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Here Are Some Links For Your Weekly Reading - April 13th, 2025

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

Lighter Links:

• How a Philosopher Who Criticized Trump and Musk Turned Out to Be an AI Experiment. (Decrypt)
• Progress Happens Because Solutions Create New Problems to Solve. (FreeThink)
• More Than Just Intelligence – Being Human in the Age of Intelligent Machines. (Every)
• Is Your Phone Secretly Listening to You? Here’s an Easy Way to Find Out. (PCW)
• Power Play Turns Toxic: U.S. Deploys F-16 Jets to Taiwan and Philippines, China Issues Stark Warning. (DefTechTimes)

 

 

 

Trading Links:

• ChatGPT Hits 1 Billion Users? ‘Doubled in Just Weeks’ Says OpenAI CEO. (Forbes)
• Trump Spares Apple, Samsung, Tech Industry From Tariffs. Here's What Happened. (LaptopMag)
• How Long Do Bear Markets and Recessions Typically Last? (Forbes)
• Top Economist Larry Summers is Highly Concerned U.S. Treasuries Were Trading ‘Like those of an Emerging Market Nation’. (Fortune)
• BlackRock's Larry Fink Says to Own Alternative Assets. But Timing Is Everything – And Bigger Funds May Not Be Better. (MarketWatch)

 

 

To Rebirth & Spring Cleaning

Next Sunday is Easter, but yesterday was the first night of Passover - an 8-day long Jewish holiday that recounts the story of Exodus. 

The overlap can be seen in DaVinci's Last Supper, depicting a Passover Seder and Jesus's last meal before his crucifixion. 

 

 

Part of the Passover Seder tradition involves discussing how to share the story in ways that connect with different types of people, recognizing that everyone understands and relates to things differently.

To do this, we examine the Passover story through the lens of four archetypal children — the Wise Child, the Wicked Child, the Simple Child, and the Child Who Does Not Know How to Ask.

The four children reflect different learning styles — intellectual (Wise), skeptical (Wicked), curious (Simple), and passive (Silent) — and highlight how we must adapt communication to the diverse personalities and developmental stages of our audience.

This seems even more relevant today, as we struggle to come to a consensus on what to believe and how to communicate with people who think differently. 

 

On a lighter note, one of the memorable phrases from Exodus is when Moses says, "Let my people go!"  For generations, people assumed he was talking to the Pharoah about his people's freedom.  But after a week of eating clogging food like matzoh, matzoh balls, and even fried matzoh … for many Jews, "Let my people go" takes on a different meaning.

After Passover, and as we enter a new season, it's a great time for a mental and physical 'Spring Cleaning,' and delve into your experiences to cultivate more of what you desire and less of what you don't.

Here is to Spring, Re-Birth, and Spring Cleaning.

Hope you had a great weekend.

Are Billionaires Popular?

We live in an interesting time. Many billionaires aren’t just business leaders - they’re also influencers, personalities, and public figures. 

While countless billionaires go under the radar, several of today’s billionaires have become controversial figures - like Elon Musk. So, how do the top 10 richest Americans rank in this so-called “popularity contest?”

via visualcapitalist

It’s interesting how many of the 10 wealthiest people in America are still flying relatively under the radar. In my head, names like Sergey Brin or Larry Page should still be household names. 

On the other side of this scale, the three richest billionaires have primarily unfavorable ratings ... with Mark Zuckerburg being the most disliked of the bunch. 

Meanwhile, Warren Buffett and Bill Gates have predominantly positive ratings - though Bill is more polarizing than Buffett. 

As an aside, the world’s richest lost over $200 billion in a single day as news of Trump’s tariffs rocked markets. For context, that drop is the fourth-largest one-day decline in the Bloomberg Billionaires Index’s 13-year history.

Here Are Some Links For Your Weekly Reading - April 6th, 2025

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

Lighter Links:

• Trump May Deport Duke Basketball Star After Brutal March Madness Loss. (TheDailyBeast)
• Rich Americans Die Like Poor Europeans. (AgingWithStrength)
• An AI Avatar Tried to Argue a Case Before a New York Court. The Judges Weren't Having It. (Yahoo)
• 'Most Disturbing Website on Internet' Can Find Almost Every Single Picture that Exists of You. (Unilad)
• The 2 Words that Spark Anxiety—and the 8 Words that Calm It. (PsychologyToday)

Trading Links:

• Stocks Lose $9.6 Trillion — How to Limit the Next Plunge’s Pain.(Forbes)
• Jeff Bezos' Amazon Quietly Launches Plan to Take Down Elon Musk. (TheStreet)
• UK Prime Minister to Admit ‘Globalization is Over’ in Response to Trump Tariffs: Report. (FoxNews)
• The Dark Money Behind Duke Basketball. (Wall Street Journal)
• $159,832,873 Bitcoin Transfer to Major US Exchange Sparks Black Monday Fears. (Investing)

How Are You Feeling About The Tariffs?

Trump announced his reciprocal tariffs this week, and the world went into an uproar and the market into a tailspin. As an immediate result, JP Morgan switched its economic prediction from "Solid Growth" to "Recession Risk"

My take: Actions Have Consequences. More importantly,  we don't know all the actions ... and we certainly haven't recognized all the consequences. This is the beginning of something bigger than it seems, and many of the outcomes are beyond our current expectations or comprehension.

Sure, we saw some fundamental shifts last week ... but know that we are in for more.

The moves were big and fast enough that most people I know haven't had the time or brain cells to ponder things long and deep enough to form a well-reasoned opinion.

The only thing I "know" is that I expect more volatility and big moves.

With that in mind, here are some charts to help keep you informed as the consequences unfold. 

 

Chart #1 - Global Stock Market Returns in Q1 of 2025

via visualcapitalist

Chart #2 - Trump's Reciprocal Tariffs on Major Nations

via visualcapitalist

Chart #3 - Tariff Shock Wipes $5.3 Trillion Off S&P 500: Index Falls 10.5% in Two Days

via visualcapitalist

Looking at the first chart, it's clear that prior to this announcement, there was a U.S. sell-off, perhaps caused by concerns about inflation and slower GDP growth. As a result, more investment was moving toward Chinese and European stocks. 

After Trump's announcement, many things happened, including a joint response from China, Japan, and Korea - something I never thought I'd see. Also, many internet netizens started to plug questions into AI LLMs and receive similar results as Trump's tariffs. Contrary to a more complex equation, it appeared as if the tariff rates were calculated by dividing the deficit and imports of a country. Ultimately, this math was confirmed by the White House Deputy Press Secretary, Kush Desai. 

It will be interesting to see what is walked back and what is doubled down on over the next few weeks. 

Do you have faith?  Do you have an opinion?  I'd love to hear it!

Understanding the Shape of Change

Change is the only constant in life, yet it rarely unfolds in ways we expect. While we sense its approach, its shape — whether sudden and disruptive or slow and subtle — often defies our predictions. As the pace and scale of change accelerate, understanding its patterns becomes more crucial than ever.

The World Government Summit put together a helpful interactive website where you can test your knowledge on the trajectory of key statistical indicators for the development of society over the past decade. Here is the text from their opening screen.

 

Can we estimate how much the world has changed in a decade? Or do our own experiences impact the perception of progress? This work challenges the assumptions we make about how key statistical indicators regarding Health, the Environment, or Education evolve through the years. 

- The Shape of Change via the World Government Summit

The first part of the process was designed to be like a guessing game where you try to predict the direction and the rate of change of key issues shaping the world (like oil dependency, pollution,  literacy, economic freedom, etc.) by answering some questions at "The Shape of Change." It is simple, easy-to-use, and has a nice interface ... but answering the questions was more challenging than expected. Try it here. 

 

The Shape of Change via the World Government

The second part of the experiment lets you explore the year-over-year changes in key statistics regarding health, education, economy, and other topics.

 

The Shape of Change via the World Government

If you want to explore this further, I asked Perplexity to give me a broad overview of the project and its key insights. Here is the link.

The data is interesting. But, perhaps, your reaction to the data is more important. 

Were there any numbers that surprised you?

Here Are Some Links For Your Weekly Reading - March 30th, 2025

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

Lighter Links:

• Watch the Jetson Personal Air Vehicle Take Flight, Then Order Your Own. (NewAtlas)
• What Anthropic Researchers Found After Reading Claude’s ‘Mind’ Surprised Them. (SingularityHub)
• The Five Things You Shouldn't Tell ChatGPT. (Wall Street Journal)
• 23andMe Has Filed for Bankruptcy: 'Get Your Data Out of There'. (CNet)
• Watch Eerie Video of Humanoid Robot 'Army' Marching Naturally, Thanks to a Major AI Upgrade. (LiveScience)

Trading Links:

• Inside Elon Musk’s ‘Digital Coup’. (Wired)
• The Top 3 Vanguard ETFs of 2025 (So Far) Share this 1 Striking Common Denominator. (MotleyFool)
• 'Used Car Market About to Go Berserk’ – Car Dealership Guy CEO Reacts to Auto Tariffs. (CNBC)
• Growth Industries and the Next Big Arenas of Competition. (McKinsey)
• Elon Musk's AI Startup Acquires X in Deal that Values Social Media Platform at $33 Billion and the xAI at $80 billion. (NBCNews)

Taking Lessons on AI from my Grandmom

Almost every event I go to nowadays ends up focused on AI. At a recent event, conversations ranged from use cases for generative AI (and the ethics of AI image creators) to the long-term effects of AI and its adoption.

Before I could chime in, the conversation had gone to the various comparisons from past generations. When electricity was harnessed, articles claimed that it would never catch on, it would hurt productivity – and woe be unto the artisans it would potentially put out of business if it were to gain traction. 

When the radio or TV was released, the older generation was sure it would lead to the death of productivity, have horrible ramifications, and ultimately lead to the next generation's failure. 

People resist change. We're wired to avoid harm more than to seek pleasure. The reason is that, evolutionarily, you have to survive to have fun. 

On the other hand, my grandmother used to say: "It's easy to get used to nice things." 

 

 

Here's a transcript of some of my comments during that discussion: 

 

With AI, getting from "Zero-to-One" was a surprisingly long and difficult process.  Meaning, getting AI tools and capabilities to the point where normal people felt called to use it because they believed it would be useful or necessary was a long and winding road.  But now that everybody thinks it's useful, AI use will no longer be "special".  Instead, it will become part of the playing field.  And because of that, deciding to use AI is no longer a strategy.  It becomes table stakes.

But that creates a potential problem and distraction.  Why?  Because, for most of us, our unique ability is not based on our ability to use ChatGPT or some other AI tool of the day.  As more people focus on what a particular tool can do, they risk losing sight of what really matters for their real business.

Right now, ChatGPT is hot!  But, if you go back to the beginning of the Internet, MySpace or Netscape (or some other tools that were first and big) aren't necessarily the things that caught on and became standards.

I'm not saying that OpenAI and ChatGPT aren't important.  But what I believe is more important is that we passed a turning point where, all of a sudden, tons of people started to use something new.  That means there will be an increase of focus, resources, and activity concentrated on getting to next in that space.

You don't have to predict the technology; it is often easier and better to predict human nature instead.  We're going to find opportunities and challenges we wouldn't because of the concentration of energy, focus, and effort.  Consequently, AI, business, and life will evolve.

For most of us, what that means is that over the next five years, our success will not be tied to how well we use a tool that exists today, but rather on how we develop our capabilities to leverage tools like that to grow our business and improve our lives. 

Realize that your success will not be determined by how well you learn to use ChatGPT.  It will be determined by how well you envision your future and recognize opportunities to use tools to start making progress toward the things you really want and to become more and more of who you really are.  Right?

So, think about your long-term bigger future.  Pick a time 5, 10,  or even 20 years from now.  What does your desired bigger future look like?  Can you create a vivid vision where you describe in detail what you'd like to happen in your personal, professional, and business life?  Once you've done that, try to imagine what a likely midpoint might look like.  And then, using that as a directional compass, try to imagine what you can do in this coming year that aligns your actions with the path you've chosen.

 

Ultimately, as you start finding ways to use emerging technologies in a way that excites you, the fear and gloom fade.

The best way to break through a wall isn't with a wide net ... but with a sharp blow. You should be decisive and focused. 

Commit to using AI in ways that give you energy, which may be entirely different from how you use it now. 

So much of what we do now is anchored in the past. This is an opportunity to transcend the old ways you did things and to shape and transform your future (and perhaps even what you believe is possible).

I was an entrepreneur in the late 90s (during the DotCom Bubble). And I remember watching people start to emulate Steve Jobs ... wearing black faux-turtlenecks and talking about how they were transforming their business to be in an Internet company – or which Internet company would be the "next big thing." Looking back, an early sign that a crash was coming was that seemingly everybody had an opinion about what would be hot, and too many people were overly confident in their views because seemingly everyone was saying the same things. 

Human nature has remained stubbornly consistent through many waves of technology. 

The point is that almost nobody talks about the Internet with the focus and intensity they did in the late 90s ... in part because the Internet is now part of the fabric of society. At this point, it would be weird if somebody didn't use the Internet. And you don't really even have to think about how to use the Internet anymore because there's a WHO to do almost all those HOWs (and many of them are digital WHOs that do those HOWs for you without you even knowing they were needed or being done). 

The same is going to be true for AI. Like with any technology, it will suffer from all the same hype-cycle blues of inflated expectations and then disillusionment. But, when we come out the other side, AI will be better for it ... and so will society. 

Understanding the Possibility Scale

It helps to understand how we bring things into existence. To start, it's nearly impossible to manifest something you can't first imagine. And there is a moment just before something happens - when it becomes inevitable. 

I created this Possibility Scale to help envision the stages of becoming.

 

 

As an aside, before today, I would not have attempted to create an image for a post like this. While I love thinking and writing, image creation was outside my area of expertise or unique ability. But now things are different. Today, I simply asked ChatGPT to create that image. Yes, it took me four tries ... each retry starting with "that was great, now help me improve the prompt to (fix the thing I wanted done differently)."  At the end, I asked it to give me the complete prompt I could reuse. Contact me if you want the prompt.

Earlier, I mentioned how long it took to get from "Zero-to-One" with AI. But don't fret; things are speeding up, and we're just at the beginning of the process. If I created a scale to show the capabilities of AI, and set the endpoint at 100 to represent AI's potential when I die - even though I'm in my early 60s, I'd put us at only a 3 or 4 on that 100-point scale. Meaning, we are at the beginning of one of the biggest and most asymptotic curves that you can imagine. That also means that you're not late. You're early! Even the fact that you're thinking about stuff like this now means that you are massively ahead of most.

The trick isn't to figure out how to use AI or some AI tool. The trick is to keep the main thing the main thing. Build your ability to recognize when and how to use these new capabilities to bring the future forward faster.

Investing resources into your company is one thing. Realize that there are 1000s of these tools out there, and many more coming. You don't have to build something yourself. It is often faster and better to acquire a tool than it is to spend money on developing and building it.

Think of the Medici family. They invested in people, which in turn triggered the Renaissance. A key to moving forward in the Age of AI will be to invest in the right WHOs, seeking to create the kind of world you want to see or the types of capabilities you desire. Think of this as a strategic investment into creators and entrepreneurs with a vision or who are on a path that aligns with yours.

As you get better and better at doing that, you'll see increasing opportunities to use tools to engage people to collaborate with and create joint ventures. Ultimately, you will collaborate with technology (like it's your thought partner and then your business partner). We are entering exciting times where AI, automation, and innovation will make extraordinary things possible for people looking for opportunities to do extraordinary things.

As my grandmother said, it's easy to get used to nice things.

Onwards!

Mad About March Madness

March Madness is in full swing and will have the world's attention for a few more days. As you can guess, almost no one has a perfect bracket anymore. McNeese beat Clemson, Drake beat Mizzou, and Arkansas handed Kansas its first first-round loss since 2006. On Friday, the NCAA said that of the over 34 million brackets submitted at the start of March Madness, approximately 1,600 remained perfect. That's less than .1% after the first day. The first game of the tournament - Creighton vs. Louisville - busted over half of the brackets. 

Before 24/7 sports channels, people watched the weekly show "The Wide World of Sports."  Its opening theme promised "The thrill of victory and the agony of defeat!" and "The human drama of athletic competition." That defines March Madness.

The holy grail is mighty elusive in March Madness (as in most things). For example, the odds of getting the perfect bracket are 1 in 9,223,372,036,854,775,808 (that is 1 in 9.223 quintillion if that was too many zeros count). If you want better odds, then you can have a 1 in 2.4 trillion chance based on a Duke Mathematician's formula that takes into account ranks). It's easier to win back-to-back lotteries than picking a perfect bracket. Nonetheless, I bet you felt pretty good when you filled out your bracket.

via Duke University

Here's some more crazy March Madness Stats: 

• Companies expect $4 Billion of corporate losses due to employees tracking games
• The highest-paid NCAA coach, Kansas's Bill Self, makes a salary of $8.8 Million
• In 2018, it was estimated that March Madness generated $10 Billion in gambling (twice as much as the Super Bowl)

 

Feeding the Madness

"Not only is there more to life than basketball, there's a lot more to basketball than basketball." - Phil Jackson

In 2017, I highlighted three people who were (semi) successful at predicting March Madness: a 13-year-old who used a mix of guesswork and preferences, a 47-year-old English woman who used algorithms and data science (despite not knowing the game), and a 70-year-old bookie who had his finger on the pulse of the betting world. None of them had the same success even a year later.

Finding an edge is hard - Maintaining an edge is even harder.

That's not to say there aren't edges to be found. 

Bracket-choosing mimics the way investors pick trades or allocate assets. Some people use gut feelings, some base their decisions on current and historical performance, and some use predictive models. You've got different inputs, weights, and miscellaneous factors influencing your decision. That makes you feel powerful. But knowing the history, their ranks, etc., can help make an educated guess, and they can also lead you astray. 

The allure of March Madness is the same as gambling or trading. As sports fans, it's easy to believe we know something the layman doesn't. We want the bragging rights for the sleeper pick that went deeper than most expected, our alma mater winning, and for the big upset we predicted. 

You'd think an NCAA analyst might have a better shot at a perfect bracket than your grandma or musical-loving co-worker.

In reality, several of the highest-ranked brackets every year are guesses. 

The commonality in all decisions is that we are biased. Bias is inherent to the process because there isn't a clear-cut answer. We don't know who will win or what makes a perfect prediction. 

Think about it from a market efficiency standpoint. People make decisions based on many factors — sometimes irrational ones — which can create inefficiencies and complexities. It can be hard to find those inefficiencies and capitalize on them, but they're there to be found. 

In trading, AI and advanced math help remove biases and identify inefficiencies humans miss.

Can machine learning also help in March Madness?

“The greater the uncertainty, the bigger the gap between what you can measure and what matters, the more you should watch out for overfitting - that is, the more you should prefer simplicity” - Tom Griffiths

The data is there. Over 100,000 NCAA regular-season games were played over the last 25+ years, and we generally have plenty of statistics about the teams for each season. There are plenty of questions to be asked about that data that may add an extra edge. 

That said, people have tried before with mediocre success. It's hard to overcome the intangibles of sports—hustle, the crowd, momentum—and it's hard to overcome the odds of 1 in 9.2 quintillion. 

Two lessons can be learned from this:

1. People aren't as good at prediction as they predict they are.
2. Machine Learning isn't a one-size-fits-all answer to all your problems.

Something to think about.

 

Feeding the Madness

"Not only is there more to life than basketball, there's a lot more to basketball than basketball." - Phil Jackson

In 2017, I highlighted three people who were (semi) successful at predicting March Madness: a 13-year-old who used a mix of guesswork and preferences, a 47-year-old English woman who used algorithms and data science (despite not knowing the game), and a 70-year-old bookie who had his finger on the pulse of the betting world. None of them had the same success even a year later.

Finding an edge is hard - Maintaining an edge is even harder.

That's not to say there aren't edges to be found. 

Bracket-choosing mimics the way investors pick trades or allocate assets. Some people use gut feelings, some base their decisions on current and historical performance, and some use predictive models. You've got different inputs, weights, and miscellaneous factors influencing your decision. That makes you feel powerful. But knowing the history, their ranks, etc., can help make an educated guess, and they can also lead you astray. 

The allure of March Madness is the same as gambling or trading. As sports fans, it's easy to believe we know something the layman doesn't. We want the bragging rights for the sleeper pick that went deeper than most expected, our alma mater winning, and for the big upset we predicted. 

You'd think an NCAA analyst might have a better shot at a perfect bracket than your grandma or musical-loving co-worker.

In reality, several of the highest-ranked brackets every year are guesses. 

The commonality in all decisions is that we are biased. Bias is inherent to the process because there isn't a clear-cut answer. We don't know who will win or what makes a perfect prediction. 

Think about it from a market efficiency standpoint. People make decisions based on many factors — sometimes irrational ones — which can create inefficiencies and complexities. It can be hard to find those inefficiencies and capitalize on them, but they're there to be found. 

In trading, AI and advanced math help remove biases and identify inefficiencies humans miss.

Can machine learning also help in March Madness?

“The greater the uncertainty, the bigger the gap between what you can measure and what matters, the more you should watch out for overfitting - that is, the more you should prefer simplicity” - Tom Griffiths

The data is there. Over 100,000 NCAA regular-season games were played over the last 25+ years, and we generally have plenty of statistics about the teams for each season. There are plenty of questions to be asked about that data that may add an extra edge. 

That said, people have tried before with mediocre success. It's hard to overcome the intangibles of sports—hustle, the crowd, momentum—and it's hard to overcome the odds of 1 in 9.2 quintillion. 

Two lessons can be learned from this:

1. People aren't as good at prediction as they predict they are.
2. Machine Learning isn't a one-size-fits-all answer to all your problems.

Something to think about.

Here Are Some Links For Your Weekly Reading - March 23rd, 2025

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

Lighter Links:

 

• Under 1% of March Madness Brackets Remained Perfect After First Day. (FastCompany)
• College BBall Team Manager, Amir 'Aura' Khan, Signs Multiple NIL Endorsement Deals.(Complex)
• The “Nietzsche Thesis” – Why We Don't Really Care About Truth. (BigThink)
• People With Psychopathic Traits Feel Less Pain—And Assume Others Do Too. (PsyPost)
• Trademarking Telepathy: Musk’s Neuralink Taps Into the History—And Hype—Of Telepathic Tech. (TheDebrief)

 

Trading Links:

• Trump Suggests US Could Join British Commonwealth If Offered by King Charles. (FoxNews)
• Meet the Billionaire March Madness Boosters. (Forbes)
• Investors Who Were All in on U.S. Stocks Are Starting to Look Elsewhere. (Wall Street Journal)
• Nvidia CEO Jensen Huang Warned About Something that Could Cost His Biggest Customers Billions of Dollars. (Insider)
• Musk Inc is Under Serious Threat. The World's Richest Man Has Lost Focus – His Competitors Are Taking Advantage. (Economist)