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What’s Important for the Business (Notes from Sep. 16 – 22, 2019) November 5, 2019

Posted by Anthony in Automation, Digital, education, experience, finance, Founders, global, Hiring, Leadership, marketing, questions, social, training, Uncategorized.
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Ah, the art of learning. What can you absorb in the time that you allotted? Hopefully it was the good stuff, the one you can apply and remember. We’re not going to retain it all – far from it. Different surveys and studies will say between 10-30%, depending if you’re reading, listening, seeing things. Repetition, talking about details or applying what you’re picking up can improve those numbers – and it’s why there is still a ton of money being raised/made on improving it (Blinkist, Anki, Quizlet, rise of audio books and podcasts). This is all without bringing in the idea that the internet has allowed such a flood of ideas that opposing ones can exist simultaneously, persisting through its strong supporters. So, if you’re not doing research and coming to your own conclusion, it’s likely to be lead to whichever way you resonate with someone/something most (or first).

In reading through Constellation Software President’s letters to shareholders, you see a valiant attempt at conveying how he, executives and board members looked at the business health for the year – and refreshingly so, not explicitly through rose-tinted glasses. He critiques and suggests an option that reversion to the mean is possible based on a lower adjusted net income and cash flow from operating activities per share. Then he went through the shareholders returns on invested capital, average invested capital, and questioned the organic net revenue growth’s performance (as he notes that this is a primary core to the main metric for their performance: ROIC+OGr). Once he goes through the metric and it’s cash flow, he mentions that they’re looking to increase acquisitions, but the environment isn’t conducive to great values, so FCF may not be fully invested at attractive levels for the future. Then, he suggests a metric to cover this with a reasonable pattern, one less subject to shareholder alterations. Open to suggestions while he develops the reasoning for what another member has suggested for a good metric, he settles on FCF increase per share compared to average net income per share.

I loved his breakdown for the shareholders – mentioning half the shares trade for the year. He breaks it down simply as short-term, indexers, enterprising investors (including institutional, but also generally long-term, long-haul holders). He openly asks them to help find directors and members of the board and the difficulty that they saw initially after their IPO. The next paragraph was a big one, so I’ll include it:

Qualified and competent Directors are very rare, and not surprisingly, the track record of most boards is awful. According to the 2017 Hendrik Bessembinder study of approximately 26,000 stocks in the CRSP database, only 4% of the stocks generated all of the stock market’s return in excess of one-month T-Bills during the last 90 years. The other 96% of the stocks generated, in aggregate, the T-bill rate over that period. This means that 4% of boards oversaw all the long-term wealth creation by markets during that period. Even more disturbing, the boards for over 50% of public companies saw their businesses generate negative returns during their entire existence as public companies.

Wow. A) The recognition of wanting to be the best and provide a great board of directors for a long-time and B) genuine concern for the long-term view and suspicion of complacency arising. Both, I’d imagine, lead him to mention that vision / strategy are not necessarily courses of action – instead, perpetual objectives as the guiding point. Whether that’s seeking them out or maintaining what they had, he made sure it was top of mind. He sees that profitable VMS businesses may no longer come to be acquirable, and that he’s on the lookout for other opportunities – without them being attractive, though, he’d responsibly return FCF to investors.

Interestingly, he looked for Constellation to be devoid of “sycophants, mercenaries and spin-doctors” and wanted it to be a place where meritocratic results bring in “entrepreneurs and corporate refugees to invest their lives and and their capital and thrive”. Quite the statement for a business of such magnitude, when, especially from the outside, many succumb to the former (hell, take a look at Tech Twitter these days and a complaint I’ve had is that people seem to be comfortable bouncing between 2-3 companies a year for 5, 8. 10+ years). I’d love to build something that sustained a drive through many levels of employees.

“I find there is no magic to managing and leading. If you are smart, work harder… treat people fairly, do not ask them to do anything would not or have not done, share the credit, keep learning and keep teaching, then pretty soon you have followers. If you make sure that the team members are energetic, intelligent, and ethical people….”

Yup. That’s the way to build a company. Find that and hold on. And then he finalizes with the board requirements (which I’ll include at the bottom).

Hope you enjoy the notes this week.

  • Mike Strasser (@mstrasser), Motiv ring founder (Wharton XM)
    • Talking about the ring and how he knew the wearable would work
  • Lee Thompson (@flashpacklee), Flashpack founder, Marketing on a Budget (Wharton XM)
    flash_pack_logo_block-1

    • Photo journalist for 15 years
    • Talking about creating a brand through pictures, story-boarding, ethos of brand
    • If you can’t tell what your hook / pitch is, probably won’t sell
    • Went on first date with his now-wife from Match, wouldn’t tell him a great business idea
      • Post-wine glasses, she had a business idea for 30+ year olds wanting to travel – friends having too much of a family/kids
      • Adventure travel company for solo travelers in 30s and 40s, not tours via bus and such
      • Next few dates were researching travel industry, setting up a business
    • Book trip as solo traveler, then have others that you are meeting everyone else
      • Boutique hotels, price points established and like-minded – typically well off in careers, cash-rich
    • Launched with $15k each, savings and jumped in
      • Nobody would spend $1k+ on trips for a company that had no reviews
      • Generated a lot of PR, did a lot of viral videos by responding to twitter hashtags
      • Spent on Google ads and lost lots of money – built the website
    • Took a trip to Egypt on a budget, “come to Jesus moment”
      • If I can get on top of that and take a picture (Christ the Redeemer picture of a workman doing damage repair)
      • Wanted to take a picture on top and took a selfie
  • Mehrdad Baghai, Alchemy Growth cofounder & CEO (Mastering Innovation)
    the-alchemy-of-growth-full-1-638

    • Boutique strategy advisory firm advising large companies on innovation strategies
    • Designing organization architecture for growth, 5-10 years
    • Active investor in tech and p/e spaces with Macquarie Group
    • Former partner at McKinsey leading Growth Practice and then 3 years as Exec Dir at CSIR, Australia’s national science agency
      • Dozens of new tech companies
    • Also launched High Resolves with his wife, Roya, in 2005
  • Fred Destin (@fdestin), GP at Accel (20min VC 1/18/16)
    logos_master_accel

    • Former partner at Atlas Venture working with Zoopla (public), Secret Escapes, Integral Ad Science, Dailymotion (acq by Orange), PriceMinister (acq by Rakuten)
    • Studied life as derivatives at Goldman Sachs, first team on credit derivatives
      • Securitization of movie rights, derivatives in Pacific region for about 7 years
      • Opted out when it went from risk hedging to arbitrages
    • Moved to Speed Ventures for investing at really early seed
    • Spending a lot of time hiring the best 1-10 executives because you can’t spend time getting this wrong
      • Take a model that worked in 1 city (like Deliveroo), scaling it to 30+ and got there in under 3 years old
        • Fit consumer model and offering for the ones – brought new kinds of service to non-delivery food
      • Seed companies failing because you hire something you don’t understand – wrong team kills the team
        • Second mistake – overestimating the things you can do in the time – reality doesn’t match
    • Setting arbitrary goals for not being worthy of being funded – most companies run out of money or come close, being patient and empathetic with founders
    • Investors need mental plasticity for adjusting expectations on what to best deliver
    • Founders feeling screwed over because it was never possible for them to communicate the right decisions being made
      • Mix of market difficulty or overambitious of timing – how to improve intimacy and mutual trust
    • He likes to spend 3-6 months knowing founders – wants to do strategic sessions, whiteboard issues how you would solve it – discovery and disagree
      • Can work through disagreements, see how people work collaboratively
      • Engineer a situation of tension – hiring / decision made, create it to see pushback
      • Could we do an 8 hour wine test / road test – can we banter and have a pleasant time being together (Boston to Montreal, London to South of France)
    • Needs to ensure performance and milestones, sounding board, interest of company / employees / customers and investor with fiduciary standards
      • Had to tell guys at Real3D and say that they couldn’t invest – told them early, though
      • Mentioned Boston VC that said he’s said “No” so often that he just fizzles out – Fred said he tries to give constructive feedback but not always
        • He used to send very detailed No emails but would receive replies about not understanding opportunity and pushback – called stupid or not getting it
        • Now he responds with “Busy with other opportunities”, but sometimes he has things fall through the cracks
    • Favorite book: Mastering Margarita, missing and saying No to successful opportunities – doesn’t rue or look back like that because portfolio co’s do well enough
      • Success measure – how long it takes for knowing (16 years for him), took 10-12 for success as investor
    • Wasn’t super excited about returning to London but was pleasantly surprised about how vibrant it was – still US is more tolerant about money and quicker pace
      • Competitors share, acquisitions are faster – Accel moves fast so it’s advantageous but not overall
      • Boston wants to import the well of technical talent and ML – hubs working together in Europe will improve it
  • Thirteen Minutes to the Moon
    • Episode 7: Michael Collins: Third Man
      • Command module pilot for the mission
      • Test pilot before being selected as an astronaut – 90% luck he landed in that role
      • Someone wrote to Eisenhower that the best option for selection for astronauts would be experimental test pilots because apt to new scenarios and flight
        • Compared to deep sea divers or others
      • Collins had been turned down the first time to supplement that first 7 – after a year of more experience, selected in class of 1963 with Aldrin
        • First flight was 1966 on Gemini X, rendezvous and docking maneuvers
        • Once LEO Gemini flights were successful, Apollo XI was announced in January 1969
        • July 16, 1969 – launch sequence day – was responsible for launching lunar module to turn it around from Saturn V rocket
      • Was an English major and just did guidance verbs/nouns memorization to control it
      • As they neared moon, they were on far side and lost contact with Houston
        • Takes back everything bad he ever said about MIT – accuracy of system was ridiculous, 3000 ft/s and only had 0.1 ft/s in any one direction error
        • If something went wrong for landing lunar module, Michael couldn’t change his speed but it’d be up to him to figure out what to do
        • Mathematicians were responsible for coming up with a list of 18 variations for problems and what to do – some they hadn’t trained for
      • He felt alone, awareness of being on the other side of the moon, solo after Aldrin and Armstrong picked up speed on their way down

 

CSI Board Role Search Criteria
THE ROLE
Thought Partner – Thought partner for senior leadership.
Long-term Orientation – Unfazed by short term pressure. Focused on CSI’s long-term issues.
Timeframe – Able to serve on the board for 20+ years.
Investment in CSI – Willing to make a significant equity investment in CSI, above and beyond board comp.
THE CANDIDATE
High Quality Business – Understands what constitutes a high quality business.
Autonomy -Appreciates the motivational power of autonomy, decentralisation.
Cultural Fit – Respects and gets along with the current senior CSI management as well as the board.
Ownership – Believes in the motivational power of equity ownership.
High Impact / Low Ego – Will intervene when necessary, contribute meaningfully, but not dominate discourse.
Out of Kitchen – Can resist the urge to get into the kitchen when there’s a chef already in there.
EXPERIENCE
Builder – Helped build or maintain (as a director, manager or major shareholder) a large
organisation (>1000 employees) over an extended period, while providing a superior
return to owners (ideally including employee owners).
Decentralized – Experience with a decentralised company (nice, not necessary).
Capital Allocation – Experience in a capital allocation role (nice, not necessary).
LIKELY BACKGROUND
Family owned business operator or director.
CEO / #2 for exceptional business.
Entrepreneur
SEARCH PATHS
Multi-generational family owned businesses with high ROIC within reach of our
network and ideally local to CSI (increases involvement, eases reference checks, more
likely to know CSI, decreases absenteeism).
High quality businesses with strong shareholder alignment.
Great capital allocators in the corporate world.
CEOs with great shareholder letters and high quality businesses.

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

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

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)
    yawnofc__400x400

    • 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

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)
    f9bf1622-04df-11e7-a9d6-0242ac110003.founder-collective-logo-black-tinypng

    • 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)
    revitaliste_3

    • 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)
    irobot_green_logo

    • 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)
    rwtxa-v4_400x400

    • 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

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.
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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)
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    • 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
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    • Assembling a risk pool (good and okay drivers subsidizing the bad drivers, or healthcare – same)
      • No economic model for skipping a segment – psychology for half price insurance (say, going to gym)
      • Half the number of customers – taking the ‘good’ ones, profitable ones
      • Insurance has mandatory loss ratios for different industries
    • HealthIQ – mechanism for exploitation on ‘health’ – in FinTech, it was SoFi on HENRYs
      • Positive vs adverse selection – debt settlement company ads, for instance – negotiate on your behalf to settle
      • Healthier people as living longer than non-healthy people – left them more profitable for proving being better
        • Gives them good customers (adverse selection for ‘quick, no blood test, 1 min’)
    • SoFi as stealing customers from the normal distribution – better marketing message “you’re getting ripped off, come to us”
    • Branch as investment – collect as much data as possible and look for correlations – small, mini-loans
      • Induction as pattern is a willingness to pay (credit is remembered) – went and got data from your phone
      • How many apps did you have? Did you look like you went to work? Are you gambling?
        • Counterintuitive potentially: battery goes dead leaned default, gambling app meant more likely to pay, etc…
    • Earnin – phone in pocket for 8 hours, last paycheck and RTS data confirming – will give money that you have earned but don’t have yet
      • Can tip interest or not – can you encourage people for positive community and people driving safely
      • Nurture better behavior – helping to turn customers into correctly priced customer (vs bank that doesn’t want them)
    • Vouch as company that failed but your social network had to vouch for you – Person X is okay, so you can even put up $
    • Tiffany & Co for a long time was owned by Avon lady – but its brand was massive and one of most renown jewelers
      • Could make sense for acquiring more customers, though
    • Killing Geico – take 20% of customers but only take the good ones
      • Selling negative gross widgets, for instance – probabilistic ones (and the bad ones aren’t needed)
    • Turndown traffic strategy – Chase turns down a lot of people for problems (can’t profitably do $400 loan, for instance)
      • Here’s a friend after they rejected them (but see traffic) – Chase will tell you to go to a startup for better underwriting
      • Amazon got right – HP book, for instance – had ad for B&N right next to Amazon (bought) – would make $1 on the ad click at 100% profit
        • Used this to reduce the price on their site and wasn’t sharing it
    • Rapid fire: “Always invest super early” – 9 weeks to decision vs 1 day – can’t get good deals at length
      • Best things aren’t cheap – they’re often expensive – better strategy can be plowing in late (“Can’t believe we’re putting this much $”)
      • Gating item for entrance into a space or into different models – cost of capital and distribution as often the unique thing
        • Geico could easily add additional traffic to start-ups
      • M&A strategy early? Encouraged and used Facebook – buy existential threat (surrender 1% of market cap to buy Instagram)
        • Facebook spent 7% of market cap for WhatsApp, Oculus, etc…
        • Buy the guys that failed trying – courage to build something new -> take them and put him in charge for person that was successful (at big co)
          • Trying to build this thing for ~10 years vs start-up that built something in 1 year (put this one in charge)
          • Ex: AmTrak buys Tesla – worse thing “You work for us” but you want products to push distribution and talent for understanding
        • Only difference was distribution and the possibility to do that
  • Jennifer Dulski, author of Purposeful, Head of Groups & Community at Facebook (Wharton XM)
    • Talked about their group initiatives at Facebook – communities policing themselves as well as methods to flag content
    • Mentioned example of having an employee that came up to her and asked if she had done a good job, she just wanted a bonus or something $
      • Taught her about incentives and why people do what they do / good to know the motivators
      • What drives people?
  • Anth Georgiades, CEO of Zumper (Bay Area Ventures, Wharton XM)
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    • Purchase / hire of Padmapper in 2016 that added quite a bit of Canada business (size of California, real estate-wise)
    • How to match both sides for a marketplace – suppliers vs customers
      • Chicken and egg – focus on one, improve other and repeat
  • Word2vec (Data Skeptic 2/1/2019)
    • Produces word embeddings – autoencoders as NN for something like compression to retrieve output successfully
      • m down to n via mathematical representation (m < n)
      • Language compression for vector rep
    • Running the algorithm training on Google’s full internet, Facebook’s news article, Wikipedia, etc… to achieve similar words/spaces
      • Not super adaptive – nonsense place for words it hasn’t seen
    • Real world application – king for word2vec and subtract male – then add in female and you get queen
      • 300 dimensional space, semantics of that example
      • Bad example: training on entirety of internet results in something like doctor – male + female = nurse (gender neutral data)
    • Feature engineering for bag of words, good example for transfer learning, also (train model on text and then use parts of it on smaller area)
      • Very large corpora for NLP but can use pre-trained models of word2vec and use it in other models
  • Sean Law (@seanmylaw), D/S Research and Dev at TD Ameritrade (DataFramed #59 4/1/2019)
    sean_law_quote_card_3

    • Colleagues thinking he tends to ask lots of interesting, hard ?s – hopefully with answers
    • If he’s a hard worker, then he’ll do great – being in industry for 3 months time – has to juggle effective time spend
    • Molecular dynamics is short time scale and lots of computing power – parallel computing before and now the growth / usage of GPUs within days
    • Hypothetical example for alternative data solutions – driving to work and listening to NPR where NASA had a new dataset that was sat imagery
      • Pollution ORA dataset for air quality – area of high commodity necessity with pollution joining
    • If building ML as a binary classifier – but don’t know where the data is (do we have to collect? 3rd party API? Internal?)
      • How much effort to get it usable in the pipeline? Then, what’s the reasonable accuracy level – better than 50-50?
      • Some signal in the noise
    • Exploring chat/voice – query account balance, stock price, news articles via Alexa/Echo
      • Headless / device-agnostic option – audio to parsing of text, understanding what customer wants (NLP) and then what it means
      • Following PoC and into production
      • PoCs can miss: scalability (unless claim is to get scalability), model accuracy (not best model immediately), real-world applications (use case in mind)
    • Interpretability standpoint – regularization, L1 and linear – constraining coefficient can be very useful (background noise from video, for instance)
      • Time-series pattern-matching as non-traditional
    • Calls to action – data failures of things that didn’t work or negative results

Experimentation & Testing (Notes from March 25 – March 31, 2019) April 17, 2019

Posted by Anthony in Digital, experience, finance, global, Hiring, questions, social, training, TV, Uncategorized.
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I know, I know. It’s a bit of a cop out to use a Game of Thrones image on the back of the Season 8 premiere from Sunday. Sue me [please don’t]. And I’ll give credit to the image creator: Instagram @chartrdaily for the fun visualization. However, after listening to Pinnacle Sports’ Marco Blume, I couldn’t help after hearing deployment strategies for their prop bets on popular TV shows, such as who will be left on the Iron Throne or the ever popular “Who dies first?” props. They experiment, hypothesize, post a line with a limit (hedge risk) and let the market decide from there. And boom – we have the theme of the week!

Antoine Nussenbaum, of Felix Capital at the time, mentioned going from private equity to start-ups and venture funding where they had to decide between backing people or belief in the company. He got first-hand experience by starting a company with his wife, successfully gaining funding, and then exiting – only to fail with a different company that wasn’t scaling. How did he go through frameworks to decide on startups to fund or help?

Mark Suster gave his take on how he comes to investment funding – sales, technical skills and being aware of each. How did his entrepreneurship experience influence his framework for funding new start ups? Why is it that there is a sweet spot for amounts based on run rate? Experimenting, failing and adjusting.

Then I had listened to 2 data scientist / researchers in their discussions of NLP parts – what to test, what they assumed to be true, how to approach new methodology and testing this methodology. Is there a limit to the progression that can be made with NLP? Why might it be relevant to decide on testing state-of-the-art further? Then, ultimately, what’s the applications for how we can use that optimization to improve the current status quo?

I hope everyone checks out what may interest them – this was a fascinating and fun week. So much so, that I suggested to a few different students for them to check out different parts (granted, I do this often, but I was quite excited to share these ones).

Cheers!

  • Antoine Nussenbaum (@Nussenbaum), Principal and cofounder of Felix Capital (20min VC 084)
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    • Partner at Atlas Global prior, p/e fund that was part of GLG Partners
      • Working on digital early-stage, venture fund and helped startups bootstrap after missing the tech side
      • Miraki, Jellynote, Pave, Reedsy, and 31Dover as some of his best investments
      • Helped start Huckletree with his wife
        • Looked for investment of $80mln but got $120mln
    • Backing someone vs backing the company initially in early stage funds
    • Raised in Paris in international environment, lived in UK as well
    • Launched 2004 software-on-demand business with 2 friends “that was not scalable at all”
    • Did M&A in the UK after leaving software
    • Felix Capital at intersection of creativity + technology, lifestyle brands: ecommerce and media, enabling tech
      • Stages – flexible capital, but have made investments from $200k – $6mln, focus on Series A + B
      • Geographic – agnostic, as long as backing entrepreneurs
      • Advisory services and focused on helping their investment companies
    • More entrepreneurs that know the playbook and how they can build, grow and scale
      • Looking for more companies that can scale globally or expanding outside with proper funding
    • Using Triangle as an example – bathing suits on Instagram strategy and launching millions of product via digital
    • ProductHunt as a blog he gets lost in – 15 min of destruction
    • Lifestyle-related excitement: food side, better life, marketplaces
    • Hard Thing about Hard Things and Capital in the 21st Century – relationship of wealth and economic wealth
  • Mark Suster (@msuster), MP @ Upfront Ventures (20min VC 085)
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    • Was VP of PM at Salesforce.com before Upfront
    • Late 80s – had an interest in development as a student in college in the UK
      • Worked initially as a programmer at Anderson (Accenture) for 8 years
      • Entrepreneurship isn’t for everyone – better to start earlier, need to have a fundamental understanding of systems (coding)
        • Python, PHP, Ruby, JavaScript – not trying to become best developer – just knowing the systems
        • Sales experience would be second – telesales or customer support – ask CEO to do an hour a week of calls
    • Started 2 software companies – one in England and then Silicon Valley, selling both – backer brought him in to VC
      • Fred Wilson wasn’t an entrepreneur, but does give you the insight
    • Don’t get the sense of urgency with too long a time – 3 months vs 12 months
      • Too much capital creates laziness and shortcuts that lead to mistakes
      • 18 month run rate for capital – takes 3-4 months to raise (start with 6 months plus)
    • Wants to see early stage companies once a month, roughly.
    • $240mln fund – invest half into companies and reserve the other half for follow-ons
      • 3 year timeframe, $40mln with 5 partners – $8mln per partner
        • Series A, B rounds where each partner is doing 2-3 deals per year when avg is $3-5mln investment
    • On his blog, has the “11 Attributes of Entrepreneurs”
      • Best known post would be “Invest in Lines, not Dots” – x-axis as time, y-axis is performance (any given day, your dot)
        • Interactions create a line that matches a pattern and he can decide if he wants to do business
      • Not a big fan of deal days or investor days where you hype up a company because of this
    • 50 coffee meetings a year – once a week, if you meet 50 entrepreneurs a year, maybe you’ll become close with 5-10 of them
      • Single best introduction is from a portfolio company CEO for an investor
    • He knows and built software company – SaaS-space since he knows how to be helpful
      • Data and video tech industry (has 11 personal investments and 5 are video)
      • AgTech as an underappreciated industry so far – stays quiet until a few investments before hyping
    • Too much company, too much money and entrepreneurs clouding the market for everyone else
    • Book “Accidental Superpower”, how demographics and topology will drive the future and how areas grow
  • Marco Blume, Trading Director at Pinnacle Sports (DataFramed #54 2/18/19)
    pinnacle_logo

    • Got into data science by “sheer force”, building quant team out from Excel going to R
      • Efficiency was by orders of magnitude since R was better than Excel
      • Could do anything with risk management, trading, sports
    • Pricing GoT, hot dog eating contest, pope election and making the lines
      • Use pricing and market analytics to let the people set prices
    • Risk management in general – maximize probability and hedging risk
      • Does the bottom line change? Does it affect anything? Regulations.
    • NBA where all teams have played each other – have a good idea of strength of teams
      • Soccer or world cup – not as much certainty with teams not always playing each other
      • Start of season has a lot more volatility and responsiveness to bets because of uncertainty
        • By end of season, bookmarkers have the price and knowledge, so they’re likely to increase risk
      • Bayesian updating
    • Goals to improve models, open new betting options to clients
      • Low margin, high volume bookmaker – little bit with a lot of options
      • Book of Superforecasting – group of people who are better at forecasting
        • Pays them already at Pinnacle – consultants, betting and paying the price
    • Much bigger R shop than Python at Pinnacle, active in the R community
      • R becoming more of an interfacing language and production language (vs C# or other), can use R-keras or plumbr
      • Teaching dplyr, rmarkdown and ggplot cover 95% of their work outside of specialists
    • GoT as one of his favorite bets
  • Matthew Peters (@mattthemathman), Research Scientist at AI2 – ElMo (Data Skeptic 3/29/2019)
    ai2-logo-1200x630

    • Research for the common good, Seattle, WA research
    • Language understanding tasks – ELMo (embeddings from Language Models)
    • PhD in Applied Math at UW, climate modeling and large scale data analysis
      • Went to mortgage modeling, tech industry with ML and Prod dev in Seattle
    • Trying to solve with very little human-annotated data, technical articles or peer-reviewed
      • Very difficult, very expensive to annotate – can you do NLP to help?
    • Word2vec as method for text to run ML on text, context meanings of say, bank
    • ELMo as training on lots of unlabeled data
      • Given a partial language fragment, language modeling predicts what can come next
      • Forward direction or backward direction (end of context), neural network architecture
    • Research community may want to use ELMo, commercial use to improve models already in prod
      • Pre-trained models available and open source
    • In the paper, evaluated NLP models on 6 tasks – sentiment, Q&A, info extraction, co-reference resolution, NL inference
      • Got significant improvements on results from the prior state-of-the-art models
      • Character-based vs word approach
        • Single system should process as much text as possible (morphology of the word, for instance)
    • Paper over a year old now but Bert was put up on ArXiv to improve upon ELMo (transformer architecture for efficiency)
      • Scaled the model that could be trained by many X’s, quality is tied to the size / capacity
      • Language modeling loss changed, as well (word removed from middle of sentence and predict before/after)
      • Large Bert models have computational restrictions – how far can you get by scaling the model
  • Kyle and early Data Science Hiring Processes (Data Skeptic 12/28/18)
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    • Success isn’t correlated with ability to give good advice
    • Conversion funnel for businesses: website that sells t-shirts, for instance
      • Tons of ways to bring people into the door / website (ads, social media campaign, ad clicks)
      • Register an account or put into cart (what %, track it, a/b test and improve)
      • Cart to checkout process (how many ppl? Credit card entered, goes through, etc…)
    • Do any sites convert faster than others? Keep track, find out why / focus on continuing it
    • Steps for job hire: video chat / task / phone screens / on-site next / offer
    • Resume should be pdf (doc may not open nicely on Mac or otherwise) – include GitHub
    • SVM – should have margins or kernel trick on resume (otherwise, don’t include it)
      •  Ex: ARIMA (auto-regressive integrated moving average) – time series data

Striving to Learn Yourself (Notes from March 18 – 24, 2019) April 11, 2019

Posted by Anthony in Altucher, Digital, education, experience, finance, Founders, global, medicine, questions, social, Strategy, TV, Uncategorized.
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There’s nothing wrong with the selection of a well-traveled path. It’s paved with a full network of people who have gone ahead of you. If you’re active and curious enough, that can lead to opportunities aplenty. But some of us feel as if that can lead to a pigeon holing or limit on what we FEEL like we could achieve. For better or worse – maybe we’re curious along different lines – following a boundary, or making a new path altogether into the woods. Jump into a new space or, adjacent markets, as popularized by Peter Thiel.

It’s hard to go against what we’re generally comfortable with. Habits have been grooved into our system of processes for a reason. I believe that if something is eating at you or there’s an overarching sense of obligation toward a challenge, relishing that opportunity is vital – and should be celebrated. 25+ years ago, maybe less so – as the fallback could have been harder. But now? Nonsense – networks are as connected as we make them out to be – reach out via Twitter to someone, LinkedIn, Facebook, Reddit, Instagram, Slack or the tried-and-true in-person coffee chats, conference meet-ups or otherwise. Interconnectedness has never been this high before. But you have to put in the effort.

 

  • Ashish Walia (@AshishW203), co-founder and COO at LawTrades (20min VC FF 019)
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    • Portfolio company of 500 Startups
    • Undergrad in Queens, then law school – read through entrepreneurship opportunities, spoke to lawyers – knew he didn’t want to be full time
    • Decentralize major corporate law firms – before you’d have to go to bottom barrel legal service or stuck paying $600 an hour for routine stuff
      • Middle boutique firms could save money and they were looking for work
    • Joining law firm is like everyone wanting to get in and everyone in wants out – if he knew this already, why not do a different thing
      • He wanted to figure things out for himself and work his tail off for what he wanted to do
      • Idea for LawTrades came up in his 2nd year of law school – businesses and lawyers-directory service, terrible traction initially
      • Using all of the resources – blogs, podcasts, videos, etc… diving in
    • Gary Vaynerchuk as sales and customer experience, as he wasn’t a tech/coder
      • This Week in Startups, Jason Calicanis as well
    • Law school as encouragement for a corporate firm, not to apprentice and then start your own thing
      • More legal technology and open, incubators popping up but not traditional
    • Attorneys with big law experience that want more control over their work-life balance are their target for LawTrades
    • Had started a podcast to drive traffic to LawTrades – had a guest on as founder of Pigeon and he thought they should apply to 500
      • Applied a few days before deadline, had Brian Wang interview while in NYC the day after, then a skype with Elizabeth Yang
        • For LawTrades, they cared about 2-3 recs after learning about the business
      • 4 days after, got in and moved from NY to CA
      • Really wanted 500 Startups because they wanted to drive distribution (vs YC as product-focused)
    • Raised small seed round with the vision, no customers that were just angel investors
    • Enjoyed BrainTree founder Brian Johnson as a nontechnical founder to make it large
      • Altucher, Thiel’s Zero to One, Quora, Medium
  • Dave Sonntag, Gonzaga Associate VP / CMO (Launch Pad, Wharton XM)
    • Discussing university brand, marketing
      • Smaller school of 6000 comparatively, but large brand name
    • Funny to me that he said that the basketball brand was priceless – invaluable
      • Primarily over last 20 years
    • Only the 2nd CMO in the history of the school
    • Started as marketer at Eastern Washington before seeing opening at GU (alma mater)
      • Trying to line up brand exposure to campaigns – bracket + donation set up for the week of tourney start
      • Last year, drove about 1/4 of the site traffic – had to prioritize the home page and stories to make them compelling
      • This year, accentuating professors and their stories (named #1 university professors by US News)
  • Chris Riccobono, UnTUCKit founder (Wharton XM)
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    • Had failed at multiple companies before thinking of returning to finance but landing on doing this co
    • Building a brand around shirts that aren’t to be tucked in – seasonality isn’t necessary
      • Built to have that offering as compared to types of shirts (Tommy Bahama – floral, Armani – club, etc…)
      • 50 stores now and the plan is to have them distribute clothing to better control distribution/supply
    • Increasing market in areas that they put a store – both online and in store
      • Tracking customer data as they go back & forth between online and in-store
      • Control experience of touch and customization to drive conversions
    • Doing once a month “fast fashion” with 4-6 designs that are only available for 48 hours or limited time for attention and marketing – demand driver
  • Linda Crawford (@lcrawfordsfo), CEO at HelpShift (LaunchPad, WhartonXM)
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    • Getting over imposter syndrome, realizing she is certainly an expert
    • From Salesforce and Siebel, had ran and grown a ton – wanted to get into start-up land again
    • Building the right team immediately, making sure everyone was on the same page
      • Had been recruited by headhunter and wasn’t predicting going into CRM, again – maybe fin or healthtech
  • Denali Therapeutics, (WhartonXM)
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    • Focusing on neuro degenerative diseases, isolating proteins that cause damage
  • For the Billions of Creatives Out There (a16z, 3/16/19)
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    • Brian Koppelman, Marc Andreessen, Sonal Chokshi
    • Creativity of business, talking about Brian’s original script with his partner – Rounders
      • Failed initially, people turned down and it wasn’t even a box office hit – super small chance to get the repeated viewings
      • Only about doing the work themselves, the rewards would come
      • Worked as bartender / music exec – would work for 2 hours to write a script
      • Were given a chance $5k to be partner – took advice from Horowitz of Beastie Boys’ sister
        • She said “if someone would pay you money without seeing it, then you should write it and you’ll have options.”
    • Balancing the success – his state initially (creative impulse being down)
      • Toxicity that made him bitter if he let the creative impulse die, even if he had other stuff going on
      • Knew he needed to do the work even if it meant failing
      • The job that was mundane / bitter (music exec), he felt better doing because he had already put in 2+ hours of writing to try
    • In Rounders – rejected by every Hollywood agency
      • Some said overwritten, some said underwritten (he still says unsure)
      • He sold the script over a weekend and Monday to Miramax
        • By Tuesday, every agency that had passed tried to sign them – he read them their notes on why they’d passed
        • All told him that they didn’t read it (assistant, reader)
      • Wanted to overstep to make success by getting a director that they agreed on the vision/leverage
    • Up to you to manage the relationships (founder and investors)
      • Learned at a young age how to talk to powerful people – outside of having college paid for or something
      • Father would put him in position to talk to people – in meetings, in production studios, etc…
      • Don’t treat them with a sense of awe or condescending. Also, make them laugh and you’re comfortable in your own skin.
        • Be able to grow, better yourself, relax and they’re not all-knowing.
      • For shows – make it on budget, crew taken care of, make people heard and listening – take notes only on what can make show better
        • Artie from Larry Sanders (show) – network executives discussion
    • Podcast Brian is not script writing Brian – major leagues now, not getting nurturing Brian
    • New Brian and Adam wouldn’t pitch movie Rounders now, it’d be show Rounders
      • Movies were the way that they communicated from the time
      • Televisions now and visual literature as much better than movies
    • Not letting emotional response dictate your actions – how do YOU comport yourself, not the other
      • Especially in partnership types (founder / CEO or other setup)
      • Has to be more important that the other gets to make the decision than you to be right (both need it)
    • Tim Ferriss w/ interviews, 90%+ meditate (quickly Marc says never so in the minority)
      • Brian does 2x / day, 20min & reduces the physical manifestation of anxiety
      • David Lynch for Transcendental meditation (David Lynch foundation)
      • Argue about journaling for introspection vs meditation as a respite or calming of thoughts
    • Billions stuff: As Good as It Gets scene response to how he writes women so well
      • More the result of everything he’s ever read, done, watched while he sits on his couch with music blasting with his laptop
      • Wants to write the characters to all be smarter than the writers are
      • How he stumbled on Vince Staples’ Street Punks in Axe’s bachelor pad (the scene and debauchery and debased)
  • Tony Kunitz, StatsBomb (Wharton XM at SSAC)
    • In london now, paying attention to premier league
      • Progression passing and going through pressure
      • Building the data, paying people to note and augment with computer vision
    • How baseball has gone through 3 stats progressions
      • First value of players and contracts
      • Changing how to play on the field
      • Now changing training and player development (swings, angles, etc…)
    • Also have changing coaches guard – need people to be able to coach properly or the new developments
  • Maria Konnikova (@mkonnikova), The New Yorker (Wharton XM)
    Books: Confidence Game & others

    • Psychology study and approaching poker after reading John von Neumann’s work on game theory
      • Appropriate mix of human decision making – very different than Go or chess
      • Luck and imperfect knowledge of others – strategy vs luck
    • Approaching Erik Seidel to be her coach – intrigue at her book research, and figured if it succeeded or not – could build a bigger audience
      • Still gives her a tough time at not knowing how many cards in a deck (52 vs 54)
      • Using the “marshmallow test” decision-making of Walter Mischel to see if people with high levels of self-control made better risky conditions
        • Made me think of how high school students beat AI experts at Berkeley AI conference after just an hour of teaching
    • Frame of references and deviations can thrive in environments of change
    • Talked about how pros de-leverage themselves by buying in on other pros (can be up to 75-80% of each other)
      • Know that one thing can boot them from a tournament, even if the math is in their favor
  • David Blanchflower (@d_blanchflower), Prof of Econ at Dartmouth (Wharton XM)
    • Children, Unhappiness and Family Finances paper, with Andrew Clark
    • How to gather the data for unhappiness and finance – not based on income
      • Did it based on “Do you struggle to pay bills?” – always, sometimes, never
      • Found that more people with kids struggle to pay bills
        • But children make them more happy, when asked and measured
    • How to change this – other countries have tried to address child care subsidies or tax breaks
    • Younger kids were also considered to be more happy than teenagers or older ones
  • Steven Rogelberg, author of The Science of Meetings (Wharton XM)
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    • Employees suffering by tons of meetings that don’t return as much
    • What type of meetings would be preferred? – Remote. What type of meetings are the least productive? – Remote.
      • Have to dial in how to make meetings more productive, especially when remote.
      • Shorter, planned meetings are better – Remote < 30min, for instance.
  • Caring Capitalism, Miriam Schoning author (Wharton XM)

Brands, Strategy and Consumer Spend (Notes from March 11 – 17, 2019) April 3, 2019

Posted by Anthony in Digital, experience, finance, Founders, global, Hiring, questions, Strategy, Uncategorized, WomenInWork.
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For this week, I wanted to reach outside of my usual Wharton/Business XM channels and the typical 20min VC, so I dove into Discussions in Digital, which is a podcast done by McKinsey & Company, focused on sales and marketing in the digital space. What happened for the week, then, was a convergence on marketing strategy and the pull from physical stores to online media. We’ve seen considerable growth of digitalisation across a bunch of different industries, so the collection and reading through the notes helps to shed light on how different companies are engaging this through the 2010s and beyond.

However, we start with none of those, and I wanted to highlight her work. Christine Heckart, who recently became CEO of Scalyr, has been an expert in the technology space since her childhood around her father but more importantly, as a veteran of Microsoft, Juniper Networks, Cisco, and Netapp. She went into depth on what it means to be a master operator in the tech space as well as how she has managed being a new executive in an established company, which can often be a perilous position.

  • Christine Heckart, CEO of Scalyr (Bay Area Ventures, Wharton XM)
    scalyr

    • 2016 Woman of Influence by SV Business Journal
    • Talked about always being the lone woman in an industry of tech and general – always curious
    • Acts on BoDs for Lam Research and 6sense
    • Building the team at Scalyr, sitting and watching when she first replaced the founder to establish some trust
      • Not breaking things immediately, but gathering information and having the strategy
      • Her responsibility to have the vision, make the strategy and execute it all within the culture of the company
    • Previously with Microsoft, Juniper Networks, Cisco and NetApp
  • Discussion with the Marketing Matters professors
    • Talking about how Target and Walmart have been killing it again (Target french)
      • Physical locations, where they have operational excellence
    • DNVB (digital native vertical brand?) that opens a showroom/store to much success
      • Can have people try items, feel them and get a sense before placing an order online or in store
        • Have it delivered very quickly
    • Cannibalism of Gap / Old Navy on market
      • What’s the difference? Old Navy was hip and cool, initially.
      • Now, Gap is just more expensive Old Navy or vice versa
      • Releasing them as new brands (Gap/Old Navy / Banana Republic, etc…)
  • Reimagining CX in Mobile Age (Discussions in Digital, 6/28/2016)
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    • McKinsey’s Brian Gregg, Michael Jones (RetailMeNot), Mahin Samadini (McK DL), Dianne Esber (McK), Mark Philips (McK)
    • Radio 38 years to reach 50mil people, tv – 13 yrs, twitter 9 months, Google+ 88 days
    • Mobile as a phone or what? Transforming experience and every industry – beauty, connectivity and in both B2B and B2C
      • Mark was at Candy Crush – how do you understand users? Not maximized yet.
        • How to construct the journey through the product – mapped out the customer journey
        • Did a lot of pre-curation depending on IP, time of device and other numbers for the apps (before even using)
    • Can start to see that people plan shopping earlier – if outside of geofence (home, elsewhere) and look where they want to shop
      • Partners can see – RetailMeNot – when they want to shop
      • “Snacking” – personalized commerce, faster and easier to buy – more you frequently purchase
        • Reiterated by Candy Crush (90sec, even, with female demographic – put kids to bed and on way to bed or wherever)
    • 80% of transactions by 2020 will still be in physical locations in the US – 80-90% will probably be researched prior to entering store
      • This number is a bit high – it’s closer to 70%?
      • Seamless vs “Elegant seams” – customer knows where the difference is between channels
      • Mobile is still conversion-based, whereas people are commitment-phobes, so they want an experience
    • Went to RetailWest in Palm Springs – a CEO had a kid who took a picture of shoes that he could make
      • Posted on Instagram, saw how many likes
      • Eventually bought the shoes, got likes, etc…
      • Friends asked him about where he got them and he ended up building that ecosystem (but it’s not just shoes, it’s everything)
    • Toothbrush industry – how do you tell people to get a new one?
      • In 1980s, created an indicator bristle to tell customers to buy a new one based on the data
      • “What’s your indicator bristle?”
    • Existing companies out there – reality for mobile being a thriving way out
      • No singular model anymore
    • Stepping stone to AI: messaging / chat – voice – AI
    • Enabled physical world with digital (gift card originally with Apple and could take a picture and get it into iTunes)
      • Talked about OpenTable reservations – expected to have it, otherwise painful
  • How Strategy is Evolving / Staying in the Hypergrowth Digital World (Discussion in Digital, 1/18/17)
    • B. Gregg, Jacques Pommeraud (fmr Salesforce), Jon Weinberg (Sephora), Dianne Esber
    • Still a role for 3 year vision?
      • Yes – any company, any phase for what you’re shooting for.
      • Strategy could be an annual process with execs getting together – not likely going to work. Needs to be more often.
    • Sometimes smaller companies don’t see the need – how do we get bigger companies to do the vision quicker?
      • Bigger/broader vision (eg geographic expansion) hard to get passed out to the company as you get larger
      • Value of strategy comes from mobilizing the strategy
    • Architecting the strategy – has to be crisp enough to make pivots without issues, consistent framework
    • At Salesforce, what matters is customer trust, then customer success
      • V2MOM – vision, values, methods, obstacles and measures
        • Vision helps define what to do, values establish the most important
          • Customer trust / success
        • Goes down all the way in the company via a memo, accessible for everyone
      • With Facebook, used example of Sheryl Sandberg’s “Have hard conversations.”
    • At Sephora, rapid expansion – how do you continue to fuel the growth? Client-centric ideas, but how do you support it?
    • Is there a role of strategy to recruit?
      • Culture of leadership – used example of sciences like data scientist / VR value and what talents can help any company
      • Need app developed, whether it’s Bird or GE or Sephora, have to bring in people to work
    • At Salesforce – Jeffrey Moore has the 2×2 matrix for 4 zones
      • Efficiency zone (non-core activities: SG&A, support), Performance zone (core biz: 80%, execution)
        Innovation (lab, test – few things to try – new biz, products), Transformation (performance hopefuls)
      • In tech – birth of AWS – complete leader and supply chain
        • Siemens – institution-based, machines/phones/manufacturing and now high-tech medical instruments and big data
          • Data lakes, analytics and data-providing
    • Ultimate investment in next 3-5 years: People, data curation (either over-investing in tools that don’t need) or army of people (same problem)
      • No difference between retailer and tech or other companies
      • Personalize experience, data, customers
  • David Zhao? Baidu (Mastering Innovation, WhartonXM) – same day as ThumbTack march 14
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    • Talked about AI in cars (from SF Bay Area)
    • Ford’s “Faster horses” comment compared to just building the cars
      • Infrastructure came next – roads, highways
    • Initial autonomous thought sensors would have to be everywhere, infrastructure improved
      • Autonomous and sensors started taking hold once prices came down and placed into cars
    • Didn’t have a great guess – but 10 years, and he wasn’t sure how
    • Said a confidence interval would place the number of miles needed at 4 billion miles (and they’re at 800k?), 5000x necessary for Autonomous ‘comfort’
  • Michele Gelfand, author of Rule Makers, Rule Breakers (Wharton XM)
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    • How tight and loose cultures wire our world
    • Establishing relationships based on being tight / loose – none of us are across the board
      • Different tendencies – clean / neat, on-time, etc…
      • Working looseness or tight
  • Allbirds Co-Founders Tim and Joey (Built Product, Wharton XM)
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    • Talked about the business strategies they’ve had to employ, learn
    • Shoe laces that were excellent but cost too much
    • Having different soles that were 3x in cost, carbon 0
  • Adam Pritzker (@adampritzker), Chairman & CEO Assembled Brands (20min VC, 3/15/19)
    • Working capital and financial services, along with cofounder of General Assembly
      • Forbes 30 under 30, VF, amid others
    • Many in his family are entrepreneurs, so he felt it naturally
      • Empowering entrepreneurs – GA develop digital, and with Assembled Brands – products and goods
    • Optimistic about retail
      • Consumer spend much higher, and retail is closing faster – closes > openings
      • 90 of the top 100 brands lost market share (which means others are growing quickly, smaller / emerging brands)
      • Khait (partnered with a founder), and was able to look at the data in order to get a capital infusion for d2c side
    • Could map out the value chains
      • Incubated, operated emerging mobile-first, built distribution, developed creative content, financial p&a, benchmark and underwriting
      • Exists before vs exists today – as they re-platform retail, financing brands can be done differently
      • Traditional: purchase order would be collateral for bank but now buyers are individuals (banks and factories can’t underwrite this effectively)
    • One brand as brilliant vs another category not working
      • Very few SKUs and strategy can underprice incumbent by selling direct to consumers (mattresses, eyewear, razors, etc… as exception)
      • Adding channels adds complexity
        • Online/offline, direct/wholesale
        • Technologies for attending to business Shopify, Google Analytics, HubSpot
        • Creative/Quantitative marketing and product dev / manufacturing all to coordinate
    • Providing the network of founders and capital based on some of that data
    • Bigger problem isn’t price, it’s finding customer value wrong
      • Happens often where costs change or aren’t understood
        • Too many SKUs, optimization of prices around products
    • Saturation of marketing channels
      • Founders don’t realize that they can get to $30mln and cut growing to just get to profit
        • Safely growing, cutting can be analyzed – if costs remain the same but revenue squeezes, or dips
      • Instagram is the new QVC (best leveraging for social discovery)
        • Instagram empowers the content organically – ex of Halo Top
    • Fundraising infrastructure as broken – said it’s getting better
      • Old: Made samples, showed to stores, got purchase orders, use them as collateral for $ from bank, made goods and sold in store
      • New: Software and systems need to get streamlined to make it easier as the channels have gotten more complex
    • Niche exits more often than big ones
      • 70-80% ownership of the company vs multiple rounds and only 5% – can be similar exits if capitalized properly
    • Coddling of American Mind & Upside of Stress (Strive to be antifragile and to invite stress, fragility) as books
    • Design / brand that he likes: Uhuru Design, founded in 2004 in high-end furniture, contract division built out over time (d2c to enterprise)
    • Scarcity of financing and benchmarks, no IRL community for physical goods
    • Organic referral and repeat purchases (always delighting customers should be great way for a virtuous cycle)
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