Capitalogix

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?

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.

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?

Triumph Through Trials: Becoming Anti-Fragile

Many of our best decisions, timeliest course corrections, or significant innovations occur after a seemingly disastrous occurrence. That's why many psychologists and self-help gurus encourage people to focus on the hidden gift that many of these experiences provide.

It's there if you look for it. That painful event becomes the catalyst for either something new, a better way, or a level-up.

The goal isn't just to survive - it's to thrive. While a robust business can withstand shocks and a resilient business can recover from them, an anti-fragile business improves and grows stronger when exposed to volatility, randomness, disorder, and stressors.  The interesting thing about this concept is that it doesn't mean not fragile. It means things that weaken other systems are actually the things that strengthen you. 

Of course, that's not the case for everyone or every event ... It takes the right mindset and the right actions to turn a trial into a triumph. 

As we see the world changing rapidly, both through AI and through Trump's presidency, I think back to 2008 and how a prior incarnation of algorithms fared against it (spoiler alert: not nearly as well as this time). They say the things that don't kill you make you stronger. Here's my trial into triumph story about that. 

 

Via Howard Getson's YouTube Channel.

Too many people become victims of their circumstances instead of choosing to be the master of their destinies. 

Life is harder for people who live a life of least resistance. Doing the hard things and making the most of bad times makes life better and, ultimately, easier. 

Tony Robbins calls this the Threshold of Control. If you push through the fear and the struggle ... as you persevere, eventually, what was scary becomes easy. You've increased your threshold, and that's often a permanent improvement.  

Here is a list of the seven steps I use to transform almost any situation.

Seven Best Practices for Uncertain Times.

1. Accept Reality: We are where we are. Focus on being complete with what happened before this – and think about this as a new beginning with an even bigger future.
2. Do Something Positive: Take action and build momentum and confidence. Big wins are great. Yet, in scary times, even small items are worth noting, building upon, and stacking. Let progress build positive momentum for you.
3. Take Care of Yourself: Increase your physical activity, meditation, and massage. Take time to eat and sleep well. Many studies show decision-making suffers when you're stressed. Caring for yourself goes a long way to improving many other things.
4. Communicate More: The natural tendency is to hide or to recuperate in private. Instead, be open and receptive to help and ideas from friends, partners, or wherever it may come.
5. Creative Destruction: The old game and the old ways of thinking are over. Shift your energy to what is working. Commit to the result you want rather than the process.
6. Increase Your Options: It often takes a different level of thinking to solve a problem than the level of thinking that got you there in the first place. So, be open to opportunities, new possibilities, and more ways to win.
7. Choose a Bigger Future: Instead of resigning yourself to playing small and doing with less, recognize that a clearing creates space for something even better. Choose what you want and call it into existence through your thoughts and actions.

They say everything happens for a reason. The secret is that you get to choose the reason, what it means to you, and what you're going to do about it. Choose well, and someday, you could look back on this time as one of the best things that ever happened to you.

Are we in a Stock Market Bubble?

The S&P 500's price-to-earnings ratio (CAPE) has recently been nearing historic highs. Traders think that signals that market valuations might be overheated. 

In December of last year, it hit 37.9, over double its long-term average of 17.6. For context, it has only exceeded that level during the Dot-Com bubble and in 2021. 

 

via visualcapitalist

Overheated prices mean that there's a significant gap between company earnings and stock prices. That disparity translates to speculation and hope driving the stock price instead of more quantitative data. 

For some historical perspective, after the Dot-Com bubble, the S&P declined by 40% in the following two years. And after its 2021 peak, the S&P sank almost 20%. 

While AI enthusiasm has brought a spark to the markets, the question is, is that hype hiding deeper issues?

On a broader note, my message to you would be that if you don't know what your edge is, you don't have one. Investors and traders should understand market indicators, economic trends, and other world factors – mainly because it's important to be educated (or at least informed). Of course, merely understanding these things does not translate to a reliable trading strategy or an edge in today's environment. 

Lastly, just because something has been true in the past does not mean it predicts the future. In trading, we use the phrase "past performance is not indicative of future results" to remind us that there is a difference between a coincidence and a correlation. Indicators like CAPE study the past, so it is dangerous to assume you can use them to predict the future. For better or worse, whether markets go up or down is based on much more than earnings and stock prices. 

But, with that said,  Warren Buffett just did something worth noting ... He sold his holdings in the S&P 500 index funds he tells everyone to buy. So why did Buffett just sell them himself?

We live in interesting times.  

Onwards!

Is The NYSE Moving To Texas?

While I mainly discuss entrepreneurship and technology trends, I still have a soft spot for trading, which remains a large part of what we do at Capitalogix. While we've broadened the industries in which we use our Capitalogix Insight Engine, it was originally built with trading technologies in mind. We have exciting new partnerships there, including a new fund.

As we look forward, I thought it was a good time to look back as well.

I'm sure you have heard about open outcry trading pits in Chicago and New York—where traders flashed hand signals lightning quick to buy and sell commodities like cattle, corn, gold, and pork bellies. Those pits, which were made famous in the movie Trading Places, thrived for decades. Nevertheless, the practice has lost out to a faster, cheaper, and quieter competitor: the computer and electronic trading.

In 2016, I visited the Chicago Mercantile Exchange and took this video in front of the S&P trading pit during live trading hours. 

 

via my YouTube Channel.

In the video, I remarked that even though it looked empty - trading volume was higher than ever. Meaning that trading had once again evolved beyond the way it used to happen. According to the CME Group, by 2015, public outcry had fallen to 1% of total volume. Here is a video of what the S&P trading pit used to look like.

 

"...the change in the pit isn't a harbinger of death for futures trading;  it's the signal of a new era." 

 

At the time, it didn't feel like a bold statement to me – because what was coming felt inevitable. And it has proven to be true. Markets have changed radically since 2016. And you can bet that the changes aren't done, as AI and exponential technologies promise to transform markets and trading again.

The process of trading and clearing is moving beyond human capabilities. As the old duties of the Exchange fade away, the focus must be on the dangers, opportunities, and strengths of a bigger future. That means new games to play, new risks to navigate, and a new set of rewards to capture.

 

Nearly empty CME trading pits in 2016 (specifically, the S&P and Eurodollar)

The new game involves not only new players, methods, and markets ... but also a new geography.

Yes, as more things become digital, geography still matters.

In 2018, the Intercontinental Exchange acquired CHX and rebranded it to the NYSE Chicago. Now, that branch of the NYSE is moving to Dallas. 

This follows announcements in 2024 of the launch of the Texas Stock Exchange, which has backing from people like Rick Perry. 

Texas is rapidly becoming an even larger economic hub. It boasts the highest number of NYSE listings, Nasdaq recently established a large base here, and companies representing more than $3.7 trillion in market value list Texas as their headquarters.

Meanwhile, lawmakers are pushing to make Texas even more business-friendly. With no corporate or personal income tax, Texas has one of the lowest tax burdens in the nation. The state also offers incentives for corporations to relocate.

All of this can be taken as a reminder that opportunities, talent, and resources concentrate where energy and funds flow. 

If you want to talk more about how to launch a business in Texas or anything Capitalogix is working on, reach out. 

A Look At Last Week's Tech Breakthroughs

We live in exciting times!

No, I'm not talking about how fast the DOGE team is terraforming government.

I'm talking about how fast the insights of exponential technologies are compounding the real-world implications of where we are and where we are going.

In past issues, we've talked about how quickly the world is changing, how fast innovations happen, and why it's not about today's tools but rather the value and capabilities of the foundational assets we build upon ... and, ultimately, the things that makes possible.

Today's commentary is different from our usual posts. Yes, the inspiration came from my weekly curation of links selected based on what captured my attention or imagination. However, today's post is about the sheer volume and density of groundbreaking innovations competing for mindshare and investment dollars. And while commercial success is a great way to keep score, we'll explore what this accelerating pace of innovation means for our future and the world.

 

So, here is a list of some of the things that made headlines this week.

• After 17 years of research, Microsoft has announced a massive breakthrough in quantum computing, resulting in a new state of matter and their new Majorana 1 chip. 
• Google announced its new AI co-scientist to help accelerate research for scientists ... and it's already finding novel breakthroughs on decade-long problems.  
• xAI released Grok 3, a significant advancement in the reasoning and performance of their LLM and a competitor to other top models like DeepSeek-R1. 
• Clone Robotics unveiled a video of "ProtoClone," a faceless musculoskeletal android robot with 1000 muscles and over 200 degrees of freedom.
• Nvidia and Arc Institute launched a new AI Bio model - Evo 2 - trained on over 100k species. This doesn't just analyze genomes ... it creates them. 
• Sakana.AI introduced the AI CUDA Engineer, an agentic AI system that automates the production of CUDA kernels 10-100x faster than with common machine learning,
• Claude announced their intention to include reasoning and web search in Claude 4.
• France sustained a Nuclear Fusion plasma reaction for 1,337 seconds - a 25% improvement over the previous record. 

Some may not matter to you now. Try re-reading the list while letting yourself be amazed at what is happening!

Any one of these is a momentous achievement that would have sounded like science fiction even 10 years ago. Now, that's one week of achievement. 

As someone whose company invents things for a living, I understand that none of these breakthroughs were actually invented last week. Obviously, a long and winding road leads to each of those announcements. However, it's remarkable to see so many significant innovations reaching the stage of public announcement simultaneously.

It's hard to quantify the impact of these innovations on not only the tech industry - but the world. 

Think about the implications. Google's co-scientist is already solving problems that humans haven't been able to solve for decades. Clone is building robots that will use the next generations of AI to transform how we think about what artificial intelligence looks like. 

Not to mention the improvement in quantum computing and nuclear fusion, industries that I've been paying attention to since the 90s. 

While any of these topics would have made a good article, in my opinion, the whole is more impressive than the sum of its parts.

If I had to pick one of those topics to highlight, I think it's now time to start focusing more on quantum computing. 

To start, here's an hour-long interview with Satya Nadella about Microsoft's new quantum chip - and what it means for AI & business. 

 

via Dwarkesh Patel

Most of you probably aren't interested in watching the whole thing, but here are some of the highlights. 

• They've created a new state of matter called a topological superconductor.
• The qubits created with topological superconductors are fast, reliable, and small ... very small.
• These new qubits are 1/100th of a millimeter, meaning we now have a clear path to a million-qubit processor.
• To put that in perspective, imagine a chip that can fit in the palm of your hand yet can solve problems that even all the computers on Earth today combined can't! 
• Satya doesn't believe in making claims about how quickly AGI is coming.
• However, he believes it is useful and productive to set a benchmark of making the world 10% better.
• He also believes the topological superconductor breakthrough makes quantum computing a practical reality that can happen in a few years - not decades +.

Prepare for things to get more interesting.

We do live in exciting times!

Investment in AI is Rising ...

It’s no surprise that capital raising is moving toward AI - and often generative AI. 

 

via visualcapitalist

From 2023-2024, over $26 billion flowed into the sector - including big deals like Inflection, xAI, and Anthropic. 

While many of the biggest investments were in foundational models and infrastructure, some money is now moving into targeted AI applications. 

AI isn’t just for researchers and the tech giants anymore ... it’s becoming more commercial.

Realistically, AI is overhyped – and there is a lot of competition. Yet, few firms have operationalized AI in a meaningful way. 

With that said, here is a question worth considering.

Where are the AI applications capable of generating returns that justify the infrastructure, investment, and focus?

The next battle will likely be in the AI Applications space. To keep it short, why hasn’t it happened yet ... and what will likely create the value we’re looking for?

 

Why Haven’t AI Apps Taken Off Yet?

  •  Cost vs. Value Gap: Many AI applications are still experimental or add only incremental value.

  •  Compute Bottlenecks: AI compute costs remain expensive, limiting broader adoption.

  •  Enterprise Hesitation: Many companies are still figuring out how to integrate AI into their operations in a way that delivers real ROI.

 

Where Might the Value Come From?

For AI investments to pay off, applications must solve big problems, not just serve as experimental tools. The highest-value areas likely include:

  •  AI copilots and automation (Enterprise AI reducing labor costs and bottlenecks)

  •  Autonomous systems (AI for analytics, compliance, and logistics)

  •  AI-driven discovery (Accelerating breakthroughs in capabilities and performance)

  •  Next-gen digital assistants (LLMs with memory, context, and long-term utility)

 

Right now, AI apps are where mobile apps were in 2008 — there is plenty of potential, but only a handful of genuinely indispensable use cases. 

Companies like Capitalogix that crack the code on industrial-grade AI applications, will drive the next wave of value creation.

It’s fun and rewarding to watch artificial intelligence become available to everyone.

As the cost of “intelligence” decreases, let’s hope more people take advantage of the opportunity.

However, the sad truth is the opposite is also more likely. As AI becomes more available, it becomes easier for it to become a distraction. 

Remember the Internet? When it first started, most of the uses were academic. Now, despite there being functionally infinite ways to use the internet to improve your life and make you smarter, most people use it for memes and distractions. 

When you think about AI, don’t just think about artificial intelligence ... Think about amplified intelligence. That is the term I use to distinguish between the technology and what people really want ... which is the ability to make better decisions, take smarter actions, and continuously improve performance.

AI isn’t about taking away the humanity from your business or automating away the things you love. It’s about allowing you to be more human – doing more of the things you’re best at - that give you energy and bring you joy.