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

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

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

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

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

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

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

Hope you enjoy!

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

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

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

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

    • Been at Microsoft for 3 years, supporting Azure for all their customers – quantum physics and statistics background from school
    • ML in cloud for customers – don’t know why they want it, just think it will be useful
      • Ex: image recognition (on techs with bodycams), HVAC documentation and augmentation or signal processing in anomalies of wave patterns
        • holoLENS use case
      • Played 2 sounds for Build presentation – her son blowing on her arm vs HVAC system custom sound – training sets and transfer learning
    • Can take a few real image and do a bunch for training: rotating, zoom, Gaussian blur, cut out background
      • Sound – same: take out environment, pauses and silence
      • Can turn 10 images / sounds into 30-50 per class
    • Active learning: model over time that can train itself and then retrain itself
    • Business domain expertise – her Final 4 model
      • #1 feature was wins, 2nd SoS, 3rd home court advantage / location – let machine validate the expertise
      • Validation of revenue drivers from machine – more importantly, if the opposite occurs – revenue doesn’t agree with data features
        • Used statistics to train data from the start in football, sports data – ncaa – teams, tourneys, prior history
          • Brought in her assumption of player-social index where they scraped sentiment and video analysis for team effects
        • Chose to use Azure Databricks (Spark background), store it in Blob and only retraining on Just-in-time in a Docker image
      • ML Flow, set of score for model – training set and .py and score.py or source data gets grouped together in Azure
        • Docker pulls them together easily and image is built, Azure DevOps can do VC
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Impact and Data to Growth (Notes from April 8 – 14, 2019) May 1, 2019

Posted by Anthony in cannabis, Digital, experience, finance, global, NLP, questions, social, Strategy, training, Uncategorized, WomenInWork.
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I started watching Street Food on Netflix and in the Osaka episode, the chef makes a great claim that can work for today’s notes: “If you want to create your own current, you cannot live your life by going with the flow.” Granted, you can use the current as a guide, but to truly create something unique, you have to hop out of the path and try your own luck. Today, I was listening to an episode even with Keith Rabois on Invest Like the Best, and he’s a proponent of not making 10% decisions, but rather investing into 10x ones – the riskiest that can pay off are the ones that will be truly incremental. The 10% experiments may improve a bit, but won’t exponentially get you scaling.

I had a great mix of NLP / Machine Learning podcasts, social/responsible corporations like United by Blue and Everytable, to go with sales thought processes, data ethics, and finance starts on a global scale. Each person / founder / company tackling unique challenges based on their individual experience that got them to that point. How can you approach the problem? And more importantly, what’s the right way that your expertise leads you to a solution for this problem?

For some, it was how to release the stigma in the cannabis industry to expose people to the health benefits as we’re legalizing in more states? United by Blue’s founder wanted a truly sustainable business model that supported his beliefs in giving back. An expert data scientist by the name of Debbie continues to improve women relations in tech and data-related fields by 1) supporting others graciously and 2) providing, particularly Latin American women, the opportunity to see how her passion for learning sparked her adventurous career.

Hope you enjoy! Leave a comment or follow along!

  • Su Wang, Elisa Ferracane in Authorship Attribution, UT (Data Skeptic, 1/25/19)
    Link to ACLWeb for paper

    • Discourse units in addition to others
      • Rhetoric structure theory (RST) – 2 elementary clauses (as Elementary Discourse Units – EDU)
      • Relation is related by an ‘elaboration’ where the 2nd sentence elaborates on the previous sentence
      • Rows are sentence pairs and the cells show the relations between the 2 (1st, 2nd; 2nd, 3rd, etc…)
    • Plagiarism detection, authorship attribution as semantic inference (both authors as computational linguistic PhD)
    • Can be unsupervised (classification of text to an author style) or supervised (accuracy or how closely it matches an author – assign key)
    • For the paper, they looked at 9 texts via Project Gutenberg and did a CNN – high-level baseline
      • Had 2 months to get it to the next level, optimization – said that LSTM performed the best but too slow for translations or 1000s of words
      • CNN can be as good as LSTM or better depending on architecture
      • Tried grammatical matrix, columns are entity, rows as sentences – subject, object, other
    • Used dataset of 19 books and 9 authors as extension of prior state-of-the-art paper
      • IMDB as another dataset – short texts with many authors (tried to do with Twitter but can’t get structure/sentence)
      • Initial data set was ~15% more accurate (99.8%)
      • 98.5% accurate for extended novel classification ~50 texts – SVM did well also of about 84-85% (more data may allow them to be more acc)
    • Looking at the different types of features – RST was more sophisticated in that the models did better in all experiments
      • Could embed or use the one factor as a distribution over other set of features
    • For IMDB dataset, discourse features nearly didn’t help – too short to establish structure
    • Human as the ‘gold standard’ but certainly not perfect. Authorship probably different task, though.
      • Would require expertise on the authors’ part. Machine can pick up on far more patterns.
    • Next for him – semantic narratives and story salads (grant via DARPA?)
      • Coherent narratives, shuffle the sentences and reconstruct the story.
  • Sylvia Wehrle, founder CEO of June CBD Apothecary (Wharton XM)
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    • Talking about the difference between CBD, THC and other strands
    • Humans as growing up with various forms of hemp oil – additive and purposeful for our evolution
    • Using the appropriate properties to go through benefits – getting the common questions out of the way
  • Donald Robertson (@donjrobertson), author of How to Think Like a Roman Emperor: Stoic Philosophy of Marcus Aurelius (Wharton XM)
    • Book discussing difference between stoic and Stoic, cynic and Cynic, etc…
    • Calm and indifference is different than how it may have been perceived
  • Sam Polk (@sampolk), author and CEO of EveryTable (Wharton XM)
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    • Sustainability at Feast (prior company)
    • Using Feast as test-tasters for EveryTable menu / offerings
    • EveryTable as sustainable, healthy food for people in an affordable way
      • Restaurants with partnerships of cities/areas that match the pricing (Santa Monica different than Watt or Compton)
      • Can order on app and go pick up meal for < $8 – able to do this with scale – try to ensure this early
    • Rolling out BlueApron-style weekly meals at the same price as in store
    • Corporate offerings where they have EveryTable coolers / fridges that take a credit card / payment and can pull out your order
  • Brian Linton, United by Blue founder CEO (Wharton XM)
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    • Originally moved from Singapore / Asia, went to college in Michigan – boredom satisfaction with sales
      • Started with ‘guady’ jewelry that was travel-related (tourist-style jades, emeralds, etc…) that he would source from home
      • Travel down to Florida / other areas and sell to region
    • Believed in doing good, so he would donate ~5% of all proceeds to ocean conservation – realized this wasn’t sustainable
      • Random donations of $1000s or %’s
    • Finally started United by Blue to develop the sustainable business model and what he believed in
  • Right Way to Get Your First 1000 Customers with Thales Teixeira (@thalesHBS), associate professor at HBS (HBR IdeaCast #676, 4/2/2019)
    • Startups failing because they try to emulate successful disruptive biz and scale instead of learning about initial customers
    • First customers are more than the money, word-of-mouth, R&D and free feedback
    • Etsy, Amazon, Netflix, Uber had no new technology (just finally had the map to see if there were cars coming)
      • Etsy went to craft fairs to recruit sellers, who then attracted more buyers
      • Pinterest tried to create a culture initially to set the tone for quality
      • AirBnb was awful initially in NY, so the founders wanted to find out – places were great but pictures were awful
        • Rented a nice camera and offered to take the pictures to improve the ones on the listings
    • What is the primary driver of value to the customers to deliver? How does technology play a role in this?
      • AirBnb had 1 engineer (founder) for a long time – increase the utilization of an expensive asset
        • Hid the options initially – didn’t have much inventory so they would email / find out and then get back to customers
        • Show availability – needed to stay in a house in the places
    • Technology is the enzyme / enabler of the start-up or experience and acquire the customers to purchase the product
      • People that like smaller companies, try new things, explore products and tell them
    • Unlocking the Customer Value Chain (Thales’ book)
  • Critical Thinking in D/S – Debbie Berebichez (@debbieberebichez) (DataFramed #58, 3/25/19)
    • Debbie is a physicist, TB host and CDS at Metis in NY (first Mexican woman to get a PhD in Physics from Stanford)
      • Promoting women in STEM, especially hispanic women
    • Metis is a data science teaching company as an arm of Kaplan in NY, San Francisco, Seattle
    • Did 2 postdocs around Columbia before going to Wall Street to work as a quant – but money wasn’t the only motivator, so she left
    • At Cambridge, she remembered speaking about Astronomy 101 as her first intro to physics class – was on 2 years of scholarship
      • She took a walk with her friend Rupesh and said that she was crying – “I just don’t want to die without trying physics.”
      • Passion drew attention and professors – offered her for a 2 year physics degree (skip first 2 if she could pass a test with complicated derivatives)
        • Had 2+ months to learn calculus, basics to mechanics and more – passed her test (9am to 9pm)
    • Mentioned going into high school to discuss data science – class was doing coding/SQL/data look on animals
      • Had 1 group that was looking over turtles – couldn’t answer the units for weight (triple digits) – not lbs, but grams
      • How this made sense – how to piece together reasoning / bias – how needed this skill was
      • Not bothering to check outliers or some data was exhibiting – why do we do it all?
      • Danish astronomer built and designed 1000 stars, which wasn’t much, but Newton and Kepler, Copernicus all derived theories from
    • Large datasets vs small datasets – insight more important vs size (big data as sometimes unnecessary)
    • Feynman quote about fooling ourselves – bias that we create.
    • History of Statistics – Stiegler, normal distribution and derivation of central limit theorem by Gauss and Laplace (1809 with Jupiter’s motion around sun)
    • With her bootcamp – she wants to attack the question of using the right algorithm and how to analyze the problems at hand
      • How to choose a data project in what you’re interested in – madewithmetis on Metis site
    •  Singular value decomposition (SVD) and reducing dimensionality, worked with Genentech founder – healthy DNA vs patient’s DNA and cancer
      • Reducing dimensions to the ones that were most relevant – NLP also
    • Think deeply, be bold, help others – Grace Hopper celebration talk
  • Dean Oliver (@deano_lytics), Data Analytics (Wharton Moneyball)
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    • Talking about how far behind NFL is behind NBA in tracking
    • There are people doing video for football, but not much – not widespread
      • Position groups will gain entirely different/new insights into how they’re playing
  • Cordasco Financial Network Planning + Sri Thiruvadanthal (Behind the Markets, Jeremy Schwarz)
    • Discussion of hedging dollar vs not – if hedging, probably wise to diversify with global
      • If not hedging, then europe may not be as great
    • Current markets say that liquidity isn’t as high with central banks, stocks start to couple and lose diversification / value
      • Decoupling early on in cycles
    • Relative value may be fine but not absolute for the dollar compared to other currencies
  • Jeppe Zink, GP at Northzone (20min VC 087)
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    • Invested in Spotify, Bloglovin, TrustPilot with focus on SaaS, fintech, mobile
    • Worked at Deutsche Bank as analyst in corporate finance, tech banker – left with 90% of team
      • Convince bank by buying principal investments before IPO in late 1990s – worked out
    • European cycles of tech – 100mln to 3bn people online, digital increase and telecom infrastructure
      • First VC firms in existence were doing integrated buyout model, which failed initially – too transaction focus
      • VCs have the talent that’s aligned with the founders now – 90% of VC firms that existed in 2000 had died in 2002
    • 10 year cycles where the great companies withstand, others don’t
    • Stage agnostic for them, series A to D rounds
      • Nordic companies of unicorns for what he has had success with
      • Europe as dropping trade barriers initially and in the 90s, broadband and smart phone starts (Nokia, Ericsson)
    • Has offices in the north for Northzone but he makes it up every other week or so
    • Try to emulate the start-up and have hunger/ambition always
      • Not trying to stagnate – venture capital vs patient (he thinks impatient is better – learn through failure and testing)
      • How fast can you learn to level up and deliver the best product? Continuous measurements, KPIs.
      • For Jeppe – momentum in product development
    • Most intrigued by fintech investing – Peter Thiel as one of his favorites
      • Most recent company was CrossLend – consumer lending with European bank lending
      • Book: Startup Growth Engines as collection of random founders and interviews

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

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

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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

Problems Require Passionate Solutions (Notes from Oct 22 – 27) November 6, 2018

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This was a week for venture, seed investing combined with a number of episodes diving into psychology and differences of people.

Week of October 22, 2018

  • Jeremy Gilbert, Strategy and Product Initiatives at WaPo (Work of Tomorrow, Wharton XM)
    • Talked about how automation has helped free up some of the repetitive processes for journalists and editors
    • Can never have too many editors – who say that there can always be more journalists
    • WaPo has looked to scale the number of stories, and that’s allowed them to provide smaller stories to more people
    • Automation in the form of Heliograph system for the election – newsy material that updates automatically
      • Don’t want journalists spending time on curation or number-gathering, should be on analysis and interviews and getting the story
  • Defy.VC co-founder, KP Trae Vassallo (WhartonXM)
    • Talking about seed stage venture and series A – 7 in less than a year and closing fund
      • Doesn’t care if bootstrapped or crowdfunding, though her and partner have invested/worked with 5 of 7 founders teams
    • Institutional start-ups have boards that could be very beneficial in identifying business models, proper ear but doesn’t exclude others
    • Co-wrote Elephant in the Valley, on women / diversity harassment in the Valley
      • Did a short poll of other women ~50 when she realized she wasn’t alone for the culture in the valley
      • Not a feeling exclusive to SV – very prominent in Hollywood, Madison Ave, Wall St, etc…
    • Doesn’t care about failures if founders have generated a learned knowledge for how to avoid or change what went wrong
  • Using Facebook to Understand Depression, Andy Schwartz and Johannes Eichstaedt (Wharton XM)
    • Surveyed some 1500+ people, actual data and analysis in World Well-Being Project
    • Went through Facebook to determine usage of certain words and language that gave indicators of depression
      • Ex: me/I when used often typically signified a higher sign of depression
      • Usage of the word ‘alone’, at all, may be a signifier (but multiples didn’t seem to enhance case)
    • Data questions of health – if you assess the subjects’ mental health status (or in general), that information becomes subject to HIPAA and other privacy laws
      • Had to control who is looking, every stroke gets logged and people must be hyper aware of what it is they’re a part of
      • If this can be used for treatment or further diagnosis, ramifications of data privacy and health are a big challenge
  • Debra Mashek, Professor of Psychology at Harvey Mudd (Women @ Work, WhartonXM)
    • Talked about how 60% of college students are women but not taking the higher-paying wages still (or majors that’d pay that)
      • Mentioned HMC’s success: Dean/President is woman and 54% of CS and 56% of Physics majors are women, going to better things
    • Often, women were deterred by initial hurdles
      • Survey/study where an online course had a pre-quiz: women that performed poorly would drop the course; males – no such thing
      • How to fix this, and make it so they aren’t put off
    • Online platforms enable women professors to be scaled (women will take a course or be drawn to it with a woman professor)
      • Easier because there still aren’t enough or haven’t been enough women in the field to draw the necessary influx of women talent
  • Javier Sotero, Corp VP of Outlook @ Microsoft (20min VC FF012)
    • Moved to Outlook after his startup, Accompli, was acquired by Microsoft for $200mln
    • Was chief architect at a startup, where he partnered with other 4 engineers at the company to buy out the product they built (for $1)
      • Company was failing, but they believed in the product and market there and transitioned into that
      • Company was called Hypeeric (sp?)
        • Sold in 2009 when they had 1000s of customers, $10mln+ in revenue, to VMWare and wound up as CTO
    • Accompli started as EiR at Redpoint, failure was Covalent (tremendous amount of capital)
      • New game, new rules (but they fell prey to old stuff – top down, Seibel-style business)
        • Showed him that you can have top tier money and intelligent people and actually fail still
      • Bootstrapped for multiple years before taking institutional money
    • Good investor for him: pushes founder to think and achieve more than you may have thought
      • Growing business with 0 capital, $15million to build already and got it for $1
      • Respecting the amount of capital brought in
      • Investors as being very helpful through the crash in 08 – maintaining build, product and the customers
      • Find a simple, straight forward approach: vitamin product, painkiller product, viagra product (blog post, not his)
        • Vitamin: not felt immediately – felt down the line (hygiene for instance)
        • Painkiller: attractive (everybody needs to fix pain) but “tolerance” or how “long-lived” product is – churn issues
        • Viagra: previously thought impossible become possible
    • His belief: venture capital as fun sheet bs and an illogical attraction toward terms
      • Remembered at Hypeeric that people would ask about valuations and he hated it
      • Incestuous, passing deals back and forth (“VC is not a true market”) – limited number of players managing flow
        • Amazing part of US and global economy – “great valuation” not a marker for anything from the business side
    • Reasons for selling to Microsoft – middle of transition from deeply loved, widely-adopted to enterprise business (and really make money)
      • Fortunate to already have multiple $ of sales and customers – 2 in Europe, 1 more in UK, and 2 in US to work closely and craft Accompli service
        • He was already familiar with that and growing up as team/company
      • Says nobody was searching app store for Accompli, so they needed to somehow deal with marketplace, such as Microsoft
    • Wait But Why blog
  • Jeff Clavier, King of Seed Funding (20min VC 069)
    • Founder and Managing Partner of SoftTech VC, closed 150 investments
    • Born and raised in France, did a start-up in fin services that was acquired by Reuter’s in the UK
      • Moved in 2000 to SV to a venture capital firm – partner at Reuters Partners fund
      • Started SoftTech in 2004, focused on early stages of industry – gap for people in few $100k’s for funding vs millions ($10mlns)
    • Been working for a few years, FitBit was his investment – ~15 per year
    • Asked if it was efficient to build hardware companies on cheap capital – introduced to founders as he was finding out about this
    • 250 microVC funds have gained $4b in funding
      • Thus, understand the type of company, location and market of your start-up
        • This should narrow your VCs that you want to target for funding/partnership (~5-10) that should have interest in what you’re building
    • SoftTech is a B2B and SaaS investor, vertical/horizontal/mobile and marketplaces, as well as connected devices (home, payments, healthcare)
      • See 3000 companies and only invest in 10-15 of them
        • Prioritize deal flow, typically, with in between connections (can get on calendar much easier with them)
    • It’s been said they’ve “forced” larger seed rounds – they look at roughly an 18 month runway (hiring eng, product to market, traction, few iterations)
      • Growth path should follow and clear the series A hurdles – ($2mil – $4mil – hardware taking more time, usually)
    • Only build a start-up about something you’re very passionate about
    • Best thing about being a VC – seeing the world through the lens of some of the most crazy and expansionary minds

Productive Purge: Less is More March 21, 2018

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There may come a time where I don’t feel this relief. Where you don’t question the purpose of keeping 10-15+ year papers that have collected dust from middle, high school and college. Some may say there is a novelty of being able to reflect upon the papers and compare but honestly, if you’ve learned, I would say that you’ve chosen what sticks to mind and what doesn’t.

In Algorithms to Live By, Brian Christian and Tom Griffiths demonstrate how sorting algorithms run our decision-making processes, both in the short-term and long-term. The default? LRU – Least Recently Used. Our memory stacks on new things learned repeatedly, pushing further the less recent events down the stack. What is concrete, reviewed, fully understood may maintain a cache available on call but the percentage of material we see that falls into place is minimal (and as we age, a smaller percentage still – albeit more knowledge overall). One of the most rewarding [re: relieving] feelings was ridding myself of materials that no longer seemed relevant, especially when space can be limited. There was a weight per space allocation that had to be measured. All of the feels or none of the feels?

What did I keep, you ask? Books. I am keeping an entire me-sized bookcase worth of books, a majority of them classics or favorites from college and my push to read more since exiting. I did also keep the Harry Potter series (it can live appropriately in my mind instead of the awful recreation the movies were – don’t @ me). From my youth, I threw away many of the fantasy and science fiction stuff. I kept WWII, military aircraft, Star Wars and Star Trek spacecraft/weapons books. The amount of creativity that went into those books to create possibilities that we have seen or may see bits of in the future is astonishing. Then I felt obligated to keep textbooks I refer back to, both for valuations/corporate finance, as well as multi-variable calculus, analysis (complex & real) and interestingly enough, my sociology and bio-engineering ethics materials.

Currently, my dresser is emptied, desk is cleaned, nightstands donated and bookcase emptied. I have my laptop bag and a closet filled with necessary bathroom materials, dress shirts, blazers/sport coats, suits, long sleeves and then 2 suitcases of t-shirts, shorts and the rest of clothes. And don’t forget the shoes. Oh, and the Xbox One to go with the stereo (which is currently on the fence for donating). That’s it, and it feels good. Again, the attachment isn’t there. James Altucher mentioned often that he has no attachment to his place of residence – not owning a home, renting as needed and in short-terms so he could move at a whim. I’m not quite there (I like the idea of returning to a place to sleep that’s consistent as I don’t strike myself as one who can just take a 1-way ticket without a time frame), but I feel closer, and it’s freeing.

We attach ourselves to the past and present and the more we do this, the more I believe there’s an anchor. Now, if it’s seen in a positive light, this isn’t a negative. They’re reminders of where all of us have been. However, attitude dictates that. And I, for one, would love to continue to be more mindful and positive of these circumstances.

I am excited for what is ahead and hope the lessons from the past influence me to provide an easier path, one filled with only new challenges to learn from.

Let’s go forward!

p.s. There’s something to be said for this in lieu of Stephen Hawking’s death last week on Einstein’s birthday / pi day (he was in Cambridge at the time of his passing, a day ahead of U.S.). A Briefer History of Time was provided as summer reading entering UC Berkeley as a freshman. This was a readable (even for non-engineers/mathy-types) book that simplifies concepts that are both taken for granted as well as presenting the inconceivable in a simple manner. I had the pleasure of attending Hawking’s lecture in the spring of that year, as well. It will remain one of my personal highlights. This is a man who wanted to feel what it was like to go into space and got the opportunity to do so after his condition worsened. We should all aim to go after what we’re passionate about – forward, upward and onward.

Productive Rabbit Hole: Learning Edition November 28, 2017

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Polina Marinova’s The Profile had a short, interesting quote from Anne Wojcicki (genetics company CEO to 23andMe) mentioning her ex, A-Rod (former baseball star propped up as poster boy leading MLB out of steroid era to somewhat disgraced steroid user, perennial dater).
It read: But when things came to an end, her mom had a few choice words about the baseball star, including the fact that he “had no academic background” & “we couldn’t have an intellectual conversation about anything.” Billionaires — they’re just like us.
“He could park himself in front of a TV and watch baseball for 10 hours a day. He wasn’t even sure he wanted to go on the yacht with Anne because the TV might not be working. I wish J-Lo all the luck in the world.”

Academic background is a convenient convolution to the idea that [A-Rod] wasn’t well-versed in the same forms of entertainment (or topics outside of baseball). That discounts his knowledge of his passion (baseball, clearly, as he’s now a strikingly good commentator/analyst). Different people can find a common ground – that doesn’t say that they must find common ground. If they’re no longer together, we can assume the latter – but it doesn’t have to be a lack of academia. That enrages me – completion of university/college does not grant an implication of being generally more intelligent / smarter than anyone else. Quite frankly, if someone has graduated recently could bring into question their knowledge of basic finance and how tuition continues a huge upward movement, doing multiples over inflation paces over the last 2-3 decades.

When I speak or see people with this attitude, I try to encourage a changing of mindset – people vary in their passions. Myself, I can enjoy many topics of conversation but there are others that I would have almost no valuable input, so I can see that and stay quiet or ask questions (if I find interest). The internet provides an endless availability to information. If you can get past the black holes of meme barrages, Facebook, Instagram or Snapchat scrolling, there are plenty of rabbit holes you can meander through to educate yourself in any number of topics. Better yet – you can find productivity in communities that support these topics everywhere via the net!

Seek and you shall find. Reading is one of my favorite ways to spend extra time learning, listening to podcasts as well as perusing LinkedInKaggle & FuturismUdemy / Coursera/Udacity/Datacamp as MOOC (courses learning) sites, Reddit & even Twitter if you search lists / interests. These are certainly not exclusive but provide collections of massive amounts of information – just have to search!

Seeking / Finding the information is one thing, but then I believe more people should do better to fact-check, compare/contrast alternative viewpoints or really seek truths. Who runs websites / what is the motivation / generally asking better questions to reflect on what you’re learning – often a lacking response (I would say skill, but I genuinely believe that more people choose not to do it, not that people are incapable of being reflective).

This all brings me to a last point that hopefully brings this information together – that it is not only an obligation to learn and question further but also to SHARE the information! This can be discussions on the internet, voicing an opinion with friends and co-workers, or simply running a play-by-play to reason through your own thought process in what you’ve amassed. Closed, one-way information feeds pale in comparison to open loops with new ideas, feedback, questions and general understanding. There is a reason we are seeing an increase in lean organizations and groups of people make larger contributions in ways we could not have imagined 30 years ago. Keep it up everyone!

Education Adjustments May 19, 2017

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A quick preview: <blockquote class=”twitter-tweet” data-lang=”en”><p lang=”en” dir=”ltr”>American higher education: Pay us tens (sometimes hundreds) of thousands of dollars to recommend some books to you.</p>&mdash; Andy Bailey (@AndrewDBailey) <a href=”https://twitter.com/AndrewDBailey/status/865251606568345600″>May 18, 2017</a></blockquote>
//platform.twitter.com/widgets.js

And this is what everyone and their moms (and dads) get bogged down with during at minimum freshman year of high school, while some do that even earlier. That is the mindset of a higher percentage of Americans in this day and age. Awareness is an excellent thing – parents should be more aware of how the process works, certainly. I think I could have been better prepared for the magnitude of it all, but it’s also possible I benefited from a mom who was proud with whatever came up for me. The pressure from school, parents, counselors, private ‘education counselors’, and now all friends as well at an earlier age scares me. It’s misguided and has created an atmosphere that approaches more of a lose-lose / lose-win than a win-win. A specific college shouldn’t be the ‘ultimate goal’ of students. Dreams/aspirations past that point, where college MAY act as a useful stepping stone, is more ideal, in my opinion.

Over the last 10 years, college costs have increased dramatically, needlessly. Yet that is what gets pushed in the middle and secondary environments – better grades, more AP’s, all the excellence for test scores and extracurricular activities if you can help it. Screw off with your joys and passions, unless they align with those above. All to throw your applications (and more importantly, their fees) into a lottery to provide you another stressful decision set (or worse, put you into a bout of depression over not being accepted into those loftily-held institutions). I’m nearly stressing myself thinking about it.

And I see it on an almost daily basis. ~3-4 times a week and more over the last 5.5 years with a rising, successful tutoring company. The expansion of centers to more states, the materials that have been pushed out are incredibly useful for achieving all of the above – but it does just that – pushes students to the brink for academic standards. When, in my experience, a majority of the ones that have been lucky enough to easily get into the top institutions were athletically gifted or born as kin of high places. Harvard, Duke, Stanford, Berkeley, NYU, Yale,  UPenn, Princeton, etc… to name a few.

Work hard, do well and don’t have the athletics or parents to gift away – lottery-bound! Enjoy. And many do get into great schools, but it’s not certain. Even in the tri-valley / East Bay Area, where schools push academics so hard. Unfortunately, high school doesn’t allow the freedom to struggle or fail without hard consequences. Students avoid that at all costs – talk amongst themselves in group chats, memes, jokes and fun poked at those that did worse. Joy found in a group sorrow if a test is particularly hard – either perked up by a curve or succumb to the deterioration of the grades.

Then there is the homework – piled on with all of the classes, typically at home. Some students are fortunate – certain subjects require less effort to understand, but most have to work at it. That leaves minimal hours in the day, either clawing away at sleep or worse, depriving some of hobbies outside of class, which depresses me. Ask a student what they want to do if they could choose and they don’t have an answer. Just maybe what they’ll study in college. In a world where it’s easier to do almost anything in any particular field / industry, few students look past studies to what they want after. It’s a constant grind, of which I’m not envious.

I believe that students should have an opportunity to work or start a company or intern for some company or field that they wish – hopefully one that teaches them whether to pursue that industry in the future. Much of what I found in college was learning what I WASN’T passionate about, not so much of what I was passionate about. People change, but skills can be gained – focus on the companies/industries you wish to live around. Never before is that more true.

Bill Gates tweeted some advice recently – a few of which I’ll share my thoughts:

  1. “AI, Energy, and Biosciences are promising fields where you can make a huge impact. It’s what I would do if starting out today.”
    Analytics drives all 3 of these. Energy is the one that may have the most impact, but efficiency is a challenger here – for instance, battery’s have made great strides, but solar has made linear strides that haven’t made any economic sense in the present. Biosciences will explode with the technology developed in recent years and the information we’ll be able to see with hardware/software connections.
  2. “Looking back on when I left college… intelligence takes many forms. It is not one-dimensional. And not as important as I used to think.”
    I completely agree. Different levels and styles of intelligence – whether it’s focuses or broad knowledge. Experts in one field doesn’t make an expert in another. Be careful with ‘experts’ and what it takes to get that title. Do your due diligence and research but open-minded in conversations with others. Everybody – no matter their intelligence – can contribute to expanding/sharpening your mind.
  3. Then he had some world-impact tweets that described some of the “inequities” of the world. “You know more than I did when I was your age. You can start fighting inequity, whether down the street or around the world, sooner.”
  4. “Meanwhile, surround yourself with people who challenge you, teach you, and push you to be your best self.” Never truer words have been spoken. People mention having mentors, but we should really have mentors, people that we mentor and peers that challenge us. The combination to make each other better make the individuals better.
  5. He goes on about this being the most peaceful time in history. Progress can be made if you think the world is getting better, and you want to spread it.

If I had my way, I would love to start something for students that partnered some businesses that could use some admin-style / research analyst work but that were willing to take on a shadow for 4-8 weeks or something over summer. Give the students some money for working and helping out, but also provide them the opportunity to what positions above an intern role may entail in the industry. Is it exciting for them? Is it something that teaches them that that particular role isn’t a fit? I think those lessons, that early, would be invaluable.
If successful, a similar college program could be enacted for frosh / sophomores that were available during the year. Far too many do not get the work experience until after Junior or senior years. We can make that better!

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