (BDB 7/16/19)
    teradata-logo-social

    • Rod Bodkin, Tech Director at CTOs office in Google
      • Was with BigDataAnalytics, bought by Teradata and grew it from there
    • Grew Google after seeing the field advancing quickly, state of the art as evolving
    • First people to put Hadoop into production – Yahoo was too scared, single algorithm took weeks at the time
    • OpenAI put out state of art compute paper – 4 year paper, 300k X computation (double every 3.5 months)
    • For Google, evolution of cloud in the enterprise is a big deal – consumer side of Google as leading the way
      • Can just put data into BigQuery because of capacity and accessibility of data – increased production 4x on data science team
    • Big investments into Anthos – open source tech to enable cloud-native services in different clouds, GKE (Kubernetes)
      • Edge TPUs as 100x faster to compute a model vs traditional mobile CPU – TPU as accelerator chip for DL
      • CPU is completely general so less efficient
      • GPU has a boost over CPU but behind TPU accelerators (starting GPU chips, Tensor unit)
    • Kaggle Days and Google IO for cloud Pixel modeling and AutoML performing very well
    • Herrari’s book – 21 Problems for 21st Century
  • Tricia Han, CEO of Daily Burn (Wharton XM)
    51w1ctcdszl._sy355_

    • Community of like-minded fitness fanatics
    • Live 365 – 30min shows on working out, regulars
    • In survey, millenials said fitness #1 and health/wellness at #5
    • Fitness had about happiness equal to making $25k more

 

 

 

  • State and Future of Robotics, ML and Digital Celebs (Venture Stories, 8/8/19)
    ht6qfyjc_400x400

    • Michael Dempsey (@mhdempsey) – partner at Compound
    • Read, Listen, Write, Talk – Cunningham’s Law – share something with a strong opinion is likely to get responses
      • More value when shared publicly
    • Robotics, ML as cascading forward – robots broadly, initially – types, how to make them intelligent (2013)
      • Drones, hardware platform (DJI as leader), space and now as unsupervised or self-supervised learning
      • Deep dive on innovation for what he’s spent the last year or two – investments, as well
    • Women’s health as growing market for fertility and experience layer in healthcare system
      • Higher-end service around egg freezing (but was shattered by Tia founders), IVF or embryo screening
      • 2 investments for him already in the space, maybe more after
    • Strategic robot acquisition for Amazon, why now? Major companies in the space – he’s punted in that space, more investors.
      • Didn’t see meaningful differentiation in the space – didn’t see a company that had that from an investing side
      • Food was where he saw robotics as consistent – grew up in the industry
      • Really easy to get pilots but not for revenue – wants full-stack robotics company
      • Robots taking over entire industry – automated X / Y / Z (rebar, construction robotics)
      • Front of house and back of house retail (analytics, stocking)
    • Weird robot applications (in-home, manicures, old person help)
    • If company is built on algorithm being best, company probably won’t survive
      • Must talk to people doing operating – not just reading
      • Self-driving cars – spent time with Daniel Gruber, discussing local maximum and rules to write
        • If you can drive in NY, you can drive in SF, LA, etc…. 2007 DARPA challenge Waymo / Tesla / Cruise as result – path-planning
        • Intelligence approach – what are incentives / agents to accomplish in a car for end-to-end approach to scale
      • 1 model to move them all – enough compute that model can solve it (DL is direct function of this, for Google)
    • Investment in data labeling space – more people moving into production requires more people getting good data and filtering data
      • Larger data builds where it may cause $50-200mln per year to label but 50% is useless
      • Environmental impact and thinking about it – consolidating data but into better (CartaAI and SkillAI)
    • DeepGram end-to-end audio inscription – 80-85% can be good, but if you mess up some key words in certain industries, it’s more expensive
      • Voice side, horizontal players are pretty good – if x% of users will have same questions, simple workflow or algorithms
    • GANs and new generation of faces – Disney and animation nerd for a while – power of IP on agencies, CAA for example and Marvel
      • Stories through animated content, Robot Chicken, others – Robert Dillon – bringing in GANs
      • Watching live action is watching someone else’s story whereas an animated one brings you into the story
    • Trusting the people that have been given permissions – Reddit or being anonymous
  • John Roese, Global CTO of Dell EMC (Mastering Innovation, Wharton XM)
    dellemc2

    • Talking about the 20 year vision to be autonomous but incremental parts until then
      • Driving assist, improved AI in driving, maybe geofenced before autonomous
      • Autonomous vehicles as source of innovation – sensors / LiDar very useful for other industries but too expensive
        • Had talked to studios about virtual studios or conferences – expense should come down with auto
      • Vast problems with uncontrolled or unconstrained problems – already have fully autonomous warehouses or geofenced areas
    • Interested in bio feedback as input to AI or MI systems
      • Used example of video conferences with sensing stress levels – clearer audio, accent correction, more people = more stress
      • Cars already using bio feedback
      • People already wearing sensors via devices – can use that as more input
    • Attacking low hanging fruit because of data ethics or biased data inputs – easier to solve problems that are valuable in neatly constrained
  • Amri Kibbler, Katya Libin, Hey Mama co-founders (Wharton XM)
    • Collaborate and share and support their work for mothers as executives
  • 13 Minutes to the Moon
    • Ep. 06 – “Saving 1968”
      • Apollo II’s first landing – without Apollo VIII, Pathfinder and 250k mi to the moon, maybe gutsiest flight until then
      • Flying VIII before end of year – “We were not ready”
      • 2 deaths of MLK and Kennedy – April had hundreds of cities taking part in riots, thousands arrested
        • 1968 Apollo program was in shock and Saturn V rocket was malfunctioning – troubled test flights
        • Almost busted in all 3 phases the last time it had flown, and the lunar module had slowed down, as well
      • Taking lunar module away from Apollo VIII – former test pilot Jim Lovell said it as Lewis & Clark expedition
        • So many firsts, risks that were enormous on a 100x scale – reason Jim was there in the first place
        • Crews normally had 6 months but VIII only had 4 – mathematicians were responsible for all of the angles and engine durations
      • 1 chance in 3 for mission successful, 1 in 3 for non-crash but unsuccessful and 1 in 3 for not coming back – wife accepted this
      • Media as delivering “death pills” for dying painlessly – respondents would say oxygen would run out and it’d be fairly painless
      • Trans-Lunar Injection – don’t shoot at the duck, shoot out front – wanted to go to 60 mi ahead of where the moon would be
        • Spacecraft needed to get to the right moment, speed, angle and altitude for the moon
        • Human computer – Katherine Johnson – was responsible for the trajectory for launch time (Hidden Figures)
        • Took 3 days from launch to get to target – Lunar Orbit Insertion
      • Astronauts were late on radio contact from dark side of moon
        • Came back to light and could hide behind his thumb – 5 billion people and everything he ever knew
        • Finishing Apollo VIII with scripture and then Good Night, Good Luck and Merry Christmas
  • Bill Clerico, co-founder and CEO of WePay (DealMakers 8/13/19)
    wepay-1

    • Leading provider of integrated payments for software platforms, raised $75mil from SV Angel, Highland Capital, Ignition Partners, August Cap
      • Founders of YouTube and PayPal also in
    • Grew up in NJ, spent time in NY and father worked in Air Force and construction – taught himself computers in 80s
      • Received a scholarship to go to BC, met his co-founder for WePay waiting for the flight for the interview 6 years prior
      • Went to do IB at Jeffray’s – advising tech and software companies with clients, passionate and building for a year to quit
    • Installed a suit rack in his car because he wasn’t going home – long hours, brutal fundraising
    • Group payments that they saw repeatedly at the age of 22 – big market for payments, testing it out
      • Wouldn’t have less responsibilities than at that time – Rich deferred law school and Bill had worked on it full time
      • Tried to pitch Boston investors and failed – less receptive to early stage investing, applied to YC instead
        • Came out to the valley for an interview
    • Spent 1.5 year to invest and took money and sold furniture and drove to the west, taking turns
      • Product was conceptual, pitch deck was opinion and it was hard to prove a market need to investors – conceptual idea
      • In YC, built product by talking to fraternity treasurers at SJSU, ski club coordinators – got them using the product
        • Went to talk to investors by showing them the traction
      • Why would a treasurer to accept payments with different product? Host bbq and invite them over. Go to dorm room and watch product usage.
        • Responsive to requests – take feedback and be better than existing solutions. Gain knowledge in start by doing things not scaling.
    • Group payments were a big problem and needed a solution – weren’t willing to pay, or pay transaction fees
      • Venmo had raised money and had a bunch of momentum by giving away services for free
      • Competitors were taking advantage, 2 years after YC – pivoted but weren’t growing as fast
        • Built an events tool, donation, invoicing tool and an API for customer use – other companies were just doing those
      • Realized they could build an API making payments experience easy and simple and let competitors do whatever
        • Saw huge traction/benefit where they could be brought in via the API (since they had raised $30mln)
        • Needed the business to be grown but expectations were higher
    • 600 lb block of ice for marketing $500 in front of PayPal Dev Conf at Moscone Center – still highest market day
      • Since PayPal had a knack for freezing people’s accounts randomly
    • Pivoted to shut off 70% revenue stream from consumer product, gaining growth on API from other customers
      • GoFundMe used them as a payments processor from when they were 2 person company
    • Prior to acquisition by JPMC – 200 employees at that time, now fintech / bank
      • Asset purchase agreement day – tired – was negotiating final points of deal in person, had some drinks to celebrate
      • Bought a cabin in Mendocino County – deal was valued at $400mln
    • Part-time partner at YC now – helping companies in general – relevant to the next entrepreneurs and the scale
    • Angel investing on the side – much longer and harder and scarier than he ever would’ve imagined
      • Reinforces this to his younger self – startup doesn’t fail unless you give up
  • Evolving Narratives in the Crypto Space with Andreas M. Antonopoulos (FYI 3/12/19)
    • With Arjun Balaji, as well — and similar for me as host, his intro to Crypto space video YT
    • Conflict of Crypto Visions article by Arjun and host
      • Identified closely with unconstrained vision and doing talks on not playing zero-sum mentality
      • Ethereum as different than Bitcoin – evolving directed by design choices
    • Engineering consists of design tradeoffs – choices of optimizing and de-optimizing parts of systems
    • If you want to make something that is Bitcoin-ish, you run into problems for all the strengths that are already inherent to Bitcoin network
      • Differentiate enough to be a new thing from Bitcoin – can’t mingle or occupy that niche
      • Is privacy a big enough differentiator to separate from Bitcoin network?
        • Strong privacy in base layer – can end up with inflation bugs that can damage sound money policy of Bitcoin for the privacy
      • Sound money vs private money – not clear yet.
    • Hard money displaces other forms of money in long term but only if they’re maximalists and logical
    • Friction levels determining switching back and forth on a wallet between utility or store of value tokens / coins in the future
      • Automated backend where they are optimized
    • Interest in Ethereum – tradeoff worth making for smart contracts and applications that aren’t just money outside of Bitcoin
      • How the technology of VM blockchains work
      • Scaling is harder in Ethereum – proof of stake has different security model than proof of work
      • Sharding, beacon chain, polka dot – not sure if it will work or what the security constraints are – could have applicability to BTC
    • Bitcoin critics – make the case for it but then explain value proposition or store of value
      • He has an opinion, others have opinions – none will determine how the market develops
      • Arguing is a waste of time. If you understand the tool that’s best for a job, you’re a better user of tools.
        • Which is the correct tool and how to use it properly – perception is limiting in general
  • Sam Yagan, CEO of ShopRunner (Wharton XM)
    sr_stack_full

    • Founding dating OkCupid and then going to Match and scaling to IPO
      • Going from running a team of 30 to 1000 in a month
    • Ecommerce ShopRunner as retailers combatting Amazon and Walmart – providing scale and guarantees with 2-day shipping for many retailers
      • Joining after Michael Rubin had founded it on premise of “Amazon for all others”
    • Making sure they have AMEX partnership to make it easy for customers
  • Travis Katz, VP of Product at Skyscanner (Wharton XM)
    image1-4

    • Had been cofounder of Trip.com and at Myspace prior
    • Social media giants Facebook and Myspace – selling to NewsCorp and getting revenue compared to funded Facebook acquiring users

Transformation of Innovation (Notes from Aug 12 to Aug 18, 2019) September 4, 2019

Posted by Anthony in Blockchain, Digital, education, experience, finance, Founders, global, Hiring, Leadership, marketing, NLP, Politics, questions, Real estate, social, Uncategorized.
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Hello! Hope Labor Day treated everyone properly, whether you snuck in some time-and-a-half pay for work, avoided it altogether or vacationed. I am going to keep the brief at the start short today because there’s a common theme. And I have been considering longer form writing without the notes on other topics maybe once or twice a week.

From last week – I still am working on the 13 Minutes to the Moon podcast – excellent. And it’s engaging as they went through the building and prep work that went in to getting there before decade-end.

The new segment that a16z has produced with the 16 minutes on the news has been fun, especially if you like an audio version of what’s been popular in tech/news. Sonal has done a great job leading most of them. I found the two that I listened it related to the title – transforming innovation. Software as eating the world (any company/product/service that can be digital will force the company to become software company), along with digitizing many of the slowest movers because the pressure has become high enough (re: Fed with ACH Now). At some point, in order to command more control or to make sure you aren’t disrupted out of the market, companies have to compete and give the customers or users what they want – faster, easier transactions in Fed Now’s initiative.

There were also some fantastic investors / founders that are included. How they developed and framed their careers to step from one thing to the next. If you noticed, many of the 20min VC episodes I listen to are in order from 2015 to now 2016. Fascinating to hear the comments made at that time to update to 2019 (as many of the same bullish comments are made with caveats that have yet to come to fruition – and valuations increased accordingly).

Hope you enjoy the listens!

  • 13 Minutes to the Moon
    268x0w

    • Ep 05 – “The fourth astronaut”
      • Intertial navigation – if you have your speed and know where you are, can control where you’re going
      • Self-guiding ballistic missiles that couldn’t get thrown off course via radio or otherwise – knew where it was
        • GPS, primitive computer received navigations and could adjust course if necessary
        • Charles Stark Draper who founded MIT’s guidance instrumentation lab
      • Had been a grad of Stanford and went to MIT and became leading expert in aircraft instrumentation / guidance
        • Dedicated to the astronaut program, so much so that he applied – was turned down
          • Practical application with such sensors to be useful was his expertise – size / practicality in flight control systems
      • Had to convince everyone that the computers would work and be trusted
      • Apollo bought 60% of the chips that were out and being manufactured – huge boost for computer industry
        • Good hardware required good software (an afterthought)
      • Called on programmers for building the software Margaret Ate Hamilton (started as programmer, then was in charge as program manager)
        • Developed a system to write software so that it would be reliable and she sought out the bugs/errors – no way to do it otherwise
          • Right times vs wrong time, wrong data, wrong priorities (interface errors) – we take for granted everything we have now
        • No rules or field at the time (akin to “Do you know these English words?” – yes, you’re qualified)
        • Don Isles – math graduate looking for something to do next who joined in 1966, software had been written initially – app code to fly was starting
          • Lunar landing phase commanding – in retrospect, huge – but it was a job at the time
      • Apollo Guidance Computer – 70 lbs in 1 cu ft, 55 W with 76kb, 16-bit words, 4 kb were RAM R/W memory, rest was hardwired
        • Got to the moon on punch cards – 100 people working on it at the end – submit in one run overnight and run simulations
        • 2 women that worked to keypunch before working as full-time – printed lines of code to turn into punch codes
      • Noun-verb inputs for flying – lunar landing, for instance
        • Built the computer interface with idea of “Go to moon” and “Take me home” but it instead had 500 buttons and was much more interactive
          • First system where people’s lives were at stake with it – fly by wire system. Astronauts didn’t control it, they controlled the joystick, etc…
    • Ep 06 – “Saving 1968”
      • Armstrong and Buzz Aldrin
  • Fed reaction (a16z, 16min on the News, 8/12/19)
    ah-logo-sm

    • FedNow – 24/7 open service for access to checks faster to launch in a few years
      • Half the population lives paycheck to paycheck and should care for the $30 overdraft fees that a ton of people do
      • Massive amount of losses to banks here in the US
    • ACH batches all payments in a day or maybe twice vs instant
      • Realtime payment network – 26 banks but need all banks to be a part of this network
    • Against Fed would say to just run the regulatory part vs the operational side
      • Obligate banks to join ACH, etc…
      • Infrastructure for checks has not updated to the tech advantages that we’ve gotten to now
      • Catching up to rest of world, which is 10 years ahead
    • Death of retail – Barney’s filing for bankruptcy, closing 15 of 22 stores
      • Been around since Great Depression
      • Ecommerce coming and direct to consumer is going toward market share
      • Highly leveraged fixed costs, inventory but can go sales to hemorrhaging money and become unviable
    • Grocery is largest single category of US retail, more than apparel and personal – completely immune to digitization historically
      • Inventory is better served close to consumer, physical grocery as distributed warehouse
  • Philipp Moehring, Head of Angelist EU (20min VC 1/6/16)
    1_n4gganmndofil1udzwkgca-300x225

    • First European hire for Angelist since Jan 14, venture partner at 500 Partners and Principal at SeedCamp
    • Angelist Syndicate for his
    • Worked for a bunch of startups during his studies, but realized he didn’t want to work for a large company or consultancy like when he started
      • Worked for a professor that was doing research on VC – did his thesis on same topic, asked for data
      • Fulltime job came from a guy who went off on his own to start firm and he was asked to join
    • MBA in Tech Management and Tech Entrepreneurship, where management is very different there
      • Analyst and associate work can be a great job but it’s not a quick way to partner or anything
      • Seeing founders doing a second business after 7-8 years, even after do great and get raises
        • People don’t usually stay at their first job for 8 years but starting at VC, people will jump to a startup second
    • EU vs US scene – SV where VC started and is much more advanced, simply due to a lack of epicenter
      • Angelist looking to get into Series A (not necessarily leading, though) – movement
    • Certainly London for VC – number one ecosystem in Europe, as the largest metro area, tech and VC and money
      • Hard to copy for other places – culture, politics and what makes the city to be interesting
      • Berlin has the momentum as the number two, as well as Stockholm or in Finland, maybe Paris (inward), Lisbon and distribution of eastern Europe
    • $400mln funding for Angelist from CSC Upshot into syndicates – GPs investing directly
      • Does his 500 Partners role on the side – usually someone with investing on the side and has more firepower
      • Wants the deal flow or coverage in the areas they won’t have
      • Knows an entrepreneur and can get in the chance on seed or small amounts to invest in
    • Known the partners at 500 Startups for a bunch of years and could invest similarly to his Angelist style
      • Could be flexible and born out of the way the fund is positioned and investing
    • Most exciting for him is having people that he’s invested in hitting their stride and succeeding
    • William Gibson as a writer who influences his thinking, Snowcrash as a book that depicts the future
      • Looks more at science fiction for tech advances now
    • Most read blog – too many to count, Brad Feld – has a tool called SelfControl against social media
  • Phil Libin (@plibin), co-founder and CEO All-Turtles (Mastering Innovation, 8/8/19)
    220px-at-logo-red-label-stacked-opaque-2048

    • Discussing real problems with AI

 

 

 

  • Andrew Chung, Founder and CEO Innovo Property Group (Marketing Matters, 8/7/19)
    • Partner at The Carlyle Group, US real estate
    • Started IPG in 2015
  • Stefan Thomke, professor at HBS (Wharton Knows, 8/13/19)
    31ii5kqtk5l._sx330_bo1204203200_

    • Discussing his paper on magic stick of customers
    • Online experiments – running them quickly and decisively

 

 

 

 

 

  • Ivan Mazour, (@ivanmazour) founder and CEO of Ometria (20min VC FF 029)
    ometria_owler_20160227_081547_original

    • Serial entrepreneur, author, investor – Ometria: predictive/marketing analytics platform
    • Born in Moscow, parents PhDs – mom brought him to UK to study math @ Cambridge
    • Started his first thing in property since that was biggest, public industry to get involved
      • Around 26, didn’t utilize any of his studies and data-focused nature, so he leveraged proceeds with his cofounder to make angel investments
    • Wanted to become relevant and learn about tech industry – made 30 investments in 4 years, stopped prop dev, did a Masters in App Prob
      • Refreshed knowledge to build a data company
      • Founding after investing – wrote a blog post as his approach to investment and his dream
        • Build a truly world-leading tech company but accepts lack of experience
    • Thought about how much capital to allocate to invest and how much to invest to be taken seriously – needs to be able to learn from it
      • Angel investor as $20-30k pounds
      • Received a second seed or extension round with Ometria – significantly bigger than seed, but reality is not enough for Series A
        • Hire more engineers, increase team from 20-30. But Series A would be to set up internationally and expand S&M
    • One-sided barbell – huge amount of funding on early, early stage investing
      • Anyone can work to get funding at early, small stage – lots of companies are vying for more eyeballs from bigger ones they need
      • At late stage, if you have the metrics, you’ll have the funding – growing 300%, hit $1m ARR and no question you’d get round, SaaS-wise
    • Launched as an ecommerce analytics company, wanted massive market for data – $3tn ecommerce and retail
      • Launching 2013, analytics was hottest thing (KPMG raised $100mln fund for this only) – by 2015 for big round Ometria, analytics wasn’t relevant/interesting
      • Fascinating to experience – marketing was far more important – actions engaging revenue and data, leveraged
    • First ones to come in were validating – people who he worked/invested with previously
      • Angels that were amazing, AngelLab’s Rachel that was meeting best founders and seeing best companies
      • Had tried to sell Phil as a customer on Ometria and he ended up investing – Alex is on board as 2nd largest institutional investor
    • Pitching angels vs other investors
      • With angels, he had engagement metrics, not revenues – introduced team and had beta user metrics (logging in 7x a day and loving it)
      • Four founders and engagement of platform that allowed closing of round
      • For VCs, chart of MRR that was up and right – increasing growth
    • Several funds liked the company and wanted to consider investing – said he should’ve held off, probably – got excited and continued conversation
      • Waste of time for both sides – hadn’t moved far enough on VC metrics to get a big enough investing for what you’re raising
    • Offline retail – stores won’t go away – thinks there will be an entire platform that will be an ecommerce platform that is based on personalization
      • Product recs, change website and order them – complicated and difficult – best platforms aren’t designed to do that – $1bn company
    • His highlight: sitting in his boardroom after increasing it, Elizabeth Ying (PayPal, head of D/S), Mike Baxter, Allie Mitchel (Huddle founder)
      Looking around that they were talking about his company and making a few investments that he was CEO of and they had 10-20 years experience
    • Favorite productivity tools: ToDoIst, Google Keep for managing main reports, HangOuts
    • Favorite books: Rich Dad, Poor Dad as formulating a way of thinking, and Dale Carnegie’s How to Win Friends and Influence People
  • David Tisch (@davetisch), MP at BoxGroup, Inc (20min VC 1/11/16)
    site-logo-home

    • Also, cofounded Spring – brands to consumers via mobile with his brother, Allen
    • Coded as a kid, kept using the internet, entryway into internet and software – didn’t think of it as investor
      • Went to college and law school, became a lawyer and joined real estate finance in m&a but he did that for a year and wasn’t into it
      • Started a company, experimented and sucked – sold to a larger company and was there for 2 years at KGB
      • Went to TechStars – launched and run the NY program after he had made 3-4 investments
    • Cementing of the NY scene would be a magnet company like Amazon, Facebook, Apple, Google – huge magnet for talent
    • The Box in NY as a cool club that he hadn’t been to and his first investment was in a company called Boxy
    • A 20th employee is exponentially more valuable than a seed stage investor – tries to be an valuable investor, though
    • Magical utility or happiness for user or incredibly polished path to where you’re going – different from early days of mobile
      • Should happen soon – hasn’t happened since Snapchat/Tinder as consumer
    • Spring for him – exact opposite of sitting above the clouds as VC and strategy – incredible other side with his brother
      • Mall on your phone – 1200 brands directly (Etsy as maker’s story) – single mobile experience to make it better
      • Free shipping and free returns in 2015 for marketplace and working with their partners
      • VIP, customer service, making a single experience
      • Apparent that the opportunity was sitting there – he had told his brother “Don’t start a company”
    • Doesn’t read much – watches a lot of tv and consumes that as a way to learn
    • Finding his partner Adam at Techstars is probably the highlight
    • Reads online a lot – design blogs/architecture/city – Fred Wilson as successful VC in NY
    • Invested in SmartThings – sold to Samsung a couple years prior and built into products
      • Deep affinity for space, so he invested into Nucleus – video intercom in houses but it allows outbound, also
      • Uncomplicates the phone – primary thing on cell (voice, messenger and text bringing into house)
  • John Wirtz, CPO at Hudl (Wharton XM)
    hudl-logo.1de182540fb461fded02ad2cb75963d4945c560d

    • Coaching and products innovation – getting cameras at 50 yd line or in arenas
      • Not so much looking at point-to-point tracking or high speed for baseball, softball
    • More on tracking all high school players and colleges – uploading of highlights and working with coaches
    • 95% coverage now
  • Software has eaten the world (a16z 8/18/19)
    • Marc and Jorge Condo discussing computer science and its eating healthcare
    • Term from his essay in 2011 after starting firm, tech industry is 70+ years old after WWII, packing $500 that used to be $10-15mln
      • Pessimism after recession – Marc held opposite opinion as just starting (platform built)
      • 3 claims: any product/service that can be software product will be software (boomboxes, cameras, newspapers, etc…)
        every company in the world in those products will become a software co
        as a consequence of 1 and 2, long run the best software company will win
    • Incumbents in auto industry – cars are very dangerous, very hard and software companies think otherwise – value of car is in software (500 in 50 mi radius)
      • Surprising innovation fields: legal, insurance, real estate, education, health care
    • Never imagined investing in new car companies – new industry in 1890, 1920s Henry Ford
      • One new major car company attempt by Preston Tucker (Automotive – Tucker movie, catastrophe)
      • Went from hundreds in 1910s to 3 in 1920s and after
    • Profound technological revolutions as ML/DL/AI as incredibly innovative and cryptocurrency
      • Software founders for how to use and those that haven’t – can be quite transformative
    • Fundamental transformation with internet was music industry – triple whammy – people loved music (? Often dogs eat dog food? – not case in music)
      • Isn’t it great customers love music so much? They want the thing – showing consumption. Music executives said no. Suppliers refusing the demand increase.
      • Pricing issue – want 1 song vs 12 songs on label. Price-fixing collusion by the 4-5 labels. Could overcharge by factor of 10.
      • Consumers were breaking law but the correct reasons. Was immoral, illegal by price collusion.
      • Went from Napster, Kazaa, Limewire, Frostwire, BitTorrent (all investor catastrophes as too early since they couldn’t get pricing from labels)
        • Spotify as 15 years later where investors were scarred but time had come
    • When layer commoditizes, the next layer can become massively valuable – focus is on commoditized layer (contraction for recorded music purchases)
      • US market for live concerts grew 4x in aggregate demand – unlimited access to music, so fun is concert and experiences
    • Marc as serving on board of hospital – mission in terms of health care and medical research and school – nonprofit with highly motivated people
      • Design and build a new hospital – finally opening in 2019 (2005 green light)
      • Well-functioning boards that he sees as 7 people vs 25 or so in hospital
      • Quality problems in auto industry in 1950s / 1960s initially, unsafe at any speed – 70s/80s/90s was TQM – debug quality manufacturing
      • Medical compliance issues – 1/3 not filling prescriptions, 1/3 just take cocktails of them
        • Organ transplants are only 60% compliance
        • Assembly line requirements to motion – decode for running properly, maybe do that for hospitals and doctors – Purell, even
      • EMR at Stanford – $400mil one bid, $100mil to Epic and $300mil for implementation system Perot Systems
        • Interoperability and open source, building on everyone’s creativity (except Epic) and APIs
    • Eroom’s Law – price of bringing new device or drug to market doubles every 10 years – VCs in both decided the economic cycles were too different
      • Names now for VC are ones that aren’t the same big firms
      • Founders are different, as well – PhD in bio but programming since 10 or hybrid tech to pitch
      • Missing middle as converging of scientific domains and getting a16z’s new partner, former Stanford professor in the middle who helped spin it up
    • Digital therapeutics, cloud biology, IT applied to Healthcare
    • Defend market or advance innovate market but SV is starting from scratch – experiments in tech, or business (famous train wrecks)
      • Portfolio approach to experiments – 10 experiments in 10 different parts of biotech / industry – look at successes and asymmetric returns
      • If there are big companies that can do obvious things, they’ll be good at increment – industry does different ones
    • Need evangelical marketer or sales – Jobs’ saying how to envision the picture because consumers have no ability to project this
      • Elon’s Model S – no superchargers or charging at home – had to paint a picture to demonstrate it, get enough sales to build the chargers
  • Dan Granger, CEO founder of Oxford Road (Wharton XM)
    oxford-road-agents-of-influence-logo

    • Advertising in LA helping acquire new customers and branding

Big Goals: Being the First (Notes from Aug 5 – Aug 11, 2019) August 27, 2019

Posted by Anthony in Blockchain, Digital, experience, finance, Founders, global, NLP, questions, social, Strategy, Uncategorized, WomenInWork.
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A friend recommended the 13 Minutes to the Moon podcast. I wish I could shout out that friend, but I currently have no recollection for who it was. Sorry! I’ve been recommending it to anyone that wants an intriguing documentation and story for the decade sprint to putting a human on the moon – and everyone that contributed to that goal. If you need more convincing, Hans Zimmer did the music production, as well. So, it has to be epic, right?

So, that’s what I would strongly suggest everyone listen to. The rest were incredibly interesting, as well.

The co-founders of Original Grain discussed watch making, selling out of backpacks and getting the approval of their military brothers before finally catching on and building the business. Setting out their approach and moving back to the PNW. Co-founders of Lovevery talked about mixing the product, box subscription service with educational, proven research and why Jessica chose this model and building their own over the licensing / branding other toys/puzzles.

Nick Maggiuli, of Ritholtz and Of Dollars and Data discussed why he’ll follow / listen to others that he may disagree with in case something clicks that makes him update his information to change his mind. Then, discussing that the market isn’t zero-share after Ken Fisher mentioned that his firm ($30bn plus) could be wiped from the face of the planet and nobody would ultimately notice when the market handles $50tn overall. 30bps – can aim high and ultimately it comes down to your execution, rarely others.

Then, Morten Lund talked of the EU investing scene, his success early, bankruptcy soon thereafter and deciding what he wanted to see and do. Sometimes you have to toil in decisions before landing what you seek.

Hope everyone enjoys the notes and checks the episodes out!

  • 13 Minutes to the Moon (BBC Worldservice)
    • First episode – ‘We choose to go’
      • Lousy communication as they dropped thrusters to 10%
      • Something happening in computer that caused issues – Armstrong was nervous (rarely)
      • Worry when Sputnik was placed up and a dog in the next month before putting a person there (BBC / Moscow reported)
      • Not having hopeless odds – could do a crash program to get men on moon by 1967, 68
        • German (vonBrown) who set up the rec for the course to get on the moon – recognized Russians needed 10x improvement
      • V2 rocket program – never having wide support but post-demonstration, went to mass production
        • Nordhausen – very aware of concentration camp workers, mistreatment and threat of sabotage
        • Surrendered and Americans were all-too-happy to accept them for rocket program (and space)
    • Second episode – ‘Kids in Control’
      • Steve Bales as the 26 yr old kid who could shut off the mission
        • Guidance officer in mission control team – lunar modules onboard computer by MIT design – controlled flight to moon’s surface
      • Junior technical in backrooms to Gemini flight controller for Apollo by age 23
      • Rapid recruitment style in technical and sciences – just threw them in for trainings and went from there
        • Hiring on rapid basis – bring on board, operations, engineering, training
      • John Aram – math and physics in North Texas to mission control – recalled so many acronyms (never been to a big city)
        • Moved to murder capital of the world, 6 weeks later and told his wife – maybe we need to load up and go back
          • We ain’t going back, she said.
        • Looked over electrical systems and the spacecraft’s electronics.
      • Average age of operators was probably 27 years old, grads of 1964 or so (older didn’t work out as well)
      • Simulations would run 20 different scenarios to demand engaging reminiscent of a fighter squadron
        • Had to trust each other well, kids and wives knew each other – risky things
        • Apollo I that killed the crew in 1967
      • Not enough time at home – many divorces from not being at home and holidays missing
      • In the trench – Gene Crantz: room bathed in blue light by the screens, smell of the room, people in for long time
        • Stale sandwiches, old pizza, full wastebaskets, coffee burnt into the hotplate, but you get feeling something will happen
        • System needed Gene’s toughness, former Marine, constant chain-smoking and needed that guidance from the flight director
      • Calling program error 1210 – never seen it in simulation and Steve had called abort – in actual mission, they got 1202 from Buzz
        • Setting a set of rules for program alarms – Steve got help from a 23 year old in the back – Jack Garmin
        • No call to abort if everything else is good – took 15seconds to push
    • Episode 3 – ‘Long Island Eagle’
      • Slowing descent was the plan, but they ended up going faster
        • Surface wasn’t what they had anticipated
      • Why is the lunar module the way that it is – way it looks? Form follows function.
        • Landing and flying in space – very different than aerodynamics for earth atmosphere
        • LTA1 – cleaner than a surgical room, higher pressure (dust and contamination avoidance)
        • Puncture a hole in skin with a pen – needed lightness and fuel efficiency
        • All engines in lunar modules had to be without electrical failure, so they were just latches with combustible gases
      • Lunar module designed by aeronautical engineers – aerodynamic and smooth, glass but had to evolve
        • Glass was too heavy and crew survival was supercritical
      • December 1968 was supposed to be lunar module flight but they flew around the moon instead
        • Would make it, but it would be close to the decade
    • Episode 4 – ‘Fire to the Phoenix’
      • Fire in the spacecraft – BBC report of Apollo I explosion, January 27 1967
        • Lost 3 heroes – Roger Jaffe, Ed White (first to walk in space in Gemini program), Gus Grissom (piloted Gemini flights)
        • Mercury and Gemini – everyone working there, 350-400 working on Apollo but at the height, it was 400k
        • Management challenge to build the program
      • Here to find out about Mr. Johnson for Block 2 design (Houston didn’t know who was in charge by 1964)
      • First space module in August 1966 delivered for flight testing, behind schedule
        • Jan 26, 1967 with service module perched on top of an Apollo rocket
        • Sitting in pure oxygen for the flight vs testing scenarios (t-shirts, atmosphere at sea level)
        • 30th of January, killed in the first / explosion of the Apollo I rocket
      • Accident had been an awful wake-up call but no national clamor for stopping the program
      • Hatch needed to be redesigned, reduce oxygen while on launchpad, new fire resistant found, electrical circuitry adjusted
        • Heat shields and modules to be tested, Apollo II to be canceled, 21 months to Apollo VII
          • Backup crew for Apollo I was the crew for VII – phoenix patches and honor the first
        • Spent 11 days in space and go around the moon – testing all systems that it could, from engine to navigation
  • Matt Britton, CEO of MRY, Suzy (Wharton XM)
    • Media entrepreneur and consumer trends expert
    • Suzy is ‘Siri for brands’
  • Ryan and Andrew Beltran, co-founders of Original Grain (Wharton XM)
    425133_t810

    • Watch category, growing up in the PacNW and serving in the military (Marines)
    • Trying to find a product that he wanted to start a brand of
    • Going to China to see manufacturing and get ideas
    • Selling the first out of his backpack, initially, to military guys
      • Got buy-in on quality that they stood up but not a ton of traction
  • LovEvery – Love Every – Jessica and Rod, founding partners (Wharton XM)
    loveveryforweb

    • Jessica worrying about giving her babies the best nutrition, and curious about what the brains craved
    • Approaching research and deciding on toys

 

 

 

  • BERT (Bidirectional Encoding Reps from Transformers) (Data Skeptic 7/29/19)
    • Neural network with input arbitrary length of text – minimal form and characters
      • Output is a fixed length vector, numeric rep of the text – can do automated feature engineering for ML
      • Translation step for encoding for the machine using masking
    • Chatbot for question answering – wouldn’t do specialized tools for observe
    • BERT develops a general option (vs ML where there isn’t enough training data)
      • Trained on general knowledge, wikipedia corpus or reddit, etc… and apply transfer learning
  • Nick Maggiuli, Of Dollars and Data (Standard Dev 5/30/19)
    • Head of Data Analytics at Ritholz Wealth – data and interesting
    • Behavioral investor line test – being the 8th person in line and hearing others in Ash experiment
      • People purposefully tell you the wrong matched line and 76% of time, switches idea – changes vision in this case
      • Connecting to fake news in the realm of bias – pie chart that showed top 5 S&P 500 on right side, bottom 282 on left
        • Data just tells you the biggest 5 companies – may be just the 5 largest that represent a total share (consistent)
      • Crowd makes the narrative, often and then people agree and it becomes an echo chamber
    • Following crypto people despite not believing in it because they may know something that he hasn’t seen or know
      • Change minds based on some information. Trend following, for instance (price signal, 200ma – will stop working at times – Corey Hoffstein)
      • Doesn’t believe in technical analysis but has to be convinced by some information to make the jump
    • Blog post: Most Important Asset (host ran the survey) – bet that none of you offered every $ of Buffett wouldn’t want to be him
      • 5%, so maybe 3% are trolls. But he wants to live his life. Human capital and time is the optionality.
    • Best book he’d read about retirement “Retire Happy, Wild and Free” and doesn’t discuss money
      • Financial crisis isn’t the priority – it’s existential – what’s your time that you want to worry about
      • Some people could go to the beach every day and not care, others do differently
    • Trading his time for tasks and outsourcing things – working otherwise and doing it via his hourly wage
      • Anything you’d regret on your deathbed for missing things that you’d want to do – ends meeting, one thing but otherwise, go for it
    • Ken Fisher at Investment Conference (EBI with Barry and Ken talking)
      • “We have no market share” – 30bps as money to be managed out of $50tn when they’re $30bn
        • Could disappear and nobody would notice (except their clients)
      • Enough pie overall where they’re not competing against each other
      • Not interested in the discipline, so any general discussion is improved and bringing people in
        • Rise of politics and twitter probably keeps some viewers away but looking at competition and peers for learning
        • Brian Portnoy writing at the same time, sharing information and going back and forth with same publisher
    • Funniest fintwit: Ramp and Josh Brown, smartest Jim O’Shaunnessey and Jesse Livermore, MMT – “Trusts Cullen Roche”
    • Book that he read early in his career when he was bored – What It Takes by Ellis – best firms in handful of industries
      • If they ‘reject us, we made the wrong choice on the person so it’s good anyway’ – Korbath in legal
  • Morten Lund, seed investor in Skype (20min VC, 1/4/16)
    • Investor, co-founder including Airhelp, 100 other startups
    • Visiting university before getting kicked out – used computer to get premade direct marketing which wasn’t possible prior
      • Turned it into a digital ad agency and made it the largest in Scandinavia and sold to Leo Burnett (ad agency) as digital acquisition
      • Could build company by then
    • Made a small incubator by then with the money he had
    • Called for investments in Kazaa initially – wasn’t comfortable with that because biz model was for iTunes but no power to negotiate with labels
      • Was helping business development at the time
    • Guys had idea of doing Skypr – wifi sharing network – shut down by 10-15 investors who didn’t want to go further
      • Calls couldn’t be afforded so why not do a digital phone with the sound cards – helped fundraise and paid founders’ apartments
        • 300-400k users after 20 days launch – roughly $50k brought back $50mln
        • When it took off and worked, it was exciting – Estonia guys being crucial and understanding p2p from Kazaa, as well
      • Very involved in the brand – ICQ (impossible to understand)
    • Bankruptcy 7+ years prior had to refocus him and figure out what he wanted to do – nothing wasn’t working
      • Co-founding, starting and investing all kinds of 70-80 startups
    • Learning that things will take 3-4x longer and 3-4x costly
      • Founder in mind for admiring – David Hilge (Unity), Reid Hoffman, demonstrating stamina
    • Spending time at TradeShift – empty on cash and barely surviving holding onto his house – internet as media business that was fairly large
      • Every bank has a budget of $1bn in tech spend – immense amount of people running around doing nothing
      • Partners came to him to do digital invoicing structure for English structure and wanted to do consulting (agreed on cloud-based platform infrastructure)
      • Every company has different file formats and being consistent (Christian becoming a rock star) – ability to close huge clients
    • EU fintech community – browser era in 94-95 and nobody knowing how to handle it – legislation is getting easier to deal with
      • Web bank is a media but can do all kinds of interesting things with accounting – unwind IBM and legacy providers from cloud
      • If you want to sell big, have to go to US but if you want to do early or continue building, can be in the EU
      • Becomes obsession for $1bn level – consequence shouldn’t be this, though – not justified without revenue
    • Favorite book: Shantaram, fun with Richard Branson (knowledge exchange), The Economist as blog, Hippocorn – placeholder or executor affiliate

Fun Founder Stories (Notes from July 29 – Aug 4, 2019) August 21, 2019

Posted by Anthony in Automation, Digital, education, experience, finance, Founders, global, Hiring, Leadership, marketing, medicine, questions, social, Strategy, TV, Uncategorized, WomenInWork.
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Starting with a discussion of Neuralink (Musk’s… brain-child of a company for neural lace) and how it reminds the a16z crew of invasive compared to non-invasive surgeries / medical tech. How did TikTok vary itself in the social space and explode in popularity? Harry Stebbings of 20min VC had been going on and on about HiringScreen and finally had the founder on which was fun to hear. Richard’s origination story for the company and his path that he took was fascinating.

Then I happened to listen to a few different shoe companies with founders on serendipitous and creative stories. One traveling to a new and different country and absorbing the culture to his story. The others, seeing a problem that seemed to arise and noticing there should / could be a solution. Then catching breaks for each of the 2 companies – including the bootstrapping and doing it on their own as something that was fun enough helping people solve those problems / be happy with their footwear. I strongly suggest looking at Sabah shoes for men’s drivers-ish and Birdies for women who go to parties where they may need slippers or comfortable everyday ones.

E-sports and digital discussion for a16z was fun in how society is adapting to digital experiences or how they meld entertainment. For those that don’t think esports may be viable, it’s easy to argue in the cases where they watch reality tv or even game shows (which have been around since tv). It’s just changed how we consume and perceive it as interactive live games vs recordings. Also, malls that are less successful or in areas have been able to take advantage of the space available.

Vivino’s CEO joined and talked about how he is trying to socialize and give people options in the wine space – which, let’s be honest, is always a good thing. Goldie Chan discussed filling the gap in an employment by consulting, by accident, nearly. She turned it into a full pivot consulting and has taken advantage of her great skills at marketing. Hope there’s something for everyone!

  • Neuralink & Brain Interface (a16z 7/21/19, 16min on the News)
    1200px-neuralink_logo.svg_

    • With Vijay, Connie Chan, JPM
    • Announcement of neural lace – culture sci-fi by Ian Banks – processor & sewing machine
    • Non-invasive vs invasive (femoral artery all the way up to the brain)
      • LASIK as invasive / dangerous (still even, but now much better, accepted)
    • Announcing in rats and in monkeys now (surprising his president)
    • TikTok as 3rd most dl app behind WhatsApp and FB Messenger, 1.2bln MAUs – having huge influence at VidCon
      • Sponsored by YouTube but TikTok had a large presence, the ban in India
      • Short, 15sec videos – 1 hit piece can trigger enough people
    • How would they make money? – ecommerce, restaurants, retail – short videos for ads/commercials
    • FaceApp – probably nothing to worry about – unless high profiled public official, NatSec Space, leverage
      • Someone getting negative information or leakage – accusations of the country in general is silly
      • Countries consider privacy differently – in the US, convenience / UX will trump privacy for 15min of joy
        • Europeans, Germans, Italians for instance are more private
    • iHeartRadio announcing direct listing – before, emerging from bankruptcy or spinning off
      • Repurposed after Spotify / Pandora
  • Mobile malware and Bipartisan drug pricing (a16z 7/28/19, 16min on the News)
    • With Martin Casado, Jorge Conde, Jay Rughani
    • Monacle as mobile malware – March 2016 Android-based application
      • In security, netsec and endpoints – protecting desktops, for instance
      • Attacks phone with 2FA, even, and less secure
      • Can take calendar event, account info and app messages, reset PINs
    • Drug pricing – Medicare Modernization Act – why can’t Medicare use its purchasing power to negotiate medicine prices?
      • Part D – Medicare covering prescription prices, prevents HFS from negotiating any part of the value chain
      • Price of insulin where they get price hikes – new therapy gets $2mln for cures (R&D) differences, conflation
      • Price of successful drugs have to make money for drug and all of the failures
        • Counterargument – US subsidizes R&D for the world
        • Complex industry structure: manufacturers, distributors paid to move drugs through channel
          • Pharmacy benefit manager – who is eligible, who’s not – what are drugs for conditions and prescriptions
            • Helps insurers who gets the drugs – takes an economics layer
          • Insurers reduction drug spends, for $1 spent, manufacturer gets a small %
      • Dropping from $8k to $3100 out of pocket
        • Cap by tying to inflation (for growth) or annual price increases
        • May start higher prices because you can’t increase it much
    • Chain is not transparent, but also complex – tech can have an impact but needs help from policy to drive out some inefficiencies
      • Free market works if there’s transparency – what is a medicine and can you make it fair enough for everyone
      • Current system is not set up for the new medicines (extending life from 10 years to a cure)
  • Richard Hanson, CEO & cofounder of HiringScreen (20min VC FF028)
    psrzsqo86j9gj71wrqli

    • Founded in Hong Kong in 2015
    • Studied law in Cambridge, did 11 years recruitment consultancy in London before moving to Hong Kong
      • Then created his own recruitment firm – had his own looking at 196 cv’s for an EA for someone
      • Score, sort and select candidates
    • Tech advances in recruiting industry – job boards and sourcing is at all-time highs
      • Barrier to application is all-time low but have too many to look for (especially manually)
      • Psychometric and phone facility stuff to find relevant candidates – get on with themselves
        • Go through rest of funnel to invest in the process in more efficient manner
    • Had always wanted to live in Asia – pretty exciting, bullish for Asia in general
      • Hong Kong, Singapore, Japan as hubs
    • If you have an idea, try to find someone or go ahead and do a view of what it may be executed on
      • He had the idea, went to his cofounder Luke (better at project management side)
      • Prototyping mockups and getting through the first steps efficiently – may hit a dead-end a few weeks in
        • Validating idea as soon as possible – customer or problems for people (heads of recruitment firms for his problem)
    • Making an effort to code or understand a bit of the UX (in his case, CSS and HTML to understand a bit)
      • Compared to languages in a foreign country
      • When his CTO introduces people, he wants to be confident about what the developer has been doing and understanding their past
      • His responsibility to show an effort/commitment in the job role
    • Looking to raise a round – HiringScreen did it in 8 weeks
      • Competitive slides, why you want to raise, how to convey mission statement, skill and productivity gaps
      • Understanding his potential investors, as well
    • Accelerators – choosing the right ones? He’s with the Blueprint Accelerator by Swire properties
      • B2B focus, no equity in startups – working space and Swire network of companies (conglomerate of different co’s in verticals)
      • Sponsored him and tried to help advance the company by talking to other HR talks
      • Mentions Brinc as hardware accelerator near the top
    • Idea of equity early on would depend on your assessment of what the startup needs?
      • Super low cost – accelerator with working space?
      • Product but proven use case – Blueprint to trial product and test it
      • Balance the need with the equity they’re taking
    • The Alliance book by Reid Hoffman for looking at employee and employer workplace, tour of duty principle
    • Brad Feld and Jason Calacanis’s blogs, Reid Hoffman as the most admirable founder – better people to take LinkedIn on
  • Jennifer Golbeck, College of Information Studies and Affiliate Professor at UMD
    • Talking about social media research, truth and justice
  • Carl Ericson, CEO & cofounder of Atomic Object (Wharton XM, Mind Your Business)
    atomic-object-wordmark-500x265

    • Grand Rapids, Ann Arbor software product development company and why he chose there
    • Sails at Grand Rapids Yacht Club
  • Bianca Gates, Marisa Sharkey, Birdies co-founders (Wharton XM)
    m_5a61f34b331627f3f88fe26b

    • Discussing how they started them and Feb 14 – when she landed an article with a SF Chronicle fashion correspondent at a dinner party
    • Driving up to the other in order to get all 2000 orders packaged and sent out

 

 

 

  • Mickey Ashmore, founder of Sabah Shoes (Wharton XM)
    sabahtwotone

    • Doing a 6 month project after Seattle in Turkey – turned into 2 years as the only non-Turk
      • Grew an affinity for the people, culture, food and trends – girlfriend’s grandma at the time gifted him a pair of handmade shoes
    • Returned to NY and beat the crap out of the shoes – wanted another
      • Reached out to the maker (current partner) and bought another pair
      • Ended up getting 5-6 in different colors, customized without the flip – people said they were awesome
      • Ordered 300 – could get 150+ and did a party to showcase them with cocktails, enjoyed hosting
        • Got 30-40 orders on the first night, decided to do it for the rest of the summer “Sabah Saturday/Sundays”
    • Realized it could be a business after in the summer he was making more from shoe sales than his NY P/E job
    • Expanding from 3-4 employees to 40 and expanding from a home to a warehouse – border of Syria/Turkey
      • Has a few key employees that are Syrian refugees – part of the brand and they showcase it on the site
        • Not branding directly, but definitely part of the story
  • Goldie Chan (@goldiechan), digital marketing expert of LinkedIn and actor (Wharton XM)
    • Discussing quitting her job and making a fake company while unemployed
      • Turned into a marketing consulting gig – had a few clients, had to create a company
    • Now doing talks and discussions
  • Kurt Seidensticker, CEO of Vital Protein (Wharton XM)
    ca400555-4bb7-4c66-a217-b5ac910cba73._cr5101107332_pt0_sx600__

    • Collagen and explaining to people how it was – getting some in to Whole Foods through them asking
    • Didn’t hit him until he was in Italy and 2 random women at a café pulled their Vital out
    • Did about 10 companies, 2 succeeded enough to pay for kids college and allow him the freedom
      • Was doing Vital during another company until it surpassed the other
  • Fortnite, esports, Gaming (a16z, 16min on the News)
    • 2 million concurrent livestreaming – not as big as GoT, for instance
    • With Andrew Chen, Darcy Cooligan (investing team on consumer)
    • Bigger prize pool for Dota 2, $3mil for Bugha’s win was larger than Tiger’s Masters victory
    • 10 years for Riot and League – still grossing billion, WoW / Runescape
    • Billions of video consumption between Twitch, YT (and now Microsoft Mixer)
    • iPad can play Fortnite pretty well, for instance – massive multiplayer opportunities
      • Instagram and this generation for coming together as people – Minecraft/Fortnite
      • Gaming and cultural zeitgeist to hang out with friends
    • Sonal did a fight with editorial desk and had seen it for a profiling in 2013 – argued it was similar to sports
      • Big business and much of the same thing – management company, played 2+ years for 6-8 hours, sponsors, fans
      • Performance entertainment and personality-based
        • Comparative for game shows – other people answering trivia, reality tv
    • Strong incentives to keep games going – user-generated content
      • Established player leading way to user-generated thereafter
      • For Fortnite, building levels (similar to mods and mod community in Minecraft and Roblox)
    • Games stadia for esports and digital dualism (in real life compared to virtual – game is the bridge)
      • Malls building areas for this part
  • Chris Tsakalakis, CEO of Vivino (Bay Area Ventures, Wharton XM)
    aws_vivino_logo_600x400.cb594b3d79815eece9e8c685a7b8d043b7910b95

    • Having users and getting customers – at least 1 employee in each region where they sell
    • Mostly in US, Europe – hq in Dublin
    • Bunch of users in Asia / South America (Brazil, specifically), but don’t sell there yet
    • Not taking VC until more recently

Idea Conversion to Algorithms (Notes from July 22 – 28, 2019) August 14, 2019

Posted by Anthony in Automation, Digital, education, experience, finance, Founders, global, Hiring, Leadership, marketing, medicine, questions, Strategy, Uncategorized, WomenInWork.
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There is quite a bit in this week’s notes to unpack. Most of the stories and experiences provided by the guests, though, premised around testing a hypothesis or quickly trying to solve a problem in a manner that, once validated, could become much more efficient. When trying to make the solution more efficient, whether data or AI-driven, then further questions have to be asked to ensure a proper, scaleable and ethical solution. Lauren deLisaColeman discussed the ML application ethics and what guides them. Karim Galil observed that patient history was stodgy and doctors weren’t in to new things that could save them time because of the catchup time. So he had to produce a solution that could be effective immediately and worth giving back doctors time – he chose oncology to do it in.

Alyssa Dineen discussed profiles as well, but of the dating variety. There were more ways to screw up than attracting attention. At first, she could do it manually before realizing she could improve the work she did and make it better for both business and clients. Khartoon at Spotify talked about how they started at Spotify with freemium model and the streaming aspect before connecting that with all of the data to their corporate and enterprise partners. In turn, the two-way data sharing enabled them to pivot nicely to provide more value and eventually into a paid model that helped the business. Lastly, Max Bruner talked about his hell of a journey where he eventually landed at Metromile, but not before building Mavrx in the best form of dirty solutions – cameras from planes. Then realizing what could be attached and automated to be a full provider to farmers in much of farmland US and improving it. Quite the product path.

Curious about this concept for much of college / graduates.
Idea possibly worth pursuing – saw post on similar idea. Fake VC – take seed or series A opportunities, combine with data plan (via other post). Have various students make their opinions on what to seek, whether funding was good. How to think of next steps? Make action plan, but templated and maybe try to get an argument. Podcast/videos presenting either side. Try to talk to startup that received. Good sourcing examples, data (limited) problems, industry seeking.

Hope you enjoy the week’s notes and check everyone out!

  • Lauren deLisa Coleman (@ultra_Lauren), Digi-cultural Trend Analyst (Wharton XM)
    • Forbes contributor, discussing AI and ethics of ML applications
    • Who makes the rules – is the data guided?
  • Karim Galil, Founder of Mendel.ai (Wharton XM)
    mendel-logo

    • Working in Egypt initially, wasn’t in Cairo but started in Sinai – beach and did surf/kitesurfing lessons deal
      • Talent was not as abundant, but did a project with Pfizer, Dubai government and others
      • Egypt had free healthcare but hospitals couldn’t pay for procedures that may have been experimental – trials would allow it
        • Wouldn’t hear about trials until it was too late in his oncology rotation
    • Observed that you could have a dating record online and perfect match, but not catch up on papers in context in industry
      • Had to start somewhere – landed on oncology – wasn’t a junior vs senior thing – few doctors had the time
    • Losing patients to cancer and messy medical records – trying to improve the healthcare industry
    • Can get a bunch of oncologists to drop everything and work as data scientists
      • Cheaper in Egypt and feasible – fair salaries to do this
      • In the US, very unlikely to happen as oncologists are far above data scientist salary
    • Medical matching service – AI-powered to do trials for language content
    • Paying ~30 employees, where 15 of them are oncologists
  • Alyssa Dineen, Style my Profile founder (Wharton XM)
    style-my-profile

    • Personal stylists online and in NYC
    • Wanting to expand – mentioned Forbes article and expanded 3x
      • Mostly from out of the NYC area
      • Would love to open LA, SF, Chicago, most urban areas
  • Daniel Korschun, assoc prof of Marketing at LeBow Drexel (Wharton XM)
    • Marketing and branding for Kaepernick’s Betsy Ross argument
      • Nike blew opportunity to turn the flag into a very big positive – “Unity” or 13 civil rights activists
    • Owning the branding, making sure to keep it different
    • Making statements or seeing both sides can attribute your opinion without actually doing so
      • Being “informed” by museum after making case for both sides
  • Chandra Devam, CEO of Aris MD (Wharton XM)
    arismdlogo-tealrevised

    • Discussion of iTech NASA competition with Star Trek-surgery
    • A/R and V/R applications – board with the tech
  • Rachel Glaser, CFO of Etsy (Mastering Innovation)
    sell-jewelry-on-etsy

    • Search algorithms to increase sales
    • Etsy as vintage space – defined as 20 years, or handmade materials or put together
    • Have to stay ahead of counterfeit and trends

 

 

  • Sitar Teli (@sitar), MP at Connect Ventures (20min VC 12/30/15)
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    • Doughty Hanson Tech Ventures, series A round in SoundCloud
    • Dual degree in MechE and Econ from Duke
    • Taught English in South Korea for a year, 3 years in IB in US – Broadview (M&A, tech focused)
      • Enjoyed working with the companies but not the banking side – best part was to hear how companies started and early days
      • Hadn’t considered London in 2005 when headhunter had reached out
    • Gaming, fintech, music & content, adtech where Europe is producing big, growing companies now (2015)
      • More cross-pollination of entrepreneurs going back and forth or partnering with others
      • IB moving into VC – different perspectives for her 2 other partners
    • Starting a new fund – “one of worst startups you can think of” – competitive against established funds
      • Build brand, reputation, product and designing it (not just money but experience) – how to work with the founders
      • First year – founders aren’t necessarily eager – want a seriousness that came with business cards
      • Allocating $100 – she’d do $90 to the portfolio and investments, $10 to rejections and focus
        • For No’s, make it quick and even in the meeting or cut short
    • Looking for companies
      • Founders that really understand the market they’re building for – how passionate, how much time to understand, experience
        • CityMapper founder – public transport and how they move through the city and how it can help
        • Stockholm-based Oxy – music creation app (prior at SoundCloud) – digital music tech, digital to greater number of people
      • Founders on a mission (other than $)
      • UX-focused and at the center of what they do
      • As an aside, whole lot of $ (maybe at seed) but it’s not the only bucket – ecommerce, adtech, depending on what founders are
        • Thesis: investors can dictate the entrepreneurs and align them
    • Crowdfunding alongside VC – many biz don’t need venture capital but do need capital
    • Amazing Adventures of Kavalier as book
  • Khartoon Weiss, Global Head of Verticals at Spotify (Wharton XM)
    open-graph-default

    • Starting with the streaming service as free and eventually getting into freemium / subscribers
      • Providing value to users and charging for it
    • Analyzing usage data from subscribers and free users to personalize the experience for listeners and serving brand partners
    • Core value of giving creative artists the opportunity to live off their art
    • Advertisers will see data in events that drive music playing
      • For example, an eclipse occurring will produce more song plays with eclipse themes – can drive user advertising for it, connect brands
  • Max Bruner (@maximusbruner), VP CorpDev at Metromile (Wharton XM)
    metromile

    • Talked about Mavrx, geospatial and agtech company
      • Flying drones and then planes over farmland to assess and improve efficiency
      • Didn’t have the initial equipment when they went to South Africa (needed data during US’s winter)
        • Had pilots take their cameras, IR and others
    • Most of clients were in the midwest – eventually sold to various parts of the vertical
    • Attended UW-Madison in econ and Arabic – did a year abroad between Egypt and Qatar (at the time, nice and hadn’t been through revolutions yet)
      • Felt like something was missing so returned to DC where he worked in the DoE under Reinvestment and Recovery Act

Universal Laws: Parkinson’s Law (Notes from July 15 – 21, 2019) August 6, 2019

Posted by Anthony in Automation, Digital, experience, finance, Founders, global, Hiring, Leadership, marketing, medicine, questions, Real estate, Uncategorized, WomenInWork.
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I included in my thrice-weekly newsletter the blog post by Morgan Housel espousing some of the most common universal laws of our world today. Once you know of them, it’s tough to not consider them in your everyday life. I’ll be honest and say that I hadn’t heard / didn’t know the name or origination of a few, including Parkinson’s. However, I wanted to comment on it because of its commonplace position on my timeline (and in the way I generally price much of my consulting work).

Parkinson’s Law: Work expands to fill the time available for its completion.

ML and apps – attention. Phones and apps have stolen hours of attention over the last 3-4 years (Wharton XM blog) — 3 hours to 4+ hours for the average, now

How do they squeeze in more DAILY? Work efficiency, likely. Most probably don’t have 8 hours of real work – ask anyone. What do we think the % is? I understand there are roles that probably see a full day a few times a week or in certain weeks (looking at you, auditors/accountants/finance/strategy/consultants) where projects line up or during busy times. Even retail / seasonal / cyclical has busy seasons – boosts that require full focus. But generally, not.

Work time vs value – if you can finish a project in 24 hours, charge more because the allowable time outside of that is higher or do you take the full time or project out for time in case of a problem / feedback / there? See: consultants working with a client, maybe a new client? Value = price but want to keep them. Can’t do too low. Can’t go outside of the range. Sweet spot of pricing and expand the time. Expensing to look like the time is filling. I can’t knock any firms taking advantage of this, especially when most have derived the business model from value creation, but it does seem that as time goes on, keeping that price premium and time valued becomes less of an advantage used for good and merely an indicator of what they should bring.

Time will tell for those that hang on the longest. Hope you enjoy the notes.

  • Cynthia Muller, Dir. of Mission Investment at WK Kellogg Fdn (Wharton XM, Dollars & Change)
    • Discussing consulting and the people or culture parts (@cynmull)
      • Merger where everything, paper and number-wise, looked like a perfect match
      • Failed miserably – many of the top producers were unhappy and the merger allowed them to leave easily
    • Satya Nadella at Microsoft reimagining the purpose – got to everyone PC-front but had to overhaul
    • Measuring people – upper quintile in survey of 500k employees (~500 companies) – middle management ratings of purpose
      • 7% YoY performance over others – not lower or upper – middle management was determining factor
  • Scott Kupor (@skupor), MP at Andreesen Horowitz (Wharton XM)
    • Discussion of becoming full-shop, including investments and RIA
    • Value add other than capital is very important to him
    • Tries to make decisions and No comes with why?
      • Sometimes they are wrong, see founders again and some have come back with addressing the reasons “no”
    • IPO extensions to 10+ years vs 6-8 – private and liquidity-driven
      • Discussed employee needs as a big reason for why it will stay 10-12 and not increase
      • Can’t compete with Google or others if you aren’t liquid
      • Early on, private companies aren’t worried about that with the people that can take the risks
    • Secrets of Sand Hill Road book, going through that
  • Brian Kelly, co-founder of The Points Guy (Wharton XM)
    tpg-primarylogo-color-28129

    • Selling to Red Ventures – taken private recently, also
    • Partnering with hotels and airlines to build an app in Austin – connect accounts, personalized, direct to airlines/hotels
      • Make it easier and hopefully change it for the better consumer experience
      • Turning it into a tech company moreso than a media one
    • Blogging initially, leaving Morgan Stanley – consumer-focused and not driven by partnerships
    • Only takes credit card partnerships instead of airlines or others
  • Benito Cachinero, Senior Advisor at Egon Zehnder (Wharton XM)
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    • Former CHRO at DuPont, ADP and leading succession processes
      • VP of HR for JnJ Medical, Corporate HR VP for MA Divestitures at Lucent Tech
    • Born in Spain, knew he wanted out at an early age
  • Eric Hippeau (@erichippeau), MP at Lerer Hippeau Ventures (20min VC 12/21/15)
    lerer_hippeau_ventures_logo

    • Chairman of RebelMouse, co-founder of NowThis Media
    • CEO in 90s of Ziff Davis initially as media company, the publisher of PC mags as well as conferences
      • Being in tech business moreso than media – sold to p/e firm before they sold to SoftBank
      • Before selling, they were about to be 2nd institutional investor in Yahoo but SoftBank made bid for 1/3 of Yahoo before IPO
      • He went to Yahoo Japan which allowed them to get a lot of source just due to the company
    • Sold business in late 90s, joined SoftBank as investor and opened firm in NY with them before his own
    • Backing company or business requires some business experience and growth/hiring and strategizing are all important
      • All partners at LHV have operating background – biggest difference is probably the time horizon (need really long view as VC)
      • Had just closed 5th fund, very satisfied with the work life instead of operating – running as a startup
      • $8.5 mln initially – no full-time employees initially, until the 2nd fund
    • First investments are at seed level, have always kept money in reserve for follow-on
      • 70% of co’s are in NY
    • Value add for LHV, generally – 2 levels of support
      • Product that is a technology platform that they plug everyone into
        • Recruiting and marketing database, best practices, current series A/B investors and what they’re seeking, Comms layer
      • Each company assigned to one partner and associate – bespoke plan and a to/do list for each company
        • Intros, branding, pricing, organizational structure and growth
    • Biggest problems for portfolio co’s – dependent on sector
      • Ex: SaaS: correctly size marketing opportunity for going after the right, big companies – largest/most important get a premium on the valuation
    • First check is typically $750k – $1mln – characterize this as collaboration between other funds
      • As long as terms are acceptable, let others lead or whatever is best when the companies are the best
    • Best pitch: what they’re looking for is the Big Idea – original, large market, tech-enabled, timing
    • Drone Racing League as public, recent investment: fantastic idea as drones are becoming more popular, variety of them, popularity of video games
  • Sumeet Shah (@PE_Feeds), Investor at Brand Foundry Ventures (20min VC 12/23/15)
    • Investments include Warby Parker, Birchbox, Contently
    • Grad from Columbia in 2008, biomedical and went to p/e through Gotham Consulting Partners (engineers at firm, diff industries)
      • P/E as two party system – deal team of firm and the client portfolio company
      • Lots of outside the box thinking, project work for 2 and B/D for 3 years
      • Met Andrew Mitchell who is the boss at Brand Foundry
    • July 2013 moved into start-up with friends with Gist Digital – help with bizdev
      • 6 months in, help with capital – Andrew reconnected – was offered a full-time job into vc
      • March 2014 was when he went full-time and after the first year is active – seed rounds, pre-seed occasionally
    • Paul and Sarah Lacey – series A crunch with tech/software/app-focused
      • Invested into Cotopaxi for $3mln seed round
      • Working alongside Indiegogo and Kickstarter and have invested in crowdfunding
    • Marketer, operator and technician and his due diligence takes between 2-4 weeks, typically
      • Take on doubles/triples compared to unicorn returns that are worth it – Eilene’s opinion to do unicorns
    • Believes over time that building reputation with doubles and triples, will stumble on a unicorn – those are the ones that can make the fund
    • Most value from investors – sign of weakness is not reaching out to investors
    • Different mindsets of East vs West coast
      • NY looks at building sustainable businesses, SV/SF is a $1 to a dream mentality (need this, still)
        • Want to look at revenue streams, traction, etc… but loonshots are ‘safer’ in SV
      • Founders as female-led – 7 of 13 of their investments have female founders and 3 of them are 2 co-founders female-led
    • No general people in the startups that may catastrophically fail in SV, so it’s okay for the funding to be gone
      • Bullish on TechStars Boulder, looking at ventures or accelerators that are growing in that region
    • Things A Little Bird Told Me as favorite book and most recent investment with LOLA – women’s biodegradable tampons
  • Carolyn Witte (@carolynwitte), co-founder & CEO of Tia Clinic (Wharton XM)
    z6kdoir2_200x200

    • Going from a tech AI program / chat – making women be comfortable with talking to a message
    • Before doctor appointments to after, and then having them bring her in with the doctors
    • How to interact – realized that they needed to complete the offering with their own clinic

 

  • Jessica Bennett, gender editor at NYT, “In Her Words” (Wharton XM)
    • Sympathetic attitudes and gender
  • Boris Wertz (@bwertz), founding partner of Version One (20min VC 12/28/15)
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    • Top early-stage tech investor, board partner at Andreesen Horowitz, COO of Abebooks.com that sold to Amazon in ’08
    • 2005 named Pacific EY Entrepreneur of the Year
    • Internet 1.0 in 1999 – wanted to be apart of it – started JustBooks with some friends
      • Built it to Europe’s market leader and then sold to competitor AbeBooks before Amazon
    • Took proceeds and put into 35 internet and mobile companies – early wins, early exits and decided to do it professionally
      • First fund was $18mln
    • Power of bringing together customers across the world and finding the book – buyers/sellers in small marketplace with hard-to-find
      • Years and years of book fairs or local inventories that they were limited to
      • Passionate customer stories and being part of the company – personal way to see how marketplaces are important
    • Transportation vertical with Uber as unlocked in marketplaces
      • Mobile first, others – and their investments
      • “A Guide to Marketplaces” book by VersionOne
        • Precision for a thought that may have been in your head when you write – clarity
        • As supportive as possible to the startup ecosystem and how to impact entrepreneurs in portfolio or outside
        • What does VersionOne get excited about and how do they contribute or help?
        • 50 page guide put together for a framework and concise – depth but not overly so
    • Attractiveness of marketplaces
      • Fragmentation of supply/demand – more people on either side of marketplace, buyers/sellers
        • Buyers/suppliers sometimes want a monogamous relationship – doctors, cleaning personnel – don’t want to get someone new
        • Cab driver / uber – doesn’t matter who drives A to B as long as it’s safe
        • Transactional relationships vs monogamous
      • Size of underlying market, ebay grew from collectibles to all sort of products
      • Specific niche market – what is the kind of market you can address – specially-crafted goods
        • When he looks – lens of VC that needs a return, so needs to see a return on capital in 5-7 years
        • Operators can be great in this case because it can be very profitable, bootstrapped or friends/family money to get and grow
    • Demand or supply first? Any marketplace chicken and egg.
      • Depends on marketplace but once you have network effects, it takes off
      • Uber paying drivers to be idle just to have people in the area and have the supply
      • Addressing supply – how much to have? Hotspots.
        • Which transactions work really well?
        • Price point? Vertical? Certain buyer/supplier? AirBnb doubled down in NYC higher value rentals. Just needed that initially.
    • Trust and safety becomes more important after some attention – supply side with hobby sellers with a little bit of their inventory
      • Power starters are the ones that are stronger. Professional sellers.
    • Mobile first marketplaces and on-demand marketplaces excite VersionOne the most.
      • Services / products as on-demand (Fueling of cars, for instance)
      • Fascinated by decentralized marketplaces built by blockchain – will they ever make money but can’t generate money on own?
    • Measuring as VC: how happy are entrepreneurs, were ones that they met with taking away stuff, serving/help them and get feedback
    • Favorite book: Hard Things, Blog/newsletter – Fred Wilson’s
    • Overhyped: on-demand, Uber for X thing – underlying drivers for Uber’s success, for instance
    • Underhyped: quicker hype cycles – blockchain, VR/AR, drones and anything new is all over it in few months
    • Marketplace Key Metrics: gross merchandise sales and take rate (revenues compared to the gross sales)
    • Recent investment: HeadOut mobile first marketplace for travel experiences (NY, LA, Chi, SF, LA, Vegas)
      • Upcoming experiences in next 24 hours in that city

Refresh the Old and Tired (Notes from July 8 to 14, 2019) July 30, 2019

Posted by Anthony in Automation, Digital, experience, finance, Founders, Leadership, marketing, questions, social, Uncategorized, WomenInWork.
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For the abundant discussion on big tech, rise of tech and the valley’s obsession with all of it, there are quite a few industries that have had much longer staying power. They’ve proved their worth, decades and decades in. There are still railways. There are still cars. Manufacturing persists. CPG and everything that that entails last. Walmart, as much as people love (or don’t) Amazon, it’s still a lion’s share of commerce. Tech has improved and allowed them to have this staying power. Additionally, enabling improved efficiencies can allow new players in the industries to fundamentally change how they’re viewed.

Industries include tv – nonpartisan and bipartisan news with Carrie Sheffield. a16z gets into online from offline forms of services, restaurants to tech-enabled deliveries, as well as the rise of CAA and the agency fights. Then we have traffic and building with a consultant in that space. The next industry was making the legal space a little more transparent – provide a marketplace where information becomes symmetrical. I believe these are ways that simple pain points that can be improved through a technological lens give access to a value that wasn’t there before.

Hope you enjoy the shorter posting and the notes as more detailed. Check each of the wonderful people out!

  • Carrie Sheffield (@carriesheffield), co-founder of Bold TV (Wharton XM)
    slack-for-ios-upload-1

    • Discussing bipartisan vs nonpartisan
    • Growing up in very conservative areas and then going to the coast – seeing both sides, especially media
      • How it was to be in media
    • Fake news as non-fact-checked as well as actually fake – ~70%+ considering bias
    • Intellectual diversity along with everything else – thinking differently vs looking diverse
      • Used example of Google AI conference canceling on a colleague who was a conservative, black woman
  • Chia Chin Lee, CEO of BigBox VR (Wharton XM)
    ravlfjtl_400x400
  • Initially trying VR and finding it sickening – didn’t work (Oculus)
    • Tried HTC Vive and fell in love – had a room set up and felt enthralled
    • Hardware and platform may get cheaper with tech
      • Opportunity lies in the software side – connecting to others and industries

 

  • Entrepreneurs, Then and Now (a16z 6/29/19)
    • With Marc, Ben, Stewart Butterfield (@stewart)
    • 10 year anniversary for a16z in late June – how has the environment changed?
    • Class of 2009 entrepreneurs were some of the most special: Todd McKinnon, Martin, Brian Czesky
      • To get to that point, needed to earn your stripes
    • O2O – online to offline (AirBNB, Uber, DoorDash, Postmates, etc….)
      • Founders that may be more operationally-focused since those require that
        • Maybe more similar to semiconductor founders from the 1970s, start of 80s
    • Dual discipline people as they got more involved in healthcare or bio-related
      • 10 years ago, Bio PhD wouldn’t know much on computers but now, dual PhD’s
    • Economics + CS – discussion of field of economics with empirical / quantitative economics compared to physics or formulas
      • New inventions by economists with machine learning and data
    • New ideas – thought venture firms had lost way, founders/operators that built businesses who would help out on boards
      • GPs started to get more abstract ideas, professionalized
      • Institution and ecosystem, network and fundamental staffing model – pay at a16z is different than other VC’s
    • If priority was to find best founders at the best opportunities, shouldn’t matter which stage they’re at – miss things, maybe
      • Skype deal early, multiple entry points – working with entrepreneur and being stage-agnostic
      • Tech bubble bursting – “can’t possibly start fund” – 2009 was Khosla and them
        • Mentioned ‘crusty’ or ‘grouchy’ VC’s
    • Much of the tech was at an inflection point – Salesforce as only SaaS, iPhone not quite there yet, Uber, Airbnb
      • Maybe the main response should be “No, this thing is stupid” as more accurate
      • Never thought it was a bubble – prices of companies are always incorrect (future performance, which nobody knows)
      • East coast vs West coast – not obvious, find what each argue about
    • How high is up? Online pet delivery, all actually happening
      • What are the exploratory bets? Are markets ready? Are people ready? Regulators?
        • Sometimes it’s the pioneer, sometimes it’s the last – time and effort for founders, personality, other
    • No individual company gets 25 years to prove something – maybe 5 years for a hypothesis
      • Morale issue losing faith or architecture issue – prior architecture (ex: mobile dev in 2002, system on archaic and aging-in-place)
      • VC’s will do the same thing – kid doesn’t know about failed experiments – VC freeze themselves out (ones who don’t know will often invest)
        • Can you learn lessons from failure – maybe you should learn nothing – “That doesn’t work.”
        • Edison as trying 3000 combinations before the filament, Wright brothers trying many
    • Copying the model from CAA – Michael Lovitz and describing the whole thing – not a collection of individuals
      • Operating platform, system and infrastructure with professionals across the network
      • Compounding advantage year over year – but why can’t they copy? They were paying themselves all the money
        • Nobody wanted to take pay cuts – 80% to hire everyone at such a scale
    • Top end venture investment – need something working (product-market fit, product)
      • Do they know what they’re doing? Can they do their job scaling?
      • Second-time or later founders – can do what they want and figure stuff out?
        • Problem may be with the good idea – investments on that idea or otherwise (fragmented idea with nothing)
      • Idea maze to find out what the ideas are – haven’t gone through that
    • VCs can’t invest more than 20% of funds that aren’t primary equity investments – crypto, for instance (vs RIA)
    • Deadwood as creation of city or state – horrifying obstacles
      • Why History is Always Wrong? (Taleb’s narrative fallacy, for instance – often more complex)
        • Don’t even know body, climate still (too complex) – can converge on science to Newton’s laws, others
      • Can’t Hurt Me by David Goggins
  • Scott Kuznicki, Pres and Managing Engineer at Modern Traffic Consultants (Wharton XM)
    logo-text

    • Traffic control tech – California high speed rail vs autobahn style
      • Autonomous lanes?
    • Designated autonomous – level V vs others, depends on density and adoption
    • Thinks parking structures with flat tops could be converted or pay for cost
      • Multipurpose, solar, green or plants etc…
  • Risk, Incentive and Opportunity in Starting Co (FF 027, 20min VC)
    logo-062fd8699c93a47b2e8278975e71b84870194fd30c288607f1e06c92a4e831a0

    • Daniel van Binsbergen, CEO and co-founder of Lexoo
      • Online marketplace connecting businesses and lawyers
    • Founded it in 2014, got an investment for $1.7mil
    • Friends always asking for referrals – kept a short list of them
      • Seemed great, “quoted $X – is that good?” – perception of complexities
      • Could put make a marketplace together for transparency
    • Kept 100% of his income boosts – got used to his training salary so it wasn’t as big a risk
      • No kids meant it may have been easier – really disappointed if you didn’t give it a go – decision already made
    • Legal space’s lack of progression in tech – incentives in wrong place
      • Hourly model still for law – if you spend less time on work, you would make less money
      • Risk-spotting for lawyers
      • Senior partners have heaviest voice – not exactly lining up for retirement in the near term vs long term
    • Highest goal may not be senior partner – fixed fee, sharing risk, more open to innovating with own practice
    • Lexoo initially – didn’t have tech skills for it, had a vision in his head but didn’t know best way
      • Didn’t build full-scale solution, did a forum for $15 website, form to fill in
      • Arrived in his email – he would then contact lawyers and fill in Word template – get their responses and quotes
      • Attached the lawyers’ quote and response to a doc and pdf and send back to clients
      • Automated only when he couldn’t handle the workload – hit limit on evenings and quit
        • Lawyers paid 10% commission on the quotes
    • Focus on business ideas – tech isn’t the big solution – market innovation (access to litigators)
    • Investors at Forward Investors – introduced through a friend who knew them through squash partner
      • Difference between FOMO on being convinced vs other investors who have a sense of opportunity
    • Fav book: The Mob Test – how to ask questions to get useful feedback, asking questions to customers in the wrong way
      • Would you use the product if it does X, Y, Z – most definitely? Instead of asking what the customer problems are.
    • A lot of work in Trello, for goals, and Sunrise app – Microsoft’s indispensable for calendar meetings
  • Facebook Bargaining Bots Invented a Language (Data Skeptic 6/21/19)
    • Auction theory and econometrics – equilibrium strategy
    • Neither agent is incentivized to change strategy if the other stays the same
    • Plateau of events in real life – baby, marriage, life changes, job, lease ends in time
    • Discount is a single floating-point decimal, ex 0.99 ^ t
      • Everything known – can calculate based on common knowledge and discounts
    • Gaussian distribution, mean 100k, 10k – ignore tail in negative and renormalize
      • Rubenstein one-sided incomplete
    • Game: don’t know private value now, but can have probability distribution
      • Update with Bayesian with behavior
      • Classic ML: corpus of examples of negotiation, mark up conveniently, objective function to maximize reward (post-agree)
      • Opportunity for RL – patterns for language utterances, insult or compliment or neither – recognizing strategy
        • Character level or nothing to ask it
        • Conversations for language you don’t understand and the reward – can you do this optimally?
    • RL + Roll-out with 8.3 to agent and 4.3 to other algorithms (94.4% agreement)
      • Roll-out was 7.3 and then RL – 7.1 and last place was 5.4 for likelihood model
    • Training data was in English, negotiating over 3 items – shortcut its job, RL wants the short path to reward
      • His example – loses points if you went to pits but to reward – chance at falling
      • Wasn’t worth it to move, so he had to do a penalty for not moving
      • Penalty for Facebook example was agents continued to communicate in English
      • Put a time constraint, maybe
  • Transfer Learning with Sebastian Ruder (@seb_ruder), D/S at DeepMind (Data Skeptic 7/8/19)
    deepmind-1

    • Generally, TL is leveraging knowledge from different tasks or domains to do better on another task
    • Not a lot of training data, may want to pretrain – models to train on imagenet, for instance
      • Language modeling to train on large corpora and use that on a bunch of other tasks
      • Source vs target data: task stays the same but can adapt between source and target, say sentiment of reviews
    • Classic benchmarking, may have ImageNet moments over last year – features of pretrained models applied on more powerful NLP
    • Google XLNet’s most current, BERT and ELMo as others – pace of improvement has been great
    • Difficulty of target tasks – can be good for 100 samples in target source on binary tasks, maybe, 50 even?
      • 200 examples per label, question-answering or reasoning, examples must be increased
      • If we can express target task as a conditional language modeling, can do fewer or even inference
    • Pretraining is costly due to large clusters on your own, but now can be public pretraining where you can finetune quickly
    • Area of common sense reasoning – infer what a question means or expressed depends on what may not be said
      • Grass is green, entity facts (son of a son), inquiries for language model – incorporate to modeling

Connecting the Generations (Notes from July 1 to 6, 2019) July 23, 2019

Posted by Anthony in Digital, experience, finance, Founders, marketing, questions, social, Strategy, Uncategorized.
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So, we’re going to connect one of the authors’ titles of the books they wrote for our theme today. Connecting the Generations from Marc Freedman’s “How to Live Forever”. Granted, he was discussing the generational split between boomers, millennials, Gen Z and the workplace surrounding them. How do mentorships work in reality, if at all? How to find a bidirectional, productive mentorship? These are questions Freedman discusses in that book.

Another section that I want to focus on is the boom in gaming, specifically esports. Computers and games arose in in the late 1950s but became more of a thing to get probably by the 70s. As consoles came about, they became even more prevalent for those growing up in the 1980s as something we were used to seeing. My father, for instance, bought a Nintendo 64 on the opening weekend, and we would play together a few nights a week before bed – Mario Kart or Goldeneye. Though there were multiplayer games, these were mostly co-op and local, outside of tournament style, 1 on 1 games such as Mortal Kombat or MVC. Surely there were Super Smash tournaments among others but it took until the first decade of the 2000s to take off, if I were to guess. Now, gaming’s turned into a whole other animal – the ease with which you can get a console / pc that can run the top performing games and connect with friends makes the whole thing a new experience, and one nearly everyone can get on board with. YouTube / Twitch came about after streaming platforms like justin.tv and others came about, and many people like background noise or enjoy the commentary/gameplay aspect of watching compared to playing. I saw the other day that the top 5 individual gamers are above $1mil in prize money for playing – without any sponsorships included (that brings Ninja to above $5mil).
Kyle Bautista, COO of Complexity Gaming, discusses how they brand and seek opportunities for the competitors that are on the team, and where he sees the industry going. By comparing it to other sports, he tries to see value in working with younger players but because it doesn’t necessarily require the same separation of skills that athletes do, it’s a challenge to find out what age group or what type of player may be of most value or have the most potential to help get to a professional status. It’s a different world than the 90s, and I find the gaming one fascinating growth-wise.

Then we had a pair of Forward Partners discuss the ideology behind their firm. Focusing on very early startups – sometimes even the founders and building out the product or idea. Dharmesh Raithatha, product partner at FP, talked about the process for how they build the idea with a discussion of many people in the space, prospective customers, different markets on their frustrations or problems, if they have any solutions and where they go for help. Do the founders have the ability to inspire people with them as well as the customers who may be along for the ride?
Matthew Bradley discussed value that Forward brings outside of the checks, which tend to be a bit larger for the first money of those they have chosen to invest with. What does the 1 year timeline look like? Who are the first 100 or 1000 customers? And are there questions that should be asked that haven’t been covered? For the next thing, he was suggesting healthcare or something in medtech field instead of fintech or consumer, which could be more saturated.

As the next generation of branding and marketing, post-internet and more mobile-first, Peter Adams, of Marketing Dive, discussed the options for established brands to make plays that come off genuine and impressionable. For instance, the Taco Bell hotel. There are brand advocates who will love it, according to him. I’m a fan of Taco Bell, but I’m not sure that would be me. Definitely a creative way to drive some awareness, and if the opportunity is pulled off, it can work! Interestingly enough, he discussed the partnership of Nike / AirJordan and Fortnite – where players and sneakerheads don’t get physical shoes or items, but actually just the digital versions as skins. With the player base of a game such as Fortnite, it was a huge opportunity to get more people aware of the brand of Nike and hoping to allow a connection between the game and physical world that may drive sales. Brands have to be careful with how they approach this, though, in order to attract the right market as well as execute it in a way that is plausible.

I hope you enjoy the other notes I included here. If you have questions, you can reach me on Twitter or leave a comment. Have a great week!

  • Kyle Bautista (@coL_beef), COO GM Complexity Gaming (Wharton XM)
    a40blaub

    • Discussing esports and the partnering brands
    • Meeting with Jerry Jones, who’d purchased a team
    • Sees all types of similarity between esports and other athletes
      • 10,000 hours + rule
    • Talent evaluation at an early age – working on that and trying to improve 
  • Dharmesh Raithatha (@dhrmshr), Product Partner at Forward Partners (20min VC 096)
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    • Idea stage investments – great products in AI, former employee at Mind Candy, BBC
      • Founded 2 startups, sold one
    • Background working in startups as software developer and then product management before leaving
      • Met Nick Brisborn, MP, said to meet for and work for 6 months
        • Strategy and multiple companies – said yes to all firms with product people
    • Want synergies in sector expertise – early stage funds can be helped by these people, CEO may be process-based
    • Difference between Nick – who has done it extensively and him – learning
    • Open hours monthly – spend 15 min to pitch or getting advice – sees certain commonalities / niches
      • Ones that seem exciting pop out because they’re different or unique, and they understand that
    • Investment themes for what they’ve invested in or problems that you haven’t found
      • Brainstorm lots of ideas, talk to people, observe & understand the problem
      • Tend to take people who are solo founders that are non-technical – not sure how to build the idea, maybe
        • Hard to evaluate or understand who is good – but he’s anti-outsourcing
        • If you can, cultivate relationships
    • Founders that do well – very good understanding of their uses & seeking the right people
      • Ability to inspire, big vision wrapped up – 10x better aim
    • New founders come in – can see the problem. Have the investment.
      • First month will be to talk to people – speak to 40+ to seek customer segments and market.
        • What problems? What solutions do they have? How do they feel? Where do they go?
        • Watch people solve the problem themselves, immerse themselves in the problem?
      • Ex of Lex – Founder’s Friday legal market – launched w/ forum/landing page
        • Tried to match lawyers with the clients. Understood the software he needed to build and the product.
    • SV Product by Marty Cagan
    • Massive interest in health tech – MindSpace, GP fixes, access to data earlier
    • Most recent investment: The Gifting Company
  • Marc Freedman (@marc_freedman), author of How to Live Forever (Wharton XM)
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    • Discussion of the split generationally in the workplace
    • More people living at home longer – even after the crash, still increasing
    • People are used to being with others, but sometimes the mentorship game doesn’t work bidirectionally

 

 

 

 

  • Peter Adams (@patchadams), Reporter at Marketing Dive (Wharton XM, Marketing Matters)
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    • Target, Amazon, Walmart jumping into content space
    • Discussion of Nike and Foot Locker branding – popups that are genuine
      • Digital footprint for awareness – Air Jordan with Fortnite
        • Did they need revenue split?
        • Taco Bell as a leader in the experiential branding space – launching hotel soon
        • Had a few popups – “Cantina” in Vegas – wedding venues, renting out restaurants
  • Matthew Bradley (@mattyjam), Investor at Forward Partners (20min VC 097)
    • Super-early stage London VC and Betting Big on Consumer Fintech
    • Father had done investment banking, so he went there first – ‘legit’ career in 2006
      • Structuring a derivative for midmarket pension fund in UK – packed up immediately after
        • Did an MBA, few start-ups that failed and invested in others
          (1 doing Series B)
      • Finance stuff, investing in small businesses and looked at venture capital – took unpaid internship at Forward and is there now
    • Idea stage funding because they have a team of product people, full stack developers, designers, recruiters to give success
      • Offering $250k at this stage which is significantly larger than others
      • Path Forward as operator framework for proven need for prototype/product for first 100 or 1000 customers
    • As an ecommerce fund, can test cheaply/quickly – why they look for the early adopters
    • More $ in series A than ever before – round sizes are getting larger, so more startups are staying in seed earlier
      • Late vs early, crowdfunding and angel rounds
    • Google Ventures took on LostMyName, a portfolio company, and wanted a TransAtlantic investor
    • Asking questions to entrepreneurs 3 or 4 times, varies for team – teasing out assumptions and questions
      • Go-to market size, 1 year timeline, initial target customer
        • He’s a big fan of open-ended questions: Is there anything that he hasn’t asked that he should ask?
    • With new YC’s announced, he says there are a repeat of clones that show up in the UK – not necessarily a bad thing
      • Startups have to often think of different problems, say payer difference in healthcare
      • Consumer credit bigger in the US than UK, probably
    • Accelerator route – gold standard for incubator can almost always been great choice – but launching and consider market
    • 50 next unicorns report: overweight in consumer tech and on-demand services and underweight in healthcare
      • Believes in consumer financial services and healthcare
    • The Master and Margarita as favorite book
    • Funding landscape in London: yes, more chickens – more eggs – more $
    • Most read blog / newsletter (he said he reads 1.5 – 2 hours a day): Mattermark Daily, Term Sheet, Nick’s (boss), Tunguz, Mahesh
      • First round review weekly is a great one for early stage startup
      • Thiel as investor – lean methodology being bashed, crowdfunding not necessarily as replacing VC
    • LiveBetterWith – aggregator for nonmedical products that help people live with chronic diseases – super early stage
  • Jose Benitez Cong, co-founder and CEO of Plause (Wharton XM)
    plause

    • Growing up both Mexican and Chinese – couldn’t speak English, couldn’t speak Chinese
      • Was dropped off as a kid to his grandparents’, who spoke Chinese – school started Monday and he needed to figure out English
    • Hustling to do window washing and scaling it while he couldn’t drive (saved money – until he started spending it on girls later)
      • Scaling of window washing broke after doing orders and calendars because money wasn’t as easily split for not equal shifts
  • Bill Glaser, Bacon Chips – co-founder of JUST (Wharton XM)
    • Bacon chips – PIG OUT brand, all vegetarian
      • Formulated by David Anderson, former chef at Beyond Meat
      • Mushrooms that are flavored to taste like bacon with a tech patent-pending
    • Mushrooms as umami and making sure the consistency worked to be crunchy
    • Getting investment capital – some $1.5 million
  • Catapult Ventures Darren & Rouz Jazayeri (Wharton XM)
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    • Technologists, looking for solutions
    • How they came to the name

Sharing, Building and Community (Notes from June 24 – 30, 2019) July 16, 2019

Posted by Anthony in Digital, experience, finance, Founders, global, Leadership, medicine, questions, Real estate, social, Strategy, Uncategorized, WomenInWork.
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If you hadn’t noticed or read from the start, you should know that I’ve gone in order from the start on the Twenty Minute VC episodes. Many of the conversations are from 2015 and 2016 so they end up as a bit of a history lesson and window into the mindset surrounding capital / founding at that time. Bubble discussions or higher capital raises are comical when we now know what today looks like – higher, still. Although I’d say geographically, expansion has exponentially grown as it’s become easier and more common for firms to seek out what they really believe is an edge for them. Interestingly enough, people also don’t stay where they were, especially over a few years. As I look them up to refresh and review for these posts, it can be very enlightening to see where they are currently – did they start a new project? Open a new fund? Move on to different industry?

David Teten was one of those switchers, as he was with ff V/C at the time, and now over at HOF Capital. Similar role but perhaps more focused on what he’d like to see. Also, many of the firm founders and partners aren’t heralded for having more than a few roles – some probably for different reasons, but I look at that for myself as a way to stay extremely excited about continuing to learn every day, every week. To believe in yourself to be capable of doing great work, helping to create as much value as possible in the most efficient manner, hopefully. Weird that many people receive flack for multiple positions when many of us strive to follow a few particular, but potentially different, things. For this, I admire David in keeping up with his roles, while keeping us all in the loop of his thoughts, generally, as well.

Next, there were two involved in real estate, housing and construction that were pretty much aligned. What do I mean? Both believed the rising housing (and estate, generally) costs have come as construction costs have increased significantly. This is creating unduly pressure, and making it more difficult for projects to get done. Maggie Coleman went through real estate differences for certain types, while John Rahaim of SF mentioned precautions that are being taken for the coastline and bay.

Then, we had Ryan Hoover, who runs ProductHunt, and is one of my favorite follows. He built what he and his friends wanted – a place to share ideas and products to try. And 5 years later, here he is. I won’t spoil some of the nuggets that he shared, including a few of his favorite books and monetizing once he knew it was real. Not to be outdone, a discussion with Phil Southerland covered how he has built a strong community of athletes born or having diabetes. To demonstrate how they can grow, he helped form a team of all diabetics and professionally rides to bring awareness and improve the lives and conversations surrounding them.

There is important work being done by many people, including ourselves. If we can better someone’s life, it’s likely worth doing it if you’re enjoying it. We can help by just being who we are and doing what we would like to do. I’d love to hear some of your ideas or thoughts regarding the people covered in this week’s notes.

  • David Teten@dteten, Partner at ff Venture Capital, founder and Chairman of HBS (20min VC 095)
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    • Alumni Angels of Greater NY, largest angel group in NY
    • How to Disrupt the Investing Business
    • Grew up in Marin Co, played with computers – consulted and taught Excel as a kid – bah mitzvah on knowledge test
      • Fired when he was 16 from financial services company because they figured out password was pw for admin
    • In college, worked briefly in strategy consulting before investment banking in tech – business school where he started multiple ventures in Israel and US
    • Joined ff VC in 2011 when it was 3 – now 27+ people, as largest headcount seed VC in Canada, Amsterdam, Israel, UK, US
    • Company ff should be generalists – broadest possible but don’t invest in life sciences due to no expertise there yet
      • Can’t predict in advance, so they want companies that are interesting with high growth potential
      • Admires outbound of TA or Summit, but something like SignalFire to look at data for high growth
        • Resources to help founders to reduce write-offs (1 in 6 fail for them) which attracts inbound (2000+ a year)
          • Filters down to ~12 a year to invest
    • Google Ventures / SignalFire and others as algorithmic approaches to source – increasing importance but not validated thesis
    • Loves their model as efficient – frustrations at other vc’s (80% of time with people / co you can’t invest in – partying and not meeting anyone)
      • Nobody at ff has a job as origination, Angelist as disrupting the generalist VCs (those that don’t have added value)
    • Top 3 Important Ways to Support Companies: capital raising, finance acceleration team – CFO acting, recruiting
    • How to determine value add as entrepreneur
      • Reference check
      • Do the math on portfolio: for ff, 60 portfolio co’s (active in 2/3), 24+ ee’s
        • How many people in the team? How many portfolio co’s? How many checks?
          • Use that to determine person-hours you can expect
        • What sort of technology platform to support the company?
      • A16z as huge operational side – finance, marketing, etc…
        • Short list for companies doing this – very capital intensive
      • Believes that there will be some shrinkage in the model in a downturn if it’s not fully thought out
    • Very illiquid asset class (mentioning to LPs) – 12 different academic studies for 18-54% median returns
      • 10+ years for cash returns, lot of institutions aren’t okay with that time range
      • David Swenson (head of Yale endowment) has argued long-lasting liquidity premium for illiquid asset classes
        • Even the most liquid asset classes aren’t liquid when you want them to be (2008, for instance)
    • Indiegogo as seed – crowdfunding space, competitors aren’t invested in – watch Angelist very closely, though
      • Services from Angelist as they look around at different parts of deal flow
      • Encourages member space to get involved in angel investing for next generation of companies – exposure to ecosystem
        • Promote economic growth
    • Research study: Disrupt investing – security, for instance
      • Secure (ID verification), Distill Networks (blocks bots), IONIQ (from Atl, secure cloud usage)
      • New processes and make them efficient: Addapar (Excel/PDF), Earnest Research (nontrad datasets eg: cc info, email receipt mining)
    • VC usage of social media: much more aggressive, judicious but no breakfast tweeting – sell
    • Edward Tufte – Yale prof, must read
    • PandoDaily as top blog – not afraid to make enemies, discuss what they do
    • SkyCatch as most recent – drone tech, set of tools for collecting data via drones – construction use case (Kamatsu client)
      • Monitor exact status of project, imperative they know where everything is
  • Maggie Coleman, MD and Head of Intl Capital at JLL RE (Wharton XM)
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    • Looking at different real estate measures – single family homes, for instance
    • Do different assets in real estate require a different measure to draw attention from foreign investors?
      • Didn’t seem so – would depend on where the capital was coming from (their own environmental basis)
    • Construction costs as outpacing many other costs – affecting many markets

 

  • John Rahaim, Director at SF Planning Dept (Wharton XM)
    • Having to adjust for the changing seaboard – will regulatory measures be taken?
      • No mechanical or living people in commercial buildings on the first floor, for instance
    • Says there are already precautions being taken on the bay – 5-8 feet, for instance
    • Construction costing so much already that it’s been very difficult to get building done post-land acquisition
      • Estimates of $600-800k for this due to inflationary and costs passed from the building companies
      • Said he had some 36? Projects that are being held up
  • Ryan Hoover (@rrhoover), Founder @ ProductHunt (20min VC FF026)
    ph-logo-3

    • Best community builder, Twitter engagement, winner of TC Best New Startup of 2014
    • Just wanted to build a consumer-focused thing to discuss with his friends about app ideas or companies
    • Put it on Quibb and Twitter – manual things initially, set up an email subscription, personal email connecting with people
      • Keep building communities otherwise it peters out
    • First iteration was RoR built over 5 day Thanksgiving holiday – core is the same, people using and community growth
      • Having people tell them and comment on ideas (used it as their new home page)
    • How to plan to go from early adopters to mass market?
      • Eager enough to participate, engage and not necessarily representative of the common users
    • Categorizing Podcasts and putting them on the home page – barrier before, now based on episodes
      • This Week in Startups, Startup Show (by Gimlet founders), Jake Gyllenhaal ep of Mystery Show (Gimlet media) – is he 6′ tall?
    • Worked on Hooked with Nir Eyal, using some in ProductHunt
      • Email digest is the trigger – action is to open / click on something to find inspiration or interesting
        • Built email variability – some consistency, surface different titles and content
      • Follow collection, clicking follow, reward is updates on the collections – permission for emailing to reinforce and come back
    • Ryan’s favorite collections: featured ones, Russ has game collections (browser ones), Julie created bakednight
    • Betaworks kept popping up on their engagement charts – Twitter very active, products (Without, where would he be?)
      • Always tagging the authors and being genuine, personable, funny or light-hearted
    • Monetizing PH – at its core, download/use/purchase products with the right intent
      • Over time, will explore more of this
      • Fundraising: first time for Ryan, different as a side project and growing
    • Quibb as newsfeed other than Twitter and also Crunchies where they announced Shipt but said “Actually, it’s PH”
    • Sunrise as calendar app, Pomodoro – no longer. Favorite book: Art of Game Design by Arty Shell
      • User psychology and game mechanics, how it applies to tech products as well. Game design not always thought about.
  • Brian Solis (@briansolis), author of Lifescale (Wharton XM)
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  • Survey on how social media has changed / warped views for girls
    • Hadn’t fully released yet

 

 

 

  • Phil Southerland (@philsoutherland), CEO of Team Novo Nordisk (Wharton XM)
    novo-nordisk

    • Living with T1 diabetes and bringing awareness
    • T1 and T2 can be helped, dealt with and he’s trying that
    • Cycling team focused on it
      • Full team is athletes with diabetes
        • triathletes, runners and cyclists

Blast to the Past – Past Drives Future Growth (Notes from June 17 to June 23, 2019) July 9, 2019

Posted by Anthony in Uncategorized.
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I’ve included a few repeat guests but from different podcasts. Fun to see how different the discussion can be with a different host. So, if you’ve been following along, hope to hear that you recognize Eric Topol and Joseph Jaffe’s names.

I was quite intrigued by Archit Bhargava’s work at Niantic in marketing their games further, along with the creative process behind how they started. Niantic did Pokemon Go – and what went in that from starting with the maps and what game may have worked (some… ~10 years later). The Crew communication app also had a fascinating introduction story to get to where they were – from sitting in a tequila bar coming up with the name to finally developing an enterprise communications app.

Then, there was a number of data science-centered episodes (of course). A16z had a discussion in ML and AI for medicine – how we see it, where it stands, where it’s weak and should improve. Back to the future was also a method for the Endangered Language Project where 2 contributors were on Data Skeptic discussing their research while at USC going through NLP on languages that are losing speakers/writers/people to pass it on.

One of the most exciting and energetic guests were the co-founders of Bulletin Space, though. Two women who eventually decided to make their brand a woman-centric platform focused on products by females for females, and providing them space to do great work.

Hope everyone enjoys!

  • Archit Bhargava, Head of Global P/Ming at Niantic Inc (Work of Tomorrow)
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    • Discussion of Harry Potter game after Pokemon Go
      • Social aspect of exploration
      • Partnering with cities and maps points of interests
    • Revenue model – in-app purchases vs sponsored placement of gems / pokemon
      • In Japan, partnered with McDonald’s
      • US – Starbucks and gyms
  • Joseph Jaffe (@jaffejuice), author of Built to Suck (Wharton XM)
  • AI and Your Doctor, Today and Future (a16z 6/13/19)
    deep-medicine-cover

    • With Eric Topol (@erictopol) (author of Deep Medicine) – cardiologist and chair of innovative med at Scripps Research, Vijay Pande (@vijaypande)
    • Didn’t expect AI and medicine to be such back to the future – outsourcing so many things that could get us back to the 70s and before
      • Doctors spent more time with humans, patients due to big business, EHR, admin wants more “efficiency”
      • On Twitter – kid drew a drawing of going to doctor – it was a doctor with his back turned typing on his computer
    • More tech is less computer – fundamental problem, not even drawing eye contact
      • NLP can already liberate time, some UK emergency rooms, as well – eliminate the distraction and data clerking
      • Encouraging to have the speed/accuracy for transcriptions, ontology and organized data
    • Google AI  on improving the voice processing
    • Min discussion / comm b/w doctors for treatment/diagnoses
      • In his book, he went through his knee replacement surgery – orthopedist wasn’t in touch with his congenital condition
        • Logistics and coordination for computers – for thyroid cancer, maybe would need endocrinologist with oncologist
      • How do computers know things that we don’t know now? Complementary – big data has appetite for it (humans – contextual)
    • Radiologists have a false negative rate of 32% – ground truths for x-rays / scans that it won’t miss – basis for litigation (missing some)
      • Best use of time for doctors would be understanding and discussion with patients
    • Diagnosis in general – once trained, doctors are wedged into their diagnostic performance for their career
      • Kahneman’s System 1 + System 2: if doctor doesn’t think of the diagnosis in first 5 minutes, they have an error rate of 70%+
      • ML is reflecting system 2 since it’s trained off of doctors doing system 2 – but with an aggregation of 1000s
    • Up to 12mil errors in medicine a year – can improve upon this, easily
    • Negative components potentially:
      • Can’t trust unilaterally, need oversight
      • If FDA approved, have to watch for cohorts – deep liabilities, ethics, privacy issues – have to be tradeoffs and considered
    • Rolling out AI – NHS is the leader in genomics (ER rooms without keyboards), China with scale and advantages – data on each person
      • Limitation of data in the US and otherwise, no strategy here as well – other countries have a lot of resources spent / proposed
      • Education and training has a full wing for AI in the NHS
    • Professional organizations have not been forward thinking – maintaining the reimbursement for their members
      • Worst outlier, outcomes and mortality – worst, especially due to spending ($11k per capita)
      • Naivete of diet and having the same diet – not just glucose responses, but triglyceride tracking – non-normative responses to same thing
    • Wiseman Institute in Israel cracked code on promoting health – glucose, lipids in blood – eventually see outcomes / prevention by diet
      • Numbers of level and data for each individual – specific bacteria and the sequences, physical activity, sensors for stress, sleep
      • Need hundreds of Ks of people to learn more and on a broader spectrum
      • Can give retina picture to Intl retina expert and it’s 50-50, but an algorithm is 97%
        • Polips in colonoscopy, K level in blood thru smart watch w/o blood
    • Why did people go into the medical profession in the first place?
      • Care, helping people and seeing people – but now have highest suicide, burn out and everything
        • More depressed which leads to more errors and cycles
    • Could do remote monitoring, for instance, for all of non-ICU patients
      • Hospitals won’t allow it, they’d be gutted. Hospitals are problematic – 1 in 4 get injured or sick.
      • Only quick adoptions are enhancement of revenue (think: robotic surgery rooms)
      • Comfort of own home – can sleep, see loved ones, clearly cheaper (average is $5k / night)
    • Cardiologists thought you’d have to look at the QT interval – only 1 part
      • Flunked with the algorithm – Mayo Clinic wanted all data and use the full cardiogram
      • AI / ML already have a great driver detector
    • Easier for machines to do new things with no regulation – rare cell detections, genomes
      • Imagination is our limit / machine limit (unsupervised learning limited by annotation, for instance)
      • Prediction has not done as well as classification, clustering (uses his stepdad as an example, who was resurrected)
    • Not there yet for multimodal algorithms – doctor doesn’t have to do typing – AI figures out diagnosis
      • When you go to see a doctor, you want to be touched – the ‘experience’
      • He doesn’t use a stethoscope anymore, he uses a smartphone ultrasound for EKG – shows the patient in real-time
        • Tools of the exam may change, but interaction will be intimate still – have to get back to this
  • The Death of a Language, Endangered Language Project (Data Skeptic 6/1/19)
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    • USC students research Zane and Leena, CS / App Math and CS / Cog Sci
    • Using unsupervised learning to assist classifying pho (basic unit of sound in speech) names of endangered languages with PyTorch
    • Last living speaker of a language dies – globalization has rid the world of a number of languages (Latin, inc)
    • Helping linguists and a sociological effort to carry on the language – Zane’s father speaks a dying Italian dialect (Venetian, so not living)
      • Very similar to Italian just from listening to audio but has different conjugation / words for some
    • 3.5 hours of audio from 4 speakers collected by their professor in an area near the Northern Italy
      • Most valuable for research – more speakers to improve dataset
      • Output as recommended start and stop times, unsupervised labels for the times – rec time for pho name
    • Slicing audio file into many small segments, labeling them and then combining the adjacent segments
    • Built classifier with an NN – series of vectors (condensed, auto-encoding of audio data)
      • 7000 spoken languages but estimated that half will go extinct by the end of the century
      • Manual transcription is tedious, so hoping it will assist linguists in proscription
  • Three-Legged Stool, Chuck Akre – Akre Capital founder (Invest Like the Best, 6/18/19)
    chuck-akre-1024x1024

    • Managing $10bn after forming firm in 1989
      Being in “one-stop town” quality of life, not being disturbed by outside events or people

      • Distracted or curious by friends, their thoughts – he spends a lot of time reading vs screens
      • Thing that disappointed his son, a tenured professor without luxury of being highly select
        • best students (those that got A’s) wanted to only know what would get them an A, rather than have curiosity
    • 3-legged stool as more stable than 4 legged – can deal with uneven surfaces
      • Rates of return in common stocks were higher than any other asset class in unlevered case
      • “Once a guy sticks his hand in your pocket, he’ll do it again” – human behavior happens to be antithetical sometimes
      • Legs: quality of business enterprise, quality and integrity of people running it, what is their record for reinvestment and opportunity for it
    • Own exceptional businesses, don’t sell them
    • Bandag – “tire business” but looked at returns on capital and they were 3-4x everyone else
      • Wanted to figure out what business it was in – Marty Carver (founded by his father) was a different feel
        • Retreading bus and truck tires, early 70s had tanked oil + petroleum so dealer’s had skyrocketed costs
      • Bandag passed on savings to their dealers in the evidence that they had to reinvest the money in their stores – new ones, franchises
      • Created huge dealer loyalty – trucks/buses’ tires are constructed so that they retread 2-3 times
    • Weren’t smart or quick enough to get into FANGs or otherwise – couldn’t figure out the value creation in quick span
    • Mastercard March 2010 – during Dodd-Frank, Congress act, Durbin amendment – Mastercard/VISA selling at 10-11x
      • Discovered operating margin on returns over capital “not enough words that were superlative enough” – still above average after cutting 50% twice
      • Everybody wants some of that – jamming every expense into the income statement to reduce how good margin is
        • What’s causing that? How do they have it?
    • Wall Street – wants transactions in general (his biz model – compound capital) – create false expectations on earnings estimates
      • “Miss by a penny, beat by a penny” – gives them opportunities since markets behave irrationally
      • Dollar Tree as 3 major players and that was it
    • How do you measure whether you’ve been a success at running this business? Or we hit our earnings target or board goals, etc.
      • Impact of compounding economic value per share. Not trained to do that.
      • O’Reilly as duopoly and buying and deleveraging – capital allocation change / International Speedway
    • Growth of antennae – American Tower Corp (buying in Africa recently) – 5G won’t be here soon, but they’re acting as gatekeeper
      • Microsoft as the OS toll
    • Collecting datapoints and making judgments on them in general, whether you’re an English major, pre-med, investment management
      • Reading business biography learning behaviors
    • Land conservation plan / donations
    • What is the source of pricing power for each company?
  • Named Entity Recognition (Data Skeptic, 6/8/19)
    • Entities as core features of a sentence, idea
    • Text file analyzing or software doing a good job of named entity
      • If you give labelings, some are from computer vs English majors (Turing test)
        • Using SpaCy for NER – hard problem, different expectations but not great – just good
    • Chatbots seeking NER – flight example, for instance – pull out things that are mentioned
      • City is destination, airline mentioned
    • BERT can do NER pretty well – Google Assistance and chat interfaces have been improving
      • Semantic web projects can pull entities out of documents and connect them in knowledge graphs
      • Transfer learning – pretrained model on generic model and use that as jumping off point
  • Carmax: Way Data-Science-powered Car Buying Should Be (BD Beard, 5/28/19)

    • Tod Dube, Chief Architect for Data Science at Carmax
    • Adding 1 store per month, no. 3 wholesaler (to Barrett Jackson, eg), $18bn in rev, #1 used car
    • Determining pricing is through ML, but now omnichannel – looking/exploring cars interactions
      • Customer service buying exposure
    • Changing how data scientists go about their job – laptops with minimal compute power, governance issues trying to fit onto laptop
      • Analytical leadership to push tech to do things better – how to make availability
        • Security, data losing, privacy, model
      • Shift data and move data around but if data moved in 3 weeks – how can you iterate easily
    • Architectural changes from laptop / personal side to service and data warehouse pulls / data centers
      • Azure service response – pick use case, can’t swallow the elephant (replatform rec that were done today – handwritten code)
      • 2 week sprints for changes before – different cars, reasons, prices and availability
        • What tools could help? SaaS, subscription to bridge the gap – Had python (Jupyter, Spyder, Anaconda) / R
      • Started a data lake because of use case
        • Had to pivot and find data scientists (Type A – analytical, business; Type B – data engineer, why model is necessary for data)
    • Consulting partners as unsung heroes to figure out how to build out a team or look at problems
    • Spark as a Service, Spark as data lake, DataBricks (Delta Lake), Azure customer
      • Will auto finance almost any cars, call centers – better enabling customers in financial choice
    • Walk-on song for conference: I’m Not Afraid by Eminem
    • Spends money on tech, iPad Pro new now, MacPowerUsers (how their workflow is)
      • AI, weather on sprinklers for rain predictions
  • Ali Kriegsman, Alana Branston, co-founders of Bulletin (Wharton XM)
    bulletin

    • Switching from platform with competitors like Etsy, Bazaar to drive sales, initially
      • Had creative, original content and hooked brands up with some unused channels/media
      • Asked brands/customers after > 100 brands – ‘peak’ initially
      • They talked about how valuable, but expensive, physical space was – pop-ups individually, Brooklyn Flea, etc
    • Decided to do pop-ups in big parking lots – ineffective, felt the heat – literally (12k sq ft in parking lot outside)
      • Shrunk it and rented out a front space from a bar – charged $300 * 30 brands for pop-up for a weekend
        • Worked for both brands and them – realized they could do that ~10 months
      • Grinding for the year, made money equivalent to month of prior sales, but 7 days / wk wasn’t scalable
    • Finetuned branding for pop-ups to female founders, female products (had men originally)
      • Best products at time were stamped necklaces, ready-to-wear clothing increasing
  • Sucharita Kodali (@smulpuru), Retail Analyst – Forrester (Marketing Matters)
    forrester
  • Danny Leffel, CEO, cofounder of Crew (Wharton XM)
    0ed3222e-7f0e-4606-9e27-789e09b4f110-1548112861887

    • Communications app for everyone on professional page
  • Bryan Murphy (@bryanpmurphy), CEO of Breather (Wharton XM)
    breather_website_logo

    • Talking about the optionality to get working space

 

 

 

 

  • Dan Widmaier, CEO cofounder at Bolt Threads Biotech (Wharton XM)
    nav.logo_

    • Using spider silk and attempting to synthesize stronger proteins for apparel, clothing
    • Tie was the first – needed a quick demonstration
    • Have gone on to other materials, solving environmental waste of apparel

Different Ways to Create (Notes from June 10 – June 16, 2019) July 3, 2019

Posted by Anthony in Digital, experience, finance, Founders, global, Hiring, Leadership, NFL, questions, social, Strategy, training, Uncategorized, WomenInWork.
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3 fantastic sounding women to start. One in VC and finance, discussing the difference between NYC and SF for her. The second compared in-house marketing strategy and outside influence. What’s that look like? How much control is there? Last, but certainly not least, was an author who discusses something that I’ve seen with family and my sister – the challenge of raising a child while balancing some semblance of normalcy in work. What’s expected from yourself? What should be reasonably expected from work? What’s a balance?

Those women: Erin Glenn, Julie Scelzo and Lauren Smith Brody.

A few sportsmen discussed data and capital. Sixers Innovation Lab and former exec for And1 mentioned how they think about growth in Philadelphia and the brand, who can they support in the community that can also help with the team. John Urschel, former Baltimore Raven, is a published mathematician now who discussed the influx of data collection and analysis among all sports and teams. What they can do makes a great athlete experience, fan experience and overall performance improves.

A plethora of rising stars followed, from Kanyi of Collaborative Fund to Sofia Colucci of Coors and the co-founders for SHINE text. Hope you enjoy my notes and you check out the podcast episodes!

  • Erin Glenn (@leeeringlenn), CEO of Quire (20min VC FF025)
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    • Entrepreneur as kid – day business for summer camps, then management consulting, IB and took a company public (econ consulting firm)
    • Got bug to start own thing in 2010 – joined KIXEYE in SF for 4 years, video game company
    • Wanted to go to NYC (as kid in OK) – went to meet w Betaworks, fell in love with Quire
      • Mutual conv to join Quire – loved it – equity crowdfund co
      • Venture-back co’s enabling portion to raise for community & mission
        • Min. investment is $2500 – supporting larger investments as well, up to $250k
    • Likelihood for investors to get taken advantage of – Title III discussion (investors with <$100k income/net worth can invest up to $2k or 5% of income)
    • Mattermark study on investor bases that exist and why people do invest
      • Investor and diversity – minority, gender, big differences in those that follow Mattermark or others
    • Crowd won’t provide scaling / grow money (the $50mil+ rounds), but community can help participation at a lower level
    • Motivation to invest, other than financial incentive – supporting company’s mission + founders, spurring economic growth + innovation
      • Real commitment to realize dreams, grow economy
    • Benefits with crowd investing for company – moral and psychological
      • Supporters of the company can invest, which is reinforcing for doing it – customers that are owners of the business spend more, loyal, etc
    • SF vs NY startup ecosystems and CEO role
      • Had joined Quire with 2 suitcases, dog and air mattress after 2 days there
      • CEO role – really fun and exhilarating with challenges daily, gained confidence at eliciting feedback from ideas
        • Coming up with better solutions and getting them to help because we don’t have all answers
      • Intensity and vibrancy, competitive spirit in NY even though it’s smaller-feeling
        • Want to take on SV and not give up the competitiveness
        • More female founders in NY – fashion, finance, media in senior executives trying new things
    • Favorite book: Magic Mountain ahead of WWII in Europe, Switzerland
    • Favorite blog: Fred Wilson’s and Tim Cook as favorite innovator
    • Gimlet Media (first investment), Kano, Duel as others
  • Julie Scelzo, executive creative director at McGarryBowen (Wharton XM)
    mcgarrybowen-logo-2

    • Talking about marketing difference between in house and outside
      • Going from Creative MD for Pandora to take on MGB AMEX
    • Moving from agency to internal at Facebook – not even a salary bump, but just felt right
      • Worked helping clients was rewarding but she missed creating
  • Lauren Smith Brody, author of The Fifth Trimester (Wharton XM)
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    • Discussion of parental leave in the workplace – if uneven with your partner, mixing it up or staggering
    • First 6 months as crucial for development – how to best alleviate this
      • Every person is different and has different attitudes
      • Nobody can generally be told how something may feel for them
    • Having the partner available in the first 6-9 months provides evidence that they’re capable, and can understand some of processes
    • First day of work being scary – moreso as a parent – train whole life to be in workplace
      • Can be comforting back at work, not so much for first days as a parent
  • Dilip Goswami, Molekule Air Filters (Wharton XM)
    • Being his father’s son, a typical engineer
    • Developing and deciding what part of product to have in house vs outside
      • Hybrid model
    • Having customer support and knowing it worked – shipping and using that as validation
  • Seth Berger, founder and CEO of And1, Sixers Innovation Lab (Wharton XM)
    170718_innovationlab

    • Discussing how coaching basketball to young adults was so helpful
    • Marrying And1 with his passion for basketball and teaching and being around it
    • Sixers Innovation Lab – knew Josh from the 90s working on a failed internet co originally
      • Helping with capital up to $1mn and seeing 10x returns so far
  • John Urschel (@johnCurschel), Former lineman with Ravens, MIT mathematician (Wharton XM)
    • Talking about the lifelong balance of math / football from his memoir
    • Thinking about where analytics may be super exciting in sports – real-time strategy if they’re allowed the computers / data on-field/court
      • Tracking data is so strong, it’d be interesting to see what coaches may do to get there
  • Nathan Furr, Curtis Lefrandt, Innovation Capital author (Wharton XM)
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    • Author discussing how innovation costs resources
    • Talking with Marc Benioff and others for the most innovative leaders

 

 

 

 

  • Sofia Colucci, VP Innovation of Miller Coors (Measured Thoughts, Wharton)
    • Introducing a new brand, Cape Line, into the world
      • Usually a 1.5 – 2 year process for a corp this size
      • Cut it down and released in 2019, dropped the other project (Project Sprint)
    • Had already done market research, wanted a more healthy, alternative to beer for women – cocktails in a can
      • Packaging and what that would look like after tasting
  • Jennifer Pryce (@jennpryce), President CEO of Calvert Impact Capital (Wharton XM)
    • Impact capital and how they grade different companies on the degrees for investment
    • Infrastructure, seeing them surpass $1bn
  • Marah Lidey (@marahml), Naomi Hirabayashi, co-founders of SHINE app (Wharton XM)
    246x0w

    • SHINE as a wellness app for meditation
      • Gaining ground with their superusers – seeking feedback
    • Self-care platform, weren’t sure how they attracted so many men – but it’s definitely catered to their experiecne
      • Reached out to one of the first superusers that was male to get his input and to have influencers help
    • Product-market fit and development was always based on how they wanted the app to be- what they were searching for
  • Kanyi Maqubela (@km), Partner @ Collaborative Fund (20min VC 094)
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    • From South Africa originally, investments into CodeAcademy, Reddit, AngelList, AltSchool, TaskRabbit
    • Founding employee of Doostang, attended Stanford Uni & worked on Obama campaign in 2008, as well
      • Dropped out of Stanford, compelled by interest to see other part of world – did a startup, $20mil of VC funding for a couple startups
        • Being young, decision to leave was easy but once he’d left, it was tough
        • Making friendships and lasting connections easily in college – some communities outside, in pro world, was rough
      • Met his partner, Craig, while finishing school and doing work in design – convinced him to help him with CF
    • Investors are those that believe in collaborative economy – nodes, peer-to-peer and nodes for networking
      • Every consumer/employee/companies have obligation to align interests and value sets
      • Looking at companies to focus on impact and values – aspirational culture as outcome of collaboration
    • For the fund – stage specialization or theme?
      • Theme may be time-efficient-oriented. Reminder that many of most successful people have skipped on massive wins multiple times over.
        • Altman mentioned about having a point of view and heuristic to drive decisions (whether it’s stage or theme)
    • Being a partner at 30 – GPs with skin in the game
      • As young, have to have been very successful early or came from money to get into the fund
      • Needs to prove himself but as younger, may have been very risk adverse in the sense he wasn’t free-swinging
        • Facebook went public 7 years (quick for industry, but not necessarily quick for a fund) – feedback loop timeframes
      • Million ways to market as investor, drive value as portfolio, data, theme or stage specific
        • Blog as high leverage marketing for himself, writing is how he clarifies his ideas to himself and the public
    • Limits and is very prescriptive for the networking aspect of VC, conferences – wife in medical school so when she’s free, he makes himself free
    • Accelerator / demo days as good for investing – he likes being first institutional round, but thinks demo day to discover is not their best way
      • Sometimes the due diligence for demo days of seeing what’s out there
      • He uses them to talk to other VCs, see source and deal flow – coopetition – high leverage, high marketing channel
      • His best way in is likely the portfolio companies under them – he looks for connections for new places and vouch for them
    • Naming Fidelity markdown of a bunch of companies – saying that private companies are being treated like they’re public companies
      • Realtime prospects that are valued – can go up or down, financing or not
      • Private crowdfunding to create liquidity, getting to cash flows and thinking about dividends, debt, crowdfunding – IPO bar is so painful
    • Fav book: Brothers Karamazov – Dostoevsky as “fiction bible”
    • Union Square Ventures as the one he looks up to – Benchmark, also (Read ebooks)
    • Concept of Founder-friendly – agency from founders holding them responsible, but becomes messy / complicated
    • Most recent investment at that time: CircleUp was series C, crowdfunding platform for CPG – other forms of financing for orgs will be transformed

Innovative Investing (Notes from June 3 – June 9, 2019) June 25, 2019

Posted by Anthony in Automation, cannabis, Digital, education, experience, finance, Founders, global, Leadership, medicine, NFL, questions, social, Strategy, training, Uncategorized, WomenInWork.
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The primary theme of the week seemed to be how data can get pooled together to determine a signal and how to learn to seek the best way we, as individuals or teams, can discern valuable content to motivate actions on that information. Data is plenty – it’s a matter of gathering, curation, analysis and testing before putting it into action. This is done by any number and types of companies nowadays – this is a source of advantage seeking that forward-thinking ones make, in my opinion.

Since my notes were more detailed, I’ll try to keep this brief. The wonder people below hailed from banks (First Republic Bank), funds like Emerson Collective and Womens VCFund, marketing company like BEN or LikeFolio and then David Epstein’s Range, Sinead O’Sullivan’s work on space or the data Rohan Kumar collects with Azure Data.

Create a hypothesis. Test the hypothesis. Put into action, or iterate. Rinse, repeat. Good luck!

  • Samir Kaji, (@samirkaji) MD @ First Republic Bank (20min VC 093)
    first20republic20logo_gkg

    • Leading private bank and wealth management, before at SVB
    • 1999 – “anyone with a pulse could get a job” but he was working selling vacuum cleaners at dept store
      • Was told by family to get a real job – applied to first business SVB, got resume in and interview immediately before starting
      • First couple years were tough – learned a lot, but was 2004 until companies had scaled and were getting bigger
    • First 10 years were tech companies, series A and B and venture debt – post 2009 Lehman / Bear, went to venture group at SVB for 4 years
      • Made the move with a few others from SVB to First Republic, now leading team in micro-VC and early-stage tech co’s
    • Says the micro-VC is more entrepreneurial & collegial compared to extended stage VC’s
      • First fund is that you can get traction for a second or third one, fees as pressure – most likely why many people come from some wealth
        • Writing large checks as GP, as well
      • 2-2.5% management fees initially vs 1 / 25 or 1/30 model
      • 1999 – 2002 distribution was 0.9x and you’d get 10x return (whoops) – very difficult for funds to get 2-3x for LPs
    • Barriers to entry much smaller for $20-25million as compared to $500mln – institutional, etc — he can go to family friends and high net worth
    • Seed over next 5 years: contraction in space (wrong), but said there isn’t enough returns for funds to max it
      • 1100 in the 2000 year and burst
      • Continued prominence of Angelist platforms, maybe an integral part of the ecosystem
      • Starting to see use of data (Mattermark, CBInsights, SignalFire) to more efficiently identify and action at this level
    • Favorite book is Phil Jackson’s – behavioral psychology, Give and Take is another one
    • Really respects the pioneers of the industry and first-time fund-raisers
      • Mike Maples, Michael Deering, Steve Anderson, Jeff Clavier when it wasn’t a thought
    • Habit – reading book or blog post for 20min in the morning before email
      • Disconnect from audio / video devices and reflect for an hour
      • 2 hours a day for family/friends and disconnecting, as well
    • Thomas Redpoint, Mark Suster, Brad Feld, Strictly VC, Ezra at Chicago Ventures
    • Knows awesome fundraisers but terrible at returning capital – didn’t mention any
  • Collectively Driving Change, Laurene Powell Jobs and Ben Horowitz (a16z 5/27/2019)
    emerson-full-logo

    • LPJ – founder, president of Emerson Collective
    • Grew up in NJ – father passed away in a plane accident when she was 3 – 3 children.
      • Mom remarried so there were 6 of them. Wooded area of NJ.
      • Core values and dedication to education to get out of the area.
      • She went to Upenn – first student from her high school that went to Ivy League – ~20% went on to more schools
    • Addressing East Palo Alto school as a volunteer to help – 1st talk, 0 had taken SATs
      • What happens when you’re first to graduate high school? What’s it mean to the information from family?
      • What happens to be first to want to go to college, thrive&complete it?
        • To have the aspiration, can be a leader in the family – translator, get sucked into all problems
      • Started with 25 freshmen – would have to come with friends for responsibility mechanisms – for College Track
        • 3000 high school students, 1000 college, 550 grads
    • Collective of leaders, innovators – education inequities, access and need for enhanced/robust curriculum
    • 10 year time horizons – getting them together is scheduled with Monday all-staff meetings (3×3 matrix of videos)
      • 5 cities, sometimes philanthropic speakers or reports
      • Discussion of reading as you fall behind through third grade before switching to reading to learn – already behind
    • XQ as SuperSchool dream – 17 of 19 will open in August
    • Caring about impact and solving problems, not wealth increasing – wants access to policy or money and not taxes
      • Judged Giving Pledge for not wanting to be more philanthropic
      • Environmental, edtech portfolio, cancer / oncology investments, immigration incubator, new thinking to old problems
    • How do you know when you’re succeeding? Collecting data on everything they do.
      • Example: XQ – schools and districts, state of RI as switching to statewide competition
      • Chicago has good data for fatal/nonfatal deaths (I disagree)
    • Imperiled or important institutions like journalism and media need to be sustained, how many join?
      • Concentrating and following where IQ is migrating (hahaha – what a joke)
  • Data Infrastructure in the Cloud, Rohan Kumar at BUILD conference (Data Skeptic, 5/18/19)
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    • Corp VP of Eng of Azure Data Team at Microsoft – SQL and data services, open source, analytics, etc
    • Trends in data engineering in the cloud, serverless and hyperscale
      • ML and AI and enabling applications – shifting to edge vs cloud – analysts predict 70% will be on edge devices
      • Solutions and private edges – training in the cloud and deploy them on the edge applications
        • Data platform needs to be the right foundation
    • Highlight for him from conference: work they’ve done on relational databases in the cloud – as volumes grow, scalability challenges
      • Hyperscale for Azure and PostgreSQL, as well as MS SQL soon enough – system scales with needs (they’ve tested <= 100TB)
    • Acquired Citus Data, support scaling out the compute layer – strong team, great product, matches in Azure and open-source
    • Releasing serverless option for Azure database – costs designed to stay low and optimized
    • Analytics side: customers wanted to do real-time operational analytics – didn’t want to move them outside of their core product
      • How is data distributed and having compute be co-located with the data to gain Spark efficiency being nearest to node
      • Support Jupyter notebooks across all APIs to modernize to do more predictive analytics
      • Attempting to build out pipelines requires too much scripts, instead have Data Flows in Azure Data Factory – no-code and UI
      • Wrangling data visually and seeing if something can be recognized or learned to repeat across other columns/tables
    • Latency won’t be ideal if compute nodes occur nonlocal to the data changes – can’t do 50,000 nodes all at once
    • Excited for the future: Horizon 1 (next 8-12 months), Horizon 2 (~3 years), Horizon 3 (moonshots)
      • H2: Hardware trends, what do customers want? Pushing boundaries of AI and ML, healthcare, gaming, financial services, retail
  • Wide or Deep? David Epstein, author of Range (Invest like the Best, 5/28/19, ep. 133)
    • First book’s research lead him to get into specialization and finding kernel for next
      • Some countries: turning around national sports teams – why don’t we try other sports? Contrary to 10,000 hour rule.
      • SSAC – debating Gladwell – athletes have a sampling period instead of first gene – delay specialization
        • Used Tiger vs Roger – Roger had tried a ton of sports vs Tiger who was born and was playing golf
    • He was not good at predicting what people/public would attach themselves on to – 10,000 hour rule – race/gender as most talked (but weren’t)
      • 10,000 hour rule were based on 30 violinists in world famous music academy (restriction of range)
      • Height in American population vs points scored in NBA (positive correlation) but if you restrict height to NBA players, negative
    • Finnish cross country skier who has genetic mutation similar to Lance’s boosted
      • Sensitivity to pain and modification to your environment – also sudden cardiac arrest in athletes (what pushed his interests)
      • Book as opposition to Outliers and Talent Code – interpreted a lack of evidence as evidence of absence (genetics matter)
        • First year he read 10 journal articles a day and not writing – they were making conclusions they could not make based on their data
      • Differential responses to training – best talent were missed because we don’t know about training responses
    • Collection and exploration phase – competitive advantage for expansive search function to connect sources or topics
      • Has a statistician on retainer, essentially, to check models or surveys
      • Wanted to know what he was missing – “how come I broke the 800m women’s world record after 2 years of practice? – genetic difference”
        • Racing whippets – 40% had a genetic defect that gave them more muscle and oxygen
    • All of sports as a limited analogy (problem after Sports Gene; now, more tempered)
      • Robin Hogarth addressed “When do people get better with experience?” Don’t know rules, can try to deduce them but can’t know for sure.
      • Kind learning environment: feedback immediate, steps clear, information, goal ahead
      • Wicked learning environment: can’t see all information, don’t wait for others, feedback delayed/inaccurate
    • Study at Air Force on “Impact of Teacher Quality on Cadets”
      • Have to take 3 maths – calc I, II, III (20 kids randomized) – professors best at causing kids to do well (overperforming) systematically undermined their performance thereafter
        • 6th in performance and 7th in student evaluations was dead last in deep learning
        • Narrow curricula were better at the test that they had at the end would be negatively correlated with going forward in performance
      • Teachers that ignored what was on the test taught a broader curriculum (making connections vs procedures)
    • Learning hacks: Testing (wonderful – primed to test ahead of learning), Spacing (deliberate not-practicing, Spanish ex spread 4 hour twice, 8 hours), Mixed practice
      • Ease is bad – known time horizon for when you have forgotten again – interleaving and spacing mixed
    • Passion vs Grit (“Trouble with Too Much Grit” – Angela Duckworth’s research)
      • Duckworth did a study at West Point for East Barracks cadets – candidates score (test + leadership + athletic) was not good prediction of doing this (overall it was good)
        • Grit was a better predictor for making it through East Barracks – she questioned whether it had an independent aspect
        • Variance for grit was probably 1-6%, especially after “flattening” groups – looking at people that had a narrowly defined goal for short periods (cadets or spellers)
      • Cadets were scoring lower on grit at late 20s vs earlier – tried some things, learned others about what they want – grit is poorly constructed
        • Look holistically – if, then signatures (giant rave – introvert, small team – extroverts) right fit looks like grit – developmental trajectory as explosion matching spot
    • Choosing a match for a future them who they don’t know in a world they can’t comprehend – people that find good fits (in practice, not theory)
      • Paul Graham’s “Commencement Speech” that he wrote “Most will tell you to predict what you want in 20 years and march toward it.” (premature optimization)
        • Everything you know is constrained by our previous experiences – limited as a teenager – just expanding and learning as you go forward
    • Gameboy example – with so much specialized information that can be disseminated easier – can take from all types of domains and recombine them
      • System of parallel trenches – can be broader much easier now – hired people for Japanese and German translations
      • Japanese man profiled in his book – technology was changing faster than sun melts ice – didn’t get Tokyo interviews
        • When he got to Kyoto company making playing cards, he was a tinkerer who was maintaining machines – started to mess with them (arms)
        • Turned them into a toy, and it was Nintendo – cartoon-branded noodles (failed), and had toy development
          • Lateral thinking with withered technology – stuff that’s cheap, easily available – takes into other areas
            • Remote control, more features – wanted to democratize this and strips it down – LeftyRX only left-turns
        • Sees calculator from Sharp and Casio and thinks he can do a screen and handheld game – small games
          • Had issues with Newton’s rings so he found other small tech (credit cards embossed) to fix small pieces
      • What it lacked in color, graphics and durability (could dry it out, batteries would be fine, split it up, “app” developers because it was super easy to understand)
      • In areas that next steps were clear, specialists were much better – less clear, generalists were more impactful – depends on the specificity of the problem
        • 3M had a lot of areas for this, “Periodic Table of Technology” – post-it note came from reusable adhesive that had no use for
        • Only Chinese national woman to win Nobel – “Three No’s” (No post-grad, foreign research, membership in academy)
          • Interest in science, history – Chinese medicine for treatments of malaria – world’s most effective treatment from ancient text
  • Greg Isaacs, BEN (Branded Entertainment Network) (Wharton XM, Marketing)
    Print

    • Discussion of getting data from Netflix / Amazon / Hulu / tv to better match brands and advertising
      • Dirty data via a wharton grad who set up a survey style
      • Cohorts and demographics, along with psychographics
    • After getting data, attempting to approach Youtubers / social media influencers, tv spots and channels or shows to get their brands in front of the right people
      • More pointed, depending on what interests are for their cohorts
      • Creative storytelling as the change of cultural mind shift has increased
  • Understanding the Space Economy, Sinead O’Sullivan (@sineados1), entrepreneur fellow at HBS (HBR IdeaCast #684, 5/28/19)
    • Facebook, Amazon (3000), SpaceX (12,000) and other funding like Blue Origin / SpaceX / asteroid mining or travel
    • Global space economy as $1tn by 20 years – currently $325bn so it would need to 3x
      • Breaking apart space resources and otherwise – earth-focused (delivering or existing in space that helps earth)
        • Exploration or creating interplanetary existence
    • Running out of space in space for satellites – comparing to airplane docking / loading
      • $2500 per kg now to launch, used to be $50k / kg
    • Reliance had been on unilateral agreement for space policy – one tech startup launched a satellite that didn’t have permission (but no fall-out)
      • Food / grocery stores, wifi, phone, insurance pricing due to satellite data – reliance on services are increasing as the market increases
      • Thinks that we’re close to seeing the cheapest cost of launching – cites SpaceX, but won’t allow everyone to participate
    • Ultrahigh accuracy will require higher powered satellites – GPS, nonmilitary grade is ~0.5 m – thinks it will prevent autonomous vehicles solution
    • Ton of money going into asteroid mining but thinks it’s better for testing missions to Mars and figuring out the problems for future
      • Looking at Uber at start and say “people won’t get into a stranger’s car” or other cases as how we see the future – going to Mars, etc
    • Earth-focused space technology – 100+ launched satellite start-ups, micronano satellites, relay companies, downstream analytics
      • More touchpoints for everything in this manner
      • SpaceX will increase public and government intervention and within 50 years, maybe see a human launched there
  • Investing w Twitter Sentiment, Andy Swan (@andyswan), LikeFolio (Standard Deviations, 4/25/19)
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    • 1700+ tweets examined per minute in LikeFolio – discovering consumer behavior shifts before news
      • Direct partnership with Twitter to create massive database and how they’re talked about to look for mentions
      • Purchase intent, sentiment mentions – trends across product categories or brands
    • Example – Delta (as host is a loyalist) – making adjustments
      • Expectations are the relative part – comparison to the baselines (metrics compared to itself as baseline)
    • Put out a comprehensive report on Apple day after keynote event – September 14, 2018
      • Consumers were unimpressed with iPhone lineup – more price sensitive than maybe they’d considered
      • Apple Watch was the silver lining – stock / sales may struggle over 3-9 months (upgrade cycles)
    • WTW version of keynotes – NYE resolutions – subscribing early to drive revenues the rest of the way
      • Purchasing mentions were only up 30-40% compared to 5 or 7x weekly mentions (big difference)
    • Shelf-life and how to consider the sentiment data – lead time may be binary corp event (same store sales or year)
      • Couple months with Apple, for instance, but with Crocs – resurgence that persisted to current time
    • Set up keyword structure and brand database – “I’m eating an apple” as opposed to an Apple mention – human eyes to ‘label’
      • “Closed my 3 rings” – apple watch but sarcasm / spam that wasn’t caught (estimates at 2-3% of data)
      • If spam / sarcasm are consistent portions of the data, doesn’t really have an effect
    • Twitter Mood Predicts Stock Market – Bollen, Mao, Zeng (88% and 5-6% predictions) – fund closed up shortly
    • Advantage being better than analysts or pricing and codifying sentiment behavior compared to past quarters, data
      • Some consumer trends analyzed as true tipping point or actual movements
      • Public prediction before productizing their modeling – made 40 and were 38-2 (confidence as highest)
      • Investing as very specific, concentrated and holding ammo compared to trading with option spreads and has risk profile built
    • https://arxiv.org/pdf/1010.3003.pdf
    • Diversification as 20-25 stocks, doing it over time and with conviction can be done
    • Starting in Louisville for his fintech company, host in Alabama, for instance
      • Talent can be more difficult to seek out but the world is globally flattening via the internet
      • 70% lower overhead cost than being in SF, for instance – developers would anyhow be in Slack channels / not a big deal
      • Reduction in cost maintains greater control of company since they don’t have to take reduction of equity to gather more
    • Network effects don’t matter if you don’t have a great product or product-market-fit
    • Free association game
      • grapenuts: best cereal (Co’s been around for 100+ years, branding and $ spent and they can’t figure it out)
      • Fintech Future: individualization and customization
      • Victory: most important thing in life, achieved what you set out to do – setting goals and achieving these
      • Bourbon: pappie von winkle – collecting for dust on shelf 10 years ago and now going for $3000
  • Jonathan Abrams, co-founder Nuzzel news (Launch Pad)
    nuzzel

    • Landing hedgehog as the mascot – animal as cute, 99designs and surveying 50 friends – 25 men/women
    • Discussing how VC’s don’t have great advice, especially when general – too hard to be an expert in such a wide range
      • Finds it easier to be very context-driven and providing solutions or action-oriented questions to founders
      • Investing now easier with YC and Angelist, etc…
    • Timing and other mistakes he made – out of control, losing equity part early (but depends on where you are / what you need)
  • Etan Green, professor at Wharton (Wharton Moneyball)
    • Discussion on paper of how sharp money comes in at horse racing tracks
      • Difference between sites – fairground action compared to tracks, and specific to region (New Orleans, Minnesota, for instance)
      • Big sharp money comes in very late, pushing the underdog prices to higher values
        • More expensive to bet while at the track than the APIs enabling higher volume bets
        • Books at the track are incentivized to bring in as much $ as possible, so $0.20 on $1 vs $0.15 rebate on $0.20 for volume
    • Value and differences in how people will bet
  • Edith Dorsen, Women’s VCFund founder, MD (Wharton XM)
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    • Talking about their focus on first fund, approach
    • Opportunity for finding diverse founders, 25% of their fund had a woman founder
    • Starting a second fund
    • Had consumer tech, enterprise and not so much b2b, but trying to increase
      • Hard to say or give advice if one of their partners don’t have expertise in the domain
  • Sophie Lanfear, Silverback Films producer on Netflix “Our Planet” (Wharton XM)
    • Species that are dying, going extinct
    • What we can do about it
  • Aliza Sherman, Ellementa co-founder, CEO (Wharton XM)
    logo

    • Discussion of client talks when she made them aware of her cannabis endeavors
    • How friendly the community is
      • Then knocked the idea that ~30% was female to start before diving off a cliff
    • CBD to mask opioids – does it really do anything from a pain/treatment perspective, though?
      • Anti-chemo because of CBD – really?
    • Sounded too rehearsed – made it sound fake, not genuine
      • Passion/motivation/mission and kept repeating as the best advice she could give – painful

Matching Environment to People (Notes from May 27 – June 2, 2019) June 20, 2019

Posted by Anthony in Automation, Blockchain, Digital, experience, finance, Founders, global, Hiring, Leadership, questions, social, Strategy, Uncategorized, WomenInWork.
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In this particularly busy week, I found the theme of the week to be particularly amusing, but coincidentally or not, the dominoes fell that way. Normally, a theme arises like that because everyone is in finance or the same segment or conference is aligning. I just happened to catch a week where the insight that I drew from each person reflected similarly.

Meredith Golden, a dating consultant of sorts, discussed how she assesses all levels of dating profiles for her clients. She goes through a process that she’s dialed in to obtain her optimum level of clients as well as the right approaches to proceed. Asking herself what she wanted was key in determining how she’s grown her business, especially as an entrepreneur and CEO.

Chief Instigator Matt Charney. Now that’s a fun title. And I won’t ruin it. He goes through his past with Disney and Warner Bros and why/how he moved into the HR tech doing marketing – what he saw and how it’s different now. Fascinating and fun segment.

Part of the fun of being an entrepreneur is deciding who you want to do business with. But when it’s difficult, especially at the start, you’re most excited to get ANYONE to work with (unless you luck into that massive customer to start – rare rare rare). This is Kyle Jones of iCRYO found out. Then he gained traction, quickly, and realized he needed to be a bit more diligent in who he wanted to work with – what was ideal for the business, as well as the brand moving forward.

David Epstein likes throwing wrenches, I imagine. He authored the book Range, testing the generalist vs specialist question. As a generalist masquerading currently as a specialist, I appreciated what he was talking about the strength of generalists. But I do understand the place that specialists have in our society, especially deep tech, research and other exceptional areas.

Deb DeHaas grew up under the tutelage of her mother who fought the idea of being an accountant growing up to learn and adapt to the idea of being told what she could/couldn’t do wasn’t ACTUALLY an assessment of her ability to do those things. Such a simple, fascinating concept. She could totally be an accountant, engineer, as she pleased. Took a lot of perseverance but she had a manager at Andersen (before folding) who was a woman and told her to always chase what she wanted – now she’s leading the Inclusion and Diversity team with Deloitte’s Corp Governance Arm. Quite the story of growing up and what she learned.

Not to be outdone, Kim Wilford, who acted as General Counsel for GoFundMe, discussed how she came into her role in charge of the nonprofit arm, and what they’ve done in growing the company and its donations. How to connect marketing, wearing multiple hats and helping people help others. Inspirational while metric-driven, not just dream-built.

I hope you enjoy the notes – a few I didn’t write extra here but had fascinating insights into Happiness Hacking, investing in founders and how they grew companies such as Vroom and GoodEggs. Let me know what you think!

  • Meredith Golden (@mergoldenSMS), CEO of Spoon Meets Spoon (Wharton XM)
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    • Talking about having 6-7 clients
    • Ghostwriting messages
    • Client work depends – assessing / diagnosing the problem
      • Not matching (pictures), profile, messaging, getting them to meet, etc…
    • Metrics based on what the initial diagnosis was
  • Matt Charney, Executive Editor – Chief instigator at RecruitingDaily (Wharton XM)
    screen-shot-2014-06-22-at-2.46.49-pm

    • Talking about workplace and conspiracies

 

 

  • Kyle Jones, iCRYO Franchises (Wharton XM)
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    • Franchising initially – would’ve been a bit pickier when starting but too excited to land first deals
    • Out of 100 franchises, they’ll go with ~5 or so
    • 10 franchises, working on doing a big deal to launch 100+

 

  • David Epstein (@davidepstein), author of Range (Wharton XM)
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    • Discussed how Nobel laureates and creative types are often generalists that spend a lot of time learning / making
      • Stumble on new ideas or concepts in their work
    • Generalists aren’t bad – allow to see a different perspective and combine ideas
      • Think “The Quants” – relationship between corn prices compared to research on _

 

 

 

  • Deb DeHaas (@deborahdehaas), Chief Inclusion Officer, C4Corp Gov Deloitte (Women at Work)
    gx-global-center-for-corporate-governance-new-promo

    • Discussed her mother, who had passed away at the age of 90 recently, who was told she couldn’t be an accountant
      • Wasn’t her role – she pursued it anyhow and ended up being an engineer before quitting and being a community leader
    • Worked in Gulf Oil’s accounting dept and helped her husband through med school
      • First councilwoman in her town, elder at the church
    • Deb started at Andersen until it folded, worked for only one woman but she was taught there were no barriers
  • Bentley Hall (@bhallca), CEO of Good Eggs (Wharton xm)
  • Mitch Berg, CTO of Vroom (Wharton XM)
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  • Alex Salkever (@alexsalkever), Vivek Wadhwa, authors “Your Happiness… Hacked” (Wharton XM)
    • With Stew Friedman, finding the middle ground of tech with children / teenagers and the happy medium
    • How is it that we find some things appealing but others are a burden
    • Facebook being a publishing agency – aren’t they responsible for what the product? “Newsfeed” example.
    • Google Maps or Waze as a hindrance at the local level – dangerous, maybe?
      • Extremely valuable, still, in new places / out of the country, especially
        • Different, maybe, for walking if alternative is talking and communicating with others
    • Problem with Facebook / Whatsapp – Whatsapp unmoderated group chats and only requiring a phone number
      • Encrypted, but what cost? Facebook – for Vivek, just limits to 1-way action
    • Social media as killing people – think India’s problems
  • Ed Sim (@edsim), FP @ Boldstart Ventures (20min VC 092)
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    • LivePerson, GoToMeeting are 2 of his biggest investments as lead, exited / public
    • Started a fund in 1998, DonTreader Ventures – left in 2010
      • Idea was to bring SV style to NY – VCs would look at financials / models, but they looked at people and product – focus on markets
      • Most investors were corporate but cratered after 2008
    • Started a new seed fund for sticking with what he knew as well as recognizing a shift in 2007 for open source and cloud – consumer-based
    • SaaSify vertical markets with GoToMeeting founders who wanted to do new things – $1mln, $1.5mln
      • Enterprise people were looking to get a market for small ~$1mln investments
    • Hated starting a fund – “Fundraising sucks.” – Could find a great enterprise and tech entrepreneurs at seed stage – got $1mln and made 10 inv
      • First 5-6 investments were less than $5million pre-$, sold 4 by 2012 – had option values for series A or being sold to strategic companies
        • Entrepreneurs wanted to sell in those cases, but with cloud, definitely found that it was reasonable and cheaper to do SaaS
    • First / second generation founders or single vs others – “No single founders”
      • As the first institutional round, they’re first big money in. Last few investments were second or more founders – little bigger rounds
      • If first-gen founders, funding rounds are smaller – deep expertise in their field (and have to be engineers building product)
    • “Enterprise can be fucking hard” – have to know the industry – he has 20 years, partner has 10 and new partner as building 5 companies
      • Why he went this route? Started at JP Morgan as building quant trading models as liaison Business QA between engineers and portfolio managers
        • Derivatives models to real-time pricing models – feeds from Reuters or others, risk metrics and crank out the other side
      • Enterprise was exciting to him
    • Could take enterprise founders and redo or build a new company by changing the pain point – customers can be repeat because new pain point
      • Harder to do that in consumer
    • Leads come from founders – roughly 75% as recommendations from portfolio companies (wants to be first thought or call)
      • Helps founders get their pick and decide where to go – if you have an analyst report, may not be a great market opportunity initially
    • Environment of seed funding: Jeff Clovier of SoftTech as one of few microVC’s and now it’s 400+
      • Just want to be hyper-focused and being nimble – main value add as understanding the cadence (2 founders coding together to selling)
      • Stratification of VC – best ones have gotten so large that they can’t write small checks efficiently
        • Entrepreneurs don’t want $5-10mil immediately out of the gate – mismatch, looking for less for less dilution
      • Deal flow of crowdfunding: says sometimes they will leave $250k after leading for AngelList or building new relationships
    • Jason Calcanis blog Launch Ticker, trend as rise of the developer (multiple people in company using same thing – buying licensing)
      • Messaging as another interesting trend in the enterprise space – his most used app – Slack (SlackLine – private, external channels)
    • Most recent investment – stealth investment in a repeat founder (founded and sold before) – security focused on developer
  • Kim Wilford, General Counsel at GoFundMe (Wharton XM)
    go_fund_me_logo_courtesy_web_t670

    • Talking about joining, hadn’t considered nonprofit space
      • For profit arm and the nonprofit
    • Mentioning pushing marketing and following metrics for raising vs donations
    • Can influence news stations and push for higher engagement
    • Done almost $5bn in funding across 50 million donations

How to Humanize Data for Enhancement (Notes from May 20 – 26, 2019) June 12, 2019

Posted by Anthony in Automation, Blockchain, Digital, experience, finance, Founders, global, Hiring, Leadership, NFL, questions, social, Strategy, Uncategorized, WomenInWork.
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I’m going to keep this brief this week, as I’m trying out an added format of posting. I believe I’m going to test Nuzzel news to connect and share the links of articles I’ve read through the week (maybe once or twice – weekend one out on Monday, and another for the week through Thursday?). This post, concentrating on my week’s podcast or segment listens, will still go out. That’s my goal, though.

The week I listened to these, I was actually on my way to Monterrey with my family, though, so I had a solid 90 minutes each way to go through some longer episodes – thankfully, I found Doug’s take on culture and leading a community with Eat Club very insightful, as well as a blockchain discussion by the a16z squad particularly fun.

With the news and media focused on AI, Bias, Diversity and Ethics of ML and scariness of algorithms, it’s good to hear opinions that are focused, but thoughtful on the premise of what is being proposed. In a vacuum, yes, these can be dangerous. However, that’s not often the case when models are being deployed into production. Some are unintentional or started with a simple question of relationships (think Cambridge Analytica and how it started via Likes research on music at Facebook). That’s not necessarily justification for something that clearly had a large impact, but we’d like to know that teams are improving and have that awareness now more than ever before. That’s a positive.

I believe that these episodes, though, take a bit more of a nuanced approach of mathematics and numbers and attributes a human eye that has acquired the necessary expertise to design better models or come up with a better framework for action. We hear that with Dan Waterhouse of Balderton Capital (of a delightful Applied Math degree), who had to learn to apply more of an operational and human/market behavior investor since he had the metrics focus while learning. Then, a fascinating segment with Laura Edell, a sports fan, who struggled to believe that the metrics that were widely accepted as ‘most accurate’ (re: not necessarily max accuracy) included all components of what could be measurable – made some assumptions to test based on twitter/media analysis and coupled it with the data that was widely acceptable to come up with an excellent Final 4 Model.

To continue the theme, not to be outdone, Geoffrey Batt and Nikos Moraitakis each spoke of differing aspects of metrics that they honed in on and ignored the common threads of why those weren’t valid, despite what they saw as opportunities. Geoffrey as it pertained to Iraq investing and Nikos in the form of starting and building a company in Greece, not exactly the traditional hotbed. However, each persisted and are successful today – so there’s a lesson in doing the things that we want to do.

Remember, ultimately, numbers and averages usually take the aggregate, collection of those that may not have had the timing, willingness or ability to push but with enough persistence and support, some will certainly persevere.

Hope you enjoy!

  • Doug Leeds (@leedsdoug), CEO at Eat Club (Dot Complicated, Wharton XM)
    cropped-logo-highres1

    • Talking about going from Ask.com to Eat Club – other companies, as well
    • Quiz leading in was on different likes/dislikes
      • Harry Potter-themed eating pop-ups
      • Anti-spoiler pin (digital, season and episode to avoid conflict)
        • Anything was good that brings community together
        • Said that there were employees at work that took off Monday after GoT finale since they hadn’t watched
    • Delivery people are employees, not contractors – become regulars at corporate events and a part of the culture
      • Help build the culture of the locations – food and how they match
      • Building culture of Eat Club with improv – ability to improve skills there, as well
    • Eat Club numbers – 1000+ companies served, about 25k lunches provided
      • Regional difference of Indian focus in NorCal, Mexican focus in SoCal
        • Acquired an Indian food provider for new techniques – Intero?
        • Acquired another, as well
  • Five Open Problems Toward Building Blockchain Computer (a16z 5/16/19)
    ah-logo-sm

    • Ali Yahya (@ali01), Frank Chen and looking at crypto
    • New paradigm has to improve upon one or two particular ways for new applications, but likely sucks in most others
      • Mobile phone as enabling behaviors for instagram/uber and such with camera and gps in the phones
      • Have to trust the company currently to do what they claim to be doing – trust Google with so much to have the interactions
      • Now, have a computational fabric that separates the control of human power, self-policing and security bottom-up
    • Difference in communication cost – bounded on the end by speed of light
    • Trying to make networking efficient – miners propogating to other miners – blockchain distribution network
      • 1 MB vs 2 MB blocks but can kill some small miners
      • Agreeing on blocks or updates are final
    • Non-probabilistic vs fast – need to be faster than 60 minutes, for instance
      • Improvements on networking layer with Ethereum 2.0, Cosmo and cost or Proof of Stake (vs Of Work)
        • Who gets to participate? PoW requires everyone to compute an expensive proof of work.
        • PoS – intrinsic token that you have to own in order to buy participation, 2% ownership says 2% of the say to say yay or nay
        • Cost of participating is less expensive because it’s intrinsic
      • Practical for everyday use, small interactions between people and machines or people
      • Trust as the bottleneck to scale
    • 3 Pillars of Computation/Scalability: Throughput, latency, cost per instruction
  • Daniel Waterhouse (@wanderingvc), GP at Balderton Capital (20min VC 091)
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    • Sits on boards of Top10, ROLI, Lovecrafts, TrademarkNow etc
    • Was 5 year partner at Wellington Partners and invested in EyeEm, Hailo, Yplan, Bookatable, SumAll, Readmill (sold to DropBox), Qype (sold to Yelp)
    • Break in 1999 by getting to work at Yahoo for about 10 years before getting to venture in 2009
    • Applied Math background, tend to understand complexity and appreciate solutions in technology – different experience for entrepreneurs
      • Learned to be less metric-driven – less obsessed on numbers and data, more human and market dynamics
    • Operators vs career VCs – successful firms take different skills at different times
      • Exit, raising money, portfolio management, scaling, growing
      • Important to watch how a business is grown, whether it’s yourself or by being a long-term investor or close in other ways
    • Entrepreneurship as a career path and as a global one, investors in similar mindset and ambition – can take it anywhere
    • More seed capital and smaller checks than later in Europe at this time – maybe more competition higher stages
    • Thinks that consumerizing SMB software has a lot of room to grow, as well as enterprise software – easier UI-driven tools
      • Developments in AI – mentioned real-time trademark analysis (TradeMarkNow, for instance)
      • How to give great recommendations after gathering consumer tastes and insights
    • Book: The Brain That Teaches Itself – neuroplasticity of the brain
    • The first $10mln you invest, you’ll lose – advice
    • Overhyped sector: food delivery; Neglected: apply behavioral science to tech problems
    • Favorite blog/sector: longs for better content – thought TC was great when it was started, but now it’s Medium individual articles
    • Most recent investment Curious.ai – made it in 40 minutes & ambition was compelling
  • Geoffrey Batt (@geoffreysbatt), Nature of Transformational Returns (Invest Like the Best, 4/9/19)
    • Iraqi equities – history of asset classes
      • Time and patience is a big factor for how you look for results
      • Japan, for instance, 1950 – 1989 100,000% return but now is still below the peak from 1980
    • May have a decade of not working out return-wise
      • Nothing to show for investments, incredibly challenging, especially now – hedge funds or LPs
        • Reporting weekly or daily basis, long-term investment could be 6 months or 1 year – pulling money after first issue
      • Hard to ride out periods of long-term returns (think: re-rating countries)
    • LPs as agreeing to the time horizon – maybe investment committees that are making decisions on career-risk for institutions
      • Iraq to one of those – not likely to get paid off if it works, but if it doesn’t, get demoted or fired
      • Had to approach HNW and family funds – adjacency risk for people next to seed investors (if one is weighted on fund)
    • As student, he majored in psychology – said there was a guy in the seminar class that was a unique thinker
      • Daniel Cloud had co-founded a fund that invested in post-Soviet Russia before doing his PhD
      • Asked Geoffrey to come work for him and learn investment markets
    • Wanted to find next big thing – first, find a place that everyone thinks is awful (in 2007, this was Iraq)
      • Does perception meet reality? How many people dying in the war every month?
      • Country portrayed as “failed state” but oil production was increasing, CPI was 75% yoy but now 5-10%
        • Currency appreciating against the dollar, now civilian casualties in a month were down to 200 from thousands
      • Normal visit to Baghdad – mundane here, out-of-place was that 2 guys in middle of afternoon were playing tennis, kicking soccer
        • Visit companies, stock exchange, meet executives, go to a restaurant, how easy is it to hail a cab, get around
        • Critical process of infrastructure – are people paying in dollars (bad sign), local currency?
    • News media is just not set up to convey complexity to the audience – alienate, progressivism as a service, readers change
      • Experts don’t have skin in the game so they don’t face career risk – betrayal if you suggest otherwise, likely (even if true)
    • On his first trip, mentions Berkshire – early 1990s where they first invest in Wells Fargo
      • Managerial skill in banking is paramount if levered 20:1 (make 5% mistake and you’re done)
        • Don’t want average banks at great prices – want great banks at slightly unreasonable prices (thought about this in Iraq)
      • CEO of first Iraqi bank – unsecured loans to taxi drivers – less likely to take out the loan “between you and I, I’m a cowboy”
      • Entrepreneurs in these areas have to be better than others because of the instability vs the stable environments
    • Stock and capital guys – stock may trade at 3x earnings or 4-5x FCF, top and bottom lines growing at 20% per year
      • Usually just put there as knowing someone powerful but they can be bigger as allocators
      • 2008-09: Size at the time of the stock market – traded 3 days a week, 10am – 12pm on a white board
        • 60-70 companies, maybe 20 suspended from trading because 0 annual report – $1.8bn, smaller than Palestinian market
      • High growth company that is super opaque – can’t meet or won’t meet with CEO, maybe some others that state-owned enterprises that just want to keep paying salaries; maybe 5-10 companies that are investable
        • Equally weighted these companies initially and was still learning – now, he developed relationships and is on the board for companies
      • Does he want to put more $ and concentrate on the companies that he trusts and follows the guide
    • Largest holding for them – Baghdad Soft Drinks (Pepsi bottling and distribution for Iraq) – mixed-owned enterprise in the 90s
      • Local businessman (Pepsi is the dominating market share – ~70-80% vs elsewhere where it’s split) saw it was mismanaged
      • By 2008-09, were going to default on the loan they were floated – businessman bought the loan, fired management & 2000 ee’s, switched equity
        • Within a year, it was fully certified, tripled production, profitable business
    • Now, 5 days a week but still 2 days a week – had foreign investor interest, $5-6bn, couple IPOs successful
      • One telecom has about $1bn market cap, 14.5% dividend yield, 33%+ FCF yield
      • Foreign money came in 2013 but ISIS scared them off – coming back and interest from banks – arranging trips and momentum
      • Key problem – no 3rd party custodians (compared to Jamaica or even in Africa, HSBC or anything) – working on getting one
        • Makes it difficult to bring in foreign money – exchange is the custodian (which is actually safe)
        • No margins, cash-based market and settlements of t+0, no short selling (can’t sell unless have stock)
      • Oil collapse depressed prices and ISIS issue but has been up over last 2-3+ years, cheaper today than when he invested 11 years ago
    • Multiple expansion is the question for returns – 1x to 25x or 4x to 15x – depends on what they are as compounding
    • Kobe Bryant complimented him after a junior year game in high school – already looked at as a superstar – saw Geoffrey was dejected
  • Nikos Moraitakis (@moraitakis), Founder, CEO Workable (20min VC FF024)
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    • VP of BD at Upstream, enterprise sales in 40 countries in 4 continents
    • Wanted to start a company with type of what they wanted – centered around product, engineering company, starting in Greece
    • SMB over Fortune 500 because of product-focused and not corporation or enterprise-based
    • Applicant-tracking systems (ATS) – keep track of arcane process, don’t want to touch things – collaborative processes
      • Simple interface to solve problem of recruiting model (which is still 50+ years old)
    • Problems aren’t location-based – they’re conceptual – designing product, PMF
      • Opening with $500k or 50-200k if needing to get started, not necessarily $5-10mln like other markets or tech hubs, industry
      • Hiring engineers that are good in Greece isn’t so much a problem if you have a good company and network to attract talent
      • Moved to US not for VCs (doing good business, VCs pay attention) but they had 50% of customers without having anyone in US
        • Wanted to start customer support infrastructure, services and otherwise
        • Talked about marketing or accounting businesses on tech that taught companies that it may be worth it to update
    • Metrics that he pays attention to: month-to-month above $2mln annual revenue, ratio of new biz and lost biz
      • Not celebrating fundraising – few drinks but says it’s like having new shoes at the start of a marathon
      • Talking about investors and the relationships built to work together
  • Jaz Banga (@jsbanga), cofounder, CEO of Airspace Systems (Wharton XM)
    airspace-metal-crest2x

    • Meeting Earl, cofounder and maker, at Burning Man – drone being annoying above him while he did tai-chi
    • Prototyping the interceptor drones after seeing military request proposals – had an issue with drone over nuclear subs
    • Can place thermal scans and other security or rescue methods
  • The Transformer (Data Skeptic 5/3/19)
    • Encoder/decoder architecture of vector embeddings word2vec into a more contextual use case
    • Keyword lookup may not work (using ex of bank – river bank vs financial)
      • Humans at 95%+ accuracy, computer maybe around 50%
      • Encoding as correct interpretations and weights for context – emulating process
  • Laura Edell (@laura_e_edell) from MS Build 2019, NCAA predictions on Spark (Data Skeptic 5/9/19)
    build-2019-intro

    • Been at Microsoft for 3 years, supporting Azure for all their customers – quantum physics and statistics background from school
    • ML in cloud for customers – don’t know why they want it, just think it will be useful
      • Ex: image recognition (on techs with bodycams), HVAC documentation and augmentation or signal processing in anomalies of wave patterns
        • holoLENS use case
      • Played 2 sounds for Build presentation – her son blowing on her arm vs HVAC system custom sound – training sets and transfer learning
    • Can take a few real image and do a bunch for training: rotating, zoom, Gaussian blur, cut out background
      • Sound – same: take out environment, pauses and silence
      • Can turn 10 images / sounds into 30-50 per class
    • Active learning: model over time that can train itself and then retrain itself
    • Business domain expertise – her Final 4 model
      • #1 feature was wins, 2nd SoS, 3rd home court advantage / location – let machine validate the expertise
      • Validation of revenue drivers from machine – more importantly, if the opposite occurs – revenue doesn’t agree with data features
        • Used statistics to train data from the start in football, sports data – ncaa – teams, tourneys, prior history
          • Brought in her assumption of player-social index where they scraped sentiment and video analysis for team effects
        • Chose to use Azure Databricks (Spark background), store it in Blob and only retraining on Just-in-time in a Docker image
      • ML Flow, set of score for model – training set and .py and score.py or source data gets grouped together in Azure
        • Docker pulls them together easily and image is built, Azure DevOps can do VC

Thinking Through Data (Notes from May 13 – 19, 2019) June 5, 2019

Posted by Anthony in Automation, Blockchain, Digital, education, experience, Founders, global, Hiring, Leadership, medicine, questions, social, Strategy, Uncategorized.
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This week we had a hefty dose of medicine, biotech and data discussions. However, it isn’t just focused on the technology and innovation for these incredible people, but rather the frameworks of the thought process that goes in to their decision-making. We can ask “Where did we go wrong?” or “What assumption do we make that should/would be challenged?”

Annie Duke is excellent in assessing this on the spot, but she sheds light on the steps she takes to get to that level. Much of what we believe / view tends to be outcome-based, which is fine because that’s easiest to see. However, it’s rarely consistent in the path to get to that success point once we change the problem. That’s what we should focus on – consistent thought processes to make strategic decisions. Outcomes are one metric of measuring the decisions, but not an end-all, be-all.

AI mixes with a few of our guests, including Mir Imran and Eric Topol. How does it play a part in how we will progress? What may AI teach us about our historical research? Are there more optimal methods of delivery?

Emily Oster and Hanne Tidnam discussed societal effects of technology and decision-making. With technology becoming more and more ingrained as a part of everyday life, is there a point-of-no-return or is it okay generally? Or, is there a limit? Time will certainly tell – studies / surveys don’t have the information available to give us any insight since the time-scale is so recently biased. Technology has outpaced the level at which we can make data-driven decisions in this manner.

Bruno Goncalves discussed text mapping and language processing for how different dialects of the same language can indicate demographic patterns in various locations (focused initially in Brazil). He mentioned it was interesting to track words / phrases and how they changed throughout history for English, primarily – harder to track Spanish. If there’s more data available (say, mobile text / audio or email?), may be easier to break down by parts of towns/cities, but currently, it was limited to general, larger blocks based on Twitter text (which is sparse, generally, anyway).

Suranga of Balderton Capital discussed his movement from London to San Francisco and what he’d observed as a tech employee, then executive and founder and the difference between the environments. His excitement for the future comes from the societal change that infrastructure of technology may enable. Then there was a darker side when we heard the author of Ghost Work – Mary Gray – as she said there is a larger split of work designed for specificity as we improve the AI / ML models that have been deployed. What is needed work-wise or what can be automated? Are those good? Biased? We’ll see.

I hope you enjoy my notes and hopefully you’ll check out a few that sound interesting! Thanks again to the people that continue to keep me up to date with what I love to learn.

  • Eric Topol (@EricTopol), author of Deep Medicine, cardiologist (Wharton XM)
    deep-medicine-cover
  • Deep AI and medicine – asking how to properly apply deep learning or AI to medicine
  • Yet to have a drug made by AI
  • Bayesian principles failing in medicine community
    • 12% of women get breast cancer, yet we ask them to do 1-2 years mammograms
      • 10 year span, 60% will get a false positive (yikes!)
    • Adopters of Apple Watch and its cardiogram / heart information are treated unilaterally
      • Young, healthy and curious people may not have any arrythmia so any abnormality (totally normal) may be misdiagnosed
        • Signal from heart rhythm from one person may be different from another
    • Says it’s a sign of being behind (3rd industrial vs 4th for the rest) when Stethoscope (invented 200+ years ago) is still sign of industry
      • Analog, no option of recording and is still very subjective to the doctor listening
      • This, despite advances in imaging and scans otherwise
  • Mir Imran, Chairman & CEO of Rani Therapeutics (Bay Area Ventures)
    21bf244196ea49469935c6e51910eec6

    • Talked about the big equity stake his fund took in the company, wanting it to be a big hit
    • Drug development, say, an insulin pill compared to injections (spent 150+ years on solving this)
      • Stomach / pill form in past is only 0.5% or < 1 % efficacy – can’t intake that many pills or cost-effective
    • Designing pill that is pH-shell-dependent to identify intestine pain receptors are limited (can inject no problem)
      • Pill recognizes pH change by dissolving outer shell (to pass thru stomach), then sugar-needle injects
      • 1000s of animal trials and just passing pills
      • Started trials ~18 months ago in Australia for pill traveling (using x-rays every 30 min to track)
        • Then progressed into drug for giantism, along with looking at other biologic diseases / solutions
    • Don’t want to limit biologics to a single buyer (Novartis, Genentech, etc…) – keep it open
      • Investments from Novartis and Google initially ~$150mln worth now
  • Mapping Dialects with Twitter Data (Data Skeptic 4/26/2019)
    • With Bruno Goncalves about work studying language – now @ Morgan Stanley
    • Started with research in CS and Physics, moved eventually to Apache weblogs, email, big router logs, Twitter conversations to study human behavior
      • Turned into looking at Twitter check-ins with the log using longitude and latitude
      • Language used: order maps, areas dominated by specific language (drawing boundary between French and Belgian in Belgium, for instance)
        • Intermingling cities that attract many languages
    • Spanish changing from one areas to another – everyday words, phrases
      • Can use the location data to determine the area of dialects – splitting Brazil, for instance (South, North and then central American)
      • Dividing grid cells into km x km – maybe not determinate of gradients of English vs Spanish since they were testing dialects of Spanish
    • Each row corresponds to each cell and words, but the matrix essentially loses the meaning
      • Ran PCA analysis and K-means on the clustering
    • He’s gathered 10 tb of data from Twitter, corpora and looking at millions of tweets – too few data to look over time
      • Measuring language changes over time was difficult for Spanish, but easier with English
      • Used Google books, for each language and counting bi-grams in how many books – popularity of words
        • Corpus of books published in UK vs US for Google books (1800 – 2010) for reliable data, but further back was less popular
        • Could normalize for words on how American vs British words were (and the mixture)
    • Recently, looking at demographic splits of language now with more digital / online presence
    • Training spellcheck based on dialect or demographic splits
    • Doing this stuff part-time now – how to train a model to detect use of language in this sense
      • Using word embeddings to detect automatic meanings of slang to determine the different meanings
  • Matt Turck with Plaid co-founder, Podcast
  • CSR in Gaming Industry,  (Wharton XM)
    • Discussing how it can be weird to gain competitive advantage and share
    • CSR as large subjective to the person looking in
    • Gaming companies chip in to gambling addiction hotlines / help / etc
    • Particularly in Las Vegas / NV, CSR survey determined that direct opportunities in water conservation, energy and green energy
      • How can they more efficiently run such large operations
    • Survey had about 80% of the gaming industry represented, from servicers to manufacturers to casinos themselves
  • Suranga Chandratillake, GP at Balderton Capital (20min VC 090)
    balderton-capital-logo-1

    • Founded blinkx, intelligent search engine for video/audio content in Cambridge in 2004
      • Lead company for 8 years as CEO through journey to SF, building a profitable biz and going public in London
    • Early ee at Autonomy Corp, engineer in R&D and then CTO when he went to SF
    • Belief in technical person shouldn’t be CEO – idea has been replaced in US (probably split)
      • Jack Dorsey, Zuckerberg (went into Dorsey and the idea 2 companies that aren’t really overlapping)
    • Been impressed by both Gates and Zuckerberg
      • Knowing the code and going through to understand everything
      • Zuckerberg’s acquisition of Instagram (ridiculed for $12bn and how right he was – surpassed Twitter’s users)
    • 2 Things for Tech going forward – changing infrastructure
      • VR and including drones or autonomous vehicles – hardware progression and mobile phones for what CAN be done
      • Societal difference – how we change to gig economy or how we work and spend time each day
    • Changing investments – just announced investment in Curious.ai
      • Shorter term where society is changing (eg: Nutmeg for planning pension plans, cheaper and available)
    • Structure for Balderton as equal partner VC – not sure it’s the most efficient model, but thinks it’s the best
      • Equal partnership where the partners have all the same number of votes, compensation and identical split
        • Removes the politics and impacts the partners and the stakeholders (founders that may be affected)
      • No single group that can carry the vote – hiring becomes very difficult because you need an equal
    • Knowing when to stick and when to switch
      • Deciding when to say “We don’t do that” and pivoting and being right
    • Exciting company for investment that he’s done recently – Cloud9
      • All development being done in the cloud now
  • Nick Leschly, CEO Bluebird Bio (Wharton XM)
    bluebird-bio

    • Purpose Built, 5/14/19

 

 

  • A Guide to Making Decisions (a16z 5/12/19)
    • Emily Oster, Hanne Tidnam discussion
    • Health and personal spaces – “right” thing isn’t a difference for some
      • Cocoa crispies, eggs and the preference for why you eat them, not just health-related
    • Impact of breast feeding vs not and looking against obesity
      • Less likely to be obese if breast feeding
      • Random trial for this is from Belarus in the 1990s where they requested parents to some breast fed
      • Siblings in choice to breast feed – almost no correlation if they did or did not
    • Constrained optimization – money or time
      • As parent, making choices based on preferences but have constraints
      • Recency bias for current literature – only data will be problematic and that it can only support a relation
    • Regression discontinuity as drawing a line and then seeing interventions and how they may change or affect outcomes
    • Screen time as having evidence that’s just very poor
      • Not easy to run randomized trial on – iPad or lifestyle would have to change for trial
      • Apps in short term doesn’t have the info available for results / outcomes
      • Studies currently don’t have any conclusions on phones/tablets – little
      • Bayesian updating on uncertainty – if 2 year old spends 50% of waking hours, that’s bad. Where’s the limit?
    • Last time went to doctor – very concretely made a recommendation of “2 hours max in a day”
      • How does the information get to that level of the system?
      • Conversations occur with doctors where they essentially make the lines that stick, pass on
    • Recommendations go out as arbitrary but now are made as truth – terrible without the decision
      • People that take the recommendations are likely more different or health-conscious
        • Added another layer (vitamin E, for instance) – those that adopted did many other things
    • Just be wrong with confidence – can be right, lots of good options
  • Innovating in Bets (a16z 5/8/19)
    • Annie Duke (@AnnieDuke), Pmarca, smc90
      annie-duke-thinking-in-bets-199x300
    • Every organization and individual makes countless decisions every day, under conditions of uncertainty.
    • Thought experiment: posing Seahawks run the ball and are stopped vs passing and throwing pick
      • Once there’s a result, it’s very difficult to work backwards to assess the decision quality was.
        • Outcome was so bad – it was in the skill bucket. Or – oh, there was uncertainty.
      • Very slow in NFL, for instance, to adopt analytics according to the numbers
      • 4th and 1 – should unanimously go for it since numbers say the other team will get 3, expected
    • As a decision maker, we likely choose the route that keeps us from getting yelled at
      • We allow uncertainty to bubble to surface – conflicted interest – long run vs short term
      • 2×2 matrix of consensus vs nonconsensus and right vs wrong
        • CR fine, NC-R genius, CW – fine (all agreed), NC – W really bad
        • Outcomes are right and wrong – hard to swipe the outcomes away
      • Thinking or allowing uncertainty in human driving and killing a human vs autonomous vehicle
        • Black box not understanding autonomous vs THINKING understanding another human (“Didn’t MEAN to do it”)
    • Anybody in business – process, process, process
      • R/E business – everybody in room after appraisal is 10% lower vs 10% higher (similar analysis)
      • Outcomes come from good process – try to align that an individual’s risk matches with corporation’s
        • Rightest risk – model could be correct (tail result) or risk decision (and deploying resources)
    • Most companies don’t have SITG – how to drive accountability in a process-driven environment so results matter?
      • How do you create balance so outcome caring about is the quality of forecast?
        • State the model of the world, places and what you think. How close are you to the forecast?
      • When you have a bad outcome and you’re in the room?
        • How many times do people say “Should we have lost more? Should we have lost less?”
      • Learning loss – negative direction on how to figure out? Poker example of betting X, X-C or X+C
        • Bet X and get a quick call. Should’ve done X+C (learn, regardless of opposite getting a card)
    • How much can you move an individual to train thinking? Naturally, thinking in forecasts more. Will have reaction and lessons quicker.
      • Getting through facts quickly and having the negative feedback – not robots
      • Improved 2% which is amazing – what are YOU doing to not make it worse?
      • “Results-oriented” as one of worst for intellectual work – need a process.
    • Story of “something is happening” is not a good story. Hard to read journalism now for him because they’re both “non-consensus”.
      • She’s optimistic that people can be equipped to parse narrative to be more rational. Pessimistic of framing and storytelling currently.
      • “Not making a decision” is making a decision but we don’t think of it that way.
        • Really unhappy in a position. Did the time frame thing “Will you be annoyed in 1 year?” – Yes. Nondecision didn’t feel like decision.
      • Mentions not having kids – time, energy, heart and decisions associated with indecision.
    • On individual decision, you have: clear misses, near-misses, clear hits
      • Bias toward missing – don’t want to stick neck out. Have to see it in aggregate. Forecasts.
        • Anti-portfolio / shadow book is really about when you include clear misses vs near-misses.
        • Fear is that the ones that hit are less volatile or less risky will be returning less than shadow portfolio.
      • Says it’s difficult to do with 99:1 turndown vs investments. Sampling.
        • Time traveling with portfolio – bounce out and see if “if this is 1 of 20 in portfolio” vs “invest vs not”
    • Conveying confidence vs certainty
      • I’ve done my analysis. This is my forecast. Is there some piece of information I can find out that would change my forecast?
        • Bake it into the decision. Not modulating the forecast – 60% to 57%. Costs and time differences.
      • Putting confidence interval on earliest dates and another probability, inclusive, on latest day
        • “I can have it to you on Friday 67% of time and by Monday 95% of time.”
        • Terrible to ask “Am I sure?” or others “Are you sure” compared to “How sure are you?”
    • Pre-mortems in decision analysis
      • Positive fantasizing vs negative fantasizing (30% closer to success by thinking of hurdles in front of you)
      • What happens if you ask out crush and they say yes? What happens if you ask out crush and they say no? – No’s more likely.
      • Teams get seen as naysayers – individually write a narrative on pre-mortem – good team-player is how do you fail?
      • After outcome, we overweight regret – don’t need to improve this much. Look out a year and see if it affects you.
  • Mary Gray, author of Ghost Work: How to Stop SV from Building a New Global Underclass (Wharton XM)
    51zsewdgdol._sx331_bo1204203200_

    • Research with coauthor at Microsoft Institute
    • Discussion of the b2b services that run in the background – used Uber’s partner as example for driver verification ID
      • Beard vs no beard on default, for instance – need close to 100% accuracy and algorithms/vision can’t pick that up just yet
    • Humans that run mechanical turk or various tasks on classifications
    • Technology used to be cat vs dog and now it’s species of dog – likely tech will enable more specific classifications but not remove intervention
      • Running with surveys, captioning, translations, transcription, verifying location, beta testing are all tasks
    • Used another example for “chick flick” meaning or 2012 debate with Romney’s “binder full of women” comment
      • Needed humans to assign relevance and to provide or connect proper context (Twitter, for instance)
    • Facebook and its content moderators, most social media companies do this
  • Trends in Blockchain Computing, (A16z, 5/18/19)
    • Get paid for AI data or encrypted data – can still train a model on it but nobody would know exactly what the data is
      • Long term accrual – depends, also, on if it’s on AWS vs open-source
    • Gold farming and ex-protocol websites in WoW, for instance – virtual worlds

Leadership: Data and Strategy (Notes from Week of May 6 – 12, 2019) May 30, 2019

Posted by Anthony in Automation, Digital, experience, finance, global, Leadership, questions, social, Strategy, Uncategorized, WomenInWork.
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This was a very fun week for listening. I caught a ton of material and insights from very creative leaders on how they’ve looked at strategy and building great teams, align companies and progress in a successful manner. Their methodologies or frameworks didn’t always align, which was also refreshing to hear. We often get stuck on the same methods if we hear them repeatedly – I’m under the impression that this becomes dangerous if held as a truism when others may question this way or go away from it – there isn’t a one-size-fits-all to building businesses! Especially when information is plentiful, and people / ideas are a few clicks away.

Zeke Zelker is a super-creator who has pushed the envelope of creating and producing engaging videos, whether it’s marketing material or tv or films. Definitely worth checking out, especially as media content in video / audio has increasingly been the mode of consumption.
Benito Cachinero of the Egon Zehnder Leadership program talked about 4 things he looks for and teaches in leadership. Also, he covered the importance of how to strategically allocate resources when looking for growth or expansion, both in economic and human capital.
A CES overview of consumer tech trends by the a16z squad was intriguing! Alarms, smart home and other products that caught their eye as options to drive the future of homes and how we’ll interact on an everyday basis.

Caryn Seidman-Becker  discussed privacy of data and personal biometrics as the CEO of CLEAR – trying to improve the ease of security while fighting the image that people think of when hearing what it is they do to enable this. Brett Hurt was fascinating – building multiple companies early in life and calling up his friends to start a new one. Deciding the name? Hilarious. All of this before getting into Clarabridge’s sentiment analysis with Ellen Loeshelle. She realized how much different types and ways to look at data / text could help in analyzing a plurality of business cases, across many industries – not just customer data for their clients. Last but certainly not least, Stephanie Cohen needs no introduction – but she discussed how she perceives data for company progress and leading the groups needed to achieve her goals.

I hope you all enjoy!

  • Zeke Zelker, Creative Transmedia Branding (Wharton XM)
    • Talks about his films being cine-experiences, and as a DIY videographer how he can control all aspects
      • Considers business along with creative direction – makes sure to align them
    • 4 phases of content: ignite, sharing short form content, main event, reward
    • iDreamMachine – his prod co. & producing Billboard about 4 people living on a billboard
    • Has 7th most viewed drama on Hulu (InSearchOf) – engaging audiences to become a part of the story
    • Encourages people in the environment to create content, whether it’s a blog or short snippets – become part of the overall story
  • Chris Carosa, author of From Cradle to Retirement: Child IRA (Wharton XM)
    51ip9g4cewl._sx331_bo1204203200_
  • Making money as child, pre-teen and then teen
    • Child: golf balls selling – golf course, lemonade stands, etc
    • Preteen: babysitting, lawn mowing, card collecting
    • Teen: W2 eventually, card collecting, babysitting and other types – photography, writing
    • Parents can save $ for child by investing in child IRA ~$1k or up to gift amounts of $6k now as long as W2 income

 

 

  • Benito Cachinero, Egon Zehnder Leadership Solutions (Wharton XM)
    • Previous President HR at DuPont HR
    • Discussing potential ~4 factors for leadership (direct contradiction to measurements in being accurate)
    • Aligning resources for growth strategy in new markets – China vs Midwest, for instance
  • Pulse Check on Consumer Tech Trends (a16z 1/17/2019)
    ah-logo-sm

    • With Benedict Evans, Steven Sinofsky
    • Trends at CES – no consumer product themselves, just a lot of all parts of supply chains / manufacturing
      • Batteries in 10k – 100k, so know what you want
    • TVs were not curved (nobody bought curved) – had 3 ft bar and tv came out above it in 10-15sec
      • Or edgeless Samsung blocks “The Wall” where you could make them as large as you wanted – LCD in any shape/size
      • Sizes could be anything now, amortized supply chain and manufacturing plants vs idling
    • Media content providers and apps
      • Pausing / syncing and Samsung apps with Apple video – clunky or AirPlay hardware
      • NorCal vs SoCal or California vs other states (think Apple phone vs the rest)
    • Easiest product to get alarm from 12+ companies for an hour to plug stuff in and it’s done
      • Proprietary electrical wires until they got low energy Bluetooth and now it’s everywhere
      • Lock or other nuts and bolts having SKU proliferation or new homes
        • Have to know gen contractors, Home Depot, developers and fragmented
    • FirstAlert smoke alarms – mesh wifi since they’re hardwired or battery
      • Put wifi in the alarm (to go to phone, etc…) – lots to do it with insurance or risks
    • Alexa chip supplier to connect everything
      • Apple tried to do Home Kit but eliminated everyone because almost nothing was implemented – wasn’t easy
      • Amazon has leverage for hardware but it has to benefit them for Alexa and being useful
      • If all makers saw HomeKit, could join war for Alexa vs Assistant (now that everything has their discovery appliances / connect)
      • Compare electric toaster to holding bread in front of fire and similar progressions
    • Show about running experiments is CES vs show about finding business value
    • Cultural part of CES – Japanese hand clapper
      • The founder of Ukrainian and employee and others that were hustling
  • Caryn Seidman-Becker, CEO of Clear (Wharton XM)
    kc6vuppj

    • Biometrics and buying Clear
    • Talking about the reactions for people getting to skip lines – make it more efficient
    • Allow TSA agents to work on what is actually important
    • Trying to describe to change customer behavior in the privacy aspect of what they keep
    • Biometric data but encrypted and secure

 

  • Brett Hurt (@databrett), co-founder and CEO of data.world (Wharton XM)
    logo594x144

    • Discussion of Edgecase (Compare Metrics), BazaarVoice (running backend for a lot of ads)
    • How they stumbled onto the data.world site – calling his co-founders of next big idea
  • Rod Hochman, MD and President, CEO of Providence St Joseph Health Leadership (Leadership in Action, WhartonXM)
    • Talking about being a junior member of the board of physicians when he started out
    • Leadership and how he went into the administration side as a young physician
    • Administration for many physicians is beyond the time / scope of many – hard to think of it without doing MBA or taking time
      • Important to combine the two for the expertise and management
    • With this business, how much is going on between clinics or hospitals and the network
  • Sentiment Analysis, Ellen Loeshelle, Dir. of Prod Management at Clarabridge (Data Skeptic 4/20/19)
    clarabridge-analytics

    • How positive or negative a customer may be expressing a review or otherwise, polarity
    • Academically, may have entire text as positive vs negative
    • Clarabridge – helping their clients understand their own customers
      • With hotel experience: could be multiple levels – service, cleanliness, check-in, overall
      • Using a clause, individual tokens, lemmas, parts of speech and how they’re related
    • Dealing with 21 languages natively, and having computational linguists on staff to understand the grammatical syntax or individual contractors
      • Vocabulary can change, but not necessarily syntax (think: sick)
    • Sentiment is rules-based engine as BI tool for her end users – full control / transparency for analysis
      • ML in place with w2vec for tuning rules in the engine since those change based on context/industry
    • Flipping sentiment or negating and modifiers as using the extreme ends of sentiment analysis (-5 to 5 scale)
      • Structured stays similar, but lexicon changes contextually and sarcasm / transcriptions as more difficult unless obvious or explicit
    • Sentiment goes along with their emotion or effort analysis for customers
      • Enterprise tool and APIs for engine on enriching internal systems
      • Considering sentiment analysis as table stakes now – different than when they first started when they were ahead
    • Client in small kitchen appliances used Clarabridge to treat sentiment on competitors, specifically for pressure cookers
      • Eventually saw that the sentiment split for pressure cookers and that pushed them into doing Instapot
  • Stephanie Cohen, Evolution of M&A and Corporate Strategy (a16z 5/7/2019)
    A Goldman Sachs sign is displayed inside the company's post on the floor of the NYSE in New York

    • Stephanie – CSO for Goldman, member of management committee, Was in M&A and investment banking for Goldman
    • M&A is experience-based business, M&A with same people – rarely would be one-and-done – just a method of executing strategy
    • Bad examples of M&A – likely hard to keep up with growth or expectation of growth but tries to buy the growth
    • Her worst example: Fiat Chrysler with government owing, Canada + US and pension
    • Trends: velocity of M&A is greater (cited $1tn of M&A last quarter), amount of private equity has about $1.5tn for buyers (divest vs sell)
      • When she started, needed a strategic buyer – now, just need to provide an answer to how the business is a good alone activity
      • China / Asia as higher volume in general
    • “Anti-trends”: still very analog as M&A, person-to-person; continued evolution may come with digital capabilities
    • Preparing or thinking of selling:
      • Don’t wait too long to sell (assets no longer strategic, more the business will atrophy) – be proactive of business portfolio
      • Build relationships early on with financial or strategic buyers
    • Best M&A banker he’s seen: Tim Ingrassia (analyst originally) – corporations, legal, bankers
      • Friendly, relationships and doing business without ‘playbook’
    • Figuring out strategy, which companies you want to buy and the alternatives (top targets, organic version, next a, b, c plan)
      • What to pay, rumors of what others would pay – what’s it cost to you?
      • Thinking creatively about deal? How to design the right compensation packages? What’s the integration strategy?
      • Clients are thinking of deal with integration people and how to get synergies to work the best
      • “Charm offensive” – ultimately, most sellers make decision on valuation – if you’ve developed best relationships, you get other information
      • Walk-away price
    • Top down vs bottom up strategy – mentions $CAT as shifting toward RR vs sales, and not unique to just financial services
      • Not one instead of the other (fee-based vs recurring) – good deposits bring in other clients
        • Creating and building business with the right economy within various parts of the business
      • Going forward, people running businesses everyday have the best idea of how to exploit markets
        • If client-focused and outwardly-focused, should come up with great ideas together and to push forward
      • Exploration is hard or unnatural – high-energy, client-driven and solving in a creative way
        • Creative and quiet thoughts – leaders need time away, but people have to be exploratory to consider new plans
        • Example for tech and how to have the right conversations based on seeing what other companies are doing
        • She says that with how fast tech is growing, they need to work together and partner
    • Accelerate as trying to push new ideas
      • Committal vs part-time – allowed them to fund and go with their idea, or keep them head of board
    • Belief in fintech for a huge opportunity – have tended to build things on their own, but have pivoted to not do everything
      • What should we buy? What should we build? Want fintech to come and partner with Goldman.
      • Most of life is on phone and it’s almost seamless – but not financial life for mobile
  • Ruth Zukerman, Co-founder of FlyWheel Sports and SoulCycle (Wharton XM)
    • Creative director

Dissecting the B2B and B2C Models(Notes from April 29 to May 5) May 23, 2019

Posted by Anthony in Automation, Digital, education, experience, finance, Founders, Hiring, questions, social, Strategy, training, Uncategorized, WomenInWork.
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Here we see a few longer episodes to discuss investing into different biz models. I listened to a collection of founders that started funds, did a bunch of investing, bet on themselves, worked hard and ultimately caught a few breaks in spaces that were extremely unconventional and some that weren’t.

Keith Rabois – if you don’t know who he is, I’d strongly suggest looking up some of his work – went over the differences he sees as an operator compared to being an investor. What do you want to focus on in each position and what competitors to focus on.
David Frankel is another current MP who started by building and exiting his own companies. His discussion focused on how he tries to align founders and investors at the early stages of start-ups – how he frames this to be most productive. His secret though: following the founders, themselves, and trusting they have ideas that can carry ideas.
Another MP at Founder Collective is Eric Paley – though he came from the biotech space before joining.

Amy Frederickson was a fantastic listen on the Business Radio channel. Taking second hand, vintage items and giving access to others who see beauty in them. She connects contractors in upholstery and sourcing furniture that may not be seen for what it could be and connects them with those that may have great use. I’ve heard similar stories to this being done in the second-hand space like boutiques or even goodwill – connecting foot-traffic-primary stores to the internet and allowing everyone a chance at these creative, hand-picked items.

Angela Bassa was on DataFramed talking about her managerial experience in the exploding data science field (and before). How she’s had to adapt, how she treats peers and effectively communicates – all very useful in discussion of solving the right problems in an organization.
This was a great segue for me into another a16z episode on decision-making. How to ask the right questions and ensure you get a sufficient answer. Mining the proper data for it and turn those into insights.

To finish up and not make the intro super long – I kept notes on a few other investment managers and the differences in strategies for different clients, investors and the framework for posing performance in the right light.

I hope you enjoy the notes and please check out everyone’s episodes!

  • Keith Rabois (@rabois), Inv Partner at Khosla Ventures – If You Can’t Sell Them, Compete With Them (Invest Like The Best – 12/18/18)
    investors-khosla

    • Investor, entrepreneur at Paypal, Square – investments in AirBnB & Palantir, Opendoor
    • Paul Graham’s “Clients too stuck in their ways, compete with them” – when a person doesn’t want to take advantage of tech
      • Creating money, vertically-integrated business – build the platform (adoption risk, sales cycles, economic issues for being reliable on others)
        • Provide end product to customers
      • Quintessential example as Apple – control component to create user experience – derivative product doesn’t control own fate
    • 7 Powers – book for strategic leverage
    • Irrational for the 2 guys in the garage – has to be unexpected reaction to market, team, etc — but can’t take over from scratch by following ‘playbook’
      • He’s in the business for investing in a top 100 company
      • Strategic leverage should be that the accumulated advantage should be easier – skill / talent ability normally degrades
      • Anomalies give you insight into a paradigm shift (can’t get 10x growth from UI, etc…) – end of why questions should be incrementalism
    • Secret is a belief system about the world that others don’t appreciate it – time determines if it’s true or false
    • Home as primary home as more a commodity than an art – touch/feel. Not works of art.
      • Focuses on digital health, where data is abundant. Network effect there.
      • References – take Opendoor – could make an offer for house that’s fair but you’d be uncertain with money or closing on time
        • Knowing people will make the credibility factor easier – trust matters by vertical/industry
    • Paypal had a $100k guarantee for the $ – partnered with Traveler’s Insurance as trusted brand, and used FDIC for insurance up to $100k
    • Healthcare costs ex-LASIK seem to be going up – mediated through payers (ins co’s)
      • Can improve UX, reduce cost and improve quality at same time with technology enabled – Guardant Health with liquid biopsy
        • Made it significantly cheaper to get biopsy results
    • Giving founders feedback on what they’re doing – how are they liking what they’re doing
      • As an operator, needs to make a 70% conviction and decision (as an investor, he needs to be in the 10-50% suggestions)
      • Assessment of talent is similar and understanding tradeoffs may be both of operator/investor
      • Risk profiles are different – understanding as operator where the strategy changes over time for the company (investor may be 0x to 10x)
      • Investor gets paid to learn new things, try new things – much more like baseball
        • Operator, conversely, may be like football where you should try things but need buy-in from others with your team
    • Lean start-up as stupid idea – cohesive strong strategy that can be done with less capital
      • Product-market fit isn’t required for validating fixing an idea / postulation (fat start-up – $10mil to fix real estate, for instance)
    • Steve Jobs mentioning saying No to good ideas (10% ideas) vs the 10x ideas – need experiment to get to that capability
      • Bad ideas in venture: lots of failures – 30% in baseball is good
      • Why does nobody emulate Apple or other successful companies do? Avoid the failure mentality.
        • Obsession about design and practical thinking – not empirical thinking. Book: Creative Selection
    • Interview question:
      • If you are a product, how would you describe your value proposition? – initially had product instincts – wasn’t world class, but knew business
    • Founders want to affect the real world – computer was escapist initially, but now it’s a controller for the real world
      • New capabilities / opportunities, lots of people leverage that for positive behavior, so now he says there are more ‘hard science’ innovation
        • Healthcare, biotech, autonomous, etc…
      • Early stage, pricing matters less because you just need to be correct directionally for the company, not so much off
        • How much, though, is risked by industries or risk/reward – what’s on table?
        • Later stage matters more for balancing portfolio.
    • Learning through osmosis with someone that’s very smart
      • Calling people to get feedback on certain ventures based on other talented people’s responses
    • Is there high-growth startup ex that hit escape velocity that a large competitor has beat?
      • Being paranoid is smart, but focused and talented team will out-execute a large entity
    • Narrative violations – common being fake news – average American is more informed than any other American in history
      • Average American is more informed than any other person in history, by orders of magnitude
      • Interesting question: given the resources, is the person smarter or dumber than what they used to be? Voter more/less informed?
        • Accessibility to products is so abundant now – anyone can Google or find other information
          • Definitely true in the US, maybe harder for other areas in world
      • Platforms are now more democratic versions of printing presses
    • Different components to acquiring and learning skills (athletes as needing to do, guitar probably playing songs, surgeon both reading/dexterity)
    • Most investors forget the lessons of strategy, he thinks – differentiation is your friend (mentions YC as having different mentality, economics)
      • Not much pioneering at VC level – Horowitz (and his autobio) initially, but not much innovation since – Khosla, Lux as vertical integration, maybe
      • Midlevel manager of engineering can be efficient from recruiting standpoint – what level you’re at, where you can pick from 350 companies (to 10)
    • Upside of Stress – book that’s very important, he believes — more stress and tolerating it is how you can be more successful
    • Things that stick with him – how they remember how others impacted him or vice versa, little things
      • Cascading of good/inspiration & how it changed trajectory – rewarding
  • David Frankel (@dafrankel), MP at Founder Collective (20min VC 088)
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    • Founder, CEO of Internet Solutions (ISP provider in Africa) then became a super angel
    • Founded FC with his partners for seed stage investing
    • Graduated 1992 in Elec Eng undergrad – IS acquired eventually for $3bn in mid-90s
      • Was doing ventures with FCF, made many huge mistakes, he said and remained on Board for acquiring co
      • Went to HBS – hated first 3 months but then graduated in 1993 – b2banking, b2consulting (jokingly) – but met a ton of great people
      • With capital, could back almost all of his classmates starting (first or entire checks) – had 27 companies after graduating
    • Challenge for FC was to ask how to institutionalize seed stage investing?
      • Not a lifecycle fund, just seed stage – may follow in Series A (not as lead), but hadn’t through the first stage
      • Wanted to create most aligned fund with founders – not net buyer when company is net seller
      • Believe they can make the most difference up front but not as they go forward
        • Who can be first hires? Management team gelling?
        • 2 years in, he says, they become much less useful – happy to be on board or pull off
    • Working with Chris (over at a16z) – says it’s a waste of time to look at incremental
      • Chris pitched 2 ideas before Site Advisor
    • For people not in the network – David loves hanging out with people and is very curious
      • People default to what we love doing – have to enjoy hanging out with them
    • Invested in Uber but he didn’t know in a million years how that would have been predicted on what they did
      • In the moment – Groupon just completed $5bn round and they were invested
        • Was excited about a competitor in Korea as he liked the founder, even though he believed it was “house of cards” industry
    • Comparing engineering student to business school – eng 1 in 1000 idea is Facebook, but volatility very high – business school lower volatility
    • Term Sheet as read blog, uses Twitter / TweetDeck to curate lists
    • Typically anti-sector because he follows founders moreso than industry specifically
    • East Coast vs West Coast (center of universe) – output of talent from Boston and east coast is different
      • Depends on types of company (consumer / mobile is Bay Area-centric) – Boston good for tech/biotech
    • One of favorite portfolio companies-PillPack in disrupting pharmacy & something simple
  • Amy Frederickson, Founder of Revitaliste (Wharton XM)
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    • Vintage furniture in interior design space – making it very simple to reupholster or otherwise refinish furniture
    • Discussion of her partners on the furniture side – volume doesn’t necessarily make it better if they can’t do more work / spend more hours
      • Limitations that she’s had to be careful – try to change mindset and buoy them
  • Eric Paley (@epaley), MP at Founder Collective (20min VC 089)
    • CEO, co-founder at Brontes Tech before acquisition by 3M for $95mil
    • Started a web developer company with brother and cousin in 1990s, had a bunch of startup clients and others that weren’t
      • Abstract Edge – still run by brother/cousin, but when the dotcom bust happened, sees overconfidence
      • Bad times – may learn better – he wanted to go to biz school & learned a ton
      • Looked at 3D imagery while in business school thru MIT partnership – interesting and looked at the space – had to ask “What to do with it?”
        • Facial recognition, industrial inspection, endoscopy, video games, etc…
        • Late in game, struggled with money raising and decided to look at dentistry (mass customization – every orthodontic device as singular/unique manufacturing, dental impression but if you could change this, you could have a lot)
    • First investor was David Frankel (from before – $500k into Brontes)
      • David calling and say “Thought the founder liked me but would you mind doing reference call with them?”
      • “Can you sit down with the entrepreneur and let me know what you think? – I’m out of town for 2 months in South Africa, so I trust you.”
      • Started to look for deal flow for David while he was out – with the other guys
    • As he was looking at leaving 3M, he was talking to venture companies and saw that top quartile VC’s didn’t feel like they were doing as well as they had
      • Came together with the 4 partners and should start a fund – underlying premise with better alignment at seed stage
      • Pro rata doesn’t align founder to venture – founders don’t get the option if they’re not doing well
        • Dollar average up cost-basis vs down. $8, 10, 15 million valuation vs $30, 50 or 100 million – but it’s more along the average dollar
          • Weighted later with pro rata investing
    • Believes there are plenty of seed funds that are doing well, but he’s surprised by the limited amount of funds that stick to seed stage
      • Conventional wisdom / FOMO for lifecycle / follow-ons
      • They have 3 unicorns at that time as well as a lot of good returns outside of that
    • Fooled By Randomness – NNT book as his favorite applicable to VC, frameworks for tilting the probability
    • Founder role model for him – said he was lucky to have Kelsey Worth, founder of Invisalign ($1bn company in 5 years)
      • She was on the board, would come out a day a month and help him out – dive deep and give an opinion without being dogmatic
    • Mentioned a recent investment as Cuvee – attempting to increase wine storage / pourability to 30 days
  • Angela Bassa, Director of D/S at iRobot (DataFramed #48 11/12/2018)
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    • Managing D/S Teams and how to organize development of algorithms and the processes
    • Corporate business organization of data science teams vs packaging and product building or open source work – known for more of that
    • Undergrad in Math, went to Wall Street after – got a lot of data analysis in the market, wasn’t a match for her ~15 years ago
      • Then went to strategy consulting – focused on pharmaceutical strategy, testing and experiment analysis
      • Went to marketing services industry – finally saw big data – (no longer any single machine work)
    • Talked about excelling as an individual contributor and moving to management as a different discipline in itself
      • First person she managed: quit the first day, had been a PhD graduate and assumed he was working with her, not for? (What a prick?)
    • Worked with teams in ops, finance, IT, engineering, R&D, etc…
      • Re-orgs for data science portion – always changing branches
      • If data science isn’t the product, within legacy/corporation, the team needs time to figure out the objective of the organization
        • Get past exploration and become experts
        • Her take on managers would be that they create space (o-line) for individual contributors to do their work as quarterbacks
    • As teams grow in size over time (using her experience as Manager and Director from ground up), potential vs low-hanging fruit
      • High visibility and high sophistication to give a leg up on what could be possible for the organization – low-hanging fruit is easy
      • Starting data science team have generalists but very good to mature into a better team, specialization
    • Humility for data scientists – avoiding the correlation factors that you build from gathering and going through data initially
      • What kind of questions should be answered?
    • Parts of data science that you can’t teach – how vs wanting to answer questions
      • Certain bootcamps are worthy of what they teach, organize – mentioned universities as not having programs until recently
        • Mentioned a team member trained initially as marine biologist – traveled and researched pods of dolphins
          • Modeling expertise for a fleet of robots as operating independently and together
    • Harder for C-suite to not be able to talk data in the strategy sessions for decision making
      • Common pitfalls of manager:
        • Data team doesn’t know how the data is gathered or where all it’s coming from
          • Have a data party or something to organize the data creation, designed, labeled, and stored
        • Not overpromising or underpromising
          • Lend credibility to actual outcome – being honest, transparent with other disciplines to interrogate situations
    • Her paper for HBR – Managing Data Science for AI
  • The Future of Decision-Making (a16z May 1, 2019)
    • Frank Chen and Jad Naous (via YT initially) of Enterprise Investing team
    • Digital transformation where industries are shifting to this design
      • Changing from manual to automated, digital processes and more agile
      • People’s roles will start to shift around – demand for new tools and dynamics for who wins in spaces
    • Product management – features or bugs would have been surveys manually or collecting data to figure out problem and sort them all
      • Now, the tools automate these from the product itself, often – now they can look at the dashboard of numbers
    • Marketing side: Growth hacking and market engineering – low cost to increase growth in certain parts of customer segments
      • Decision-making and creative work is the human part that can’t get automated
      • More people in the middle of the enterprise are becoming analysts – BI tools aren’t going to be enough
    • Types of tools should be operational tools that give answers to questions that they need immediately
      • Where is the bottleneck in the funnel? How to eliminate?
      • Competitor is having a flash sale – how much revenue is impacted or what segment should I target?
      • Generally, analysts would have to spend time and $ to get an answer (“$10mil to get a report that you didn’t need in the first place.”)
      • A/B test has to be continually monitored
    • Jad worked at AppDynamics – one of easiest things to sell is Performance Monitoring Tools – prevent systems from going down
      • Harder to prove ROI to other orgs – sales, marketing if they need continual results / ongoing
      • Want to have self-service tools vs full-service from someone else
      • Not analysts but instead the functional operational people – marketer, growth hacker, product manager, business people
    • AirBnB already open sourced SuperSet – ad-hoc access to data for results, used by 100s co’s – presentation layer product toward technical
      • Imply (one of his investments) for analytics and processing layer – store streaming data into database and do the analytics / presentations
      • DataBricks – processing layer
      • ETL layer is the one that has not gotten traction – domain specificity (healthcare vs ride-sharing or finance)
        • Currently too much integration issues and organizing
    • 3 categories – operational intelligence – sell tools for incumbents to enable intelligence
      • Target csm or sales or product manager (crowded currently, hardest to win)
      • Segment-focused vendors – sensors and analytics to oil & gas companies, for instance
        • Vertical solutions for industry
      • Vertically-integrated, operational intelligent company that competes against incumbents – Lyft / Uber, AirBnb, etc…
        • Biggest value but hardest
    • Non-IT buyers: Grocery, Construction, Oil & Gas – operationally efficient and commoditized as long-standing business
      • Minimal change in efficiency can be a huge value (Costco at $12.5bn ’17 on 11% margin)
      • Capital deploy for Exxon Mobile ($230bn capital invested, ROIC 9.5%)
    • Particularly excited by SuperSet, Imply – infrastructure tools – people seeing analytics and tools as necessary for business
      • Software vendors into large, existing industries – hardest would be economic profiles will be very different
      • Selling into stagnant markets (minimal margin) and not used to new tech – cycles will be long
        • Huge businesses to get in
      • Need to educate/prep investors – really bright light at end of tunnel
      • Need to become experts and trusted advisors in the domain
      • Help with software and services in the industries
  • Josh Wolfe (@joshwolfe), founder/MP at Lux Capital – Tech Imperative (Invest Like Best, 4/23/2019)
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    • Tackling massive scale problems – China as infrastructure power vs the states
      • State or story-sponsored role becomes more powerful with internet-enabling
    • Checklist of 5 main things (Xander of GoPro, now SurveyMonkey)
      1. Nail down the strategy of company – what are you going to do?
      2. Deliver capital to pursue strategy – clear, cohesive and sell
      3. Brilliant team to execute, drop others to start mission.
      4. Communicate the hell out of it – partners, competitors, media, press – keep consistent answer.
      5. Hold people accountable – if people aren’t and the goals aren’t clear, not effective organization.
    • Story – memorable, easy to repeat, conveys meaning in a clever way
      • Want to elicit an emotional reaction – putting meaning in a story for an individual
      • Portable ideas as superpowers – leaders being able to harness this, or the audience (maybe of the shared values)
        • How to aggregate the ideas
    • Abundance of liquidity to illiquidity or leverage (eg $200mln check in growth-equity round at $1bn (from $100mln) but if down-round, then the check has a big stake in it as creditors)
      • LPs and endowments are overextended – he’s telling people to look at secondaries, not venture
      • Sequoia was appealing to greed – sop it up and have to write bigger and bigger checks (get a big fund and put to work)
        • SoftBank as big problem pricing up rounds – either visionaries or producing paper assets as collateral against debt
        • Tesla as horrible balance sheet and illiquidity
    • Zoom doesn’t need to need a big business, but Uber/Lyft depends on strangers and investors to buy in to future
    • TurboChef (fast like a microwave but toasty like toaster) – Subway vs Quizno for $4k ovens
      • Sell to Subway – 20k places for purchase orders – but they got Coca Cola to buy the contracts for Subway in exchange for them to be in the stores
      • LatchAccess (one of his co’s) – remote by cloud from phone to consumer
        • New build and buildings (now 1 in 10) – did contract with WalMart / Jet
    • Some firms get lucky and parlay it into success – maybe wrong in process
      • What was process? Where did you get lucky? Where were you smart? How did you structure deal?
        • Benefit you, founders, investors
      • Price vs intrinsic value – public doesn’t do this, but path-dependent in portfolio (repeat entrepreneurs)
        • Team vs sole GPs – total equal partnerships and all mixes
        • Portfolio mix, super early stage, low probability of high financing risk
        • Others who are good at metrics / business, growth metrics
        • Subsector – fintech, crypto, etc… as experts
    • Tribes with a mantra
      • “Life sucks” – gangs, people homeless
      • “My life sucks” – 9-5 and get home and just crack a beer and grow for that
      • Like what they do – “I’m great, you’re not” – silo information, zero-sum and leave as free agents
      • Lux as “We’re great, they’re not” – robbers cave – how to get people to bond vs competitor / enemy
        • Sometimes it’s an entity – exogenous threat, devil – big oil, martians
      • Ultimate “Life is great” – mission driven, maybe Google / Facebook initially – cause/effect of money
        • Still climbing mountain, goal to reach – complacency maybe
    • Judgment: should we be disciplined about price?
      • Andreesen said only 10 good companies but you want to be in each one – but there are 1000s of decisions to be made
        • Pay any price for the ‘best’ or be discriminated – lead to FOMO and price action
        • Mentioned Cruz and setting up GM deal ($20mil at $60post vs $20mil at $80post, but GM came in and paid 11x)
      • In private markets, if you rejected them, you don’t get another chance.
    • Values: observable around morality (tech around morality and morality around tech)
      • Existence of an option is a good thing – military as a hot topic, tech as both sides affected
        • Had invested in Palantir offshoot for virtual wall for Homeland – has lots of immigrants who were deeply affected
      • Drone options or even autonomous driving (say, those who die as organ donors for the donor list)
      • Compares China’s pipeline from government to technology – decisive advantage will let them be ascendant
        • Moral discussions slow this down – barriers to experimentation
      • Real value of CRISPR isn’t the feature, but what it leads to in the platforms (ex: X-Men / Cerebro – Variant for rare populations)
        • 23andMe and Ancestry as targeting the ‘boring populations’ vs what they’re doing
          • 1000 individuals for rare conditions that have a metabolic rate that raises in the evening – what if this was monogenic / targetable?
    • Sci-fi vs Sci-fact as narrowing — ‘it will rot your brain’ as doing the next $10bn+ industry
      • Mentions engineers and Fred Moul (founder of Intuitive Surgical) starting Orace – just betting on him to recruit the right people
        • $8mn at $20mln valuation – for 5 years $90mln forecast and $450mln – then got a bunch of investment)
          • Exit for 63x for $6bn to J&J – completely flawed process on an order of magnitude
    • Directional arrows of progress if spotted increases probability of success on subsector
      • Lighting: burning flame -> bulb -> led; memory, energy density
      • Talked about Calliopa – he wanted to focus on gut-brain access – taste / sugar receptors (Charles as Chilean professor at Columbia)
        • Half-life of tech: 50 years ago, 25 years ago personal computer, 12.5 years ago laptop, 6.25 years phone, 3.5 iwatch, 1.5 airpods
          • More intimate over half-life and improved
        • Had to meet “Rearden” – “I can get rid of that” – Bill Gates’ right hand guy, polymath, PhD neuroscience after undergrad as Classics/Latin
          • Put on wrist strap that could detect 15k neurons that innervate the 15 muscles in your hand – perfectly model this
            • Can control it just by thinking of turning on whatever you’re speaking of
          • We don’t have input problem – we have output problem — too linear
            • Series A and Google/Amazon invested $30mln – want to sell after maximum value
      • Do you find companies that touch near the directional arrows?
        • Don’t need to implant in brain, can read the neurons – 5 years ago you didn’t have everything that was required – power, IoT
    • Moral imperative to invent technology, instruments to invent genius – encounter the technology that eventually inspires others
      • Losing touch with humanity – where is the song after sung? Find way to reduce human suffering.
    • Are there enough entrepreneurs in real technology frontiers? Is vs ought (jokes about competition)?
    • If you can spot “What sucks?” – can you discover something “Wait, what?”
      • 100mln mice – can’t you put sensors/automation for this?
      • Document storage (Mushroom vs atomic storage, not REIT for storing docs) – banker data, scan them – IronMountain can’t do it
      • Entropy information – he gets more optionality by giving information, but death of privacy is coming with convenience
        • Mentioned graphic novelist “Why the Last Man?”, side one called “The Private Eye” about everyone being surveilled – wearing masks
        • Socially and personal privacy is a losing battle but industrial side makes sense
        • Mentions blockchain for voracity – Banksy for private store (analog), authenticity
    • Special operations spending time for 2 weeks – Asia: Philippines, Thailand, Malaysia, Singapore, Japan
      • Coalitions forces, training, sniper, subsea, Seals, cutting edge tech – able to look at things for laser targeting
        • He was there for “What sucks?” – humbled by voracity, proud by the intelligence and what he could do and who he was with
      • Optical signals for those that get through program are the opposite of the big guys – stunning, talented, quietness “stoic intensity”
  • Ayan Mitra, Founder, CEO at CODE Investing (formerly Crowdbnk) (20min VC 089)
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    • Enterprise architect and tech mgr, worked with M&S, Orange, and First Direct
    • Software eng by trade, started in mid 1990s and built internet framing for Bank Offers Direct
    • Was in NY when Kickstarter kicked off in 2010, and saw the regulation was ready for this type of investing
      • Made the concept popular, regulated funding, or Kiva-type – early stage investing is a lot more popular in Europe/UK
      • JOBS Act as regulation freedom for positive step for alternative financing
    • Wave of changes where technology is being brought on the systems and the benefit goes to the investors and markets
      • Quick and transparent – believes it would’ve happened regardless
    • Crowdbnk – reactively do due diligence, price and valuations – invest alongside with investors on their platform
      • Look to raise growth capital for equity and debt – not a pure platform/marketplace
      • Minimum / maximum – equity looking for $500k – 2mln pounds, debt – secured/asset-backed $1ml – $5mil
        • Investors – $10k pounds a year to be diversified and properly investing
    • Valuation class by Ashwin (NYC) – intrinsic valuation (creating, discounted by time and risk) or momentum valuations (price willing to pay)
      • VC could benefit from diversifying investment base – early round by Index recently
    • In crowdfunding, consumer brands may have an easier time going down crowdfunding pick
      • Harder for others to understand some of other sectors / SaaS, for instance
    • Debt funding is #168bn and growing, but small compared to financial services
    • Drawing attention as a focus over time, consumer behavior changes
      • By being more efficient, they can return value to investors and people on the platform
    • Book mentioned: Intelligent Investor – Ben Graham
      • Seth Godin’s blog
    • War chest vs planned capital injections – not a binary answer (eg: compete against Uber – good luck without war chest; tech-enabled services)
    • Funded a company called Breezy – simplifies user interface for older generation, potentially – team/value and invested by US VC’s
  • Andrew Hohns, President, CEO of Mariner Infrastructure Investment Management (Wharton XM)
    • Conceptualized and founded IIFC Strategy as part of his dissertation at Penn
      • Funding gap in project finance to address world’s infrastructure needs
        • Talked about growing projects in Africa, India and others
    • Started a fund as he finished school – raised $500mln for capital projects
      • Including a $1bn transaction with African Development Bank completed with multilateral bank and private investors
        • Provided approx $650mln in additional lending capacity
      • Credit Agricole in 2017 that was “biggest impact investing deal yet” by Financial Times to allow an extra $2bn of funding toward green projects
    • Managing the originations networks for funds with relationships with many global financial institutions

Marketing and Investing Large (Notes from April 22 – 28, 2019) May 14, 2019

Posted by Anthony in Digital, experience, finance, Founders, global, Hiring, questions, social, Strategy, Uncategorized, WomenInWork.
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As a fintech-focused external analyst on pre-seed startups, I see and track as many as I can in the space. It’s allowed me to follow along, at a distance, some of the very interesting companies that are growing in finance and financial services industries. The glut of capital available has produced some successes and many failures for those looking to disrupt the industry – especially one that’s so large. And many are finding out that there are plenty of reasons why it tends to move particularly slowly and, at times, frustratingly inefficiently. You need a ton of users / customers (and the right ones) to make sure the business is sustainable at the level of efficiency you’re requiring to offer up a ‘better’ (re: cheaper) product. But then you must still maintain those levels at a much larger scale. And that’s where companies see you have to pay extra to acquire customers by marketing or offering other avenues in, thus decreasing that margin that was supposed to streamline the business and disrupt that portion of the industry. Cat-and-mouse or dog chasing its tail, often.

What tacks on to that difficulty? Well, the big fish in the pond aren’t just wallowing in comfort, waiting for disruption. Nope. Quite the opposite now. They’re flush with cash or the economics to develop solutions in-house. Or, when they see they’re scheduled to be beat, they come knocking on the door of the ones interested in an exit – purchase, M&A. Banks and the big institutions acquire the necessary innovation to diversify and improve their product offerings. Disruption – not so fast.

Ultimately, I’m not asking for these innovative start-ups to stop. Quite certainly the opposite. Their improvements and new ideas catch the attention and hasten the pace at which the incumbents must move. And it all makes for an exciting follow!

For my notes, I listened to an Ally Invest CFO discuss why he sees getting into mortgages is good for a rising banking company (one of our fintech follows). Then, a Senior VP of Marketing at Coca-Cola talked about how they align creative direction with their brand, despite not pounding red or drinks all over advertisements or songs. What have they learned to be so successful (for SO long)?

Then, one of my favorites in a while was a segment with the authors of Nine Lies About Work. I’ve followed Marcus Buckingham’s YouTube channel for a bit now where he spells out some misconceptions about the typical ‘culture’-speak of workplaces. One of my favorites: Culture is a myth. Simply, workplaces typically have an aura and vision around them, but once you’re there, this may dissipate or be something that depends on the person you’re speaking with (how do THEY view the workplace). In smaller, start-up teams, they’ll likely agree with each other – culture is the similarity of the workers. However, especially as the company grows – this will often change drastically, and by levels.

Last but not least, we had a few fantastic women on episodes exploring The Muse and Tough Mudder. The Muse co-founder, Kathryn, discussed wanting to be a very different company from what she’d experienced before. And how to give people insight into various places. Then Rabia talked about the trajectory for the Tough Mudder races and what may be on deck to bring in more of the family.

Hope you enjoy!

  • Tom Desmond, CFO Ally Invest (Wharton XM)
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    • Went to school at Kellogg, talked about how they were trying to make it easier for investing
    • Ally getting into mortgages and seeing why – thought market remains attractive
      • Mortgages as being on 10-yr timeline, quite different than other offerings
  • Geoff Cottrill, Senior VP Strategic Marketing at Coca-Cola (Marketing Matters)
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    • Talking music and the tie-in between marketing and brands
    • Artists controlling a lot more of their own brand – becoming easier as agencies aren’t as prevalent as in the past
      • Can start and produce on their own, without agencies
    • Talked about a commercial with Pharell, who was incredulous at not having to mention the company – gave him creative freedom
      • Coca Cola ran a song and gave it away first (via their site)
      • Different types of connections, brands
    • Have to be authentic in brand, customers and consumers can sniff out if it’s not intentional, on-brand or paid without authenticity
  • Ashley Goodall and Marcus Buckingham, Nine Lies About Work authors (Wharton XM)
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    • Talked about how the company doesn’t particularly matter, it’s what you’re doing there – even though people say that
      • If culture is so monolithic for a company, why would your experience be different than another person? It doesn’t.
      • We care about the companies we join, not the companies once we stay.
    • Lie #2: best plan wins – more details and variables for the nitty gritty, but the plan becomes irrelevant as you spend time on it
      • Rendered moot because the real world doesn’t wait – plans scope the problem but not present the solution
      • Wanting to know what action to take – plans are rearview
    • Lie #4: Best people are well-rounded – theory of excellence is wrong (excellence can be defined in advance – which it can’t)
      • In order to grow, defined definition of excellence and we can tell you how to get to Warren Buffett success (we don’t say that)
      • Excellence isn’t homogenous
    • Lie #5: People need feedback – based on 3 false beliefs
      • 1: I am the source of truth about you – have to tell you that you lack empathy or charm, or otherwise.
        • Only thing a manager can do is be a reactor – “I am confused, bored, etc..” – a rater of myself.
      • 2: Learning is filling empty space. Insight and patterns recognized within – more revealing what is vs not there.
      • 3: Excellence can be defined in advance. Defined above. Used Rick Barry as example (granny-style vs ‘normal’)
      • Can be an audience to others, and help grow and excel, but in a different manner.
    • Lie #6: People can reliably rate other people. Mediated or seen through this lie through work.
      • Can see the ineffectiveness on rating systems (pattern / tool is an idiosyncratic rating – mirror, not window).
      • Not biased – it’s a natural pattern of ratings based on who you are, not who you’re rating (variation is ~60%+).
    • Lie #7: People have potential. (Performance and potential grid)
      • Person has substance – potential and we buy into the ‘bucket’ or exponential growth for people
        • There is no measurable data on these people. Can’t do it. Immoral.
    • Lie #8: Work/Life Balance Matters – who has ever found this?
      • Balance as a recipe for stagnation – how to replace this with an aspiration
    • Lie #9: Leadership is a Thing. (US has $15bn industry for this)
      • Defined in advance and in isolation from the person doing leading.
      • Only thing that is common amongst leaders is that they have followers – followers into the uncertainty of the future.
      • Create the sense of confidence that trumps the future – the way, though, is very different by leader.
  • Rabia Qari, Senior VP of Marketing & Sales Tough Mudder (Marketing Matters)
    2a1e66b4770724e3b40d07888973e1b1

    • Settling on Tough Mudder 5k and the full, instead of the half – had brand ambassadors that understood the growth opportunity
    • Now have Little Mudder and Rough Mudder (dogs), family affair
    • Had tried a half marathon before the 5k but community and team decided it wasn’t going to work – removed some of the spirit.

 

 

  • Kathryn Minshew (@kmin), CEO of The Muse (Wharton XM)
    small_logo

    • Talked about how the companies always looked the same
  • Steve O’Hear (@sohear), Techcrunch writer (20min VC FF021)
    tcJoined TC in Nov 2009, but had taken a break in June 2011 to found Beepl

    • Landed funding and in Nov ’12, was acquired by Brand Embassy
    • Enterprise over consumer from out of Europe – network effect is stronger in the US as English / general language
      • Spotify, gaming companies as the exceptions, possibly
    • Liked the fundraising meetings – thought it was fun but scary
      • Absolute conflict of interest where you want to tell the VC whatever to get the funding, but as soon as you’re signed, you’ll be partners
    • PR and coverage as a distraction – but he doesn’t think that TC makes / breaks a start-up
      • If you make a bad product, you’ll be found out by users/customers immediately
      • If you are making a good product, you’ll be found out still – didn’t matter for TC coverage or not (though probably brought in more eyes)
    • TC does more meet ups and conferences, less moderation of comments and conversation via Twitter or in community
    • As a writer/reporter, they don’t have to pay attention or worry about stuff
      • Editorial freedom but can write what they feel or passionate about – unique to TC / type of journalism
      • As publications grow, they usually lose the freedom, but in this case – they’re one of the best places to write
    • Best interview was Wozniak, as a fan of those that brought the pc to public
    • Inspiration from politics for journalism
    • Harry as saying that Eileen was the only one who had ever said “No!” and he was a bit annoyed, though enjoyed.
  • Josh Levin, CSO OpenInvest

Data Science in Your Business (Notes from Week of April 15 – 21, 2019) May 8, 2019

Posted by Anthony in Automation, experience, finance, Founders, Hiring, questions, Stacks, Strategy, training, Uncategorized.
Tags: , , , , , , , , , , , , , , ,
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It feels appropriate to have the week of Google I/O’s conference to be the one that aligned with my notes where data was the primary focus, especially when Google was pushing ease of technology (centered around giving them access to more data). There were some excellent memes/pictures around for the differences of Facebook asking (hah) for data compared to Google (where they have a ton of it already but they mention the stuff coming).

Kaggle, a research data competition site, held a conference centered around hiring and careers in data with guest speakers from some of the most interesting companies working with data, including Google. Listening to career-based or hiring podcasts related to the field gives insights to how corporations or orgs focus on the spectrum of people vs skills. The other side of this would be a discussion on how data science teams can impact the business at value. What can be done with the data? Is it helpful? Which metrics are measurable and important?

A few episodes went into the business and general application of research in the data. Research on how personality and music are interrelated or satellite imagery from NASA to provide various live solutions – and to what extent they can be designed to be used. A few non-data science-specific podcasts dealt with FinTech, HealthTech and marketplace tuning. How do startups fight against incumbents in various marketplaces? Are their offerings sustainable or do they break the model of what we have seen?

Hopefully my notes provide some incentive to go back and listen to one or each of the podcasts. Or connect via Twitter to talk more!

  • Validating D/S with QuantHub, Matt Cowell CEO (BDB 4/2/19)
    e9qpszxn_400x400

    • Also with Nathan Black, Chief Data Scientist at QuantHub
    • Talking data science – math with business and IT skillsets
    • Companies are manually doing tech assessments with candidates / roles – programmer-based primarily
      • QuantHub looks at a comprehensive, scientific approach to assessment of the stack of what may be necessary
    • NLP of resume, and then Bayes’ updating for input and results from that
      • Assessment platform at the core and using it for hiring (natural use-case) but then benchmarking organizational skills
      • Aggregators of content and matchmaking (say, data analyst up to data engineer – wrangling, SQL improvement)
    • Assessments done and individuals won’t be charged – overall value in helping talent
      • Building the training side in the next quarter
    • How do companies engage QuantHub? 5min to get running – align the incentives for using it / relationship.
      • What are the challenges? What are the skillsets? What do you mean that you want them to do?
      • Requirements changing by different statistical methods (along with computing power, designing algorithms vs latest research)
      • Knowing/vetting data scientists as having to do the role / job – can you mirror the actual job requirements? (try vs buy, potentially)
    • Cloud computing or hardware innovation as ‘cool’ in a world of software – highly critical, depending on certain organizations
      • Some orgs NEED the data improvement there (Kubernetes, Docker, Cloud, Spark vs Power Excel user)
    • Matt as a product strategy guy – book “Monetizing Innovation”
      • How do you determine what the market and customers want
    • Nathan’s book – “Make It Stick” on how you can improve learning methods
  • James Martin (Staffing Lead, D/S at Google) – Getting Noticed in D/S (Kaggle CareerCon 4/17/2019)
    google-cloud-platform-for-data-science-teams-4-638

    • Looking at field – ML Engineer to Quant/Statistician to Product Analyst to Data Analyst
    • Research tips: Open source projects (understanding current trends, gain experience, make connections)
      • Job descriptions (take time to research the differences, tailor approach)
      • Market research (professional networking, connect dots between companies you’d consider)
    • Resume tips: Concise (focus on telling a story on the experiences to highlight outcomes)
      • Factual (if listing skills or strengths, use examples to support them)
      • Related experience (highlight specific projects related to area you’re applying)
    • Networking tips: Professional profile (be detailed but concise about the skills you use and experiences)
      • Targeted outreach (connect after a conference, target approach for conversation)
      • Conferences (meet/greet if possible, follow up via email, LinkedIn, twitter)
  • Gidi (Gideon) Nave (@gidin), Assistant Professor of Marketing (Marketing Matters)
    • Cambridge Analytica before Cambridge – music research and how it relates to certain traits
      • Extroversion and openness were 2 big ones that they could pull from 5 traits (MUSIC)
      • MUSIC: Unpretentious, Sophistication were 2 of them
    • Could pull personality cues from 20 second, unreleased clips based on scores of 1 to 7, also
      • More agreeable people had higher scores in general
    • Personality on 5 (OCEAN – Openness, Conscientiousness, Extroverted, Agreeable, Neuroticism)
      • Questioned whether they could use music to test for the personality (as opposed to the other direction)
      • Personality is established at a young age, so can music likes on Facebook give you a personality side – as mentioned, it did ~2 better than others
  • Fintech for Startups and Incumbents (a16z 4/7/2019)
    • With GP Alex Rampell (@arampell) of CEO/cofounder of TrialPay and partner Frank Chen