Web/Tech

  • Don’t Touch That Dial

    History may not repeat itself exactly … but it often rhymes. News stories, however, seem to replicate.

    There is nothing wrong with your television. Do not attempt to adjust the picture. We are now controlling the transmission. We control the horizontal and the vertical. We can deluge you with a thousand channels or expand one single image to crystal clarity and beyond. We can shape your vision to anything our imagination can conceive. – The Outer Limits (1963)

     

    via YouTube

    It almost feels like an episode of Black Mirror, watching these stations quote the same pre-determined diatribe on fake news and its danger to our democracy.

    The very message they are purportedly supporting, in the video above, directly contradicts their actions. 

    Most people realize this happens to some degree, but it seems different when presented like this.

    I believe I am reasonably aware and somewhat immune from propaganda. That probably isn't as true as I'd like to believe.

    Meanwhile, Sinclar Broadcast Group owns nearly 200 stations in 80 different markets and wants to buy more. That is a powerful platform to deliver mass messages and influence the zeitgeist of its audience.

    It used to be true that winners wrote history (think empires, wars, etc.). Now, the one that delivers the most broadcast narratives shapes the emotional and seemingly logical responses to what we perceive to be happening around us.

    The result impacts elections, financial markets, buying choices, and countless other areas of our life. 

    We see and hear it every day about politics, wars, economic issues, and many other things we don't focus on enough to notice.

    As A.I., Bots, and social media grow, our ability to discern truth from 'truthiness' weakens. Especially with the growth of deepfakes

    What do you think about this?

  • A Brief Look At Bear Markets

    Main Street and Wall Street are often at odds.  Terms like "retail" and "professional" or "smart money" and "dumb money" highlight the difference in perspective and access to tools, processes, and even information.  

    The biggest disparities happen at turning points.  Today, many companies are posting record profits, but markets are volatile, gas is expensive, and inflation is high.  So, we're getting some mixed signals.

    It may be too soon to say we're in a recession, but we are experiencing a downturn. 

    Here is a comparison of recent market corrections showing each decline's intensity and duration.

     

    Ezgif.com-gif-maker (5)via Reddit (Dow Jones Market Data & the WSJ)

    While this chart is a week or two old, it shows some interesting data.  While there are a few shorter drops, most were longer and deeper than where we currently are. 

    Thus, we could have further to go … but it could also be a sign that we're responding better to market issues than in the past. 

    Ezgif.com-gif-maker (6)

    via Cascade Financial Strategies

    The blue areas represent past bull market durations and returns (total and annualized).  The red areas represent past bear markets.
     
    Note: this chart is from 2018 – Nonetheless, it is a good reminder of the bigger picture.
    I remain optimistic about the future state of our economy.  That doesn't mean there won't be pain.  Still, I believe that technology continues to increase the size of our potential pie and the capabilities we can leverage as a catalyst to recovery. 
     
    As a bonus, if you want to see a flashback to the Great Recession, here are two pieces of my market commentary from the time.  It's interesting to look back and see how my writing has changed. 

    How are you feeling about the markets and our economy?

  • Are We Alone In The Universe?

    Information Is Beautiful has an interactive data visualization to help you decide if we're alone in the Universe. 

    As usual, for them, it is well done, fun, and informative. 

    For the slightly geeky amongst us, the model lets you adjust the estimate by playing with two equations: the Drake equation and the Seager equation.

    The Drake equation estimates how many detectable extraterrestrial civilizations exist in our galaxy and then in the Universe based on factors like habitable planets, change of life, and then intelligent life, and then the amount of time a civilization sends signals into space. 

    The Seager equation is a modern take on the equation focusing on bio-signatures of life that we can currently detect – for example, the number of observable stars/planets, what % have life, and then % chance of detectable bio-signature gas. 

    6a00e5502e47b28833026bdead6236200c-600wi

    via Information Is Beautiful

    For both equations, Information Is Beautiful lets you look at various default options – but also to play with your own choices to adjust the outcomes. 

    For example, the skeptical default answer for Drake's equation shows 0.0000062 communicating civilizations in our galaxy (which is still 924,000 in the Universe).  The equivalent for Seager's equation shows 0.0009000 planets with detectable life in our "galactic neighborhood" and 135,000,000 planets in our Universe. 

    Even with the "lowest possible" selection chosen, Drake's equation still shows 42 communicating civilizations (Douglas Adams, anyone?) in the Universe.

    6a00e5502e47b288330263e980107a200b-600wi

    via Information Is Beautiful

    One of the most interesting numbers (and potentially significant numbers for me) is the length of time a civilization sends signals into space.  Conservative numbers are 420 years, but optimistic numbers are 10,000+. 

    If any aliens are reading this … don't worry; I won't tell.  But, we will find out if you voted in the last election.

  • Where Are The Aliens?

    This week, there was a U.S. congressional hearing on the existence of UFOs.  While there wasn't any proof of aliens, they did admit to phenomena that they couldn't explain with their current information.

    There are many stories (or theories) about how we have encountered aliens before and just kept them secret.  For example, in 2020, a former senior Israeli military official proclaimed that Aliens from a Galactic Federation have contacted us - and that not only is our government aware of this, but they are working together. 

    In contrast, I have found it more realistic and thought-provoking to consider theories about why we haven't seen aliens until now.

    For example, the Fermi Paradox considers the apparent contradiction between the lack of evidence for extraterrestrial civilizations and the various high probability estimates for their existence. 

    Let's simplify the issues and arguments in the Fermi Paradox.  There are billions of stars in the Milky Way galaxy (which is only one of many galaxies).  Each of these stars is similar to our Sun.  Consequently, there must be some probability of some of them having Earth-like planets.  Further, it isn't hard to conceive that some of those planets should be older than ours, and thus some fraction should be more technologically advanced than us.  Even if you assume they're only looking at evolutions of our current technologies – interstellar travel isn't absurd.  Thus, based on the law of really large numbers (both in terms of the number of planets and the length of time we are talking about) … it makes the silence all the more deafening and curious. 

    If you are interested in the topic "Where are all the aliens?"  Stephen Webb (who is a particle physicist) tackles that in his book and in this TED Talk.   

     

    via TED

    In the TED talk, Stephen Webb covers a couple of key factors necessary for communicative space-faring life. 

    1. Habitability and stability of their planet
    2. Building blocks of life 
    3. Technological advancement
    4. Socialness/Communication technologies

    But he also acknowledges the numerous confounding variables, including things like imperialism, war, bioterrorism, fear, moons' effect on climate, etc. 

    Essentially, his thesis is that there are numerous roadblocks to intelligent life – and it's entirely possible we are the only planet that has gotten past those roadblocks. 

    6a00e5502e47b28833026bdeacdf44200c-550wi

    What do you think?

    Here are some other links I liked on this topic.  There is some interesting stuff you don't have to be a rocket scientist to understand or enjoy. 

    To Infinity and Beyond!

  • Top 10 Most Overhyped Technologies (From 2008)

    Just because something is overhyped, doesn’t mean it’s bad. Gartner's hype cycle is a great example of this. Every technology goes through inflated expectations and a trough of disillusionment, regardless of whether they're a success or failure. Sometimes a fad is more than a fad. 

    Screen Shot 2022-05-15 at 8.45.33 PM

    Humans are pretty bad at exponential thinking. We're not bad at recognizing periods of inflection, but we're very bad at recognizing the winners and losers of these regime changes. 

     

    Screen Shot 2022-05-15 at 2.26.23 PM

     

    There are countless examples. Here's a funny one from Maximum PC Magazine in 2008. It shows that hype isn't always a sign of mistaken excess.  This list purported to show things that were getting too much attention in 2008.  Instead of being a list of has-beens and failures, many of these things rightfully deserved the attention.

     

    Maximumpc

    It's been 14 years since this came out. How did the predictions hold up?

    Facebook has become Meta, and is one of the big five. The iPhone has sold more than 2.2 billion phones, and accounts for more than half of Apple's total revenue. And the list keeps going. Multiple GPU video cards, HD, 64-bit computing, and downloading movies from the internet …

    It's hard to believe how poorly this image aged. 

    The trend is your friend while it continues. Just because something is overhyped – doesn't mean you shouldn't be excited about it. 

    Onwards!

  • How Tech Giants Make Their Money

    In 2021, the Big Five – Alphabet (Google), Amazon, Apple, Meta (Facebook), and Microsoft – generated over $1.4 trillion in revenue.

    How did they generate that revenue? We know they sell products … but we also know that we're often the product they sell. 

    Google and Facebook each make a lot of money selling you (or data about you) to advertisers. 

    The image below shows how Alphabet generated its revenue.   The full infographic shows that breakdown for each of the Big Five.

    Screen Shot 2022-05-01 at 3.49.00 PMClick to view the other companies via visualcapitalist

    Apple, Amazon, and Microsoft, primarily sell products (like more traditional businesses). On the other hand, almost 98% of Meta's revenue (and 81% of Google's revenue) comes from advertising. 

    Unsurprisingly, all five companies saw significant growth during the pandemic. 

    Though the economy shrank in the past two years, societal changes continued to push demand for big tech's products and services. 

    Will growth continue or slow down? 

    I'm curious what you think.

  • How I Got Started In Artificial Intelligence

    Recently, I've had several people ask about how I got into AI. 

    There are a couple of different answers, but I shot a video to go through the main points. 

     

    Click here for a transcript

    You could argue that I got my start in AI with my most recent company – Capitalogix – which started almost 20 years ago. You could also say that my previous company – IntellAgent Control – was an early AI company, and that's where I got my start.  By today's standards, the technology we used back then was too simple to call AI … but at the time, we were on the cutting edge.

    You could go further back and say it started when I became the first lawyer in my firm to use a computer, and I fell in love with technology. 

    As I look back, I've spent my whole life on this path.  My fascination with making better decisions, taking smarter actions, and a commitment to getting better results probably started when I was two years old (because of the incident discussed in the video).

    Ultimately, the starting point is irrelevant. Looking back, it seems inevitable. The decisions I made, the people I met, and my experiences … they all led me here.

    However, at any point in the journey, if you asked, "Is this where you thought you'd end up?" I doubt that I'd have said yes. 

    I've always been fascinated by what makes people successful and how to become more efficient and effective. In a sense, that's what AI does. It's a capability amplifier. 

    When I switched from being a corporate securities lawyer to an entrepreneur, I intended to go down that path. 

    Artificial Intelligence happened to be the best vehicle I found to do that. It made sense then, and it makes sense now.

    I wouldn't have it any other way. 

    Onwards!

  • A Few Graphs On The State Of AI

    Every year, Stanford puts out an AI Index with a massive amount of data attempting to sum up the current state of AI. 

    It's 190 pages that detail where research is going and covers current specs, ethics, policy, and more. 

    It is super nerdy … yet, it's probably worth a skim. 

    Here are a few things that caught my eye and might help set some high-level context for you. 

    Investments In AI 

    A-bar-chart-of-global-corporate-investment-in-ai-by-investment-activity-2013-2021

     

    via AI Index 2022

    In 2021, private investments in AI totaled over $93 billion – which was double the investments made in 2020. However, fewer companies received investments. The number of companies receiving funding dropped from 1051 in 2019 to 746 in 2021.

    At extremes, putting greater resources in fewer hands increases the danger of monopolies.  But we are early in the game, and it is safe to interpret this consolidation as separating the wheat from the chaff. As these companies become more mature, you're seeing a drop-off similar to when the web began its exponential growth. 

    With investment increasing, and the number of companies consolidating, you can expect to see massive improvements in the state of AI over the next few years.

    We knew that already – but following the money is a great way to identify a trend. 

    Increased regulation is another trend you should expect as AI matures and proliferates.

    Ethical AI 

    A-chart-showing-number-of-ai-related-bills-passed-into-law-in-25-select-countries-2016-2021 A-chart-showing-number-of-ai-related-policy-papers-by-u-s-based-organizations-by-topic-2021

    via AI Index 2022

    Research on the ethics of AI is becoming much more widespread – while the research influences papers, it is also a catalyst for new laws.

    AI's academic and philosophical implications are being taken much more seriously across the board. Many people recognize that AI has the potential to impact the world in unprecedented ways.  As a result, its promise and peril are under constant scrutiny.

    The adoption of AI might seem slow … but like electricity (or the internet), it only seems slow until it's suddenly ubiquitous.

    As you find AI in more domains, the ethics of its use becomes a more pressing concern. There is a lot of potential for abuse of technologies like facial recognition and deepfakes.  Likewise, people worry about mistakes, judgment, and who's liable for errors in technologies like self-driving cars.

    Luckily, you have many of the world's greatest minds working on the subject – including the Hastings Center.  

    Many factors contribute to the speed of AI's maturation and adoption.  Here are three of the obvious reasons. First, hardware and software are getting better.  Second, we have access to more and better data than ever before.  And third, more people are actively seeking to leverage these capabilities for their benefit.

    Technical ImprovementsScreen Shot 2022-03-31 at 2.01.17 PM

    via AI Index 2022

    Top-performing hardware systems can reach baseline levels of performance in task categories like recommendation, light-weight objection detection, image classification, and language processing in under a minute.

    Not only that, but the cost to train systems is also decreasing. By one measure, training costs for image classification systems have dropped by a factor of 223 since 2017. 

    When people think of advancements in AI, they often think of the humanization of technology. While that may eventually happen, most of the progress in AI comes from more practical improvements and applications. Think of these as discrete capabilities (like individual Lego blocks) that help you do something better than before.  These capabilities are easily stacked to create prototypes that do more.  Prototypes mature into products when the capabilities are robust and reliable enough to allow new users to achieve desired results.  The next stage happens when the capabilities mature to the point that people use them as the foundation or platform to do a whole new class of things.

    We're past the trough of disillusionment and are on the slope to enlightenment.

    Practical use cases abound.  Meaning, these technologies aren't only for giant companies anymore.

    AI is ready for you to use.

    If I think of a seasonal metaphor, it is "springtime" for AI (a time of rapid growth).  But not for you unless you plant the seeds, water them, and start to build your capabilities to understand and use what sprouts.

    As a reminder, it isn't really about the AI … it is about understanding the results you want, the competitive advantages you need, and the data you're feeding it (or getting from it) so that you know whether something is working.

    You've probably heard the phrase "garbage-in-garbage-out."  This is especially true with AI. Top results across technical benchmarks have increasingly relied on extra training data for combinatorial and dimensional reasons. Another reason this is important is to compound insights to continue learning and growing.  As of 2021, 9 state-of-the-art AI systems out of the 10 benchmarks in this report are trained with extra data. 

    To read more of my thoughts about these topics, you can check out this article on data and this article on alternative datasets

    Conclusion

    Artificial Intelligence capabilities are becoming much more robust and more able to transfer their learnings to new domains. They're taking in broader data sets and producing better results (while taking less investment to do so). 

    It isn't a question of "If" … it is a question of "when." 

    AI is exciting and inevitable!

    Let me know if you have questions or comments.

  • Will Robots Take Your Job?

    The fear of a robot-dominated future is mounting … But, is there a basis for that fear?

    It's a common trope in film, but as we all know, media is meant to capture attention – not emulate reality. 

    Michael Osborne and Carl Frey, from Oxford University, calculated how susceptible various jobs are to automation. They based their results on nine key skills:

    • social perceptiveness
    • negotiation
    • persuasion
    • assisting and caring for others
    • originality
    • fine arts
    • finger dexterity
    • manual dexterity
    • and the need to work in a cramped area

    6a00e5502e47b288330240a4b2c074200d-600wi

    via Michael Osborne & Carl Frey (Click For A Comprehensive Infographic)

    There are various statistics about the rate of change for robots taking jobs. Many expect that ~50% of current jobs will be automated by 2035.  Turns out, that statistic is from Michael and Carl, and the numbers were 47% by 20341

    Realize that statistic actually refers to the risk of them being automated. That number doesn't take into account the realities of cost, regulation, politics, social pressure, preference, or the actual work and progress necessary to automate something – so it's unlikely the full 47% will be realized. 

     

    6a00e5502e47b288330240a4b2c15f200d-600wi

    via The Economist

    Nonetheless, many use that quote to point toward a dystopian future of joblessness and an increasing lack of middle-class mobility.  

    Mr. Frey isn't a proponent of that belief … and neither am I.  

    Automation and innovation free us to focus on what matters most (or what can create the most value). The goal is not to have machines let us be fat, dumb, and lazy … it is to free us to focus on bigger and better things.

    Industrialization created short-term strife – but vastly increased the economic pie over the long term. So did electricity or the internet. It's likely that future automation will have similar effects, but it's possible to minimize the pain and potential negative impacts if we learn from previous iterations of this cycle. The fact that we're so far along technologically in comparison to previous revolutions means we're in a better position to proactively handle the transition periods.

    New tech comes with both “promise” and “peril”. We must manage the short-term consequences of the new tech – because it is inevitable. With that said, by embracing innovation, we can make sure it is a boon to the middle-class (and all of society) and not the bane of their existence.

    Throughout history, technology has always created more jobs than it has destroyed.

    Progress means the restructuring of society’s norms … not the destruction of society.

    When we first started using technology, that progress allowed humans to stop acting like robots (think farming and manufacturing). As technology improved, we have "robots" that seem to act more like humans. They can play chess, or shoot a basketball, etc.

    The truth is that humans didn’t act like robots. They did what they had to to survive. As technology improved, we look back and have trouble imagining a time when humans had to do those things. Technology often focuses on the most pressing “constraint” or “pain." It isn’t getting more human, it is simply more capable … which frees us to ascend as well.
    There are many aspects of humanity that robots can't yet replace. But as we move forward, technology will continue to free us to be more human (which I assume means to be more creative, more caring, more empathetic, and more original).

    Doom and gloom sell. It's much easier to convince people something's going to be painful than amazing (because we're creatures of habit, and our monkey brains fear pain much more than they enjoy pleasure).

    Our attitudes and actions play a pivotal role in how the world impacts us.

    We are positioned not only to survive the revolution but to take advantage of it.

    AI is a gold rush, but you don't have to be a miner to strike it rich. You can provide the picks and shovels, the amenities, or a map that helps people find treasures.

    Onwards!

    _________________

    [1] Frey, Carl & Osborne, Michael. (2013). The Future of Employment: How Susceptible Are Jobs to Computerisation?