Capitalogix

The Rise of AI Art and Its Implications

The last time I talked about AI Art specifically was in 2022 when Dall-E was just gaining steam. Before that, it was 2019, when AI self-portraits were going viral. 

On both occasions, it still felt like the relative infancy of the technology. I compared it to VR getting another 15 minutes of fame. 

The images at the time weren’t fantastic, but it was a massive step in AI’s ability to understand and translate text into a coherent graphic response. The algorithms still didn’t really “understand” the meaning of images the way we do, and they were guessing based on what they had seen before - which was much less than today’s algorithms have seen. They were also much worse at interpreting images. As such, when you tried to use AI to recreate an image, there were a lot of hallucinations. The algorithms were essentially a brute-force application of math masquerading as intelligence. 

 

Fortunately, AI imagery has come a long way since then. However, with that improvement comes more ethical concerns. 

The rise of AI-generated art has sparked a complex and ongoing ethical debate, with compelling arguments on both sides. At the heart of the discussion lies the question of authorship, originality, and the impact of automation on human creativity and labor.

Proponents of AI art argue that it represents a powerful extension of human imagination. Just as past innovations—such as photography, digital editing, or sampling in music—were initially met with skepticism, Advocates argue AI-generated art is simply the next evolution in the artistic toolkit, and it democratizes access to artmaking. As a result, those with less skill - or time - can explore new styles, generate concepts, and be creative in a new form. To this end, they see AI not as a threat but as a collaborator—another brush or chisel in an artist’s hand.

However, critics raise concerns about the ethical implications of AI art, particularly in how these models are trained. Many AI systems are built on vast datasets scraped from the internet, including artwork by human creators who were neither consulted nor compensated, leading to accusations of IP theft. Moreover, they argue it sets a dangerous precedent where creative works can be replicated and commodified without consent or attribution. Lastly, on the idea of democratization, they would argue that art is already accessible to all and that people should be willing to explore skills not only to be good at them but to enjoy them. 

 

 

The most recent trend has been a great example of this argument. The launch of OpenAI’s new image generator, powered by GPT-4, has empowered users to transform their photos into various famous media themes - like Renaissance paintings or  Studio Ghibli anime images - which ironically goes against the ethos of Studio Ghibli and Hayao Miyazaki. The studio is known for its commitment to the craft, with carefully animated and hand-drawn scenes. Their films are known for glorifying nature and living in harmony with it. Miyazaki also believes that AI art is disrespectful to the “life” found in human-created art. 

 

“I feel like we are nearing the end times. We humans are losing faith in ourselves.” - Hayao Miyazaki 

 

I’m a massive fan of AI - and even AI art ... but as the technology continues to evolve, society must grapple with how to integrate these tools in ways that honor both progress and the rights of the artists (and people) whose work—and livelihoods—may be at stake.

What do you think?

AI: We're Not Just Prompts!

AI’s trajectory isn’t just upward—it’s curving ever steeper. From DeepMind’s groundbreaking models to Flow’s democratization of filmmaking, people are becoming used to how quickly AI technology improves.

 

Breakneck doesn’t even seem adequate to explain the scale of the movements. Because it isn’t just about the rate of change – even the rate of change of the rate of change is accelerating ... and the result is exponential progress.

 

Here is a simple example. Remember when you mocked AI-generated videos on social media for obvious flaws (e.g., six fingers, unnatural blinking or movement, etc.). Over the past few months, AI media quality has improved so much that spotting fakes is now difficult, even for tech-savvy people.

 

Well, we just took another giant leap.

 

This week, Google’s DeepMind unit released three new core AI models: Imagen for image generation,  Lyria for music generation, and Veo 3 for video generation.

It only takes a quick look at Veo 3 to realize it represents a significant breakthrough in delivering astonishingly realistic videos.

I’m only including two examples here ... but I went down the rabbit hole and came away very impressed.

Take a look – Everything in the clip below may be fake, but the AI is real.

 

via Jerrod Lew

The era of effortless, hyper-real content has arrived.

 

One of the big takeaways from tools like this is that you no longer need content creation talent other than your ideas.

 

An example of this comes from Google’s new AI filmmaking tool, Flow. 

What Is Flow?

What if creating professional-grade videos required no cameras, no crew, and no weeks of editing?

 

Flow can imagine and create videos just from your ideas. Kind of like telling a friend a story and having them draw or act it out instantly.

How Does It Work?

Think of Flow as a giant box of movie Legos. You can bring your own pieces (like pictures or clips) or ask Flow to make new pieces for you. Then, you snap them together to build scenes and clips that look like real movies.

Why Is This Cool?

It is becoming easier for almost anyone to create the type of content that only a specialist could produce before. The tool makes it easy in these three ways.

1. Consistent: The videos stick together well, so your story doesn’t jump around confusingly.
2. Seamless: It’s easy to add or change things without breaking the flow.
3. Cinematic: The videos look high-quality — like something you’d see on TV or in theaters.

If you want to play with it, it’s available to Google Ultra subscribers through the Gemini app and Google Labs. 

Ok, but what can it do?

Redefining “Real”

Don’t skip this next part. It’s what gave me the idea for the post.

To set the stage, imagine you’re watching a video of a person talking. Typically, you think, “This is real — someone actually stood in front of a camera and spoke.” But now computers can make a video that looks and sounds so real, you can’t tell it’s fake.

 

Anyway, this week, I saw a cool video on social media. At first, I thought it was cool simply because of the idea it expressed. But the video gets even more interesting when you realize how it was created.

 

“Prompt Theory” is a mind-bending exploration of artificial intelligence brought to life. The premise examines what happens when AI-generated characters refuse to believe they’re not real. From stunning visuals to synced audio, this video showcases AI’s new immersive storytelling power while examining some pretty trippy concepts.

 

Hashem Al-Ghaili via X

I predict you will see a massive influx of AI-generated content flooding social media using tools like this. 

Meanwhile, digital “people” with likenesses and internal objectives are increasingly going to become persistent and gain the ability to influence our world. This is inevitable. Yet, it’s still a little disorienting to think about.

 

As digital agents gain persistence and purpose, we face profound questions about reality, ethics, and human creativity.

 

And that is only the beginning!

 

Perhaps we are living in a simulation?

Global Happiness Levels in 2025

Are you Happy?

What does that mean? How do you define it? And how do you measure it?

Happiness is a surprisingly complex concept comprised of conditions that highlight positive emotions over negative ones. And upon a bit of reflection, happiness is bolstered by the support of comfort, freedom, wealth, and other things people aspire to experience. 

Regardless of how hard it is to describe (let alone quantify) ... humans strive for happiness.

Likewise, it is hard to imagine a well-balanced and objective "Happiness Report" because so much of the data required to compile it seems subjective and requires self-reporting. 

Nonetheless, the World Happiness Report takes an annual look at quantifiable factors (like health, wealth, GDP, and life expectancy) and more intangible factors (like social support, generosity, emotions, and perceptions of local government and businesses). Below is an infographic highlighting the World Happiness Report data for 2025.

World Happiness Report via Gallup

Click here to see a dashboard with the raw worldwide data.

I last shared this concept in 2022. At the time, we were still seeing the ramifications of COVID-19 on happiness levels. As you might expect, the pandemic caused a significant increase in negative emotions reported. Specifically, there were substantial increases in reports of worry and sadness across the ninety-five countries surveyed. The decline in mental health was higher in groups prone to disenfranchisement or other particular challenges – e.g., women, young people, and poorer people. 

Ultimately, happiness scores are relatively resilient and stable, and humanity persevered in the face of economic insecurity, anxiety, and more.

While scores in North America have dropped slightly, there are positive trends. 

The 2025 Report

In the 2025 report, one of the key focuses was an increase in pessimism about the benevolence of others. There seems to be a rise in distrust that doesn't match the actual statistics on acts of goodwill. For example, when researchers dropped wallets in the street, the proportion of returned wallets was far higher than people expected. 

Unfortunately, our well-being depends on our perception of others' benevolence, as well as their actual benevolence. 

Since we underestimate the kindness of others, our well-being can be improved by seeing acts of true benevolence. In fact, the people who benefit most from perceived benevolence are those who are the least happy. 

"Benevolence" increased during COVID-19 in every region of the world. People needed more help, and others responded. Even better, that bump in benevolence has been sustained, with benevolent acts still being about 10% higher than their pre-pandemic levels. 

Another thing that makes a big difference in happiness levels worldwide is a sense of community. People who eat with others are happier, and this effect holds across many other variables. People who live with others are also happier (even when it's family). 

The opposite of happiness is despair, and deaths of despair (suicide and substance abuse) are falling in the majority of countries. Deaths of despair are significantly lower in countries where more people are donating, volunteering, or helping strangers. 

Yet, Americans are increasingly eating alone and living alone, and are one of the few countries experiencing an increase in deaths of despair (especially among the younger population). In 2023, 19% of young adults across the world reported having no one they could count on for social support. This is a 39% increase compared to 2006. 

Takeaways

In the U.S., and a few other regions, the decline in happiness and social trust points to the rise in political polarisation and distrust of "the system". As life satisfaction lowers, there is a rise in anti-system votes.

Among unhappy people attracted by the extremes of the political spectrum, low-trust people are more often found on the far right, whereas high-trust people are more inclined to vote for the far left.

Despite that, when we feel like we're part of a community, spend time with others, and perform prosocial behavior, we significantly increase perceived personal benefit and reported happiness levels.

Do you think we can return to previous levels of trust in the States? I remember when it felt like both parties understood that the other side was looking to improve the country, just with different methods. 

On a broader note, while we have negative trends in the U.S., the decrease is lower than you might expect. The relative balance demonstrated in the face of such adversity may point towards the existence of a hedonic treadmill - or a set-point of happiness.

Regardless of the circumstances, people can focus on what they choose, define what it means to them, and choose their actions.

Remember, throughout history, things have gotten better. There are dips here and there, but like the S&P 500 ... we always rally eventually. 

Onwards!

Choosing To Be More Human in the Age of AI

Last week, I asked, “What do you do when AI gets better than you?” One of the key takeaways from that post was that AI is freeing you up to be more human.

My son (who helped write it) said he wished we used more examples and stories that dealt with “the future of being human” rather than “the future of work”. So, we decided that would be the “seed” idea for this post.

It’s funny, but when I started to gather my thoughts about it ... I felt a rush of emotions. 

Emotions and Logic

Emotions have frustratingly little to do with logic. Humans are driven by impulse and often by those that don’t represent our best nature. History shows that we’re driven by fear, greed, scarcity, and self-preservation. And, truthfully, that’s all “human”. But humans are also beautiful, meaning-making machines ... and throughout our often messy history, we’ve done amazing things and somehow survived.

Appreciating Life

Watching my father die was a catalyst for me to appreciate life and living more than I did. I gave a TEDx talk about that and wrote articles about the time value of a life worth living. At the end of his life, it was clear that he appreciated things more (a family dinner, a kiss goodbye, the beauty of a sunset) and that he would have done almost anything for more time. Two hidden gifts came from that “scarcity”. The first gift was recognizing that we got to choose how much more “life” we got out of the last part of my dad’s life. The second gift was realizing that you don’t have to wait for the end of life to “live like you only have a year left”.  

Final Goodbye

I have another memory from his deathbed as well. He had been out of it for a while, and I was worried that I wouldn’t get a chance to say a final goodbye and to tell him how much I loved him. Luckily, he woke up, and we had a few final lucid moments together. He looked me straight in the eyes, told me how much he loved me, and then with a touch of humor said, “Okay, so tell me how this relates to Veritas ...” which was the original name of the company I was running at that time. His final message to me was a reminder that life is not really about work.

Looking Beyond Work

Transparently, I still look at the world through a lens and filter that too often focuses on work. Yet I also recognize and strive to pay attention to the deeper meanings beyond that.

Getting back to the point of the article, it is easy to see how AI relates to work ... yet, it might be more important to consider how AI is going to affect the rest of your life. 

 

 

In the last article, we discussed how Lee Sedol, one of the world’s top Go players, retired after losing to AlphaGo. When asked about it, Lee said, “Losing to AI, in a sense, meant my entire world was collapsing.” He also explained, “I could no longer enjoy the game. So, I retired.” 

While it’s certainly his right to retire, I think it might have been the wrong choice ... or, at least, not what I would have done in that situation.

If playing Go was his passion, it might have been better for him to change how he “keeps score” to focus on his progress, rather than the distance between him and what AI could do.

As long as you believe you can get better (and have hope for continued improvements), there are many ways to leverage the capabilities and opportunities that come from that.

Many people engage in sports or games even though they know they won’t become the greatest of all time. The same is true for almost any hobby or pursuit (whether it’s in art, literature, philosophy, craftsmanship, or other fields). There will always be someone or something that can do it better, faster, or more efficiently. However, that shouldn’t be the sole determinant of whether you get joy or energy from pursuing a path of getting better at what you want to excel at.

One of my core beliefs is that the changes coming to the world will free us up to be more human. That means we have to choose what to pursue.

What’s more human than pursuing something difficult? 

The Beauty of Passion

In a world increasingly shaped by AI’s precision and efficiency, choosing to do something purely out of passion becomes a powerful act of self-expression. When a machine can paint more photorealistically or compose music with perfect mathematical harmony, human creativity finds new purpose not in competing, but in conveying emotion, imperfection, and lived experience.

 

As we focus on growing businesses and changing the world, I think it’s easy to lose sight of the passion that first got us into business. 

I do the research and write this newsletter, not because I expect it to make me a ton of money, or because AI can’t do it ... but because I enjoy it, and it’s almost like meditation for me. 

My son plays rugby despite enduring countless injuries, significant financial cost, and realizing that it takes increasing amounts of his time to stay competitive. From a logical standpoint, it makes almost no sense for him to spend scarce resources or risk such extreme bodily harm in his 30s. But he’s passionate about rugby, enjoys playing it, and recognizes how it improves other parts of his life. It is an excellent example of the time value of a life worth living. He made a conscious choice that this is what it takes to be, do, and have what he values most.

The Power of Fun 

Artificial Intelligence is probably better than you at poker ... does that mean you shouldn’t have some friends over and try to win their money?

Does it mean you shouldn’t try to learn a new instrument or write a book?

We often undervalue fun because it doesn’t always produce measurable outcomes, but fun is not frivolous. It’s how we bond, relax, and explore parts of ourselves we can’t access through obligation or structure.

We intrinsically understand this. You don’t worry about being the best when you’re playing pick-up basketball or throwing a football with your son. You’re focused on creating memories and having fun. 

Joy doesn’t need justification. 

 

Striving To Be The Best

Ultimately, you have to be willing to lose to be the best. In every pursuit, there will always be someone ahead of you. Whether it’s a faster runner, a sharper mind, or a newer technology, I want to be the man in the arena. 

It is not the critic who counts; not the man who points out how the strong man stumbles, or where the doer of deeds could have done them better. The credit belongs to the man who is actually in the arena, whose face is marred by dust and sweat and blood; who strives valiantly; who errs, who comes short again and again, because there is no effort without error and shortcoming; but who does actually strive to do the deeds; who knows the great enthusiasms, the great devotions; who spends himself in a worthy cause; who at the best knows in the end the triumph of high achievement, and who at the worst, if he fails, at least fails while daring greatly, so that his place shall never be with those cold and timid souls who neither know victory nor defeat. - Theodore Roosevelt, Citizenship in a Republic

The point has never been to be the best at everything ... but to strive for your best.

I’ve always believed the game isn’t over until I win, not because I can’t lose, but because the belief empowers me to get back up again. 

Being second best — or tenth, or just a beginner — doesn’t diminish your effort; it validates it. The climb matters, even if you never reach the summit. Humans are wired for persistence and purpose, not perfection. 

Humanity got where we are today because people weren’t happy with the status quo. They pursued greatness and innovation. Sometimes, what seems like failure ends up being the most significant success. 

AI is an incredible opportunity. It’s an opportunity to increase your productivity, to transform your business, and to redefine industries. It’s also an invitation to redefine your future and how you spend time. You can use it as an excuse to get smaller or bigger ... the power is in your perspective.

Hope that helps.

What Do You Do When AI is Better Than You?

When Beethoven was at the peak of his career, several of his contemporaries struggled to deal with the realization that they may never create anything that lived up to his creations. Brahms, for example, refused to make a symphony for 21 years. Schubert is quoted as saying, “Who can ever do anything after Beethoven?”

We’re seeing the same effect as a result of Artificial Intelligence. 

 

via visualcapitalist

The gap between human and machine reasoning is narrowing fast. I remember when AlphaGo, an AI program created by Google’s DeepMind, finally got better than humanity at Go. It was a big deal, and it prompted us to think seriously about competition in a post-AI world. If you can’t be the best, is it still worth competing? To one former Go champion, it wasn’t. He retired after “declaring AI invincible.” 

Over the past few years, AI systems have advanced rapidly, surpassing humans in many more tasks. Much like Beethoven, AI is discouraging competition. 

Was Lee Sedol, the former Go champ, wrong to quit? It’s hard to say ... but as AI gets better at more activities, it’s an issue we’ll encounter more often.

There’s always someone (or something) better. Taking a purely utilitarian approach isn’t always necessary or productive. It often helps to take a longer view of the issue.

Sometimes, it's okay to just do something because you enjoy doing it.

Sometimes you have to “embrace the suck” and be willing to put in the work to learn, grow, and progress.

Sometimes, you need to invest effort in understanding a process better to determine whether others (or automation) are achieving the right results.

The most successful people I know don’t try to avoid things with powerful potential. Instead, they leverage those things to achieve more and become better.

I advocate intelligently adopting AI, in part, because I expect the scale of AI’s “wins” will skyrocket. That means I know AI will soon be better than I am at things I do now.

It doesn’t mean I should give up. It means I have to raise the bar to stay competitive.

I have another belief that helps here. What if you believed, “The game isn’t over until I win ...”? With that belief in place, I won’t let a 2^nd place ceiling stop me if something gives me energy. AI may change how I play the game ... or even what game I choose to play ... but I will still choose to play.

 

 

What Happens to Human Work When Machines Get Smarter?

AI is changing the playing field at work, too. 

As a result, some say that AI-driven job displacement is not a future threat but a present reality.

This past week, several prominent  CEOs publicly mandated AI use, marking a shift to “AI-first” work culture, which prioritizes and integrates AI into the core of an organization’s strategy, operations, and overall culture.

Here is what I think (and you've probably heard me say this before): 

At this point, AI won't likely replace you ... but someone who uses AI better might.

Let’s face it, doing more with less is a core goal and strategy in business.

But that doesn’t mean humans are doomed. There are lots of historical parallels between AI integration and past technological revolutions. If you think about AI as a transformative force, you can hear the echoes of historical shifts that redefined work practices and intellectual labor (like the printing press, the calculator, or the internet).

We’re seeing significant changes in how we work. Instead of just having a mix of people working from home or the office (a hybrid workplace), we’re moving to a situation where people are working alongside smart computer programs, called AI agents (a hybrid workforce).

 

The rise of the hybrid workforce signifies a transformative shift in workplace dynamics. Gartner predicts that one-third of generative AI use cases will involve AI agents by 2028.

In the age of AI, success doesn’t come from battling technology — it comes from embracing our uniquely human powers and building systems that let those powers shine.

AI is coming - but it doesn’t have to be joy-sucking. Ideally, it should free you up to do MORE of the things that bring you joy, energy, and satisfaction. 

Onwards!

The Next Gilded Age ... This Generation's Carnegies, Rockefellers and Vanderbilts

Wealth is fascinating to those who have it, those who want it ... and even those who don’t.

Billionaires have always controlled significant amounts of wealth compared to the general population. However, now we’re seeing substantial wealth differences grow within the billionaire population itself. The very richest are getting much richer compared to just “wealthy” people. 

When Forbes published its first World’s Billionaire List in 1987, 140 billionaires accounted for a total of $295 billion in global wealth. Topping that list was Yoshiaki Tsutsumi from Japan, with $20 billion. A lot has changed since then. Elon Musk topped this year’s Forbes List and is now worth over $342 billion. His wealth is about 21 times more than Tsutsumi’s ... and over two million times more than the average American family’s.

A New Gilded Age

In 2017, The Guardian released an article stating that the world’s super-rich held the greatest concentration of wealth since the turn of the 20th century. According to The Guardian, 1,542 billionaires held approximately $6 trillion in collective wealth, which would put them as the fifth largest GDP at the time. 

Last year, less than a decade since the Guardian’s article, Forbes estimated that 2,781 billionaires had a combined net worth of over $14 trillion. For a little more context, some estimate that the world’s richest 1% own more than 43% of global financial assets. 

Currently, the world’s super-billionaire population is primarily made up of entrepreneurs who made their money in the tech sector, or whose industry was catapulted to new levels by technological advances. Six of the top ten wealthiest individuals on the Forbes list fall into that category.

In comparison, the first Gilded Age was established by a few entrepreneurs controlling monopolies in US rail, oil, steel, and banking.

 

The image is “Bosses of the Senate”.

The Vanderbilts amassed $185 billion (adjusted for inflation) from their railroad empire. Andrew Carnegie made $309 billion from his steel empire. John D. Rockefeller made $336 billion from an oil empire (that controlled about 90% of the American oil business). They were the stars of the Gilded Age ... and their control over major industries led to some of the largest individual fortunes in American history compared to the average population. 

It’s interesting to look at the transition from the richest in the late 1800s to the richest in 2025 ... the transition from industries like Steel, Oil, and Rail, into companies like Amazon, Microsoft, Tesla, and Walmart. While they certainly dominate the spaces they’re in, it is a far cry from the monopolies of the 1800s. 

While there are more “super-rich” individuals today than before, our wealthiest individuals still manage to have some impressive stat lines. As of the end of 2024, Bernard Arnault was worth an estimated $233 billion. Elon Musk was worth around $195 billion, and Jeff Bezos was right behind at $194 billion. Today, Bernard is sitting at $178 billion, Elon is up to $342 billion, and Jeff is up to $215 billion. Arnault is a clear example of how Trump’s tariff announcement impacted billionaires. 

With the AI gold rush in full swing, it will be interesting to see who gets added to the list in the coming years. 

Let me know when your name makes that list. I’ll do the same.

The "Chart Of The Century" In 2025: A Look At Consumer Price Inflation

In an era of economic uncertainty, few visualizations have captured the attention of economists, policymakers, and everyday consumers like the “Chart of the Century” created and named by Mark Perry, an economics professor and AEI scholar. This chart tracks the dramatic shifts in consumer prices across various sectors of the American economy over a quarter-century, revealing patterns that challenge conventional wisdom about inflation, purchasing power, and economic well-being.

The most current version reports price increases from 2000 through the end of 2024 for 14 categories of goods and services, along with the average wage and overall Consumer Price Index. Here are the key findings.

 

• Wage growth has outpaced inflation by a significant margin (123.3% vs. 90%) from 2000 to 2024, resulting in a 16.1% increase in real purchasing power.
• Sharp divergence exists between sectors: Technology and tradable goods have become much cheaper, while healthcare, education, and childcare costs soared.
• Market competition and trade liberalization drive price decreases, while regulated markets and limited competition contribute to price increases.
• Despite objective improvements in purchasing power, many consumers still feel financial pressure due to changing consumption patterns and “quality of life creep”.
• Policy challenges remain in balancing regulation with market forces, particularly in essential services like healthcare and education.

 

Core Economic Metrics: The Big Picture

The foundation of this analysis rests on three critical metrics that provide context for all other price trends:

 

Metric	Change (2000-2024)
Consumer Price Index (CPI)	+90%
Average Hourly Income	+123.3%
Real Purchasing Power	+16.1%

 

From January 2000 to now, the CPI for All Items has increased by almost 90%. That is a big jump from its 59.6% level in 2019, when I first shared this chart.

 

These numbers tell a surprising story: despite widespread perceptions of economic hardship, Americans’ wages have grown significantly faster than inflation over these 24 years. This translates to a meaningful increase in real purchasing power – the ability to buy more goods and services with the same amount of work.

 

However, this aggregate picture masks dramatic variations across different categories of goods and services. Let’s explore these divergent trends.

 

The price of technology, electronics, and consumer goods — think toys and television sets — has tumbled over the past two decades. Why? These categories benefit from global competition, technological innovation, and manufacturing efficiencies.

Meanwhile, the cost of hospital stays, childcare, and college tuition, to name a few, have surged. Why? These sectors share important characteristics: they are typically non-tradable services (cannot be imported), operate in markets with limited competition, and are often subject to extensive regulation.

Below is Perry’s Chart of the Century. To help you interpret it better, lines above the overall inflation line have become functionally more expensive over time, and lines below the overall inflation line have become functionally less expensive. 

via Human Progress

For context, at the beginning of 2020, food, beverages, and housing were in line with inflation. They’ve now skyrocketed above inflation, which helps to explain the unease many households are feeling right now. College tuition and hospital services also have continued to rise relative to inflation over the past few years.

 

Market Dynamics: Understanding the Divergence

What explains these dramatically different price trajectories? Here are several (but not all of the) key factors:

Factors Driving Price Increases

• Government regulation creating compliance costs and barriers to entry.
• Quasi-monopolistic markets with limited price competition.
• Non-tradeable services protected from foreign competition.
• Limited technological disruption in certain service sectors.

Factors Driving Price Decreases

• Foreign competition putting downward pressure on prices.
• Technological advancement reducing production costs.
• Manufacturing optimization increasing efficiency.
• Market competition forcing price discipline.
• Trade liberalization expanding access to global markets.

Looking at the prices that decrease the most, they’re all technologies. New technologies almost always become less expensive as we optimize manufacturing, components become cheaper, and competition increases. According to VisualCapitalist, at the turn of the century, a flat-screen TV would cost around 17% of the median income ($42,148). Since then, though, prices fell quickly. Today, a new TV typically costs less than 1% of the U.S. median income ($54,132).

We should also consider the larger trends. For example, In 2020, I asked what Coronavirus would do to prices ... and the answer turned out to be way less than expected. If you don’t look at the rise in inflation but instead the change in trajectories, very few categories were heavily affected. While hospital services have increased significantly since 2019, they were already rising. There were some immediate impacts, but they went away relatively quickly. 

Another thing to consider is average hourly income. Since 2000, overall inflation has increased by 87.3%, while average hourly income has increased by 123.3%. This means that hourly income increased 38% faster than prices (which indicates a 16.1% decrease in overall time prices). You get 19.2% more today for the same amount of time worked ~24 years ago. This represents a mild increase in abundance since last year. 

via Human Progress

Although 10 of the 14 items rose in nominal prices over the past 24 years, only five had a higher time price when accounting for the 123.3 percent increase in hourly wages. Those items were medical care services, childcare and nursery school, college textbooks, college tuition and fees, and hospital services. 

The Consumer Experience: Perception vs. Reality

It’s interesting to look at data like that, knowing that the average household is feeling a “crunch” right now.

My guess is that few consumers distinguish between perception and reality. However, feeling a crunch isn’t necessarily the same as being in a crunch.

For instance, we must account for ‘quality of life creep,’ where people tend to splurge on luxuries as their standard of living improves. With the ease of online shopping and access to consumer credit, it has become increasingly easy to make impulse purchases, leading to reduced savings and feelings of financial scarcity. This phenomenon is a function of increased consumption (rather than inflation), yet it still leaves consumers feeling like they’re struggling to make ends meet. Our sense of what’s normal has risen, and that’s hard to unlearn. 

 

Perry’s ‘Chart of the Century’ reveals the complex relationships between inflation, consumption, and economic growth. While households may feel financial strain, the data shows that income has outpaced inflation, and technology has made many goods more affordable. Nonetheless, there is still a real sense of economic struggle. Especially in these last few months. 

 

Economic Patterns: Regulated vs. Free Markets

A clear pattern emerges when examining the relationship between market structures and price trends.

Regulated Markets (like healthcare and education) tend toward higher prices over time, feature less price competition, and offer limited consumer choice.

Free Markets, show price decreases over time, feature greater competition, and provide consumers more options.

This pattern raises important questions about the role of regulation in various economic sectors and the balance between consumer protection and market efficiency.

With that in mind, how can policymakers address sectors experiencing significant price hikes, such as healthcare and education, without stifling innovation in tradable goods and services? 

Future Outlook

Beyond all that, here are three other key trends to watch.

• AI Disruption: Telemedicine and online education could bend healthcare/education cost curves.
• Trade Wars: New tariffs risk reversing tech price declines (e.g., proposed tariffs on Chinese electronics).
• Generational Shifts: Millennials prioritize experiences over goods, potentially easing service demand.

As we continue to innovate and policy changes, it will be interesting to see if we can make essential services as dynamically competitive as consumer electronics. While America is one of the best countries in the world in countless ways, we do lag behind several countries in healthcare and education.

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?

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.