Web/Tech

  • Artificial Intelligence Is Great, Artificial Stupidity Is Scary

    When I first got out of Law School in the 1980s, "professionals" didn't type … that was your assistant's job (or the "typing pool," which was a real thing too).

    At that point, most people couldn't have imagined what computers and software are capable of now.  And if you tried to tell people how pervasive computers and 'typing' would be … they would have thought that you were delusional.

    My career has spanned a series of cycles where I was able to imagine what advanced tech would enable (and how businesses would have to change to best leverage those new capabilities).

    Malcolm Gladwell suggests that it takes 10,000 hours of focus and effort for someone to become an expert at something.  While that is not necessarily true or accurate, it's still a helpful heuristic.

    Today, we can do research that took humans 10,000 hours in the time it took you to read this sentence.  Moreover, technology doesn't forget what it's learned – As a result, technological memory is much better than yours or mine.  Consequently, the type and quality of decisions, inferences, and actions are better as well.  Ultimately, we will leverage the increased speed, capacity, and capabilities of autonomous platforms.  While that is easy to anticipate, the consequences of these discontinuous innovations are hard to predict.  Things often take longer to happen than you would think.  But, when they do, the consequences are often more significant and more far-reaching than anticipated.

    Still, technology isn't a cure-all.  Many people miss out on the benefits of A.I. and technology for the same reasons they didn't master the hobbies they picked up as an adolescent. 

    I shot a video discussing how to use technology to create a sustainable creative advantage.  Check it out. 

     

     

    Many people recognize a "cool" new technology (like A.I.), but they underestimate the level of commitment and effort that mastery takes. 

    When using A.I. and high-performance computing, you need to ask the same questions you ask yourself about your ultimate purpose. 

    • What's my goal?
    • What do I (or my systems) need to learn to accomplish my goal?
    • What are the best ways to achieve that goal (or something better)?

    Too many companies are focused on A.I. as if that is the goal.  A.I. is simply a tool.  As I mentioned in the video, you must define the problem the right way in order to find an optimal solution. 

    Artificial Intelligence is a game-changer – so you have to approach it as such. 

    Know your mission and your strategy, recognize what you're committing to, set it as a compass heading and make deliberate movement in that direction. 

    I end the video by saying, "Wisdom comes from making finer distinctions.  So, it is an iterative and recursive process… but it is also evolutionary.  And frankly, that is extraordinarily exciting!"

    I hope you agree.

    Onwards!

  • Compute Trends In Machine Learning

    I often talk about Machine Learning and Artificial Intelligence in broad strokes.  Part of that is based on me – and part of that is a result of my audience.  I tend to speak with entrepreneurs (rather than data scientists or serious techies).  So talking about training FLOPs, parameters, and the actual benchmarks of ML is probably outside of their interest range. 

    But, every once in a while, it's worth taking a look into the real tangible progress computers have been making. 

    Less Wrong put together a great dataset on the growth of machine learning systems between 1952 and 2021.  While there are many variables that are important in judging the performance and intelligence of systems, their dataset focuses on parameter count.  It does this because it's easy to find data that is also a reasonable proxy for model complexity. 

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    Giuliano Giacaglia and Less Wrong (click here for an interactive version)

    One of the simplest takeaways is that ML training compute has been doubling basically every six months since 2010.  Compared to Moore's Law, where compute power doubled every two years, we're radically eclipsing that.  Especially as we've entered a new era of technology. 

    Now, to balance this out, we have to ask the question, what actually makes AI intelligent?  Model size is important, but you also have factors like training compute and training dataset size.  You also must consider the actual results that these systems produce.  As well, model size isn't a 1-t0-1 with model complexity as architectures and domains have different inputs and needs (but can have similar sizes). 

    A few other brief takeaways are that language models have seen the most growth, while gaming models have the fewest trainable parameters.  This is somewhat counterintuitive at first glance, but makes sense as the complexity of games means that they have more constraints in other domains.  If you really get into the data, there are plenty more questions and insights to be had.  But, you can learn more from either Giancarlo or Less Wrong.

    And, a question to leave with is whether the scaling laws of machine learning will differ as deep learning become more prevalent.  Right now, model size comparisons suggest not, but there are so many other metrics to consider. 

    What do you think is going to happen?

  • The Future of Spaceflight

    When I talk about exponential technologies, I almost always end up discussing Tesla and SpaceX. 

    Elon Musk is an interesting guy.

    220220 Elon

    Whether they end up doing everything they say they're going to, his companies massively accelerate the rate at which capabilities turn into products and platforms for future growth.

    I recently shared the Elon quote: "Stop being patient and start asking yourself, how do I accomplish my 10-year plan in 6 months?  You'll probably fail, but you'll be a lot further along than the person who simply accepted it was going to take 10 years!"

    I don't know if he really said it.  Nonetheless, it sounds like him … and I agree with the sentiment.

    The New Space Race.

    When I was young, the Space Race captured the heart and souls of Americans.  But, for the past few decades, it was in the background.  Recently, that has changed.  The space race is getting hot again.  Resources are pouring into this area, and SpaceX is leading the pack. 

    In 2018, I shared excitement that the boosters he used were reusable.  Today, people are talking about how the newest ship, Starship, could render other rocket programs obsolete. 

     

    Cost-of-space-flight-chartvia visualcapitalist

     

    While there's always room for competition, I can see many programs falling far behind if they haven't been focusing on reusability.  Assuming Starship delivers on its promises (keeping in mind that Elon is often over-confident about his timeline), it will be cheaper and more versatile than anything out there. 

    I think it's naive to assume that other companies aren't doing interesting things … but by the time they release anything comparable, it's possible that SpaceX will already dominate the market. 

    The economics of reusable rocketry isn't yet cost-effective for most potential customers, but Musk is undoubtedly moving the needle in the right direction. 

    Hopefully, he can continue to raise the expectations of both consumers and producers.  The results could be out-of-the-world.

    Right now, suborbital trips from Virgin Galactic and Blue Origin cost between 250K to 500K per trip – and trips to actual orbit cost over $50 million. 

    However, I believe the cost of space travel – and space tourism – will drop radically within my lifetime. 

    It's hard to comprehend the scale of the universe and the scale of our potential … but that's what makes it worth exploring!

    Even though we've only been talking about space travel, there are so many other exponential technologies that this applies to just as well.

    Onwards!

  • Here Are Some Links For Your Weekly Reading – February 13th, 2021

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    Here are some of the posts that caught my eye. Hope you find something interesting.

    Lighter Links:

     

    Trading Links:

  • Functional Mapping: Nature’s Desired Path

    There's a concept in design and transportation called Desire Paths. 

    The desired path is the path that users take despite the intended path by the builder of a community or application. 

    Here's a great example. 

    6tj18p093vb81Reddit via itstartswithani

    And, here's a whole community forum focused on desire paths. 

    It's often easier to take advantage of human nature … or just nature … than fight against it. 

    To that effect, I shot a short video on how this relates to your business and tech adoption. I call it functional mapping. Check it out. 

     

    Understanding the natural path for both technology and your clients makes it easier to understand and anticipate the capabilities, constraints, and milestones that define your path forward.   That means you actually have to understand the different types of users and what they expect to do.

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    Each stage is really about the opportunity to scale desired capabilities and automation.

    It isn't really about building the technology, rather, it is about supporting the desire.

    You don’t have to get it right.  You just have to create momentum in the right direction.   Meaning, if you understand what is coming, you don't have to build it … but you should figure out where you want to build something that will move things in the right direction.

    You’ve probably heard me talk about how Capabilities become Prototypes. Then Prototypes become Products.  And, ultimately, Products become Platforms.

    This model is fractal.  That means it works on many levels of magnification or iteration.

    What first looks like a product is later seen as a prototype for something bigger.

    SpaceX's goal to get to Mars feels like their North Star right now … but once it's achieved, it becomes the foundation for new goals.

    This Framework helps you validate capabilities before sinking resources into them. 

    It helps you anticipate which potential outcomes you want to accelerate.  Rather than simply figuring out what the easiest next step is … you have to figure out which path is the best next step to your desired outcome.

    The world is changing fast! Hope you're riding the wave instead of getting caught in the riptide!

  • The Future of the Blockchain

    Last week, I talked about market performance in 2021.  A decent portion of that article talked about cryptocurrency and the recent downturn (after a stellar 2021).  I'm a skeptic by nature, so it's hard for me to get behind any specific coin (even Bitcoin) at this point in time.

    This week, I had a conversation with good friends, including John Raymonds, about the topic as well.  John is much more active in the space and brought up some good points.  Something I noticed was how the level of discussion is starting to elevate and mature. People are beginning to think about secondary and tertiary value propositions. The conversation even made me think about repurposing some of our underutilized hardware in our server room for some crypto-related purposes.

    So, today, I want to focus on a different aspect of the equation … the potential value propositions of cryptocurrency as a technology – and the blockchain. 

    To start, I want to talk about Industrial Revolutions.  In part because we're at another inflection point. 

    A Look at Industrial Revolutions

    The Industrial Revolution has two phases: one material, the other social; one concerning the making of things, the other concerning the making of men. - Charles A. Beard

    There are several turning points in our history where the world changed forever.  Former paradigms and realities became relics of a bygone era. 

    Tomorrow's workforce will require different skills and face different challenges than we do today.  You can consider this the Fourth Industrial Revolution.  Compare today's changes to our previous industrial revolutions. 

    Each revolution shared multiple similarities.  They were disruptive.  They were centered on technological innovation.  They created concatenating socio-cultural impacts.

    Since most of us remember the third revolution, let's spend some time on that. 

    Here's a map of the entire "internet" in 1973. 

     

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    Reddit via @WorkerGnome.

    Most of us didn't use the internet at this point, but you probably remember Web1 (static HTML pages, a 5-minute download to view a 3Mb picture, and of course … waiting for a website to load over the dialup connection before you could read it).  It was still amazing.

    Then Web 2.0 came, and so did everything else we now associate with the internet; Facebook, YouTube, ubiquitous porn sites, Google.  But, with Web 2.0 also came user tracking, advertising, and we became the "product."  Remember, you're not the customers of those platforms – advertisers are.  And if you're not the customer, you're the product. And when you're not the customer, there's no reason for the platforms not to censor your thoughts to control the narrative. 

    Putting You In Control

    Web3 (and the blockchain and its reliant technologies) brings the power back to the people. 

    Primarily due to decentralized access with equal treatment for everyone.  Governments are already being pressured by Bitcoin and other cryptocurrencies.  But so are banks and brokerages, due to smart contracts and Ethereum.  Soon, even VCs will be impacted due to OHM fork treasuries or initial DEX offerings. 

    As Web3 gets more mature, so will decentralized finance.  Meaning, big banks, governments, ISPs, and more will have less control over the applications and uses of the technology. 

    If handled correctly, that means competition can discourage the productization of your digital presence.

    Removing Barriers

    There are many practical ways this would impact your life – but let's look at one that's already happening. 

    El Salvador recently made Bitcoin legal tender.  Talking about all the reasons this happened is beyond the scope of this article, but it does make El Salvador an excellent case study for the possibilities. 

    To start, it's now easier and quicker to buy a beer there (with Bitcoin) than it is in the US with cash.  It also stabilizes pricing in a civil war, because it's easy to move both in and out of the country. 

    Consequently, it also means that their currency holds its value as they travel to other places. 

    Let's take this to the extreme.  Let's say someone was to convert all their net worth to Bitcoin, and put it in a hardware wallet.  They could conceivably memorize their seed phrase, throw the wallet in a fire, and fly to El Salvador with only the clothes on their back.  After finding a way to scrounge up the money to buy another hardware wallet through random acts of labor … they would be in a completely new country with their entire net worth and no other footprint.  It's scary – especially for governments and their taxing authority.  But, it creates a new set of potentials and freedom.

    Now, take it a step further.  What would the world look like if you had all your health data, insurance, etc., with you anywhere you travel?  The world becomes your oyster in a way that was almost impossible before. 

    And that's only the beginning. 

    But, to bring it back to my skepticism again, there are a lot of roadblocks, inferences, and time in between today and the decentralization of the internet and finance.  And for now, that thought experiment only really works if you're willing to move to El Salvador.  The larger countries seem to be doing everything they can to discourage the adoption of cryptocurrencies. Though I think the smaller countries view this as a chance to become one of the new hubs of the world.

    However, maybe it's time for this quote by Elon Musk: 

    "Stop being patient and start asking yourself, how do I accomplish my 10 year plan in 6 months? You will probably fail but you will be a lot further ahead than the person who simply accepted it was going to take 10 years."

     

     

  • Here Are Some Links For Your Weekly Reading – February 6th, 2022

    Have you paid attention at all to the Spotify controversy?

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    Here are some of the posts that caught my eye. Hope you find something interesting.

    Lighter Links:

    Trading Links:

  • Here Are Some Links For Your Weekly Reading – January 30th, 2021

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    Here are some of the posts that caught my eye. Hope you find something interesting.

    Lighter Links:

    Trading Links:

  • 2022 Predictions

    About a month ago, I shared visualcapitalist's 2021 predictions to check how well they fared at the end of the year. 

    Honestly, the list was pretty good. It wasn't perfect, but you wouldn't expect it to be. 

    In that article, I asked this question: 

    What's going to happen as a result of the continuing pandemic, inflation, interest rates, the ongoing supply chain issues, and the growing anxiety and unrest brewing underneath the surface of the new normal? In January, we'll get to see VC's predictions. Before that, what do you expect to happen in 2022? – How'd These 2021 Predictions Fair?

    With that, here are visualcapitalist's 2022 predictions: 

    Prediction-consensus-2022-1via visualcapitalist

    Let's be clear – most predictions are either vague and easily guessed (and therefore not helpful) or random conjecture. 

    But, there's value in prediction, and there's value in analyzing the data before you. The caveat is that prediction is better when it's applied to human nature and not the machinations of fate, and data can be a distraction if it's not being carefully curated and analyzed to remain relevant to your goals. 

    For example, I agree with their general direction for technology. Tech is continuing to grow in influence, and as Web 3.0, the blockchain, and AI mature as platforms for sub-technologies, I think their importance is only going to skyrocket. 

    Prediction can also be entertainment. I certainly catch myself looking for patterns and differentiators for everything from whether my meal is going to come to the table correctly, to who's going to win the Super Bowl. 

    I know the chances are low, but I still think it's going to be the Cowboys … 

  • Betting On The Super Bowl

    Trying to get rich quickly? Want to know if the markets going to be bull or bear this year?

    Look no further than the "Super Bowl Indicator".

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    The theory is a Super Bowl win for a team from the AFC foretells a decline in the stock market and a win for the NFC means the stock market will rise in the coming year. 

    There is one big caveat … it counts the Pittsburgh Steelers as NFC because that's where they got their start. 

    If you accept that caveat, it has been on the money 33 years out of 41 – an 80% success rate. Sounds good, right?

    Come on … you know better.

    Here are some other "fun" stock market fallacies:

    Back to Reality

    Rationally, we understand that football and the stock market have nothing in common.  And we probably intuitively understand that correlation ≠ causation. Yet, we crave order and look for signs that make markets seem a little bit more predictable.

    The problem with randomness is that it can appear meaningful. 

    Wall Street is, unfortunately, inundated with theories that attempt to predict the performance of the stock market and the economy. The only difference between this and other theories is that we openly recognize the ridiculousness of this indicator.

    More people than you would hope, or guess,  attempt to forecast the market based on gut, ancient wisdom, and prayers.

    While hope and prayer are good things … they aren’t good trading strategies..

    As goofy as it sounds, some of these "far-fetched" theories perform better than professional money managers with immense capital, research teams, and decades of experience.

    I have a thought experiment I often ask people that come into my office. 

    What percentage of active managers beat the S&P 500 any given year?

    … Now, what percentage beat the S&P 500 over 15 years?

    The answer is about 5% as of 2019 (and that's in a predominantly bull market), and I have to imagine it's only gotten worse in the past two years.  That's significantly worse than chance. That means something they're doing is hurting, not helping. 

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    via Gaping Void

    There's simply too much information out there for us to digest, process, rank, and use appropriately.

    Every second you spend looking at a market is a second wasted.

    There are people beating the markets — not by using the Super Bowl Indicator … they're doing it with more algorithms and better technology. 

    There will never be less data or slower markets.

    Onwards.