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

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

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

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

  • Samir Kaji, (@samirkaji) MD @ First Republic Bank (20min VC 093)
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    • Leading private bank and wealth management, before at SVB
    • 1999 – “anyone with a pulse could get a job” but he was working selling vacuum cleaners at dept store
      • Was told by family to get a real job – applied to first business SVB, got resume in and interview immediately before starting
      • First couple years were tough – learned a lot, but was 2004 until companies had scaled and were getting bigger
    • First 10 years were tech companies, series A and B and venture debt – post 2009 Lehman / Bear, went to venture group at SVB for 4 years
      • Made the move with a few others from SVB to First Republic, now leading team in micro-VC and early-stage tech co’s
    • Says the micro-VC is more entrepreneurial & collegial compared to extended stage VC’s
      • First fund is that you can get traction for a second or third one, fees as pressure – most likely why many people come from some wealth
        • Writing large checks as GP, as well
      • 2-2.5% management fees initially vs 1 / 25 or 1/30 model
      • 1999 – 2002 distribution was 0.9x and you’d get 10x return (whoops) – very difficult for funds to get 2-3x for LPs
    • Barriers to entry much smaller for $20-25million as compared to $500mln – institutional, etc — he can go to family friends and high net worth
    • Seed over next 5 years: contraction in space (wrong), but said there isn’t enough returns for funds to max it
      • 1100 in the 2000 year and burst
      • Continued prominence of Angelist platforms, maybe an integral part of the ecosystem
      • Starting to see use of data (Mattermark, CBInsights, SignalFire) to more efficiently identify and action at this level
    • Favorite book is Phil Jackson’s – behavioral psychology, Give and Take is another one
    • Really respects the pioneers of the industry and first-time fund-raisers
      • Mike Maples, Michael Deering, Steve Anderson, Jeff Clavier when it wasn’t a thought
    • Habit – reading book or blog post for 20min in the morning before email
      • Disconnect from audio / video devices and reflect for an hour
      • 2 hours a day for family/friends and disconnecting, as well
    • Thomas Redpoint, Mark Suster, Brad Feld, Strictly VC, Ezra at Chicago Ventures
    • Knows awesome fundraisers but terrible at returning capital – didn’t mention any
  • Collectively Driving Change, Laurene Powell Jobs and Ben Horowitz (a16z 5/27/2019)
    emerson-full-logo

    • LPJ – founder, president of Emerson Collective
    • Grew up in NJ – father passed away in a plane accident when she was 3 – 3 children.
      • Mom remarried so there were 6 of them. Wooded area of NJ.
      • Core values and dedication to education to get out of the area.
      • She went to Upenn – first student from her high school that went to Ivy League – ~20% went on to more schools
    • Addressing East Palo Alto school as a volunteer to help – 1st talk, 0 had taken SATs
      • What happens when you’re first to graduate high school? What’s it mean to the information from family?
      • What happens to be first to want to go to college, thrive&complete it?
        • To have the aspiration, can be a leader in the family – translator, get sucked into all problems
      • Started with 25 freshmen – would have to come with friends for responsibility mechanisms – for College Track
        • 3000 high school students, 1000 college, 550 grads
    • Collective of leaders, innovators – education inequities, access and need for enhanced/robust curriculum
    • 10 year time horizons – getting them together is scheduled with Monday all-staff meetings (3×3 matrix of videos)
      • 5 cities, sometimes philanthropic speakers or reports
      • Discussion of reading as you fall behind through third grade before switching to reading to learn – already behind
    • XQ as SuperSchool dream – 17 of 19 will open in August
    • Caring about impact and solving problems, not wealth increasing – wants access to policy or money and not taxes
      • Judged Giving Pledge for not wanting to be more philanthropic
      • Environmental, edtech portfolio, cancer / oncology investments, immigration incubator, new thinking to old problems
    • How do you know when you’re succeeding? Collecting data on everything they do.
      • Example: XQ – schools and districts, state of RI as switching to statewide competition
      • Chicago has good data for fatal/nonfatal deaths (I disagree)
    • Imperiled or important institutions like journalism and media need to be sustained, how many join?
      • Concentrating and following where IQ is migrating (hahaha – what a joke)
  • Data Infrastructure in the Cloud, Rohan Kumar at BUILD conference (Data Skeptic, 5/18/19)
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    • Corp VP of Eng of Azure Data Team at Microsoft – SQL and data services, open source, analytics, etc
    • Trends in data engineering in the cloud, serverless and hyperscale
      • ML and AI and enabling applications – shifting to edge vs cloud – analysts predict 70% will be on edge devices
      • Solutions and private edges – training in the cloud and deploy them on the edge applications
        • Data platform needs to be the right foundation
    • Highlight for him from conference: work they’ve done on relational databases in the cloud – as volumes grow, scalability challenges
      • Hyperscale for Azure and PostgreSQL, as well as MS SQL soon enough – system scales with needs (they’ve tested <= 100TB)
    • Acquired Citus Data, support scaling out the compute layer – strong team, great product, matches in Azure and open-source
    • Releasing serverless option for Azure database – costs designed to stay low and optimized
    • Analytics side: customers wanted to do real-time operational analytics – didn’t want to move them outside of their core product
      • How is data distributed and having compute be co-located with the data to gain Spark efficiency being nearest to node
      • Support Jupyter notebooks across all APIs to modernize to do more predictive analytics
      • Attempting to build out pipelines requires too much scripts, instead have Data Flows in Azure Data Factory – no-code and UI
      • Wrangling data visually and seeing if something can be recognized or learned to repeat across other columns/tables
    • Latency won’t be ideal if compute nodes occur nonlocal to the data changes – can’t do 50,000 nodes all at once
    • Excited for the future: Horizon 1 (next 8-12 months), Horizon 2 (~3 years), Horizon 3 (moonshots)
      • H2: Hardware trends, what do customers want? Pushing boundaries of AI and ML, healthcare, gaming, financial services, retail
  • Wide or Deep? David Epstein, author of Range (Invest like the Best, 5/28/19, ep. 133)
    • First book’s research lead him to get into specialization and finding kernel for next
      • Some countries: turning around national sports teams – why don’t we try other sports? Contrary to 10,000 hour rule.
      • SSAC – debating Gladwell – athletes have a sampling period instead of first gene – delay specialization
        • Used Tiger vs Roger – Roger had tried a ton of sports vs Tiger who was born and was playing golf
    • He was not good at predicting what people/public would attach themselves on to – 10,000 hour rule – race/gender as most talked (but weren’t)
      • 10,000 hour rule were based on 30 violinists in world famous music academy (restriction of range)
      • Height in American population vs points scored in NBA (positive correlation) but if you restrict height to NBA players, negative
    • Finnish cross country skier who has genetic mutation similar to Lance’s boosted
      • Sensitivity to pain and modification to your environment – also sudden cardiac arrest in athletes (what pushed his interests)
      • Book as opposition to Outliers and Talent Code – interpreted a lack of evidence as evidence of absence (genetics matter)
        • First year he read 10 journal articles a day and not writing – they were making conclusions they could not make based on their data
      • Differential responses to training – best talent were missed because we don’t know about training responses
    • Collection and exploration phase – competitive advantage for expansive search function to connect sources or topics
      • Has a statistician on retainer, essentially, to check models or surveys
      • Wanted to know what he was missing – “how come I broke the 800m women’s world record after 2 years of practice? – genetic difference”
        • Racing whippets – 40% had a genetic defect that gave them more muscle and oxygen
    • All of sports as a limited analogy (problem after Sports Gene; now, more tempered)
      • Robin Hogarth addressed “When do people get better with experience?” Don’t know rules, can try to deduce them but can’t know for sure.
      • Kind learning environment: feedback immediate, steps clear, information, goal ahead
      • Wicked learning environment: can’t see all information, don’t wait for others, feedback delayed/inaccurate
    • Study at Air Force on “Impact of Teacher Quality on Cadets”
      • Have to take 3 maths – calc I, II, III (20 kids randomized) – professors best at causing kids to do well (overperforming) systematically undermined their performance thereafter
        • 6th in performance and 7th in student evaluations was dead last in deep learning
        • Narrow curricula were better at the test that they had at the end would be negatively correlated with going forward in performance
      • Teachers that ignored what was on the test taught a broader curriculum (making connections vs procedures)
    • Learning hacks: Testing (wonderful – primed to test ahead of learning), Spacing (deliberate not-practicing, Spanish ex spread 4 hour twice, 8 hours), Mixed practice
      • Ease is bad – known time horizon for when you have forgotten again – interleaving and spacing mixed
    • Passion vs Grit (“Trouble with Too Much Grit” – Angela Duckworth’s research)
      • Duckworth did a study at West Point for East Barracks cadets – candidates score (test + leadership + athletic) was not good prediction of doing this (overall it was good)
        • Grit was a better predictor for making it through East Barracks – she questioned whether it had an independent aspect
        • Variance for grit was probably 1-6%, especially after “flattening” groups – looking at people that had a narrowly defined goal for short periods (cadets or spellers)
      • Cadets were scoring lower on grit at late 20s vs earlier – tried some things, learned others about what they want – grit is poorly constructed
        • Look holistically – if, then signatures (giant rave – introvert, small team – extroverts) right fit looks like grit – developmental trajectory as explosion matching spot
    • Choosing a match for a future them who they don’t know in a world they can’t comprehend – people that find good fits (in practice, not theory)
      • Paul Graham’s “Commencement Speech” that he wrote “Most will tell you to predict what you want in 20 years and march toward it.” (premature optimization)
        • Everything you know is constrained by our previous experiences – limited as a teenager – just expanding and learning as you go forward
    • Gameboy example – with so much specialized information that can be disseminated easier – can take from all types of domains and recombine them
      • System of parallel trenches – can be broader much easier now – hired people for Japanese and German translations
      • Japanese man profiled in his book – technology was changing faster than sun melts ice – didn’t get Tokyo interviews
        • When he got to Kyoto company making playing cards, he was a tinkerer who was maintaining machines – started to mess with them (arms)
        • Turned them into a toy, and it was Nintendo – cartoon-branded noodles (failed), and had toy development
          • Lateral thinking with withered technology – stuff that’s cheap, easily available – takes into other areas
            • Remote control, more features – wanted to democratize this and strips it down – LeftyRX only left-turns
        • Sees calculator from Sharp and Casio and thinks he can do a screen and handheld game – small games
          • Had issues with Newton’s rings so he found other small tech (credit cards embossed) to fix small pieces
      • What it lacked in color, graphics and durability (could dry it out, batteries would be fine, split it up, “app” developers because it was super easy to understand)
      • In areas that next steps were clear, specialists were much better – less clear, generalists were more impactful – depends on the specificity of the problem
        • 3M had a lot of areas for this, “Periodic Table of Technology” – post-it note came from reusable adhesive that had no use for
        • Only Chinese national woman to win Nobel – “Three No’s” (No post-grad, foreign research, membership in academy)
          • Interest in science, history – Chinese medicine for treatments of malaria – world’s most effective treatment from ancient text
  • Greg Isaacs, BEN (Branded Entertainment Network) (Wharton XM, Marketing)
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    • Discussion of getting data from Netflix / Amazon / Hulu / tv to better match brands and advertising
      • Dirty data via a wharton grad who set up a survey style
      • Cohorts and demographics, along with psychographics
    • After getting data, attempting to approach Youtubers / social media influencers, tv spots and channels or shows to get their brands in front of the right people
      • More pointed, depending on what interests are for their cohorts
      • Creative storytelling as the change of cultural mind shift has increased
  • Understanding the Space Economy, Sinead O’Sullivan (@sineados1), entrepreneur fellow at HBS (HBR IdeaCast #684, 5/28/19)
    • Facebook, Amazon (3000), SpaceX (12,000) and other funding like Blue Origin / SpaceX / asteroid mining or travel
    • Global space economy as $1tn by 20 years – currently $325bn so it would need to 3x
      • Breaking apart space resources and otherwise – earth-focused (delivering or existing in space that helps earth)
        • Exploration or creating interplanetary existence
    • Running out of space in space for satellites – comparing to airplane docking / loading
      • $2500 per kg now to launch, used to be $50k / kg
    • Reliance had been on unilateral agreement for space policy – one tech startup launched a satellite that didn’t have permission (but no fall-out)
      • Food / grocery stores, wifi, phone, insurance pricing due to satellite data – reliance on services are increasing as the market increases
      • Thinks that we’re close to seeing the cheapest cost of launching – cites SpaceX, but won’t allow everyone to participate
    • Ultrahigh accuracy will require higher powered satellites – GPS, nonmilitary grade is ~0.5 m – thinks it will prevent autonomous vehicles solution
    • Ton of money going into asteroid mining but thinks it’s better for testing missions to Mars and figuring out the problems for future
      • Looking at Uber at start and say “people won’t get into a stranger’s car” or other cases as how we see the future – going to Mars, etc
    • Earth-focused space technology – 100+ launched satellite start-ups, micronano satellites, relay companies, downstream analytics
      • More touchpoints for everything in this manner
      • SpaceX will increase public and government intervention and within 50 years, maybe see a human launched there
  • Investing w Twitter Sentiment, Andy Swan (@andyswan), LikeFolio (Standard Deviations, 4/25/19)
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    • 1700+ tweets examined per minute in LikeFolio – discovering consumer behavior shifts before news
      • Direct partnership with Twitter to create massive database and how they’re talked about to look for mentions
      • Purchase intent, sentiment mentions – trends across product categories or brands
    • Example – Delta (as host is a loyalist) – making adjustments
      • Expectations are the relative part – comparison to the baselines (metrics compared to itself as baseline)
    • Put out a comprehensive report on Apple day after keynote event – September 14, 2018
      • Consumers were unimpressed with iPhone lineup – more price sensitive than maybe they’d considered
      • Apple Watch was the silver lining – stock / sales may struggle over 3-9 months (upgrade cycles)
    • WTW version of keynotes – NYE resolutions – subscribing early to drive revenues the rest of the way
      • Purchasing mentions were only up 30-40% compared to 5 or 7x weekly mentions (big difference)
    • Shelf-life and how to consider the sentiment data – lead time may be binary corp event (same store sales or year)
      • Couple months with Apple, for instance, but with Crocs – resurgence that persisted to current time
    • Set up keyword structure and brand database – “I’m eating an apple” as opposed to an Apple mention – human eyes to ‘label’
      • “Closed my 3 rings” – apple watch but sarcasm / spam that wasn’t caught (estimates at 2-3% of data)
      • If spam / sarcasm are consistent portions of the data, doesn’t really have an effect
    • Twitter Mood Predicts Stock Market – Bollen, Mao, Zeng (88% and 5-6% predictions) – fund closed up shortly
    • Advantage being better than analysts or pricing and codifying sentiment behavior compared to past quarters, data
      • Some consumer trends analyzed as true tipping point or actual movements
      • Public prediction before productizing their modeling – made 40 and were 38-2 (confidence as highest)
      • Investing as very specific, concentrated and holding ammo compared to trading with option spreads and has risk profile built
    • https://arxiv.org/pdf/1010.3003.pdf
    • Diversification as 20-25 stocks, doing it over time and with conviction can be done
    • Starting in Louisville for his fintech company, host in Alabama, for instance
      • Talent can be more difficult to seek out but the world is globally flattening via the internet
      • 70% lower overhead cost than being in SF, for instance – developers would anyhow be in Slack channels / not a big deal
      • Reduction in cost maintains greater control of company since they don’t have to take reduction of equity to gather more
    • Network effects don’t matter if you don’t have a great product or product-market-fit
    • Free association game
      • grapenuts: best cereal (Co’s been around for 100+ years, branding and $ spent and they can’t figure it out)
      • Fintech Future: individualization and customization
      • Victory: most important thing in life, achieved what you set out to do – setting goals and achieving these
      • Bourbon: pappie von winkle – collecting for dust on shelf 10 years ago and now going for $3000
  • Jonathan Abrams, co-founder Nuzzel news (Launch Pad)
    nuzzel

    • Landing hedgehog as the mascot – animal as cute, 99designs and surveying 50 friends – 25 men/women
    • Discussing how VC’s don’t have great advice, especially when general – too hard to be an expert in such a wide range
      • Finds it easier to be very context-driven and providing solutions or action-oriented questions to founders
      • Investing now easier with YC and Angelist, etc…
    • Timing and other mistakes he made – out of control, losing equity part early (but depends on where you are / what you need)
  • Etan Green, professor at Wharton (Wharton Moneyball)
    • Discussion on paper of how sharp money comes in at horse racing tracks
      • Difference between sites – fairground action compared to tracks, and specific to region (New Orleans, Minnesota, for instance)
      • Big sharp money comes in very late, pushing the underdog prices to higher values
        • More expensive to bet while at the track than the APIs enabling higher volume bets
        • Books at the track are incentivized to bring in as much $ as possible, so $0.20 on $1 vs $0.15 rebate on $0.20 for volume
    • Value and differences in how people will bet
  • Edith Dorsen, Women’s VCFund founder, MD (Wharton XM)
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    • Talking about their focus on first fund, approach
    • Opportunity for finding diverse founders, 25% of their fund had a woman founder
    • Starting a second fund
    • Had consumer tech, enterprise and not so much b2b, but trying to increase
      • Hard to say or give advice if one of their partners don’t have expertise in the domain
  • Sophie Lanfear, Silverback Films producer on Netflix “Our Planet” (Wharton XM)
    • Species that are dying, going extinct
    • What we can do about it
  • Aliza Sherman, Ellementa co-founder, CEO (Wharton XM)
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    • Discussion of client talks when she made them aware of her cannabis endeavors
    • How friendly the community is
      • Then knocked the idea that ~30% was female to start before diving off a cliff
    • CBD to mask opioids – does it really do anything from a pain/treatment perspective, though?
      • Anti-chemo because of CBD – really?
    • Sounded too rehearsed – made it sound fake, not genuine
      • Passion/motivation/mission and kept repeating as the best advice she could give – painful
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Thinking Through Data (Notes from May 13 – 19, 2019) June 5, 2019

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

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

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

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

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

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

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

  • Eric Topol (@EricTopol), author of Deep Medicine, cardiologist (Wharton XM)
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  • Deep AI and medicine – asking how to properly apply deep learning or AI to medicine
  • Yet to have a drug made by AI
  • Bayesian principles failing in medicine community
    • 12% of women get breast cancer, yet we ask them to do 1-2 years mammograms
      • 10 year span, 60% will get a false positive (yikes!)
    • Adopters of Apple Watch and its cardiogram / heart information are treated unilaterally
      • Young, healthy and curious people may not have any arrythmia so any abnormality (totally normal) may be misdiagnosed
        • Signal from heart rhythm from one person may be different from another
    • Says it’s a sign of being behind (3rd industrial vs 4th for the rest) when Stethoscope (invented 200+ years ago) is still sign of industry
      • Analog, no option of recording and is still very subjective to the doctor listening
      • This, despite advances in imaging and scans otherwise
  • Mir Imran, Chairman & CEO of Rani Therapeutics (Bay Area Ventures)
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    • Talked about the big equity stake his fund took in the company, wanting it to be a big hit
    • Drug development, say, an insulin pill compared to injections (spent 150+ years on solving this)
      • Stomach / pill form in past is only 0.5% or < 1 % efficacy – can’t intake that many pills or cost-effective
    • Designing pill that is pH-shell-dependent to identify intestine pain receptors are limited (can inject no problem)
      • Pill recognizes pH change by dissolving outer shell (to pass thru stomach), then sugar-needle injects
      • 1000s of animal trials and just passing pills
      • Started trials ~18 months ago in Australia for pill traveling (using x-rays every 30 min to track)
        • Then progressed into drug for giantism, along with looking at other biologic diseases / solutions
    • Don’t want to limit biologics to a single buyer (Novartis, Genentech, etc…) – keep it open
      • Investments from Novartis and Google initially ~$150mln worth now
  • Mapping Dialects with Twitter Data (Data Skeptic 4/26/2019)
    • With Bruno Goncalves about work studying language – now @ Morgan Stanley
    • Started with research in CS and Physics, moved eventually to Apache weblogs, email, big router logs, Twitter conversations to study human behavior
      • Turned into looking at Twitter check-ins with the log using longitude and latitude
      • Language used: order maps, areas dominated by specific language (drawing boundary between French and Belgian in Belgium, for instance)
        • Intermingling cities that attract many languages
    • Spanish changing from one areas to another – everyday words, phrases
      • Can use the location data to determine the area of dialects – splitting Brazil, for instance (South, North and then central American)
      • Dividing grid cells into km x km – maybe not determinate of gradients of English vs Spanish since they were testing dialects of Spanish
    • Each row corresponds to each cell and words, but the matrix essentially loses the meaning
      • Ran PCA analysis and K-means on the clustering
    • He’s gathered 10 tb of data from Twitter, corpora and looking at millions of tweets – too few data to look over time
      • Measuring language changes over time was difficult for Spanish, but easier with English
      • Used Google books, for each language and counting bi-grams in how many books – popularity of words
        • Corpus of books published in UK vs US for Google books (1800 – 2010) for reliable data, but further back was less popular
        • Could normalize for words on how American vs British words were (and the mixture)
    • Recently, looking at demographic splits of language now with more digital / online presence
    • Training spellcheck based on dialect or demographic splits
    • Doing this stuff part-time now – how to train a model to detect use of language in this sense
      • Using word embeddings to detect automatic meanings of slang to determine the different meanings
  • Matt Turck with Plaid co-founder, Podcast
  • CSR in Gaming Industry,  (Wharton XM)
    • Discussing how it can be weird to gain competitive advantage and share
    • CSR as large subjective to the person looking in
    • Gaming companies chip in to gambling addiction hotlines / help / etc
    • Particularly in Las Vegas / NV, CSR survey determined that direct opportunities in water conservation, energy and green energy
      • How can they more efficiently run such large operations
    • Survey had about 80% of the gaming industry represented, from servicers to manufacturers to casinos themselves
  • Suranga Chandratillake, GP at Balderton Capital (20min VC 090)
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    • Founded blinkx, intelligent search engine for video/audio content in Cambridge in 2004
      • Lead company for 8 years as CEO through journey to SF, building a profitable biz and going public in London
    • Early ee at Autonomy Corp, engineer in R&D and then CTO when he went to SF
    • Belief in technical person shouldn’t be CEO – idea has been replaced in US (probably split)
      • Jack Dorsey, Zuckerberg (went into Dorsey and the idea 2 companies that aren’t really overlapping)
    • Been impressed by both Gates and Zuckerberg
      • Knowing the code and going through to understand everything
      • Zuckerberg’s acquisition of Instagram (ridiculed for $12bn and how right he was – surpassed Twitter’s users)
    • 2 Things for Tech going forward – changing infrastructure
      • VR and including drones or autonomous vehicles – hardware progression and mobile phones for what CAN be done
      • Societal difference – how we change to gig economy or how we work and spend time each day
    • Changing investments – just announced investment in Curious.ai
      • Shorter term where society is changing (eg: Nutmeg for planning pension plans, cheaper and available)
    • Structure for Balderton as equal partner VC – not sure it’s the most efficient model, but thinks it’s the best
      • Equal partnership where the partners have all the same number of votes, compensation and identical split
        • Removes the politics and impacts the partners and the stakeholders (founders that may be affected)
      • No single group that can carry the vote – hiring becomes very difficult because you need an equal
    • Knowing when to stick and when to switch
      • Deciding when to say “We don’t do that” and pivoting and being right
    • Exciting company for investment that he’s done recently – Cloud9
      • All development being done in the cloud now
  • Nick Leschly, CEO Bluebird Bio (Wharton XM)
    bluebird-bio

    • Purpose Built, 5/14/19

 

 

  • A Guide to Making Decisions (a16z 5/12/19)
    • Emily Oster, Hanne Tidnam discussion
    • Health and personal spaces – “right” thing isn’t a difference for some
      • Cocoa crispies, eggs and the preference for why you eat them, not just health-related
    • Impact of breast feeding vs not and looking against obesity
      • Less likely to be obese if breast feeding
      • Random trial for this is from Belarus in the 1990s where they requested parents to some breast fed
      • Siblings in choice to breast feed – almost no correlation if they did or did not
    • Constrained optimization – money or time
      • As parent, making choices based on preferences but have constraints
      • Recency bias for current literature – only data will be problematic and that it can only support a relation
    • Regression discontinuity as drawing a line and then seeing interventions and how they may change or affect outcomes
    • Screen time as having evidence that’s just very poor
      • Not easy to run randomized trial on – iPad or lifestyle would have to change for trial
      • Apps in short term doesn’t have the info available for results / outcomes
      • Studies currently don’t have any conclusions on phones/tablets – little
      • Bayesian updating on uncertainty – if 2 year old spends 50% of waking hours, that’s bad. Where’s the limit?
    • Last time went to doctor – very concretely made a recommendation of “2 hours max in a day”
      • How does the information get to that level of the system?
      • Conversations occur with doctors where they essentially make the lines that stick, pass on
    • Recommendations go out as arbitrary but now are made as truth – terrible without the decision
      • People that take the recommendations are likely more different or health-conscious
        • Added another layer (vitamin E, for instance) – those that adopted did many other things
    • Just be wrong with confidence – can be right, lots of good options
  • Innovating in Bets (a16z 5/8/19)
    • Annie Duke (@AnnieDuke), Pmarca, smc90
      annie-duke-thinking-in-bets-199x300
    • Every organization and individual makes countless decisions every day, under conditions of uncertainty.
    • Thought experiment: posing Seahawks run the ball and are stopped vs passing and throwing pick
      • Once there’s a result, it’s very difficult to work backwards to assess the decision quality was.
        • Outcome was so bad – it was in the skill bucket. Or – oh, there was uncertainty.
      • Very slow in NFL, for instance, to adopt analytics according to the numbers
      • 4th and 1 – should unanimously go for it since numbers say the other team will get 3, expected
    • As a decision maker, we likely choose the route that keeps us from getting yelled at
      • We allow uncertainty to bubble to surface – conflicted interest – long run vs short term
      • 2×2 matrix of consensus vs nonconsensus and right vs wrong
        • CR fine, NC-R genius, CW – fine (all agreed), NC – W really bad
        • Outcomes are right and wrong – hard to swipe the outcomes away
      • Thinking or allowing uncertainty in human driving and killing a human vs autonomous vehicle
        • Black box not understanding autonomous vs THINKING understanding another human (“Didn’t MEAN to do it”)
    • Anybody in business – process, process, process
      • R/E business – everybody in room after appraisal is 10% lower vs 10% higher (similar analysis)
      • Outcomes come from good process – try to align that an individual’s risk matches with corporation’s
        • Rightest risk – model could be correct (tail result) or risk decision (and deploying resources)
    • Most companies don’t have SITG – how to drive accountability in a process-driven environment so results matter?
      • How do you create balance so outcome caring about is the quality of forecast?
        • State the model of the world, places and what you think. How close are you to the forecast?
      • When you have a bad outcome and you’re in the room?
        • How many times do people say “Should we have lost more? Should we have lost less?”
      • Learning loss – negative direction on how to figure out? Poker example of betting X, X-C or X+C
        • Bet X and get a quick call. Should’ve done X+C (learn, regardless of opposite getting a card)
    • How much can you move an individual to train thinking? Naturally, thinking in forecasts more. Will have reaction and lessons quicker.
      • Getting through facts quickly and having the negative feedback – not robots
      • Improved 2% which is amazing – what are YOU doing to not make it worse?
      • “Results-oriented” as one of worst for intellectual work – need a process.
    • Story of “something is happening” is not a good story. Hard to read journalism now for him because they’re both “non-consensus”.
      • She’s optimistic that people can be equipped to parse narrative to be more rational. Pessimistic of framing and storytelling currently.
      • “Not making a decision” is making a decision but we don’t think of it that way.
        • Really unhappy in a position. Did the time frame thing “Will you be annoyed in 1 year?” – Yes. Nondecision didn’t feel like decision.
      • Mentions not having kids – time, energy, heart and decisions associated with indecision.
    • On individual decision, you have: clear misses, near-misses, clear hits
      • Bias toward missing – don’t want to stick neck out. Have to see it in aggregate. Forecasts.
        • Anti-portfolio / shadow book is really about when you include clear misses vs near-misses.
        • Fear is that the ones that hit are less volatile or less risky will be returning less than shadow portfolio.
      • Says it’s difficult to do with 99:1 turndown vs investments. Sampling.
        • Time traveling with portfolio – bounce out and see if “if this is 1 of 20 in portfolio” vs “invest vs not”
    • Conveying confidence vs certainty
      • I’ve done my analysis. This is my forecast. Is there some piece of information I can find out that would change my forecast?
        • Bake it into the decision. Not modulating the forecast – 60% to 57%. Costs and time differences.
      • Putting confidence interval on earliest dates and another probability, inclusive, on latest day
        • “I can have it to you on Friday 67% of time and by Monday 95% of time.”
        • Terrible to ask “Am I sure?” or others “Are you sure” compared to “How sure are you?”
    • Pre-mortems in decision analysis
      • Positive fantasizing vs negative fantasizing (30% closer to success by thinking of hurdles in front of you)
      • What happens if you ask out crush and they say yes? What happens if you ask out crush and they say no? – No’s more likely.
      • Teams get seen as naysayers – individually write a narrative on pre-mortem – good team-player is how do you fail?
      • After outcome, we overweight regret – don’t need to improve this much. Look out a year and see if it affects you.
  • Mary Gray, author of Ghost Work: How to Stop SV from Building a New Global Underclass (Wharton XM)
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    • Research with coauthor at Microsoft Institute
    • Discussion of the b2b services that run in the background – used Uber’s partner as example for driver verification ID
      • Beard vs no beard on default, for instance – need close to 100% accuracy and algorithms/vision can’t pick that up just yet
    • Humans that run mechanical turk or various tasks on classifications
    • Technology used to be cat vs dog and now it’s species of dog – likely tech will enable more specific classifications but not remove intervention
      • Running with surveys, captioning, translations, transcription, verifying location, beta testing are all tasks
    • Used another example for “chick flick” meaning or 2012 debate with Romney’s “binder full of women” comment
      • Needed humans to assign relevance and to provide or connect proper context (Twitter, for instance)
    • Facebook and its content moderators, most social media companies do this
  • Trends in Blockchain Computing, (A16z, 5/18/19)
    • Get paid for AI data or encrypted data – can still train a model on it but nobody would know exactly what the data is
      • Long term accrual – depends, also, on if it’s on AWS vs open-source
    • Gold farming and ex-protocol websites in WoW, for instance – virtual worlds

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

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

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

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

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

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

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

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

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

Changing Tides – CPG, Fin Plan, VC (Notes from April 1 to April 7, 2019) April 24, 2019

Posted by Anthony in Digital, education, experience, finance, Founders, global, social, Strategy, Uncategorized.
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Spring is in full bloom! The California weather vortex mixture of April showers bringing May flowers. Only, we skipped flowers part and went straight to 70, 80 and now nearly 90 degree weather. Dry land. If that doesn’t work for some outdoor BBQ, wine tasting and good friends, I don’t know what would.

That didn’t stop the a16z podcast from having a collection of people on that focus primarily on CPG. What is changing in the industry – if anything – as it’s notorious for being slow moving? We see attempts at the various points in the distribution side but it becomes about scalability. Amazon/Whole Foods combo? Or will it be primarily food delivery? Seems similar to the car/taxi/autonomous question of ‘last 2-3miles’.

Then we have a similarly plodding industry, which was the last 10 years of growth seen in startup financing for Europe and London. How did the dynamic change for the founder of Hoxton Ventures once he left Silicon Valley for green pastures of London? Why is it that he maintains a global view while in Europe but keeping tabs on the US market?

Lastly, I wanted to reiterate a theme I’ve focused on previously, which is asking the right question and how that determines the plan for action going forward. A discussion I listened to with an NLP expert at AT&T Labs as well as in asset management and personal finance where people need to find better ways to match expectation with reality – whether it’s in data of tv usage patterns, network effect results from cell data, or agents looking to align incentives for a customer portfolio and their book.

Hope you enjoy the notes!

  • Hussein Kanji, founder Hoxton Ventures (20min VC 086)
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  • Started at Microsoft, went to Accel Partners as board observer (Playfish), acquired by EA
    • Seeds into Dapper, OpenGamma – yahoo acquisitions
    • Founded Hoxton and raised $40mn
    • Moved to London in 2005 for graduate school and had a colleague from Bay Area that made an intro for him at Accel to connect
    • Accel as $500 mln fund, to break-even on the fund, you need 40x’s on early stage, but bigger funds focus on late stage for big money and returns.
    • He became bullish on Europe in 2009, 2010 – shifting for platforms that were global.
      • Europe was historically underfunded, so focused on their domestic area (and would then run into US competitor that was bigger)
    • Raising the fund took about 3 years (‘normally’ 12-18 months)
      • They budgeted for 24 months and had aimed for $25mil
      • Americans said that venture investing wasn’t viable for Europe – “nothing on the ground floor”, can’t see, etc…
      • Europeans couldn’t see it after conservative – investing as gambling, etc
    • Once leaving Cali, “prove you’re smart” or “rolodex works” – network is just that you’re out means you’re disconnected
      • Some still have this sense, others don’t
    • At this time – US $ makes up about 2/3 of Series B or later funding
      • At the time, NY could do funding for 1Q that would be London for a year
    • Blog – Abnormal Returns – mentioned Flowers for Algernon (book take)
    • Follow up amounts – just backed a digital healthcare company
      • AI and live video with physicians – app for something wrong or not
  • Chris Maher, CEO OceanFirst Financial (Wharton XM)
    oceanfirstpressreleasimage1a

    • Talking about knowing someone when they’re nearly in default
    • Being prompt and succinct with bad news – doesn’t improve if you delay
  • Who’s Down with CPG, DTC? (a16z, 2/16/19)
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    • With Ryan Caldbeck (CircleUp, Jeff Jordan (GP a16z), Sonal
    • DTC movement with tech VC firms focused on selling prominently to consumers – not product innovation
      • Marketing companies vs innovating – can’t change distribution to compete with Amazon, so proprietary SKUs not on Amazon or retailers
      • Dozen brands have 10 companies trying to compete for you, as a startup – ecommerce can’t get big in US outside of big 5
        • $1bn profit and sales
      • CAC marketing dollars are too high now when they scale
    • Unilever (DSC) and other CPGs with biotech / big pharma buying innovation
      • Clorox and Colgate as breeding ground – “If you can sell sugar water” – Jobs / John Skully
      • Selling the same product for 30 years – wouldn’t happen in tech
        • Harvard dean book called “Different” – small improvements (mentions wider mouth on toothpaste)
          • 99% exactly the same vs 1% is different – Harley Davidson, Red Bull, etc…
    • Internet enables $5mln revenue line, not tv – long-tail discoverability – can make hits on this
      • Proliferation of cpg (Sonal questions why no DTC, though)
        • Harder to a/b test or change packaging with ‘atoms’ vs ‘bits’ – trying products, packaging
        • 2-4 sets of year with 5 stores for 6 months, then 50 for another 6 months, etc… while you’re growing (Disney example)
      • CPG companies can’t start in 5 Safeways, do it in 200 but if you miss – it could be over
    • Sonal at Xerox Park – had a big CPG client whose challenge was what happened after customer purchased product
      • Worse – knew what they sold to retailers but not what product was bought at the retailer – CC cos don’t sell that
      • Some retailers may have loyalty cards but not in way that aligns everything
      • InstaCart compelling because revenue from grocery, consumer, cpg companies interested in accessing consumer
        • First performance marketing – know everything consumer has bought
      • Used an example of Steak next to wood chips at a Safeway – different than buying an end cap which would’ve been 20+ ft away
    • Food is < 5% of online – food will be delivered locally – hard to strip out costs from 2-3% net margins
      • Tech needs to penetrate cost margins – China experimentation with restaurants inside grocery stores – Asia / India not necessarily core differentiator
      • Delivery will be a convenience over an experience (as it is now) – could be 50 year vision
        • Price, experience, convenience, assortment
    • Loyalty cards don’t actually give you much more – very self-selected but at least SOME data, though adverse selection
    • Large brands losing share to small brands – decline in distribution costs that are more shifting fixed costs to variable costs
      • Big ones are struggling to work with the smaller brands (new chocolate bar – $100k to get onto the shelf which has decreased vs internet $0.99)
      • When Jeff was managing ebay – tv would be $1mln to produce ad and $10mln to distribute for what may be efficient
        • Now, marketing is a $10k youtube or facebook ad and you can hit your target audience
      • Number of brands proliferating but grocery / CPG only growing 1-2% – $ per brand comes down (more choice vs less)
        • Sonal brings up the ‘right’ choice to the right people – not stripping the choices (say, Coke vs Pepsi)
    • Offline world has been impossible to get the data you want but it’s difficult to get what you want pulled together
      • Entity resolution – google results, Instagram, Facebook, Amazon, sold on Whole Foods – different names and decide how a product is what it is
    • 3G Effect – large South American company delivering shareholder value, R&D is first – 2% of sales; tech is ~14%
      • Some private markets in CPG – quantitative funds with AI / data scientists – repeated in CPG with all the same business models
      • Private equity / training data would be really hard to match that
    • Quant funds as looking at tech – miss outliers, no pattern, apriori; CPG could be patterned since winners are similar
      • Brand intensity with consumers, Product must have uniqueness – Vitamin Water / Kind bars
        • Kind bar had insight that they show their food (packaging see-through) and you can see that it’s not processed
        • Must resonate still (could put fish in product but may not be good)
      • Distribution gains is how you win – big winners don’t only sell in stores
        • Breadth and quality – where product is being sold (Whole Foods / Costco / brands want you to know it)
  • Josh Brown, Ritholtz Wealth Management (Wharton XM, Behind the Markets)
    • Discussing how he thinks it should be required to have managers match the client offerings
    • Takes longer but they take risk of getting to know clients and plan ahead of putting into place
    • Going after the right CFPs for the overall view – location not necessarily important
  • John Odnik, Consulting for Wharton Small Biz Dev Center & Principal at The Ondik Group, (Wharton XM)
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    • Talked about operations and sales improvements, what he looks for

 

  • Noemi Derzsy, Senior Inventive Scientist at AT&T Labs, D/S and AI Research (DataFramed #56, 3/11/2019)
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  • Started in academia but didn’t have bandwidth for O/S projects until NASA “datanaut”
    • Provide a community for supporting women in the open source, women in ML and D/S
    • Government forced NASA to opensource over 30k datasets
    • Chief Knowledge Architects, David, is very supportive of the community and open to question
      • Launch application opportunities to be selected yearly, typically, for datanauts (open.nasa.gov)
    • Teaching and pedagogy for her – network science focus on complex systems, done many workshops
    • 2006 as she finished her bachelor’s degree, she needed a thesis topic (Physics + CS)
      • Built a network (both directed and undirected) system between European universities and students who went between them
        • Small dataset snapshot from 2003, matrix form (value of university to another in a row/column)
          • Professors’ network influencing students’ movement among universities
          • Initial data was most interconnected by the level of partying done at university
    • Brief about business at AT&T Labs – solving hardest problems, and improvement should allow for efficiencies
      • AT&T owning Turner and how much tv data that allows them more recently – made a whole division
      • Advertising jump after AdNexus (now Xander) improving ads in the entertainment space with all of their data
        • She’s fascinated by bias and fairness in advertising marketing
      • Creating drones for sat tower analyzing – DL-base to create real-time footage for automating tower inspection and anomaly-detection
    • Her projects: human mobility characterization from cellular data networks – how to move through space and time and interactions
      • Large-scale anonymized data – mentions her frustration from interviewing the prior year where positions were in completely new fields
      • Nanocubes – AT&T creation that’s opensource and visualize realization
        • Large-scale, real-time data set availability with time and space
      • 2006-2010 paper about seeing the anonymized data where at a certain time in a certain city, there would be stopping of texts and move to calls
        • Turned out to be calling taxis at the end of night from bars / out
      • Networks as everywhere: protein interaction, brain neural, social, street/transportation, power, people
      • Topology can show basic features – degree of nodes/connections and their distribution, most nodes have very few but small hubs have very large connections // mentioned Twitter with few users at 100ks
        • Clustered node networks or are there homogenous subgroups – filter bubble / echo chambers
        • How to influence people – distribution understanding and seeing the dynamic processes dependent on the network structure
        • Cascading failure: info flow, nodes have assigned capacity – 1 failure reallocates the load to neighboring (power grids)
    • Product management fellowship related to data science and what vp of marketing, c-suite needs to learn or know as it pertains to data science
    • One of her favorite – unstructured data and text data in NLP as fascinating projects where you can pull features

 

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)
    00-helpshift-4-7

    • 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)
    denali-therapeutics-large

    • Focusing on neuro degenerative diseases, isolating proteins that cause damage
  • For the Billions of Creatives Out There (a16z, 3/16/19)
    SHOW_KO.eps

    • 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)

Data + Opportunities for Masses (Notes March 4 – March 10, 2019) March 28, 2019

Posted by Anthony in education, experience, finance, Founders, Hiring, medicine, NFL, questions, training, Uncategorized.
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This week was all about different types of people chasing and building what they wanted to build. What drives people – what are they drawn to? Passion, energy and asking the questions to further the quenching of thirst for the next step. Reading the notes I had for this had me down a rabbit hole for each one – thus the delay.

Interestingly enough, these founders, presidents, authors and data scientists / explorers are in different industries. We had digital tech and marketing, strategy, data science as it applied to healthcare, NFLPA / financial literacy, and education of cs and tech stacks through ISA’s.

Believe that you can learn from others to further what you do to progress forward.

Steve Mast, President and CIO at Delvinia (Measured Thoughts, Wharton XM)
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    • Using Methodify for geolocation data / surveys
    • Digital tech to help marketers, researchers and leaders collect, visualize and enable data
    • Educated as an architect, then video game designer and producer in the 1990s
    • Joined Delvinia in 2000 to build interactive design and digital marketing
      • Talked about doing events where they get volunteers to sign up for brand / marketing analysis
      • Ask 2-3 questions that are pointed, geo-enabled for brand / important points at the event
      • Makes sure not to have personal identifiers
  • Joseph Jaffe (@jaffejuice), author Built to Suck (Wharton XM)
    • Admiral, co-founder at HMS Beagle, strategy consulting for surviving
    • Talked about how Harley Davidson is in every marketing book but what are they doing now? Floundering
    • Nike ads – never talked about the product (shoes), but call to action – Just Do It
      • Nike as providing the tools for which you act
      • Used their stores as ex of environments for their product – having treadmills
        • Each employee was a runner, wearing Nike and touting the products, experts
    • Remembers asking his class if they knew the first bank to implement ATMs
      • Didn’t provide the answer – jumped into 4 P’s – one student asked what the answer was
        • Answer was that it didn’t matter because every single bank mentioned had ATMs
      • Only thing that mattered – first-mover’s “advantage” if you can keep it
      • “What are you doing now?”
  • Chris Albon (@chrisalbon), Getting First Data Science Job (DataFramed #55)
    2672ecf4-b76e-478c-9407-fc48877479bf-1515514797324

    • Data Scientist at Devoted Health, helping to fix healthcare system
    • Co-host of podcast Partially Derivative, since stopped, and had a kid / moved
    • Humanitarian non-profits, working on team for building companies with a soul
      • Devoted – health insurance company started by Todd (CTO of US) & Ed Park (CEO of health company)
        • Creating company that you’d want family members be a part of
        • Make healthcare that works (primarily senior citizens, Medicare)
    • His background is from quantitative political science – politics and civil wars
      • Perspective of research, experimental, statistics – PhD with these fellows
      • Meeting friends with a ton of amazing, applied projects (LinkedIn, etc…)
      • He needed to be applied vs research in order to get out of academia – joint Kenyan nonprofits (election monitoring and disaster relief)
      • Real data or fake reports, safety, ethic and morals come up – threat models aren’t the same
    • First hire at Brick (free wifi to Kenyan homeless, etc…)
      • Using established tools to provide others data / analysis – for a team to not know that going in, it was impressive (wizardry)
    • As a team, you can hire and absorb senior data scientists
      • People who got first time jobs at Facebook or something, got to see scale and experience that they can move on easily
      • At a Facebook/Google, end up doing heavy data analyses for the massive scale and is a big role
        • Hard, analytical challenges
      • Smaller companies may ask someone to do a ‘full stack’ / general data scientist that has to build everything on their own
    • Early on in hiring process – ex with Master’s in ML, and that’s what you want to do
      • Generalist builders at Devoted, but not strictly ML or other thing
      • Heavy AI or ML would be theory-based, dissertation level technical discussion (obvious focus)
    • Doing data science generally – many other problems – Bayesian analysis, RF, etc…
      • Far more jobs for those that are generalists at companies for business data – predicting drones watering crops, customers churn, illnesses
    • With different backgrounds, should figure out how to feature yourself & experience
      • Side projects, blog posts, portfolio, visualizations in a way that’s easy – testing, GitHub, versioning
    • Talked about his first meeting at Devoted Health – 4 data scientists in the room with a doctor, discussing the coding of health / diagnosis
      • Said he was fascinated in the meeting as he wanted to know that side, new business
    • He genuinely enjoys new techniques, analysis that he doesn’t know and learning about it – passionate about what they are and learning
      • Not hiring for junior – it’s because you will want to grow into senior
    • RF > SVM since it works out of the box, but said SVM is an awesome mathematical tool
      • Used it as a teaching point and visual – but in production, he’d never seen it
  • Eric Winston (@ericwinston), President of NFLPA (Wharton XM, Leadership in Action)
    • Talked about how important relationships and the soft skills were
    • Financial literacy as a passion of his – talked about how little players know going in, especially after college
      • College finance doesn’t teach it, either
  • Austen Allred, Founder/CEO at Lambda School (20min VC 3/8/19, FF)
    untitled

    • Bedrock, GGV, GV, Stripe and Ashton Kutcher as investors – $48M so far
    • Prior, Senior Manager for Growth at LendUp and co-founded Grasswire
      • Income inequality, financial health thoughts – nothing was moving incomes
      • Was in a small town in middle of nowhere, Utah
    • Had to live in his car in SV for a while and figured out how to schedule – during summer, would get hurt obviously
    • Raised $500k initially, couple months of cash left, due diligence – investor decided to not continuing Dec 23 (daughter was born soon after)
      • Never wanted to be in that position again – thought it would’ve been VC but it was more about a successful business
      • At YC, wasn’t focused on demo day – modeled 2 scenarios: 1 with VC money vs otherwise going wrong and seeing no VC money didn’t work
    • About the right time to raise: $1 today would be $3 or $4 later, still had much of their series A – getting dozens of VC emails and say no
      • No goal to raise B at that point, walked through the numbers with Jeff (one of investors) over dinner
      • So Good They Can’t Ignore You (Steve Martin quote, but Cal Newport book)
    • Looking at product-market fit – people would pay whatever to get to the job / signal
      • Incentives aligning, job and person – $1000 to start and pay after getting a job: Got into YC and thought no upfront deposit, etc…
      • List of 7k people, trying to refine and make sustainable
    • Training people online was tough, free upfront / no SITG – no Bay Area / NY, online engineering students
    • Iterating on all facets of business so quickly: had to do it, quickly and concurrently
      • Each 5 weeks do a project, roll people together and do an app – if they can’t, roll it back
      • “Insane” – but more people just can’t fathom DOING, the ACTION
      • Before running the experiment, they determined the metrics for success and failure (if it doesn’t happen, fail)
      • Career coaches / meetups / staff bonuses for people trying to get people hired – success of those 8 trials
    • Wright Brothers biography book and Les Miserables (humanity)
    • Changing SV – fundamental human problems, he wants them to build more, try more
    • 500k students in the year for 5 years goal

The Journey (Notes From Feb 25 – March 3, 2019) March 22, 2019

Posted by Anthony in cannabis, education, experience, Founders, global, Hiring, medicine, questions, social, training, Uncategorized, WomenInWork.
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I wanted to focus on the variety of journeys that these amazing people have been  on. All different, all learning. The commonality of assessing one’s place and moving strategically to take advantage of an opportunity that allowed each of them to do what it was, at that time, that they wanted to do or focus. I believe that is an innate skill.  Some have to build up to have the confidence to assess what they want. Others let it sit in the back of their mind until someone brings it out.

As a founder, I believe that becomes even more of an important skill. You have to not only know what you want to chase, but also where you want to go. Then, follow that up with being able to creatively attract others to do the same – whether they’re investors, customers, or potential employees/partners.

  • Julia Silge, co-author of Text Mining with R (Data Skeptic 2/22/19)
    cover

    • At StackOverflow now, phD in astrophysics, astronomy
      • Worked in academia and went to edtech start-up for academic development
      • Transitioned into data science – had needed to brush up on some of the skills and updated machine learning
      • Data scientist for 3-4 years
    • Did some public work for her portfolio, worked with state stuff on Drought, etc…
      • Thought about NLP for analyzing Jane Austen texts (public, projectgutenberg), and opened it up
        • Which parts of book have narrative more sad / joyous and sentiment analysis with heat maps
      • Started to develop TidyText package and R build with a friend – bridging text and R analysis
    • Using R as data science
      • Tidyverse database, messy real source & into the form she needs quickly
      • Mature community for statistical modeling in R
      • Text classification – regex as building blocks for effective results
    • At StackOverflow – texts every day and statistically analyze the numbers
      • Developers survey as one of the largest projects
    • Book for people who may have tried other approaches with text
      • 1st half lays out concepts, common tasks in text mining
      • 2nd half is beginning to end case study – eda, what’s in dataset, implementation of model
  • Brian Wong, Founder at Kiip (20min VC FF018)
    230px-kiip_logo_image

    • Started after university at Digg (laid off after 6 months) before starting Kiip, focused on mobile rewards network
    • People he truly knows are the ones he’s been with over 5 years
      • True Ventures, Relay Ventures, AMEX ventures, Hummer Winblad
    • Founder-friendly in his terms: creating services and ecosystem of the founders among the invested, not taking a massive chunk immediately
      • Services as you’re getting formed, early on
    • Quiet with his board – once every two, three months meet up, depending on financing
      • Sources for him if he needs others, find specific customer or advisor, analytically looking at problems
      • Trained by True Ventures initially about dealing with the board
    • Gamification tactics derived from Predictably Irrational book
    • “Nothing is ever as good as it seems and nothing is ever as bad as it is”
    • Jason’s Calacanis blog – seems to agree with a few
    • Inspired by a few founders: Elon, Elizabeth Holmes; moreso maybe less loud founders, Mike (one of his investors – NASA scientist)
    • Favorite apps: Tinder for dating, Evernote, Box app (storage – mobile app is awesome – faster than DropBox)
    • For Kiip, ad-blocking fever-pitch and being ones that can help – MasterCard as one of their big partners, usage / app data that they’re sitting on
  • Matt Lerner, Distro Partner with 500 Startups (20min VC 082)
    i9jumtd3_400x400

    • Runs the London office, specializing in conversion optimization, analytics engagement, retention
    • Helps them build and grow (Distro team) to growth engines and scale
    • Worked at PayPal in 2004, marketing director initially before later
    • Skype calls over 45 minutes, brainstorm over tests with a cycle time and see results in 48 hours – 2 days
      • Was told he could do this full-time and enjoyed it (Distro Dojo – growth to product-market fit)
        • Invest in post-seed, pre-series A typically – early stage / accelerator program for earlier
      • In London, he looks for live, functioning product with corpus of people out of beta
    • Talked about Mayvenn (connecting to the NEW episode about Series B) – Series A here
    • Where in the funnel do you need to focus on?
      • Understand the business, then brainstorm in the “dojo” – all kinds of ideas
        • 20% CTA button change occasionally – not always
    • Just invested in Fy, Founder Tom in Berlin – built entire business with growth in mind
    • Anna Kerenana “Happy families are all alike but each unhappy family is unhappy in its own special way.”
      • Companies don’t get their product out to customers in a way
      • Measuring / optimizing for wrong targets
      • Tactical things to ensure spend is done properly
      • Way to test quickly – 4 Hour Workweek – Bought 5 different ad-words and checked his titles for unpublished book
      • Paid acquisition in way that CAC is much lower than proven LTV of customer, can go quickly through advertising
        • Most businesses need organic acquisition channels over paid
    • Ultimate growth hacker – David McClure (his boss) – pirate metrics talk (viewing of video)
      • Sean Ellis (from DropBox, GrowthHackers.com owner) – mentored him at PayPal – attachment too big for email, send DropBox
      • Eddie Johns (Growth at Wealthfront, before at Quora and Facebook)
      • In London, Millen Paris?
    • Favorite growth hacking tools: MarTech talk, 500 Startups for best tools
      • Deck in show notes, Top 35 and Top 10
    • Books: The One Thing You Need to Know?
    • Tamatem – exciting startup in Dojo, Middle Eastern mobile games publisher
      • License other successful games, translate them, half the revenue and found money for developers
      • Don’t have to be good at making games – just need to have the database and quick adoption of other games
  • Chuck Smith, CEO / co-founder of Dixie Brands, Cannabusiness (Wharton XM)
    dixielogo

    • Discussing CBD vs THC products and difference in integration / vertical distribution
      • THC requires state and full distribution
      • CBD can be sold online
    • Keeping the brand as a reputable one and making sure it sees plenty of time
    • Partnership with Latin American company for full integration / distribution channels, laying foundation for easy process
      • Ventures with other companies to engage quickly or acquisitions
  • Solomon’s Code authors (Wharton XM)
    • Olaf Groth, Mark Nitzberg
  • The Ultimate Side Hustle – Elana Varon (Wharton XM)
    • Different types of start-ups and trading compensation (time vs money)
  • Marvin Liao (@marvinliao), Partner at 500 Startups – SF accelerator (20min VC 083)
    • 10+ year vet at Yahoo!, came to Bay Area/Silicon Valley in 1999 tech boom, laid off  2001
    • Left Yahoo in 2012, did angel investing and speaking at conferences, mentoring
    • Learned investing game by angel investing, though, to his wife’s scolding, didn’t do well
      • Operator as investors – used to be in the same role – lots of services
      • Online marketing / sales experts in accelerator in the portfolio
      • Both models-Greylock, Accel vs 500 Startup & First Round,service-based)
    • Why 500 Startups? Strongly focused on sales and marketing – fit for him, especially being international (global)
      • First 2-3 meetings or intros are free, but after that – some value returned
    • Went from 1100 companies down to 36 for the accelerator
      • Seed fund – 12-30 cos a week, one inv ~2 weeks – not necessarily random
    • Average check size is $50-100k – doesn’t take board seats but gets board observer rights
      • Look at pre-launch phase, consumer mobile phase wants to see traction (10mil vs 1mil downloads)
      • Won’t look at enterprise SaaS pre-launch, wants to see $10-15k mRR in established space
      • Different industries requiring different attention
    • Industries that he’s looking at – marketplaces / platforms (SkillBridge), digital health
    • Challenge in his 2 years: cycles of learning (shocked that there are arrogant investors), still treats himself as a complete novice
      • Great investor and develop the instincts, thesis and to risk being wrong a majority of the time
    • Favorite book: Art of Worldly Wisdom, Dune (science fiction – key) – SingularityHub
    • Calend.ly and Evernote, Amy.X.AI (?)
    • Take on Yahoo: “They’re toast.” No disrespect to Marissa – trying M&A and most big companies aren’t good.
    • Challenge for 500S: scaling @ quality, going from 2 accelerators to 4 in Silicon Valley
      • Lucky and systematic difference to get to that point
    • Interested in the most recent batch: Neighborly (batch 10, fintech – hates Wall Street so disrupting this), AgFinder (agtech – not much attention but such a vital part of the global problem)
  • Ashley Whillans (@ashleywhillans), Asst Prof at HBS in Negotiations, Orgs and Markets (Wharton XM – Time Poverty)
    • Went through study in Canada with subjects that would receive $40
      • One group subjected to restriction that it has to be spent on “time saving”, other could be whatever
        • Measured happiness after each day (with a call)
      • Time saving could be fast food of some sort, hiring a neighborhood boy to shop, etc…
      • Happiness was higher with the $40 spent for time saving
    • Check the white paper for time saving and happiness
  • Elizabeth Hogan, Brand Dev at GCH, Cannabusiness (Wharton XM)
    • Discussing various levels of products – CBD vs THC and other treats
    • Company founded by Willie Nelson in 2015
      • Willie’s Reserve (flower, edibles, vape products at both med and rec dispensaries)
      • Willie’s Remedy – CBD oil-based products – talked about the neuroscience behind activation with cbd products
    • 8 oz cups of coffee with 5mg dose of CBD – often bring as product demos for concerts, festivals, events
    • Marketing is difficult because of federal regulations and the big marketing channels – Facebook, Instagram, Google, etc
      • Some influencers have been used but have to be careful – can lose their accounts if wrongly done
    • Plenty of organic marketing currently, but looking for paid channels has been a difficult task
  • Hooked author, Nir Eyal, (Wharton XM)
    • Habit building – playing on pains
      • 4 different ways to take market shares
        • Velocity, frequency (think)
      • Pains as psychological effects – pleasure as a result, and minimizing pain

Location, Location, Location? (Notes from Feb 18 – Feb 25, 2019) March 15, 2019

Posted by Anthony in education, experience, finance, Founders, global, questions, social, Uncategorized.
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As I sifted back through the notes I made from that week, a common theme appeared as location. I listened to a beer company COO, Principal at Bain, Jim Collins, and a managing director. Location was key for each of them, in some way. Whether it was funding by turning rocks over in the local area, expanding slowly to keep an authentic brand, focusing on location and presence, location was a motive for each of them.

So I ask how location matters to each of us? For me, I’ve stayed in Northern California basically my whole life, primarily the bay area. It built me, but I felt like I was missing some aspect of evolving into a better self until I left the country – visited places for the primary purpose of finding what made others tick – ones I had minimal commonalities. What was different, what was the same, what’s thought common that I don’t consider common? I’d been to other parts the United States and the answers to these didn’t click until leaving.

After reflecting on these episodes, I’m torn between becoming so entrenched and specific to a great place like the Bay Area. However, being elsewhere has shown me that I think there’s greatness lying outside of these bounds. So I’d lean toward focusing on those opportunities, personally. What do you think? Enjoy your community or go searching for new?

  • Yards Brewing, COO Trevor Pritchett (Work of Tomorrow, Wharton XM)
    yardslogo

    • Talked about some metrics for their capital intensive brewing
      • Barrels per sq ft typically
    • 50k barrels all in the production house / taproom to be able to see the production and create experience
    • In 4-5 states currently, looking at $300+ revenue per bbl, 50% margin
    • Seeing so much acquisition of new brands and crafts – “purchase authenticity” rather than innovate
      • Bigger companies are near 3mil barrels, so 60x
  • Weston Gaddy (@westongaddy), former Senior Principal at Bain Capital Ventures (20min VC 081)
    br4umccm_400x400

    • YC alum with Frog Metrics (handheld survey), cofounded in college from Founders Fund, YC, Alexis O
      • Created software, low-friction, to gather info for small stores while customers were in store
    • Strategy consultant for consumer product tech with Bain, initially
    • Grew up outside ALBQ in NM, went to college on east coast – how things go together
      • WisdomTree Funds – average investor to access the market
    • Start small, but work on a big focus (market) – small problems that tackle big issues
      • Thing he learned: asking the question “Why now?” – what has changed in the market/tech that created opp
      • Assuming everything else was bad in the past is a flawed framework
    • Investing-wise, he’s in NY and focuses solely on geographically sticking to the east coast (personally)
      • Time for valuations and investing has pushed early on the west coast
    • Product has the ability to win brand loyalty above all-else with technology and the media methods changing
      • Both digital and physical products (no longer single jingle commercial, or incentives in the channel to sell)
    • Passion projects and interests in the environment – does think that it’s important to specialize
      • His is enterprise technology as it pertains to selling to CMO – marketing tech
        • Largest spenders in the corporation over the next 5-10 years
      • Sector expertise becomes more important as you get further in the company investing stage
    • Favorite book as The Sixth Extinction, Pulitzer prize – human-created mass extinction
    • Most recent investment was a second tie-on for Jet.com
  • Jim Collins as guest (@level5leaders) (Tim Ferriss Show #361)
    • Socratic advisor: asked what Tim did his PhD thesis on – language acquisition and ideograms of different approaches / pros/cons of each method
      • Had to pick a language, selected Japanese (though he did Chinese in college), and acquiring concepts and thinking of different culture
        • Sounds, tonal language (Mandarin) vs writing and the etymology
      • How much of language constrains or enhances concepts we develop (whether math or otherwise, set the limits of our world)
      • Asked about Macphee (sp?) – been holding/carrying his notes from this class since 1999
        • Jim said he’d gone back to read one about fires
    • Example of choosing the right conceptual vessel
      • Started with Good to Great research – algebra with numerator and denominator canceling out
        • Only studying successes won’t be comparative enough (think – all successful companies have buildings, does that indicate?)
        • Births of industry, explosion of new entrants – look at twin companies – why does 1 become Intel vs other?
      • Hierarchy of levels with leadership
        • Individual capability -> good team skills -> manage -> leader -> ambition with humility/will
        • Look at every speech / interview and count how many times they take credit for themselves vs others
          • Vertical pronoun I vs others
    • Time management of old
      • As a 36-yr old teacher at Stanford, taught entrepreneurship – asked “Why don’t you go do something on your own?”
        • Initially, nobody knew who he was so he could go into cave and work as he pleased – invisible to visible would scare him
        • Decaying quality of happiness: 50% new, intellectual work, 30% of time in teaching and 20% in have-to-do’s
          • For each day, accounting the day – “got up early, creative hours, breakfast Joanne, workout, 5 hours creative, dinner”
          • Can’t be below 1000 creative hours in any 365 day period, and looking at monthly numbers drop
          • Pattern in his spreadsheet – emotion columns, +2 to -2 and rates – simplicity had a lot of +2
            • Arduous days were also +2
        • Creative days sometimes not what he thought might’ve been creative
          • “you’re a genius with 1000 helpers” – shell of a company
          • Even in writing with a friend, he’ll write down 3 things he wants to chat about – even if he doesn’t get to that
    • Asked to be a sleep student and reached out to a sleep center for himself – slept and had the electrodes on, as he figured out
      • 10 day cycle sleep – (El Capitan in a day – had to be up 36 hours in the day) – wanted 70 hours of sleep
      • Fun if you wake up to guess what time it is – 20min awake, need to get up
      • Gifted to be able to nap whenever, wherever
      • “Do the bug book” – on Jim, himself – how to deploy himself
        • What are you encoded for vs what you’re good at? Fund your goals and objectives with the economic engine.
        • Started a book at request of Rachell Meyers – observing the bug called Jim
    • Wanted to dwarf 1-60 with 60-90, as Drucker discussed in Effective Executive (Jim did foreword)
      • Owing the respect to mentor times – prepare ahead and codify/reflect notes after
      • What was his fav book – “the next one” (and he went to write 10 more)
        • Asked to know where Drucker was in writing at 65 – about 1/3 through what he did
      • Don’t do 100 decisions if one can do – say, events – is there a teaching moment?
      • “You’re asking the wrong question. How are you useful?”
    • Where does Flywheel start? Jim’s: What is he curious about?
      • Research correctly and he then can’t help having ideas and concepts from that.
    • 8 mi run for his “I’m thinking of upping my mileage” – 3 mi uphill
      • Joanne was one of original “Just do it” athletes – had won Ironman in 1985
      • Got married about 6 months later
    • Importance of empirical validation (vs pure analysis)
      • Fire bullets and it’s off by 30 degree, then another at 10 before hitting – then extend cannonball on calibration
  • Erik Moore, Base Ventures MD (Launch Pad, Wharton XM)
    x3rgt2at_400x400

    • Why he chose Berkeley – 5 min from his house
      • Likelihood to run into his mentor more in same building
    • Investing in Olly which was former founder of Method seeing opportunity in packaging branding of med
      • DSC and similar with just quirky videos for brand
    • Different investment in Mayvenn – weave/hair extension distribution landing their funding: $23M from a16z
      • Changing dynamics of economics for hair stylists and making it better experience for customers
      • Good, Better, Best price discrimination tiers

Shifting Mindsets (Notes from Feb 11 – Feb 17, 2019) March 7, 2019

Posted by Anthony in Automation, education, experience, Founders, global, medicine, questions, Uncategorized.
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I think many [most] of us fall prey to the day-to-day grind of life, work and whatever we have going on. We lose out on collection and reflection, maybe some have the time to gather their thoughts. Rarely, unless asked, do we get the chance to work through introspection. The luckiest may then analyze this and work to change their mental processes. If I had to guess, I’d imagine people work through this in conversations or in reading (or both).

What do my thought processes look like? Are they consistent? Do I work through problems in the same manner, or are they dependent on material or background? Have I worked to improve?

What did I hear/read about that may influence these? How does what I worked on or read about influence my opinion/knowledge of other situations/circumstances? Is there a fundamental shift that’s occurred over time? Should there be? Can I anticipate that? Can I preempt the movement?

As the week’s theme, each of the partners or founders on the episodes assessed the known framework for which they were improving upon or changing. At Brightseed, they’re focused on asking questions on how we can transition from infectious diseases to chronic disease prevention, all in a system that has been built and established on the former (big pharma). The diagnoses, the business model, research and development and actions thereafter all influenced by how it has always been done.

  • Sofia Elizondo, co-founder and COO at Brightseed (Bay Area Ventures, WhartonXM)
    brightseed_logo_standard

    • Talked about how 150 years ago, as pharma started to ramp up, system developed to treat infectious diseases
      • Now, infectious diseases are not the primary, and chronic diseases have taken over
      • Not prepared industry-wide to deal with this (pharma designed for diagnosis and then action)
    • Food industry is health and wellness, some biotech companies trying to make names
    • Mentioned performance of big package food companies – lack of growth, especially only 2% for the biggest names
  • Joel Marcus, Exec Chairman of Alexandria Real Estate (Wharton XM)
    logo

    • Talked about only wanting to buy real estate, commercial lab buildings in bunches and lease or sell to biotechs
      • Have dealt with commercial labs
    • Google had approached and they didn’t like it initially but agreed on the premise of what they’d do
      • Uber is another, soon to be 1million acre real estate for them
  • Patricia Nakache (@pnakache), GP at Trinity Ventures (20min VC 080)
    trinity_logo_light_300dpi-447137163032

    • Father was one of first engineers at Computer Sciences Corporation, spent summers in labs and telecom intern
      • Physics and chemistry major in college – went to McKinsey after graduating
      • In 1999 went to a start-up but was also a freelance writer, later had Forbes articles, etc…
    • Interviewed Trinity Ventures in 1999 and they continuously said they were very busy
      • Joined as a contractor, then 3 months later converted 3 months later
    • 2 P’s related to gender difference in venture:
      • Pipeline: nurtured through apprenticeship model, or brought on as a senior role initially
      • Pattern recognition: notion that decisions are based on what attributes have contributed to past successes
    • Care.com has vetted profiles of caregivers for hiring – more concerning for Patricia, so she is attracted by that pain point solution
      • Ruby Ribbon partnership and learning
    • Pedal to the metal for spending and burn rate – product-market fit with a broadly-defined market
      • E-club, meal services to companies (eg 100 ee’s, goes on the app and pick what you want – variety and meals delivered at once)
    • Measuring success – returns to LPs and helping founders
      • Jim Collins “From Good to Great” – ew, but makes sense if she grew up with initial tech boom
    • Fan of on-demand economy / services, but believes there will be a shakeout of it, as well
      • Scheduled cleaning, for instance (not on a whim)
        • Cites Homejoy – wasn’t sure what the app strategy was solving, immediacy
  • Cal Newport, Digital Minimalism book (Wharton XM)
    • Talking about reducing technology overall
    • Habit forming – diets, if you’re not committed to making a lifestyle change, can’t gain the benefits
  • Yogov founder, Ryder Pearce (Wharton XM)
    0y-5xkd4_400x400

    • Mission-driven looking for making gov administrative jobs easier, less painful
      • Hard to fix this as there are so many different 3rd party / privatization attempts
    • Spent 3 months in 2016 dealing with California DMV for what he felt should’ve been minutes

  • Phil Libin (@plibin), co-founder CEO of All-Turtles (Launch Pad, Wharton XM)
    220px-at-logo-red-label-stacked-opaque-2048

    • Attempting to cover real-world problems with AI
    • Focused on Evernote until starting this – have grown broadly to eventually include biotech
    • Talked about doing 72 hour fasts after being very skeptical (as a fad, etc….)

Betaworks, Kamal Pt 2 and Automation Innovation (Notes Jan 28 – Feb 3, ’19) February 19, 2019

Posted by Anthony in Altucher, Automation, education, experience, Founders, global, questions, social, Uncategorized.
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After the short post and notes from the prior week, this one was chock full of Strictly VC episodes. I also caught a bunch of Wharton XM on innovation in automation and various questions as to its applications in novel ways (and old industries).

The first up was a fascinating innovation in agriculture discussion with a professor working at UC Davis. Oenology has so many levels to it, from climatology, viticulture to how and when to harvest along with the chemistry. Innovation using automation and AI should be able to capture a lot of value in the whole chain, all the way to the distribution and end consumers. Reduction of variability was the big takeaway here. I do wish there were more weekend days to explore wine to fully immerse, but alas, we have 2 or 3.

Kamal finished his talk with Harry Stebbings on 20min VC to discuss the future of VC and how he sees the best business done. Hands-on, smaller funds believed to be better and to work on solving the problems that keep founders up at night. Those are most exciting.

James Bell, Kia Motors’ Director of Corp. Communication and Social Media, discussed his takes on autonomous vehicles over the next 5+ years and how they’re likely to be constrained to cities. Probably reduced speeds ~25-40mph and that even if they show up, it’ll be a challenge to get adaptation on the vehicle side as well as humans adjusting. Complete network of autonomous would be easy – humans add the variability that throws wrenches into the equation.

Then, we had Chad Fowler and Matt Hartman (Director of Betaworks). Peruse the notes below to see how those went

  • Innovation in Agriculture (UC Davis professor) – Work of Tomorrow
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    • Talked about automation on acreage for vineyards
    • 33% variability in vines across many acres, AI can reduce variability which allows for better management
      • Migrant patterns changed of laborers, pricing for pickers up to $42+/hr avg
      • Tough to get teams of 32+1 team lead consistently
    • Automation / machine pickers are ~5 year break-even, $18k in cost initially per acre and can drop after
  • Kamal Ravikant Part 2 (20min VC 078)
    • Future of VC
      • Competing for talent, entrepreneurs – AngelList, etc
      • Value add more in the recent time – they didn’t do anything before
      • Give the entrepreneur the power – not just another company of the portfolio
      • Smaller funds that will do better: Vast VC in NY, Kent Goldman (board observer at his old co), Syndicates, Ferriss, Jason Calacanis, one-off funds over bigger VC’s, Rick Morini
    • Shares deals with many of his friends that he’s talked to and approached (entrepreneurship)
      • Questions include understanding the product, team, burn rate, distribution
    • Fundamentally solving a problem (keeps you up at night)
    • Book of the biggest influence – The Alchemist, The Little Prince, Hemingway, Great Work of Your Life – Cope
    • He’d play more because he spends too much time writing / working
      • Altucher as the Oprah of the internet – (Told Stebbings to avoid college and build one in Guam)
    • Inspiring leader – Elon Musk (putting his own money on the line), Naval (his brother) and putting steps to build it – power, AngelList
    • Most recent investment – Bolt – uncapped, Dan Sharp founder, payments (something he wanted to solve)
      • Interviewing each other – did it to guarantee value add
      • Can’t invest into social good or impact because it doesn’t return all the time (to pitch to his LPs)
    • Lost a lot of his money in the old company after he burned it all
      • Level of responsibility for his LPs – not wasting, has a fiduciary responsibility for building the company
  • Chad Fowler, CTO at Wunderlist (20min VC FF016)
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    • App of the year, writer
      • From the founder – ‘simplicity, design’
      • Removed everything that they could, what else could they take out
      • Why business software is broken? – self-defeating, fear-based negotiation tactics that they need it
        • Ask for everything you could possibly ever want (and if the vendor can’t say yes, then you drive down price)
    • Tech (into video games) from music (forming and writing – ‘on hold’ for 20 yrs)
      • Same mindset for tech as music – we don’t enter music for a job – you do it because you want to bring something special
    • At LivingSocial in DC, InfoEther (his co) was a talent acquisition, became a VP of Eng and took over role of CTO
      • Approached by friends in Berlin shortly after that
    • Living in Berlin / Europe – completely disconnected in the 90s but no longer in 2010s
      • Still cultural issues that may be disadvantaged – bit more behind, conservative
      • He mentions he loves the cultural and international aspect of Berlin (US, as well) but cheaper
    • He believed that the piece of software is done – the client product is done – simplicity guardians
      • Wonderlist should be the glue that recognizes or allows input for everything across your life
    • Most requested features: folders
    • Same general operations once acquired by Microsoft – operating in Berlin still, staying with the teams, etc…
    • Fav book: E-myth Revisited – why small businesses fail, strategic/systems from own career thru running company
    • At GE, started a development center in Bengalore – new, cultural uncomfortable place taught him a ton
  • James Bell, Director, Corp Comm & Social Media at Kia Motors America (Launch Pad, WhartonXM)
    • If he had to put a number on autonomous – caveat: cities or districts, maybe 5-6 years
      • Slower, 25-40 mph congestion reduced but autonomous allowed – no humans
    • Humans add the element of randomness & variability that change autonomous cars 
      • How’s a car going to treat the randomness of a human in the road or other humans
      • How will people react to cars without drivers (videos of seat-outfitted drivers at crosswalks)
    • Talked about buying the first hybrid early on and how many questions he got in general
      • Likened that feeling to what it may have been like after cars showed up post-horse/buggy
      • Inflection points of becoming ubiquitous
  • Matt Hartman, Betaworks Weeks, Director of Seed Investments (20min VC 078)
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    • Prior to Betaworks, he was co-founder of ReferBoost
    • Went to b-school, worked at Hot Potato, consumer social network acquired by Facebook
      • Went back to school and started a real estate platform
    • Betaworks – consumer internet companies with Bitly, Dots, giphy
      • 100+ people on 10 different companies, outside financing and get a bigger space if they’re building
      • Employee is under Betaworks until companies – can do seed stage, as well
    • Why seed investment side? Building, shaping and figuring out the network approach
      • Loves working on different things for different companies in the day-to-day
      • Twitter becomes much more about news vs Facebook for friends – iterations and bilateral
      • Snapchat is 1:1 but 1:many, lower friction vs Instagram that keeps it there (not 1 hour or 24 hours)
      • Habit forming activity
    • Conversations on ProductHunt were normal conversations among product designers – network structure enabled community growth
    • Meercat – one of the best product launches he’d seen (though they didn’t invest)
      • Product was well done and more tightly integrated than Periscope, really good time
      • Meercat is not great in real-time – comments / questions won’t work great for video compared to others
    • Instapaper – Betaworks co – was going through articles in audio form
      • Was consuming 6 hours of reading just in his day-to-day with lunch, walks, commute
        • Found time in listening channel
      • Native audio ads already has straightforward monetization structure
      • Multitasking can be pretty useful for being conversions in listening
    • For deal-sourcing, he gets them through coworkers’ network (people at Betaworks)
      • ProductHunt has been one that initiates deals
    • Productivity tool Drafts? – input box for notes (opens API to do add anything macro-related)
    • DigDeeper (Instapaper) – notes from twitter compiled
    • Ryan Leslie’s Disruptive Multimedia (always available via twitter/phone)
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