Today is Easter – and also part of Passover, the Jewish holiday that recounts the story of Exodus.
The overlap is evident in Da Vinci’s Last Supper, which depicts a Passover Seder (the traditional meal that commemorates the Exodus) and Jesus’s last meal before his crucifixion.
Part of the Passover Seder tradition involves discussing how to share the story in ways that resonate with different people, recognizing that everyone understands and relates to things differently. This echoes our previous discussion on happiness and how that feeling varies for each of us.
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 the need to 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 (ormachines) who think differently.
On a lighter note, one of the memorable phrases from Exodus is Moses’ “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.
As a reminder, it doesn’t take a new year to start good habits.
I am often amazed at how little human nature has changed throughout recorded history.
Despite the exponential progress we’ve made in health, wealth, society, tools, and understanding … we still struggle to find meaning, purpose, and happiness in our lives and our existence.
We underestimate others’ kindness, but it’s more common than we think.
Community boosts happiness—eating and living with others matter. Social media is a poor replacement and can actually be hurting your sense of community.
Despair is falling globally, except in isolated, low-trust places like the U.S.
Hope remains—trust and happiness can rebound with connection and a sense of purpose.
That post didn’t attempt to define happiness. Instead, it categorized data on people’s reported feelings about happiness. This post will focus philosophically on the definition of happiness.
While it seems like a simple concept, happiness is complex. We know many things that contribute to and detract from it; we know humans strive for it, but it is still surprisingly challenging to give it a uniform definition.
A few years ago, a hobbyist philosopher analyzed 93 philosophy books, spanning from 570 BC to 1588, in an attempt to find a universal definition of Happiness. Here are those findings.
It starts with a simple list of definitions from various philosophers. It does a meta-analysis to create some meaningful categories of definition. Then it presents the admittedly subjective conclusion that:
Happiness is to accept and find harmony with reason.
My son, Zach, pointed out that while “happiness” is a conscious choice, paradoxically, the “pursuit of happiness” often backfires. Why? Because happiness is a result of acceptance. However, when happiness is the goal, people often focus on what they lack … rather than what they already have or the progress they’ve made. That perspective shift drops them into the ‘Gap’ instead of letting the ‘Gain’ lift them.
Across centuries, philosophers have wrestled with a deceptively simple question: What does it mean to live a good life?
As entrepreneurs, investors, and leaders, we often chase performance, innovation, or edge — but underneath it all, there’s a quieter inquiry: Am I living well?
Happiness aside, across 93 influential philosophical texts spanning two millennia, one word consistently reappears: Eudaimonia. This is not happiness in the modern sense of pleasure, but a richer concept of human flourishing — a life filled with purpose, virtue, and meaning.
Ancient thinkers didn’t view happiness as just a passing feeling but as something deeper — a life lived in line with purpose and virtue. Some focused on developing strong inner character, while others believed it came from living in harmony with nature or a higher power. There has always been debate about how much external factors like wealth, luck, or relationships genuinely matter, and that question still isn’t fully settled. By the time the Renaissance arrived, the discussion began to shift more toward personal, subjective experience. But across all these perspectives and eras, one idea keeps recurring: happiness is something you nurture over time, not just something you consume.
Contradictions and Tensions
Thoughts on happiness contain paradoxes, contradictions, and tensions. Examining the boundaries between what you are certain of and what you are uncertain of is where insights occur.
Here are a few to get you started.
Virtue vs. External Goods: Aristotle acknowledges external goods (wealth, friends) as necessary for complete happiness, while Stoics claim virtue alone suffices. This tension challenges the simplicity of virtue-based happiness, suggesting a nuanced balance between inner character and outer circumstances.
Subjective vs. Objective Happiness: Ancient philosophers often defined Happiness as an objective state (living virtuously or intellectually flourishing), whereas modern definitions more often emphasize subjective satisfaction that varies from individual to individual. This tension probes whether happiness is a universal or personal experience.
Happiness as Pleasure vs. Happiness as Duty/Struggle: Epicureanism equates happiness with pleasure (the absence of pain), whereas Cynics and Stoics emphasize enduring hardship and discipline as the path to happiness, creating a paradox between comfort and resilience.
Three Metaphors To Help You Think About Happiness
As we’ve seen, trying to answer the question “what is happiness?” quickly leads to a mix of data, perspectives, and even contradictions — between internal and external factors, momentary feelings and lifelong fulfillment, control and circumstance.
To help make sense of that complexity, metaphors offer a useful kind of structure.
Think of the Stoic ship captain: you can’t control the ocean, but you can steer your ship, anchoring the idea that happiness is tied to how we manage our internal world amid external uncertainty. Or, Plato’s vision of the soul as a teamadds another layer: reason guides spirit and appetite, suggesting that happiness depends on internal alignment and self-governance. And Aristotle’s gardenreminds us that happiness isn’t a single outcome, but something cultivated over time, shaped by effort, environment, and care. Together, these frameworks don’t resolve every tension, but they give us a clearer way to navigate them … turning an abstract question into something we can actually work with.
Happiness Isn’t a Destination — It’s a Design
The philosophers didn’t agree on everything, but they aligned on one thing: happiness isn’t something you find. It’s something you build.
Perhaps happiness is less about chasing peaks and more about tending the kind of life you won’t regret.
I’m curious how this lands for you — especially if you’re building something big.
Reach out and let me know what happiness looks like from your vantage point.
This week, OpenAI announced it would be shutting down Sora, its popular AI video app. This is not just about killing a video toy; it signals a strategic pivot at OpenAI.
You probably weren’t Sora’s target user, but watching this montage of its top clips is a great way to see how far this impressive tech has come.
It’s a reminder that when OpenAI prunes products like Sora, it’s also pruning capital-intensive bets and risky content partnerships.
Pushing Pause on “Adult Mode”
Last October, Sam Altman announced plans for an erotica mode. However, the tension between boldness and caution shows up in the gap between OpenAI’s ‘not the morality police’ rhetoric and its quiet slowdown on controversial features.
The Financial Times later reported that the pause is “indefinite,” with Cristina Criddle citing “sexual datasets and eliminating illegal content” as challenges for OpenAI. This reflects the growing regulatory and reputational risk around generative sexual content.
ChatGPT Just Got More Reliable
OpenAI updated ChatGPT with a 33% reduction in factual errors, plus a significantly expanded memory for longer conversations.
Changes like these hint at where OpenAI wants to focus: scalable, everyday systems that drive recurring revenue.
And it doesn’t stop there …
The Great DRAM Over-Buy
Originally, it was reported that OpenAI had secured forward commitments for up to 40% of the world’s DRAM supply. This was to help their future data center growth as AI demand increases.
In plain English, DRAM is the short-term memory that lets these models think; if you want bigger, smarter models, you need a lot of it.
As these announcements roll in, many are also scrutinizing how much RAM OpenAI locked up in advance.
With this, I think the memory bull run (which began over 2 years ago) is coming to an end. Many of the large AI labs have secured more DRAM via forward contracts than what they will realistically need. This has created the sense of an artificial shortage supported by essentially FOMO on DRAM supply. Like in previous cycles, this will unwind. – Seeking Alpha
After initially pursuing massive, vertically integrated infrastructure through its multi-hundred-billion-dollar Stargate initiative, OpenAI has begun shifting toward a more flexible, capital-efficient model.
If labs over-bought memory during the AI gold rush, then shifting from owning massive data centers to orchestrating capacity from partners starts to look less like backtracking and more like smart risk management.
Instead of owning and operating the bulk of its global compute footprint, OpenAI is increasingly leaning on partnerships and leased capacity from cloud providers. Internally, this has been reflected in a restructuring that separates infrastructure design, partner management, and operations — signaling a shift from a “build everything” strategy to a “coordinate and optimize” approach (e.g., using multiple cloud providers, negotiating for power in different regions, etc.).
At the same time, the company is clearly narrowing its product focus.
Video apps like Sora are entertaining for users, but they’re also brutally compute-intensive for the providers. As you look at Anthropic’s revenue and those of other competitors, it’s clear that chat, code, and enterprise use are where the immediate growth and low-hanging fruit lie.
How This Fits the Longer-Term Plan
AI has already consumed massive funding to get here — and it will require even more to reach the next plateau.
Rather than a retreat, this shift aligns with a longer-term strategy: preserving capital, accelerating deployment, and keeping options open in a rapidly evolving compute landscape. Leveraging partners allows OpenAI to scale faster while avoiding bottlenecks tied to financing, power availability, and hardware cycles.
In that context, “Stargate” appears to be evolving—from a fixed set of owned assets into a broader, more modular strategy for bringing compute online wherever it is most efficient.
The end goal hasn’t changed: securing enough compute to train and deploy increasingly powerful AI systems. What has changed is the path — shifting from infrastructure ownership to infrastructure orchestration, and from experimental breadth to commercial depth.
This aligns with their move from non-profit to IPO. They’re clearly focused on profitability in the near term, not just the long term.
But these shifts could also signal changes that open opportunities for more players to enter the space and carve out their little slice of the digital landscape.
I’ll continue to watch how OpenAI manages the delicate balance between rapid innovation, financial pressures, and the broader public good. The story is still unfolding, and what happens next will shape the technological future we all live in.
How It Shows Up in Everyday Use
All of this might sound abstract, but you can feel these shifts in everyday usage too. If you’re curious, I use a paid version of ChatGPT throughout the day. I’ve gotten used to it; I understand when to listen and when to ignore it. With that said, I’ve also been happy to pay for Perplexity (but I use it in much more limited circumstances). It gives me access to different models, and I feel like it’s been a good value. However, today I finally decided to pay for Anthropic as well because the quality of the responses I’ve been getting has led me to change my usage behavior.
Interestingly, if I ask different models a question and then show their answers to ChatGPT, ChatGPT often favors Claude’s responses as well.
I know all of that is subject to change, and tools are leapfrogging one another with increasing frequency. With that said, I thought it was worth sharing.
Asking whether someone is happy seems like a simple question. But what does the question really ask, and what does ‘happy’ really mean?
Once you define happiness (for you), how, when, and for how long do you measure it?
These are some reasons why measuring happiness is harder and more complex than it might seem at first glance.
What Does Happiness Really Measure?
At its core, happiness means experiencing more positive emotions than negative ones. With a bit of reflection, you see that happiness is reinforced by comfort, freedom, financial security, and other things people aspire to.
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 much of the data needed to compile it is subjective and relies on self-reporting.
Nonetheless, the World Happiness Report takes an annual look at quantifiable factors (such as health, wealth, GDP, and life expectancy) and more intangible factors (such as social support, generosity, emotions, and perceptions of local government and businesses). Below is an infographic highlighting the World Happiness Report data for 2026.
In 2022, when I shared this, we were seeing the immediate ramifications of COVID-19 on happiness levels. There was a significant increase in negative emotions reported – specifically, worry and sadness. And yet, happiness scores are relatively resilient and stable, and humanity persevered in the face of economic insecurity, anxiety, and more.
In the 2025 report, one of the key focuses was the increase in pessimism about others’ benevolence. 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 on the street, the proportion of wallets returned was far higher than people expected.
Unfortunately, our well-being depends on both our perception of others’ benevolence and their actual benevolence.
The World’s Happiest Countries in 2026
Before we dive into the global trends, a surface-level view shows that Nordic nations (e.g., Finland and Denmark) boast the happiest people. Unfortunately, those represent a small fraction of the world’s population.
All of the top 10 nations have populations under 20 million. Interestingly, Mexico is a significant outlier, ranking #12 with a population of 131.9 million.
And despite what you may think, the US is also among the few large nations in the top 50.
Building a Case Against Social Media Usage
Diving deeper into the results, young people are significantly less happy than they were 15 years ago. You might assume war, economic anxiety, politics, or family structure are to blame — but much of the decline appears tied to social media use. While that may seem like a safe scapegoat or a simple hypothesis, the research supports it. While no single factor explains everything, the researchers estimate that always-available social media is a statistically significant contributor to rising mental illness among adolescents in Western nations.
Diving in a little deeper, the PISA study of 15-year-olds in 47 countries shows that those who use social media for over seven hours a day have much lower well-being than those who use it for less than one hour. In a sample of US college students, the majority wish that social media platforms did not exist.
These numbers are significantly worse in Western countries than in Eastern and African countries.
Based on their research, the Report argues that the rapid adoption of “always-available social media” by adolescents in the early 2010s is a statistically significant contributor to the population-level increases in mental illness in Western nations.
Social media is so toxic that it’s affecting the population at large … not just the most at-risk.
So, Why Do People Use It?
Many empirical studies cast doubt on whether social media makes people happy, affecting how we value, choose, and consider well-being. The main takeaway is that many individuals use social media mainly because others do. They don’t want to be left out. If social media use were decreased or eliminated, many people would benefit, and they are aware of this.
Last year, we talked about the importance of trust and social connections for well-being, but also how social media had created a very low-trust society, as evidenced by the political silos and online vitriol. Unsurprisingly, the estimated relationship between internet use and well-being differs significantly across generations, genders, and regions. It is highly negative for Gen Z, moderately negative for Millennials, near zero for Gen X, and slightly positive for Baby Boomers.
Older adults enjoy the benefits of stable trust, growing attachment, enhanced safety, and moderate digital engagement. In contrast, younger adults often experience a decline in these foundations within highly saturated digital environments.
Clearly, social media isn’t creating the healthy connections our younger generations need. Meanwhile, generations that grew up with less digital-centric relationships seem to be handling the changes more robustly.
Over the last decade, the top of the world’s happiest countries list has remained remarkably consistent.
So have global happiness levels as a whole. 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.
Large countries, like India, often bring down the averages, but even that has remained relatively consistent.
Despite that, the distribution of happiness has changed significantly. While life satisfaction is stable, how people feel day to day has shifted downward. Stress, worry, and sadness have increased globally, and younger generations are impacted to a larger degree.
Takeaways
Happiness hasn’t collapsed globally—but it’s become more uneven and, in some ways, more fragile.
In the US 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 declines, anti-system votes rise.
Worsening the situation is our growing dependence on social media instead of face-to-face relationships. Although most people realize it’s harmful and don’t want to use it, many can’t imagine missing out. As a result, they spend time and energy passively consuming content instead of being active in their own lives.
As AI‑generated content and AI chatbot partners become more common, it will be interesting to see how they reshape this data.
Regardless, humanity has always proved resilient and enduring. Regardless of the circumstances, people can focus on what they choose, define what it means to them, and act accordingly.
Remember, throughout history, things have gotten better. There are dips here and there, but like the S&P 500 … we rally eventually.
The data show that happiness is surprisingly resilient but not guaranteed.
Younger generations are paying the price for a world built around screens, feeds, and algorithms — but they also have the most to gain from changing course.
We may not control global trends, but we do control how we spend our attention, who we spend time with, and what we build together. Those choices compound, just like returns in the S&P 500. Over time, they can move both our personal and collective happiness charts in the right direction.
March Madness is in full swing, and for a few weeks, it will dominate the sports world.
Unsurprisingly, almost no one has a perfect bracket anymore.
As I write the first draft of this on Saturday night, reports indicate that only 26 perfect brackets remain. How does that happen so fast? The NCAA Tournament reminds odds makers to expect the unexpected. For example, top-seedDuke almost lost to bottom-seeded Siena to open March Madness. Meanwhile, High Point beat Wisconsin and Nebraska made a miracle happen, breaking their 0-8 March Madness streak. Of course, that’s only the tip of the iceberg.
Before 24/7 sports channels and social media, 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. So do the confounding variables, like health (mind, body, and spirit), matchup, coaching, officiating, and luck.
The Odds Are Stacked Against You
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 to 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 to pick a perfect bracket.
Even knowing the odds, I bet you felt pretty good when you filled out your bracket.
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.
Human nature tempts us to overweight recent performance, fall in love with narratives, and underestimate how little of the future we can actually see.
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 the allure of gambling or trading. As sports fans, it’s easy to believe we know something the casual observer doesn’t. We want the bragging rights for the sleeper pick that goes deeper than expected, our alma mater’s unlikely run, and the big upset we called before anyone else.
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 Help?
“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
In markets, that’s the backtest that looks perfect on paper and fails in live trading; in March Madness, it’s the model that nails last year’s pattern and misses this year’s upset.
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:
People aren’t as good at prediction as they predict they are.
Machine Learning isn’t a one-size-fits-all answer to all your problems.
That matters if you’re picking brackets, trading portfolios, or making strategic business bets.
While Duke continues to give me heart attacks during March Madness, I take solace in the fact that it’s still a fantastic school (and one of the hardest to get into)…
Infographic of the most selective U.S. colleges via visualcapitalist
Caltech leads with a 3% admit rate, while several top universities — including Harvard, Stanford, and Yale—accept about 4% of applicants. Duke is just a bit more welcoming, with a 6% acceptance rate.
Caltech’s extreme selectivity, with an acceptance rate of only 3%, is partly due to its structural limitations. The university admits about 1,000 undergraduates, significantly fewer than many top-tier institutions. This limited capacity, along with its renowned status in STEM disciplines, naturally results in a low acceptance rate.
When a small institution receives thousands of top-tier applications, admissions become extraordinarily competitive.
Popularity breeds exclusivity. For many schools on the list, lower admission rates result from maintaining a relatively stable incoming class size, despite an increasing number of applications.
How AI Changes Who Gets In
In addition, I’m curious about how AI has affected these numbers and the composition of matriculating classes. For students, AI has certainly made it easier to apply to more schools and write different essays. For schools, imagine how much harder it is to discern what’s real versus what only seems real. Now imagine how they will use AI and automation to screen applications and to monitor and engage with applicants throughout the process. The net result is that the quality and composition of incoming classes are destined to change as both students and schools evolve. And this is a microcosm of what’s happening in the job market today as well. The same tools that help students game essays are already reshaping résumés and candidate screening … but that’s a topic for a different time.
While there’s no reason to be proud of low admission rates (or to question whether your alma mater would still let you in), the schools can be proud of the quality of the education they provide and of how many students want to attend … but can any of the schools on that list be as proud of their basketball team as Duke?
A few weeks ago, I shared an AI music video. It seemed noteworthy at the time because even though the music and video were AI-generated, the result felt surprisingly human.
Here’s a question for you …
Once AI can convincingly create art, what meaningful work is left uniquely for humans?
That’s the central tension in this mockumentary-style ad for Energym. Click below to watch. It was clever … and mildly unsettling in its plausibility.
The Energym parody imagines a 2036 where humans have lost their sense of purpose. So what do they do? Exercise so hard that they generate the energy needed for the very AI that took their jobs. The video features cameos from Elon Musk, Jeff Bezos, and Sam Altman (well, at least their 10-years-older personages).
Energym is funny because it’s not as far from reality as we’d like — and it quietly says something important about our evolving relationship with AI.
Good humor is often rooted in truth. Perhaps healthy dystopian fears are, too.
When Satire Starts To Feel Real
Obviously, satire is tongue-in-cheek and often exaggerates real fears. Expect to see more content poking fun at our growing dependence on artificial intelligence.
The Energym video was produced by Hans Buyse and Jan De Loore. De Loore, who authored the script, edited, and produced the video, is also a cofounder of Kitchhock, a solo AI creative studio based in Belgium. De Loore also applies his creative expertise and the latest generative video AI technology to produce real advertisements for Belgian companies through his AI video studio, AiCandy.
AI as an Amplifier, Not a Replacement
To me, this video shows where AI truly excels: helping you bring new, unusual ideas to life that would have been hard or expensive to produce before.
I’ve seen an explosion of creative work built with new AI tools, and for the most part, that’s great. The danger is letting them automate away your own creativity and critical thinking instead of amplifying them.
If you do decide to let it replace you, at least you might get ripped in the process.
