Capitalogix

Why Don't We See Aliens?

So, if the math says it's likely that there are aliens ... why don't we see them?

In 2020, I mentioned Israeli officials who claimed they had been contacted by Aliens from a Galactic Federation - and that not only is our government aware of this, but they are working together.

There are many stories (or theories) about how we have encountered aliens before and just kept them secret. Here are some links to things you might find interesting if you want to learn more about this.

• NewsNation Segment: UFO Whistleblower Jake Barber Shares Allegations and Will Testify to Congress About Nonhuman Craft Retrievals.
• NewsNation Segment: UFO whistleblower David Grusch: 'We are not alone.'
• Dr. Diana Walsh Pasulka, Professor of Religious Studies, bridges the gap between religious studies, technological advancements, and the realm of UFO phenomena.
• Trailer for a film called "The Phenomenon."

So, while some may still believe aliens don't exist - I think it's a more helpful thought experiment to wonder why we haven't seen them. 

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. 

To simplify the issue, billions of stars in the Milky Way galaxy (which is only one of many galaxies) are similar to our Sun. Consequently, there must be some probability that some of them will have Earth-like planets. 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 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, a particle physicist, tackles that in his book and 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, the moon's 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. Even if there were others, it's entirely possible that they're extinct by now. 

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. 

• 75 Reasons We Don't See Aliens 
• Wait But Why: The Fermi Paradox
• A New Theory on Why We Haven't Found Aliens Yet
• A List of Solutions to The Fermi Paradox
• Dissolving the Fermi Paradox, Future of Humanity Institute, Oxford University

To Infinity and Beyond!

Here Are Some Links For Your Weekly Reading - April 20th, 2025

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

Lighter Links:

• OpenAI's Most Impressive Move Has Nothing to Do With AI. (ZDNet)
• AI Stuns Researchers by Rewriting Its Own Code to Overcome Limitations. (TalkAndroid)
• Meta’s New AI Tech Can Read Your Mind at Work…What Could Possibly Go Wrong? (AllWork)
• How to Enter a ‘Flow State’ on Command: Peak Performance Mind Hack Explained in 7 Minutes. (OpenCulture)
• British Anthropologist Claims Jesus' Tomb and Ark of the Covenant are Beneath the Great Pyramid. (JPost)

 

 

Trading Links:

• Trump’s Knives Are Out for Jerome Powell, Setting Up a Supreme Court Showdown Over the Fed’s Independence. (Fortune)
• First Shockwaves of Trump’s Tariffs are About to Hit the World Economy. (Bloomberg)
• America is Losing the Robot Wars. (Insider)
• The Only Way Some Manufacturing Jobs Will Return Stateside is If AI-Empowered Robots Do Them—And That’s a Good Thing. (Fortune)
• ‘China’s Elon Musk’ Uses Just Two Numbers to Demonstrate Why His Country’s Auto Industry is Now Outcompeting the U.S. And Europe. (Fortune)

Are We Alone In The Universe?

Last week, Astronomers announced the discovery of the most promising "hints" of life on an exoplanet, K2-18, 124 light years away. 

While it would only be signs of phytoplankton and other microscopic marine life, it would still be a massive finding. 

I tend to read a lot across a wide variety of sources. Recently, I've noticed a significant uptick in stories about aliens, UFOs, non-human intelligence, and non-human technology. In addition, several of my seemingly sane friends claim to have direct knowledge of projects and groups (funded by well-known billionaires) close to making very public announcements about missions, research, and discoveries in these areas, they hope will result in discontiguous innovations and asymmetric capabilities.

While I believe it's naive to assume that there's no other form of life in a universe as vast as what we understand ... I'm also highly skeptical of anyone who claims that they have specific knowledge or proof. With that said, I have seen enough stuff from people I trust to expect that our beliefs about these issues will shift massively in the very near future. As an example, check out Skywatch.ai, some of its videos, or this NewsNation broadcast.

Since we live in a time where technologies are rapidly advancing, I thought it might be interesting to test out an AI-powered chatbot designed to debunk conspiracy theories through evidence-based conversations. It is a spin-out project with roots at MIT and other top universities. Research shows that many people doubted or abandoned false beliefs after a short conversation with the DebunkBot. 

I first heard of this tool through these two articles: Meet DebunkBot, The AI Chatbot that Will Debunk Any Conspiracies You Believe and AI Chatbot Shows Promise in Talking People Out of Conspiracy Theories.

Here is a link to the conversation I had with it about the belief  "Life likely exists elsewhere in the Universe due to its vastness and the repeated conditions that can give rise to life."  To my surprise, this tool concluded that the belief is not a conspiracy theory and reminded me that:

Science for the sake of knowing is one thing. Belief for the sake of hope, curiosity, or imagination is another. The search for "life" might actually help us discover something more valuable than what we thought we were searching for in the first place.

You can test your beliefs against DebunkBot's AI. Let me know how it goes and whether you changed your mind.

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

As usual, it's well done, fun, and informative. 

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

The Drake equation estimates the number of detectable extraterrestrial civilizations in our galaxy and the universe. It factors in variables such as habitable planets, the likelihood of life, intelligent life, and the duration 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, the % have life, and the % chance of detectable bio-signature gas. 

Click here to play with the Are We Alone in the Universe infographic. 

 

via Information Is Beautiful

For both equations, the infographic lets you look at various default options, but also enables you to change the variables based on your beliefs. 

For example, the skeptic's 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.

 

via Information Is Beautiful

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

One other thing to consider is that some scientists believe that life is most likely to grow on planets with very high gravity, which would also make escaping their atmosphere for space travel nigh impossible.

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

Last week, Astronomers announced the discovery of the most promising "hints" of life on an exoplanet, K2-18, 124 light years away. 

While it would only be signs of phytoplankton and other microscopic marine life, it would still be a massive finding. 

I tend to read a lot across a wide variety of sources. Recently, I've noticed a significant uptick in stories about aliens, UFOs, non-human intelligence, and non-human technology. In addition, several of my seemingly sane friends claim to have direct knowledge of projects and groups (funded by well-known billionaires) close to making very public announcements about missions, research, and discoveries in these areas, they hope will result in discontiguous innovations and asymmetric capabilities.

While I believe it's naive to assume that there's no other form of life in a universe as vast as what we understand ... I'm also highly skeptical of anyone who claims that they have specific knowledge or proof. With that said, I have seen enough stuff from people I trust to expect that our beliefs about these issues will shift massively in the very near future. As an example, check out Skywatch.ai, some of its videos, or this NewsNation broadcast.

Since we live in a time where technologies are rapidly advancing, I thought it might be interesting to test out an AI-powered chatbot designed to debunk conspiracy theories through evidence-based conversations. It is a spin-out project with roots at MIT and other top universities. Research shows that many people doubted or abandoned false beliefs after a short conversation with the DebunkBot. 

I first heard of this tool through these two articles: Meet DebunkBot, The AI Chatbot that Will Debunk Any Conspiracies You Believe and AI Chatbot Shows Promise in Talking People Out of Conspiracy Theories.

Here is a link to the conversation I had with it about the belief  "Life likely exists elsewhere in the Universe due to its vastness and the repeated conditions that can give rise to life."  To my surprise, this tool concluded that the belief is not a conspiracy theory and reminded me that:

Science for the sake of knowing is one thing. Belief for the sake of hope, curiosity, or imagination is another. The search for "life" might actually help us discover something more valuable than what we thought we were searching for in the first place.

You can test your beliefs against DebunkBot's AI. Let me know how it goes and whether you changed your mind.

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

As usual, it's well done, fun, and informative. 

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

The Drake equation estimates the number of detectable extraterrestrial civilizations in our galaxy and the universe. It factors in variables such as habitable planets, the likelihood of life, intelligent life, and the duration 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, the % have life, and the % chance of detectable bio-signature gas. 

Click here to play with the Are We Alone in the Universe infographic. 

 

via Information Is Beautiful

For both equations, the infographic lets you look at various default options, but also enables you to change the variables based on your beliefs. 

For example, the skeptic's 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.

 

via Information Is Beautiful

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

One other thing to consider is that some scientists believe that life is most likely to grow on planets with very high gravity, which would also make escaping their atmosphere for space travel nigh impossible.

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

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.

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.

The Psychology of Gamblers

March Madness, Vegas, and Wall Street share a lot in common. 

Over Time ... The House Wins

Casinos only offer to play games that they expect to win. In contrast, gambling customers play even though they know the odds are against them.

Why does this happen? The rush of a win, the chance of a big win, and random reinforcement are common factors that incentivize people to play the lotto, go to a casino, or try to trade.

Chemicals like adrenaline and dopamine play a part as well. Even in a sea of losses, your body can't help but crave the chemical reward of even a small win.

The "House" knows this and engineers an experience that takes advantage of it.  

In the case of casinos, every detail is meticulously crafted to extract you from your money - from carpet patterns to the labyrinthian layouts, the music, the lights, and even the games themselves. 

Here is an infographic that lays it out for you. 

Bojoko via DailyInfographic

Most people aren't gamblers ... the fear of losing big inhibits them. However, when people were instructed to "think like a trader," they showed considerably less risk aversion when gambling. And I bet you have no problem filling out a March Madness bracket, even if you put money on the line. 

The illusion of control convinces us we can overcome the statistics. 

When you almost get it right - when you guess the first round of March Madness correctly, when you miss the jackpot by one slot on a slot machine, when you just mistime a trade to get a big win - you're more likely to play longer, and place bigger bets ... because you're "so close." 

It's human nature to want to feel in control. 

This is why you find a lot of superstitious traders & gamblers. If you wear this lucky item of clothing ... if you throw the dice in this particular way ... if you check your holdings at this time every day ... you have control. 

There is a big difference between causation and correlation. 

It is not hard to imagine that, for most traders, the majority of their activities do little to create a real and lasting edge.  

Skill vs. Luck

There are games of skill, and there are games of chance.

In a casino, poker, and blackjack are considered games of skill. In contrast, slot machines are considered a game of chance.

In trading, predicting markets is much different than using math and statistics to measure the performance of a technique.

Much of what we do is to figure out how to eliminate the fear, greed, and discretionary mistakes humans bring to trading.

In trading, "Alpha" is the measure of excess return attributed to manager skill, rather than luck or taking on more risk.

We believe in Alpha-by-Avoidance ... Meaning much of what we do is figure out what to ignore or avoid so that more of the games we play are games of skill rather than games of chance.

Are you playing the right game?

Skype's Kodak Moment: Remnants of a Past Era

Last week, Microsoft announced that Skype would shut down in May ... after over two decades of service. 

Hydrox existed before Oreo, and Betamax before VHS.

But Skype might be even more surprising. Skype was so ubiquitous that it became a verb and eponymous with video calling. As a world traveler, Skype also used to be the go-to international calling app.

Imagine if Kleenex, Jell-O, or Band-Aids went out of business. 

That’s what Skype did - and it’s not the first tech business to fail similarly...

Thinking Linearly in an Exponential Age

Humans can’t do a lot of things. Honestly, the fact that we’re at the top of the food chain is pretty miraculous. 

We’re slow, weak, and famously bad at understanding large numbers or exponential growth. 

Making matters worse, our brains are hardwired to think locally and linearly.

It’s a monumental task for us to fathom exponential growth … let alone its implications. 

Think how many companies have failed due to that inability … RadioShack couldn’t understand a future where shopping was done online – and Kodak didn’t think digital cameras would replace good ol’ film. Blockbuster couldn’t foresee a future where people would want movies in their mailboxes because “part of the joy is seeing all your options!” They didn’t even make it long enough to see “Netflix and Chill” become a thing. The list goes on. 

 

via Diamandis

Human perception is linear. Technological growth is exponential.

There are many examples. Here is one Peter Diamandis calls “The Kodak Moment” (a play on words of “a Kodak Moment”... the phrase Kodak used in advertising to mean a “special moment that’s worth capturing with a camera”). 

In 1996, Kodak was at the top of its game, with a market cap of over $28 billion and 140,000 employees.

Few people know that 20 years earlier, in 1976, Kodak had invented the digital camera. It had the patents and the first-mover advantage.

But that first digital camera was a baby that only its inventor could love and appreciate.

That first camera took .01 megapixel photos, took 23 seconds to record the image to a tape drive, and only shot in black and white.

Not surprisingly, Kodak ignored the technology and its implications.

Fast forward to 2012, when Kodak filed for bankruptcy – disrupted by the very technology that they invented and subsequently ignored.

via Diamandis

Innovation is a reminder that you can’t be medium-obsessed. Kodak’s goal was to preserve memories. It wasn’t to sell film. Blockbuster’s goal wasn’t to get people in their stores, it was to get movies in homes.  

Henry Ford famously said: “If I had asked people what they wanted, they would have said faster horses.” Steve Jobs was famous for spending all his time with customers, but never asking them what they wanted.

Two of our greatest innovators realized something that many never do. Being conscientious of your consumers doesn’t necessarily mean listening to them. It means thinking about and anticipating their wants and future needs.

Meanwhile, despite Skype having several features that Zoom still hasn’t implemented, Zoom recognized an opportunity during COVID and capitalized. When Microsoft bought Skype, they focused on adding several new features and expanding the range of services instead of improving the quality of their audio or video. Meanwhile, when Zoom entered the space, they brought much better servers and the ability to have much larger rooms. More attendees meant a wider variety of use cases and quicker adoption and referral cycles. They also made it easy to join a Zoom room. Instead of getting your e-mail up front and forcing you to create an account to use it, they let you join a meeting without an account. You only needed an account to host a meeting. 

They focused on making it easy to use their service and on having a clear identity instead of trying to ride every wave and become unfocused. Of course, at the same time, Microsoft stopped focusing on the tool, with an increased focus on their new competitor to Zoom, Teams. 

Tech and AI are creating tectonic forces throughout industry and the world. It is time to embrace and leverage what that makes possible. History has many prior examples of Creative Destruction (and what gets left in the dust).

Opportunity or Chaos …  You get to decide.

Don’t forget ... you don’t have to be the first mover to win in the end. 

Onwards!

Here Are Some Links For Your Weekly Reading - February 9th, 2025

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

Lighter Links:

• OpenAI's Deep Research Smashes Records for the World's Hardest AI Exam, With ChatGPT O3-Mini and DeepSeek Left in Its Wake. (TechRadar)
• You Can Try DeepSeek’s R1 Through Perplexity—without the Security Risk. (FastCompany)
• The Recruitment Effort that Helped Build Elon Musk’s DOGE Army. (Wired)
• Humans are Evolving Before Our Eyes on the Tibetan Plateau. (ScienceAlert)
• How to Naturally Boost Your Dopamine, Oxytocin, Serotonin, and Endorphins. (FastCompany)

 

 

Trading Links:

• The True Cost of a Super Bowl Ad? You Don’t Want to Know. (FastCompany)
• Trump Says America Was at Its Richest in the Late 1800s. Is That True? (MarketWatch)
• The “5 Types of Wealth”: Why You’re Wealthier Than You Think. (BigThink)
• America’s Most Generous Philanthropists 2025. (Forbes)
• Why the AI World is Suddenly Obsessed With a 160-Year-Old Economics Paradox. What Is It – And What Does It Mean Today? (NPR)

 

 

Betting On The Super Bowl Champion ...

Are you trying to get rich quickly? Do you want to know if the markets will be bull or bear this year?

Look no further than the “Super Bowl Indicator”. It has to be real; the winning percentage is high, and there’s even a Wikipedia page about it.

 

Image via NFL/Getty Images.

The theory is that 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. So, for those who care more about markets than football, you’d be rooting for the Philadelphia Eagles. 

There is one big caveat (among lots of others) ... it counts the Pittsburgh Steelers as NFC because that’s where they got their start. 

If you accept that, the Super Bowl Indicator has about a 68% success rate. Sounds good, right?

Come on ... you know better.

Here are some other “fun” stock market indicators:

• January Indicator
• Aspirin Count Theory
• Hemline Indicator
• Sports Illustrated Swimsuit Indicator
• Men’s Underwear Index
• Big Mac Index

 

Back to Reality

Rationally, we understand that football and the stock market have nothing in common. We also probably intuitively understand correlation ≠ causation. Yet, we crave order, and look for signs that make markets seem slightly 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 instinct, ancient wisdom, or 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.

To get a better perspective, here is a thought experiment to try. 

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

... Then, what percentage beat the S&P 500 over 15 years?

The answer is that, on average, less than 33% of active managers beat the S&P in any given year. Last year, 43% beat the Index. Even more interesting is that over a 15-year period, the numbers drop much further. Depending on who is measured, only 12% of active managers and about 5% of U.S. Equity Funds beat the S&P over a 15-year period.

Here are a couple of things to consider when you evaluate those statistics. First, market statistics represent predominantly bull market periods (and underperformance tends to spike during bear markets). Second, the statistics mentioned were for professional traders and funds (and most retail traders do considerably worse than that). Third, and perhaps most importantly, the implication is that professional traders’ “intelligent” choices often turn out worse than chance. That means something they’re doing is hurting performance (rather than helping it). 

via Gaping Void

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

There will never be less data or slower markets.

The only thing you can predict confidently about the markets is that volatility and noise will increase.

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

Let me know if you want to learn more about that.

Onwards.

Are you trying to get rich quickly? Do you want to know if the markets will be bull or bear this year?

Look no further than the “Super Bowl Indicator”. It has to be real; the winning percentage is high, and there’s even a Wikipedia page about it.

 

Image via NFL/Getty Images.

The theory is that 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. So, for those who care more about markets than football, you’d be rooting for the Philadelphia Eagles. 

There is one big caveat (among lots of others) ... it counts the Pittsburgh Steelers as NFC because that’s where they got their start. 

If you accept that, the Super Bowl Indicator has about a 68% success rate. Sounds good, right?

Come on ... you know better.

Here are some other “fun” stock market indicators:

• January Indicator
• Aspirin Count Theory
• Hemline Indicator
• Sports Illustrated Swimsuit Indicator
• Men’s Underwear Index
• Big Mac Index

 

Back to Reality

Rationally, we understand that football and the stock market have nothing in common. We also probably intuitively understand correlation ≠ causation. Yet, we crave order, and look for signs that make markets seem slightly 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 instinct, ancient wisdom, or 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.

To get a better perspective, here is a thought experiment to try. 

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

... Then, what percentage beat the S&P 500 over 15 years?

The answer is that, on average, less than 33% of active managers beat the S&P in any given year. Last year, 43% beat the Index. Even more interesting is that over a 15-year period, the numbers drop much further. Depending on who is measured, only 12% of active managers and about 5% of U.S. Equity Funds beat the S&P over a 15-year period.

Here are a couple of things to consider when you evaluate those statistics. First, market statistics represent predominantly bull market periods (and underperformance tends to spike during bear markets). Second, the statistics mentioned were for professional traders and funds (and most retail traders do considerably worse than that). Third, and perhaps most importantly, the implication is that professional traders’ “intelligent” choices often turn out worse than chance. That means something they’re doing is hurting performance (rather than helping it). 

via Gaping Void

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

There will never be less data or slower markets.

The only thing you can predict confidently about the markets is that volatility and noise will increase.

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

Let me know if you want to learn more about that.

Onwards.