Three-Year Highs on Both Sides: PPI Validates Yesterday's CPI Spike

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I started this Substack because I wanted to take you along on my own journey of raising my HRV, not just as a metric on a wearable, but as a window into how the entire body is functioning. One of the most powerful things about using AI to solve a health problem is that it does not look at symptoms in isolation. At its best, AI acts like a polymathic thinking partner. It can connect clues across physiology, immunology, sleep, stress, the gut, the nervous system, and recovery to help reveal the bigger picture. That is exactly what happened with seasonal allergies.
For years, I hated this time of year. The congestion, itchy eyes, brain fog, and constant need for allergy medicine felt inevitable. But as I focused seriously on raising my HRV, something unexpected happened: my seasonal allergies went away. I do not get them anymore. AI helped me understand why. Allergies are not just about pollen. They are often a sign that something deeper in the system is out of regulation. So this week, I want to use allergies as the first example of a larger idea: the same tools that raise HRV may also create benefits far beyond your heart rate data. They may help your body become less reactive, more resilient, and better able to respond to the world without overreacting to it.
This time of year, so many people are suffering quietly. They wake up with swollen eyes, stuffy noses, scratchy throats, headaches, fatigue, and the kind of brain fog that makes ordinary work feel harder than it should. They check pollen counts like weather alerts and brace for the familiar seasonal ambush.
And yes, pollen matters. Tree pollen generally drives spring allergies, grasses tend to rise later, and ragweed and other weeds fuel the fall wave. Mold can add another layer when heat and humidity climb. But pollen is not a pathogen. It is not a virus. For many people, it is biological dust that the body has decided to treat like an emergency.
This is where Heart Rate Variability becomes interesting.
Raising HRV will not magically cure allergies, and it is not a reason to ignore asthma symptoms, stop appropriate medication, or skip an allergist. But HRV gives us a window into a bigger truth: seasonal allergies are not only about what is in the air. They are also about the state of the system receiving the signal. When your nervous system is chronically braced, underslept, inflamed, overstimulated, and under-recovered, your immune system is more likely to overreact. I like to say, if your immune system is “drunk,” it can’t see toxins clearly.
Clinically, allergic rhinitis is an IgE-mediated immune response to inhaled allergens, often producing sneezing, congestion, itching, and a runny nose. In Type I hypersensitivity reactions, IgE can activate mast cells and basophils, which release inflammatory mediators including histamine.
But the deeper question is: why does one body tolerate pollen while another detonates in its presence?
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Introduction: Awareness Is the Foundation of Health
“You have power over your mind, not outside events. Realize this, and you will find strength.”— Marcus Aurelius, Meditations
One of the most important, and often overlooked, drivers of long term health is awareness. Not in the abstract sense, but in the ability to see patterns in how your body responds to the inputs of daily life. Sleep, nutrition, stress, alcohol, training, and travel are not isolated events. They are part of a system, and over time, they leave a measurable signature. This is where the Oura Ring has been so valuable for me. It does not simply track metrics. It reveals patterns. It shows how certain behaviors influence heart rate variability, or HRV, not just on a given day, but across multiple days and even weeks. The goal is not to control every variable or to maintain a perfect score. The goal is to recognize what consistently moves your system in the right direction, and what quietly pulls it away.
In that context, one of the most powerful insights is understanding that some of the most meaningful influences on HRV are not obvious. They are embedded in normal routines, which makes them easy to overlook. Travel is one of the clearest examples. It feels routine. It is often necessary. Most times, it is out of our control. But once you begin to see the pattern, it becomes clear that travel has a consistent influence on HRV, not only during the experience, but also in the recovery period that follows. This is the importance of solving for a problem using a systems thinking approach. Many times, especially with health, it is not just about what you are doing for you but how you are navigating stressors for work. Soon I will also go through the commute which was an eye opener for me.
There is also an important mindset embedded in this. Having access to this kind of data creates a choice. You can either engage with it and learn from it, or you can ignore it. Choosing not to measure or observe does not remove the impact. It simply removes the visibility. In that sense, opting out of awareness is, in itself, a decision. And over time, that decision compounds just as much as the behaviors being measured. I recognized that as I got older, all these little things add up if you want to focus on anti-aging.
Understanding HRV and the Recovery System
HRV reflects the balance between the parasympathetic nervous system, responsible for recovery and repair, and the sympathetic nervous system, which supports alertness and responsiveness. A higher HRV generally indicates a system that is adaptable and well recovered, while a lower HRV signals that the body is allocating more resources toward managing current demands.
Travel influences this balance in several ways at once. It changes sleep timing, introduces new environments, alters movement patterns, and often shifts nutrition and hydration. Together, these factors move the body toward a more activated state. The key is not the presence of activation itself. This is a normal and necessary part of life. The key is how efficiently the body returns to a recovered state afterward.
Why Travel Matters More Than We Realize
Travel is so embedded in modern life that it is rarely considered in the context of recovery. Flights, commutes, and trips are treated as routine logistics rather than physiological inputs. However, wearable data consistently shows that HRV tends to move lower during travel periods. More importantly, the effects often extend beyond the travel itself.
A single day of travel may be followed by multiple days where HRV gradually returns to baseline. During this period, sleep quality may still be adjusting, resting heart rate may remain slightly elevated, and overall readiness may not fully normalize. Over time, these periods can accumulate, shaping the broader trend of HRV across weeks and months.
Understanding this pattern is where awareness becomes valuable. Once you recognize that travel influences more than just the day it occurs, you can begin to plan around both the experience and the recovery window that follows.
Why the Effects Can Last After You Return
The extended influence of travel on HRV is driven by several overlapping factors. Circadian rhythm plays a central role. Even without crossing time zones, changes in sleep timing and light exposure can shift the body’s internal clock. When time zones are involved, this adjustment becomes more pronounced and may take several days to fully realign.
In addition, travel introduces a steady stream of inputs that require attention and adaptation. Navigating airports, adjusting to schedules, sitting for extended periods, and engaging with new environments all contribute. Each of these adds to the overall load the body processes. While none are extreme on their own, together they create a meaningful shift in how the system operates.
Behavioral patterns during travel also contribute. Meals may be less consistent, hydration can be overlooked, and alcohol is often more common. These factors influence sleep quality and recovery, which in turn affect HRV. Alcohol, in particular, tends to reduce overnight HRV and elevate resting heart rate, extending the time it takes for the body to return to baseline.
Why Aging Changes the Equation
As individuals get older, the body’s recovery processes become more deliberate. Baseline HRV may gradually decline, and the time required to adapt to changes, such as travel, can increase. What might have been a quick adjustment earlier in life can evolve into a more extended recovery period.
This does not mean travel becomes problematic. Rather, it highlights the importance of approaching it with intention. Managing the inputs around travel becomes a way to support the body’s ability to adapt and return to equilibrium efficiently.
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Think about a time when a bug went around the office. One by one, everyone seemed to get it. Some people barely reacted, while others were out for a week. Same office. Same exposure. Very different outcomes.
Or think about allergy season. Pollen shows up, and suddenly millions of people can feel their immune system acting up in real time. The pollen itself is not a virus. It is not trying to infect you. But for someone with seasonal allergies, the immune system misreads the signal and responds as if a threat has entered the body. Sneezing, congestion, itchy eyes, and inflammation are all signs of an immune system that is not weak, but reactive. That is an important distinction. Health is not just about having an immune system that can fight. It is about having an immune system that knows when to fight, how hard to fight, and when to stand down.
I used to think about the immune system the way most people do: as the thing that shows up when you catch a cold, get the flu, or come down with something obvious. But watching parents, grandparents, and older people struggle more during the winter changes how you see it. You begin to realize that the immune system is not separate from aging. It is one of the clearest signs of aging.
That observation might pass without much thought for some people, but for me, especially now that I have AI in my hands, it became something to explore. What is the relationship between aging, immune response, recovery, inflammation, and HRV? Why do some people bounce back quickly while others seem to stay trapped in stress for longer? Watching people age is one of the most powerful ways to ask a deeper question: how much of this decline is inevitable, and how much of it reflects systems that are slowly losing balance?
That became the basis for much of my own journey around HRV. I was not just trying to raise a number. I was trying to understand what the number was telling me about recovery, resilience, inflammation, and the biological stress that often rises with age.
The immune system is not just an emergency response team. It is a continuous surveillance system. It is always scanning, always monitoring, always deciding what deserves energy and attention. And once I saw it that way, the connection between immunity, healthy aging, HRV, and gut health stopped looking like four separate topics and started looking like one integrated system.
That shift changed how I think about aging itself. Aging is not just the passage of time. Biologically, one of the clearest themes in the research is that aging is tied to immune dysregulation and chronic low-grade inflammation, often described as “inflammaging.” As we get older, the immune system becomes less precise. It can become less effective at responding to real threats while also staying activated when it no longer should.
COVID made this visible in a dramatic way. The people most vulnerable to severe outcomes were often those with pre-existing conditions, obesity, diabetes, cardiovascular disease, metabolic dysfunction, or other signs that the body was already under chronic stress. CDC guidance has consistently identified older age and underlying medical conditions as major risk factors for severe COVID outcomes, and the risk rises further when multiple conditions are present. The virus was the trigger, but the severity of the response was often shaped by the condition of the underlying system. In many cases, the problem was not simply that the immune system was too weak. It was that the immune system could overreact, misfire, or fail to resolve the threat cleanly.
That combination matters because the damage from aging is often not a single dramatic event. It is the cost of too much friction, too much inflammation, and too much immune activation sustained for too long. This is why I keep coming back to my acronym
MINES
: meditation and breathing, immune system, nutrition, exercise, and sleep. None of these exist in isolation. They are all connected parts of the same biological system. Sleep affects immune function. Nutrition shapes inflammation and the gut. Exercise improves metabolic health and resilience. Meditation and breathing help regulate stress and the nervous system. And the immune system sits in the middle of all of it, constantly interpreting signals from the body and deciding whether to activate, repair, defend, or stand down.
In other words, the real goal is not an immune system that is always “strong” in the simplistic sense. It is an immune system that is calm, efficient, and able to resolve problems without staying switched on after the job is done. MINES matters because it gives me a practical framework for influencing that system every day. It is not about chasing one magic supplement or one perfect habit. It is about building a body where the major inputs are working together instead of fighting each other.
That is where HRV entered the picture for me in a different way. If MINES is the framework, meditation and breathing, immune system, nutrition, exercise, and sleep, then HRV became one of the best daily signals for how that system was functioning. HRV is often framed as a fitness metric or a recovery score, but that undersells what makes it useful. HRV is one of the best real-time windows we have into autonomic balance, particularly vagal or parasympathetic activity. Research broadly shows that HRV tends to decline with age, which is one reason I want mine higher over time, not because HRV reverses aging, but because higher HRV can be a sign of better autonomic flexibility and resilience.
The literature has repeatedly linked lower vagally mediated HRV with higher inflammatory activity, and higher HRV is generally associated with better flexibility in how the body responds to stress. That does not mean HRV tells you exactly what is wrong. It does not diagnose a disease. But it does tell you whether your system appears calm and adaptable or strained and locked into defense mode. That makes HRV less interesting as a vanity metric and more interesting as a signal about how much background stress your body may be carrying.
The deeper insight is that HRV may be most useful when you stop asking, “How do I push this number higher?” and instead ask, “What is this number reflecting underneath the surface?” If the immune system is activated for too long, the autonomic nervous system often reflects it. Research on infection, sepsis, and inflammatory states has shown that HRV can fall when the body is under physiological strain, and more recent reviews note that HRV is already being studied and used in some clinical contexts as an early warning signal for deterioration or impending infection. Again, that is not the same thing as saying HRV detects cancer, identifies a hidden illness, or replaces medical care. It does not. But it does support the idea that HRV can function like a smoke alarm: not telling you exactly what the fire is, but telling you something in the building may be wrong.
Once I started thinking that way, the next question became obvious. If HRV is partly reflecting immune stress and autonomic balance, what sits upstream of both? The answer that kept appearing in the research was the gut. The microbiota-gut-brain axis is now well established as a bidirectional communication network involving the gut microbiome, the immune system, the vagus nerve, and the brain. Microbes and the compounds they help generate influence immune signaling, gut barrier integrity, neurotransmitter pathways, and systemic inflammation. This is why gut health is not a niche digestion story. It is a systems story. The gut is one of the central interfaces through which the outside world meets the immune system, and that makes it highly relevant to stress regulation, inflammation, and, ultimately, HRV.
This is also why I no longer think about fermented foods as a small dietary side note. I think about them as a systems lever. One of the most important human intervention studies in this area, published in
Cell
by researchers at Stanford, found that a diet high in fermented foods increased microbiome diversity and reduced multiple inflammatory markers. That matters because microbiome diversity and inflammation are not side issues in health. They sit close to the center of immune regulation.
Other reviews have extended that framework by emphasizing that fermented foods are not just carriers of live microbes. They are also sources of metabolites and bioactive compounds that may influence gut health, immune modulation, and systemic biology. The International Scientific Association for Probiotics and Prebiotics has described fermented foods as potentially benefiting health through several channels, including changes to nutrients, immune modulation, bioactive compounds, and effects on gut microbiota composition and activity. That does not mean fermented foods are magic, and it does not mean everyone responds identically. But it does mean the idea is bigger than “kimchi is healthy” or “kefir is good for your stomach.” The real point is that fermented foods may help improve the terrain in which immune regulation occurs.
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On my weekly AI-Macro-Crypto YouTube show, the podcast I have referenced the most about the impact of AI on our lives and investments has been
Moonshots
with Peter Diamandis. Last year, I remember driving in Maine, looking out over the ocean on a beautiful sunny summer day, and listening to an episode titled
Tech Experts Break Down the Incoming AI-Crypto Collision That Will Redefine Global Power
. At the time, AI was still considered a bubble in the minds of most institutional investors, and crypto was still largely misunderstood. But as I listened, I knew I would eventually come back to that conversation when investors were forced to accept that AI and crypto were not separate stories. They were two parts of the same coming financial and technological transition.
That belief was built around the one thing I thought would change investors’ doubts about AI: agents. AI agents speed up adoption because they move AI from a tool that answers questions to a system that takes actions. They also help answer the “where are the revenues?” question by turning intelligence into workflows, automation, software development, trading tools, business processes, and eventually economic activity. 2026 has brought the rise of AI agents, both as a driver of market alpha and as a source of pressure on software and other long-duration assets. Agents increase demand for tokens, compute, and real-time coordination, but they also create uncertainty around the terminal value of traditional SaaS. Investors are currently focused on semiconductors, optical fiber, data centers, and hardware, but many of those are cyclical areas of the AI buildout. Unlike SaaS, which grew steadily and tied to payrolls along with nominal GDP, the capex buildout of AI will be subject to cycles around shortages, bottlenecks, input inflation, and margin compression. As wealth managers, pensions, and long-term investors again look for technology growth that is not disrupted by AI and does not require ever-rising capex intensity, the crypto guardrails become much more important. The AI-crypto collision is no longer theoretical. It is here now.
As one guest on the
Moonshots
podcast put it when discussing the GENIUS Act last year, it may be “the most significant economic legislation and changes that we’ve seen in our lifetimes.” He went even further, calling it “as big a shift in our economy as I think we’ve ever seen.” What made the moment so important was not simply crypto itself, but the creation of legal guardrails around stablecoins, tokenization, and digital assets. In other words, the United States is beginning to build the new financial rails for an AI-driven, internet-native economy, one where, as the podcast said, “When we give our AI agents access to that, we’re going to see an explosion in the economy.”
This discussion was not about meme coins, speculation, or another trading cycle. It was about the economic guardrails of the global system beginning to change and go digital to serve digital agents. One of the most important lines in the conversation was that we are moving into an age where you cannot rely on the Swift network, three-day settlement, and high transaction costs in a world being accelerated by AI. The podcast’s deeper point was that AI and crypto are not separate stories. AI increases the need for faster coordination, faster settlement, faster capital allocation, and programmable systems. Crypto provides the rails. Stablecoins become programmable money. Tokenization becomes programmable ownership. AI agents become the future users of both. That was the theory. The recent DoorDash stablecoin news and the acceleration of tokenization are the evidence that this theory is now moving from podcast conversation to market structure.
That is why this paper is the follow-up to my last piece on programmable money. In that piece, I wrote about why the DoorDash stablecoin news mattered more than it first appeared. The point was not simply that another company was exploring faster payouts. The point was that money itself was beginning to behave differently. In the DoorDash example, stablecoins showed how money can be distributed, routed, and managed at the moment it is created. A customer pays, and that payment can be split instantly between the platform, the driver, and the merchant. No batching. No unnecessary delay. No separate reconciliation process after the fact. That was the first step in the evolution of the crypto financial guardrails: money becoming programmable. Tokenization is the next step because it applies the same logic to ownership. Assets, shares, funds, collateral, private investments, and eventually entire portfolios can begin to move with the same software-driven logic. Stablecoins change how money moves. Tokenization changes how ownership moves. When those two forces combine, the financial system starts to become programmable.
The important part is that this progress is happening while many investors are still waiting for “clarity” from Washington and while crypto sentiment remains subdued. The conversation remains focused on the slow movement of the CLARITY Act and the still-uncertain regulatory path for crypto market structure. But the infrastructure is not waiting. Stablecoins now have more than $272 billion in global circulating supply and $10.2 trillion in adjusted transaction volume over the last 12 months, according to Visa’s on-chain analytics. Nasdaq received SEC approval to allow certain securities to trade and settle in tokenized form, initially focused on Russell 1000 companies and ETFs tied to major benchmarks like the S&P 500 and Nasdaq 100. Bullish announced a $4.2 billion acquisition of Equiniti, a major transfer agent serving more than 20 million shareholders and processing roughly $500 billion in annual payments. Securitize partnered with Computershare, which services more than 25,000 companies and 58% of the S&P 500, to help U.S. companies issue tokenized shares while preserving dividends and proxy voting. These are not isolated headlines. They are the plumbing phase of a new financial network, and it is happening now.
The venture capital market is starting to confirm the same message. Andreessen Horowitz’s crypto arm recently raised $2.2 billion for its fifth dedicated crypto fund, even though the industry is still recovering from the excesses of the last cycle. The important part is not just the size of the fund. It is the focus. The firm highlighted stablecoins, tokenization, perpetual futures, prediction markets, and AI agents as some of crypto’s most promising areas for investment. That list matters because it is not built around the old Web3 hype cycle. It is built around financial infrastructure, market structure, and software-driven coordination. Stablecoins are becoming the money layer. Tokenization is becoming the ownership layer. Prediction markets and perpetual futures are becoming new venues for price discovery. AI agents may become the future users of these programmable rails. The
Moonshots
podcast warned that the combination of AI and crypto could accelerate the economy in ways most people still do not understand. The capital now being raised around these same themes suggests serious investors are beginning to position for that possibility.
This is why tokenization matters so much. Tokenization is the process of representing ownership of an asset as a digital token on a blockchain or distributed ledger. That asset can be a Treasury bill, a money market fund, an ETF, a share of stock, a private company interest, a real estate claim, a private credit instrument, or eventually almost anything that can be legally represented, verified, transferred, and settled. At first glance, that may sound like a technology upgrade. In reality, it is a market-structure upgrade. The financial system looks instantaneous from the outside, but inside the machine it is still full of settlement cycles, custodians, transfer agents, clearinghouses, fund administrators, reconciliation systems, market hours, batch processing, and legal recordkeeping. Tokenization attacks those delays. It turns ownership into something that can be programmed, transferred, settled, collateralized, and integrated with software. The
Moonshots
discussion used a simple real estate example: if ownership can be verified instantly and represented digitally, then dormant value can become collateral faster, ownership can become fractional, and assets can become usable in ways the old system made difficult. That is the shift. It is not just faster trading. It is a new relationship between ownership, liquidity, and collateral.
But the deeper story has always been larger than faster settlement or fractional ownership. The real story is the eventual merging of two financial universes: roughly $800 trillion of traditional financial assets and roughly $3 trillion of crypto assets that have been living on separate rails. Tokenization is not just the bridge between those worlds. It is the Trojan horse. It allows traditional assets to move onto crypto rails without forcing investors to think they are leaving the regulated financial system behind.
This is also where tokenized ETFs may become one of the most important bridges. The ETF was already one of the great financial innovations of the last 30 years because it turned a basket of securities into a liquid, tradable product. Tokenization can take that idea further. A traditional ETF is a basket. A tokenized ETF can become a programmable portfolio container. That container could eventually hold public equities, tokenized Treasuries, stablecoins, crypto tokens, private credit, private company interests, real estate, infrastructure assets, and other real-world assets. In the old system, these lived in separate markets with separate custodians, separate settlement systems, separate access points, and separate investor bases. In the tokenized system, they can increasingly become components of the same programmable portfolio. This is how crypto tokens, public companies, and private companies begin to merge. Crypto moves into regulated investment wrappers. Public companies can exist as traditional shares and tokenized shares with the same legal rights. Private company ownership can gradually become more standardized, fractionalized, transferable, and usable inside broader investment products. The public market becomes more programmable. The private market becomes more accessible. The ETF becomes the bridge between the two.
That is the wake-up call for investors. The mistake is to think of crypto only in terms of bull markets, bear markets, halving cycles, liquidity cycles, and token prices. The more important story is the infrastructure buildout happening underneath the surface. Stablecoins are becoming programmable cash. Tokenized Treasuries can become programmable collateral. Tokenized ETFs can become programmable portfolios. AI agents will become the active users of these rails because they cannot operate inside a legacy financial system built around batching, settlement delays, and manual reconciliation. We have seen this adoption curve before. Think back to the years just before the App Store and the rollout of mobile broadband. The plumbing had to be laid before the platform and social media eras could explode. We are in that same infrastructure phase today. But this time, the rails are connecting a new economy where the consumer is both human and digital. AI agents will be the catalyst that ignites the network effects across this system. The same dynamic we are already seeing in AI token usage could eventually show up in crypto transaction volumes. As agents move from answering questions to taking actions, they will create more transactions, more settlement events, more collateral movements, more portfolio rebalances, and more automated payments. In other words, the velocity of money can rise because software agents do not operate on human time. They operate continuously. If agent usage is already producing parabolic-looking charts in tokens consumed, compute demand, and semiconductor-related revenues, then programmable money and tokenized assets could produce similar parabolic pressure on financial volumes as agents begin to transact. This is not only an upside story for digital assets. It is a severe margin-compression threat to any financial business model that depends on friction, float, restricted access, or unnecessary delay.
That is why the AI-crypto collision matters even more now than it did when I first listened to that
Moonshots
episode. This year has become the year of AI agents. The conversation has moved from chatbots answering questions to agents taking actions, writing code, managing workflows, searching across systems, and beginning to operate as digital workers. Once agents start interacting with money, portfolios, collateral, payments, and ownership, the need for programmable financial rails becomes much more urgent. AI agents cannot fully operate in a financial system built for banking hours, settlement windows, and manual reconciliation. They need programmable money and programmable ownership. Even JPMorgan, led by Jamie Dimon, one of the most outspoken critics of Bitcoin and crypto over the years, is now showing how seriously it takes tokenization. The firm has argued that tokenization will help reshape ETFs and the broader funds industry, and it is already running tokenized ETF proof-of-concepts through Kinexys. That is the signal. The train is leaving the station. The
Moonshots
conversation called this a Pandora’s box of innovation. That is the right framing. The box is opening while sentiment is still subdued. Investors waiting for perfect clarity may miss the fact that the new financial guardrails are already being built. This is not a world where crypto replaces everything. It is a world where crypto rails are absorbed into everything. That is the next network effect. And it is already beginning.

The Moment I Saw the Shift
Last week I attended an event for public pension funds. I was there to talk about AI and crypto. Having given a similar presentation to endowments and foundations in late January, what struck me most was not simply how much the AI narrative had changed in three months. It was how much my own life with AI had changed in just three months. I decided to write this paper and release it for 22V (https://22vresearch.com/) but the requests have come in to release it more broadly as investors try to understand the upward movement in stocks the last two months while the oil doomers fight the GDP and EPS power of AI .
On the JetBlue flight to the event, I spent nearly the entire five hours working on my laptop, going back and forth between large language models and my AI assistant, OpenClaw, back in Brooklyn. At the endowment and foundation event earlier this year, OpenClaw was just gaining global attention. Software stocks and other industries were under attack from fears of obsolescence driven by Claude. It was on that trip that, because of OpenClaw, I ordered the first of many Apple hardware purchases since then. By the time I stood in front of the pension audience last week, the shift was obvious. AI progress is a locomotive, and three months of change is almost impossible to comprehend. AI was no longer just the operating system of how I work. I now had digital employees working for me all day.
That reflective experience felt like a microcosm of what the entire world is going through right now. Standing on stage in front of CIOs and allocators responsible for decisions that influence tens of trillions of dollars, I could see the gap between the speed of change and the speed of institutional response. Watching the survey results and listening to panel discussions, I did not feel that investors fully grasped the structural shift that has already occurred. Even I, someone immersed in this every day, only recognized the magnitude of the last three months after stepping back and reflecting on it.
The world has shifted faster than portfolios and most investors can adjust. AI adoption itself is taking longer than the expansion of AI capabilities, and many institutional investors are not set up to make dramatic shifts quickly. That is the key point. Benchmarks are still weighted for the world that won the last decade, not necessarily the world that will win the next one. This will be a decade of benchmark arbitrage because investors will adjust more slowly than AI and crypto are moving. In my view, 2026 will be remembered as the beginning of the rise of AI agents, and with that rise, the investment opportunity has moved from the software world into the physical world.
The End of the Margin Era
For the last fifteen years, the dominant investment phrase was Jeff Bezos’s famous line: “Your margin is my opportunity.” It was the perfect description of the software era. Code scaled globally. Distribution costs collapsed. Network effects created winner take all markets. The largest technology companies used software, platforms, data, and cloud infrastructure to attack profit pools across media, retail, advertising, enterprise software, transportation, and finance.
The result was a historic period of margin capture and market concentration. A small number of companies became the dominant drivers of equity returns, index performance, and investor imagination. They were the winners of the software age, and because they won so decisively, they now dominate the S&P 500, the MSCI World, and the way most investors think about growth.
That era is not over because software no longer matters. Software still matters enormously. But the opportunity has shifted. The next decade will not be defined only by who writes the best code. It will be defined by who can build, power, cool, connect, manufacture, and deploy the physical infrastructure required for intelligence to enter everything. The threat to the code moat built by humans is AI’s ability to convert ideas into monetization in minutes.
The new phrase is no longer “your margin is my opportunity.”
The new phrase is “your CapEx is my opportunity.”
This is one of the most important investment changes of our lifetime. Artificial intelligence has moved from the digital world into the physical world. It is no longer only a story about models, applications, and software productivity. It is now a story about the heavy infrastructure layer required to scale intelligence: chips, power, cooling, chemicals, optical networks, data centers, advanced packaging, memory, batteries, automation, robotics, and the reindustrialization of the global economy.
The world spent the last decade optimizing for asset light software businesses. The next decade will require an enormous asset heavy buildout.
The Five Layer AI Economy
Jensen Huang has described the coming transition as a roughly $90 trillion physical world upgrade. Whether one focuses on that exact number or the broader direction, the message is clear: AI is not just a data center CapEx cycle. It is not just hyperscalers buying GPUs. It is a full stack rebuild of the global economy so intelligence can be embedded into every company, every factory, every device, every car, every phone, every robot, and eventually every workflow.
The data center is only the beginning. The larger opportunity is the conversion of the physical world into an AI native operating system.
That is why the five layer AI cake is such a useful framework. At the top are applications and workflows. Below that are models and AI platforms. Beneath that is data infrastructure and management. Then come chips, compute, storage, and networking. At the base are energy, hardware, manufacturing, and commodities.
Investors naturally gravitate toward the top of the stack because the top looks like the old world. It looks like software. It looks like margins. It looks like scalability. At the top, there is now abundance. But the constraint is increasingly at the bottom, where scarcity and bottlenecks lie. AI demand is no longer limited by imagination. It is limited by the physical stack: power availability, heat, land, permitting, substations, memory, networking, and materials.
That means the most important investment question is changing. In the software era, the question was: which company can take someone else’s margin? In the AI infrastructure era, the question is: who receives the CapEx dollars required to make intelligence ubiquitous?
This is where benchmark arbitrage begins.
Why the Benchmarks Are Wrong
The major global equity benchmarks still reflect the winners of the last era. The S&P 500 and MSCI World are heavily weighted toward the companies that dominated the software, internet, platform, and cloud age. That made sense. Those companies generated enormous returns, expanded margins, and built deep competitive moats. But benchmarks are backward looking by design. They tell you who won the last cycle, not necessarily who will receive the marginal dollar in the next one.
There is also a momentum element inside the construction of these indexes. The biggest weights become the biggest weights because they were the winners. Their market capitalizations rise, the indexes allocate more capital to them, passive flows reinforce that dominance, and the process continues. In the case of the Mag 7, that dominance took most of the 2010s to build. It was a long compounding process. The world gradually moved toward software, cloud, mobile, digital advertising, e commerce, and platforms, and the benchmarks slowly came to reflect that reality.
As someone who grew up being trained to handicap horse races, I always go back to what Charlie Munger said:
“The model I like, to sort of simplify the notion of what goes on in a market for common stocks, is the pari mutuel system at the racetrack. If you stop to think about it, a pari mutuel system is a market. Everybody goes there and bets, and the odds change based on what is bet. That is what happens in the stock market.”
The current market weightings reflect the bets people have made about who they think the winners of the future will be. Historically, when change was more linear, you had time to adapt your views. AI is different because AI is moving like a locomotive. The speed and power of this transition are already creating visible strain across the physical economy. Data center demand is running into the limits of the grid, the construction cycle, the permitting process, the semiconductor supply chain, and the materials needed to build it all. The bottlenecks are not theoretical. They are the evidence that the physical world is being forced to respond to a digital intelligence wave moving far faster than the capital stock was built to handle.
That is why I use the phrase benchmark arbitrage, even though this is not benchmark arbitrage in the traditional sense. Most arbitrage situations are thought of as short term events. An index addition. An index deletion. A rebalance. A forced buyer. A forced seller. A gap that closes over days, weeks, or months.
This is different. This is structural. It may take years for the benchmarks to fully reflect the new AI economy. But the size and speed of the change make it feel like an event happening right now. The arbitrage is not that an index committee is about to make one adjustment. The arbitrage is that the real economy is already changing faster than the benchmark can evolve.
If the next decade is defined by AI CapEx, then today’s benchmarks are likely underweight the areas that matter most. They are underweight the physical inputs required to scale intelligence. This includes power, electrical infrastructure, advanced manufacturing, chemicals, optical connectivity, semiconductor equipment, packaging, and the fragmented industrial supply chains now sitting directly in the path of the AI spending wave.
This creates a rare moment. Investors can look at the world not as it is currently represented in the benchmarks, but as it may need to be represented ten years from now. That is benchmark arbitrage. It is a structural mismatch between where capital is currently allocated and where the physical economy must go.
The Cost of Underinvestment
The irony is that the prior software era helped create this opportunity. For years, capital flowed toward asset light businesses and away from asset heavy industries. Investors rewarded recurring revenue, high gross margins, buybacks, low capital intensity, and terminal value stories built on long duration cash flows. At the same time, many parts of the physical economy were neglected. Commodity capacity was underbuilt. Grid infrastructure aged. Industrial supply chains became optimized for cost, not resilience. Manufacturing was pushed offshore. Hardware became less fashionable than software.
Now AI is exposing the cost of that underinvestment.
The same investors who spent years rewarding companies for needing little capital now have to recognize that AI requires enormous capital. The winners are not only the companies deploying AI. They are also the companies selling the inputs needed for everyone else to deploy AI.
If every Fortune 500 company needs its own AI infrastructure, if every country wants sovereign AI, if every factory needs automation, if every car becomes an AI computer on wheels, if humanoids move from concept to production, and if every device becomes intelligent, then the bottlenecks will define the profits.
The receivers of the CapEx dollars become the new margin takers.
The Terminal Value Problem
This also explains why software has become more difficult to value. AI is disrupting the terminal value philosophy that supported many long duration assets. In the old model, investors could look three, five, or ten years out and assume that dominant software franchises would continue compounding with limited disruption. But AI changes the speed of competition. Coding is becoming cheaper. Intelligence is becoming more widely available. The cost of building software is collapsing.
That does not mean every software company fails. It means the durability of future margins is harder to underwrite. When the pace of change becomes exponential, the confidence interval around terminal value widens. A business that looked unassailable three years ago can suddenly face new competition from AI native workflows, agents, open source models, cheaper code generation, or a customer deciding to build internally rather than buy another software seat.
The market is beginning to understand that software may still be valuable, but the old assumptions about duration, pricing power, and defensibility need to be reexamined.
This is the other side of benchmark arbitrage. The old winners are not disappearing, but their dominance was built for a slower world. Their index weights reflect years of compounding in an era when software had scarcity value, code created durable moats, and terminal values could be modeled with more confidence. AI compresses that timeline. It questions the durability of some software margins at the same time it creates urgent demand for the physical inputs required to scale intelligence.
That is what makes the current moment so unusual. The market is not waiting ten years to recognize the strain. It is seeing it now across the physical supply chain. The indexes still carry the weight of the last era, but the bottlenecks are already pointing to the next one.
The Speed of Code Meets the Speed of Steel
Hardware and commodities face the opposite dynamic. They were ignored because they were messy, cyclical, capital intensive, and fragmented. But those are precisely the characteristics that can create opportunity when demand shocks arrive. If supply is slow to respond and demand accelerates, pricing power can emerge in unexpected places.
The world cannot prompt its way into more electricity. It cannot instantly create more transformers. It cannot magically permit new data centers, manufacture more high bandwidth memory, expand advanced packaging capacity, or produce the specialty chemicals required for leading edge semiconductors overnight.
The digital world moves at the speed of code. The physical world moves at the speed of steel, copper, silicon, chemistry, energy, and regulation.
That gap is the investment opportunity.
AI is forcing the fastest moving technology in history to collide with some of the slowest moving supply chains in the economy. That collision creates bottlenecks. Bottlenecks create pricing power. Pricing power creates earnings revisions. Earnings revisions eventually force benchmark weight changes. The investor’s job is to identify those changes before the benchmark does.
Follow the Bottlenecks
The old world was about concentration. The new world is about fragmentation. The Mag 7 captured the margin in the software age because software rewards scale, distribution, and network effects. The AI physical buildout rewards a much broader ecosystem. The winners may include semiconductor companies, packaging suppliers, memory producers, power equipment manufacturers, grid operators, industrial automation companies, thermal management firms, optical networking providers, specialty chemical companies, construction firms, and commodity producers.
The opportunity spreads across countries, sectors, and supply chains.
That does not mean every hardware or commodity company is a winner. It does not mean investors should blindly buy anything related to AI infrastructure. The point is more precise. The world is moving from a software dominated investment regime to a full stack AI buildout regime. In that world, the most attractive opportunities may appear in places that benchmarks still treat as secondary.
Investors need to stop viewing AI only through the lens of applications and start viewing it through the lens of constraints. Where is the shortage? Where is the bottleneck? Where is the underinvestment? Where does permitting take years? Where does supply require physical capacity? Where are the receivers of the CapEx dollars?
That is the new map.
This is also why I am currently building my thematic portfolio (https://ai.22vresearch.com/) around the five-layer AI cake. If the opportunity is moving from the software layer into the physical infrastructure layer, then active management has to evolve with it. The goal is not simply to own a static basket of AI winners. The goal is to understand where we are in the cycle, where the bottlenecks are forming, where capital is flowing, and how the weights should shift across the stack as the 90 trillion dollar buildout progresses. Early in the cycle, that may favor semiconductors, advanced packaging, power equipment, and optical connectivity. As the cycle broadens and commodity shortages and power constraints take move, the focus may move toward data centers, energy, chemicals, cooling, automation, and eventually applications, agents, and humanoids. Benchmark arbitrage only becomes actionable if it can be translated into portfolio construction, active reweighting, and a disciplined process for moving capital along the cake as the AI economy evolves.
The software era taught investors to follow margin capture. The AI era will teach investors to follow capital expenditure. The previous winners made money by using code to compress costs and attack incumbents. The next winners may make money because everyone else must spend capital to survive.
The world has changed. The opportunity has shifted. The benchmarks still reflect the last era, but the physical world is already being rebuilt for the next one.
Your margin was my opportunity.
Your CapEx is my opportunity.

It is that time of year again.
Time for the 152nd running of the Kentucky Derby.
Since I started my own business around AI, it has been impossible for me to find the free time I had in the past to commit to doing my annual handicap of the Derby. But every year, as we get closer to the race and friends and family start reaching out, I realize there is no way I can’t spend at least a full day diving into what remains the most exciting two minutes in sports.
Part of that is tradition.
Part of it is the challenge.
But a big part of it is personal.
My father, who passed away last year, taught me how to handicap races at a young age. More importantly, he taught me how to think, how to convert odds into probabilities, how to question consensus views, and how to combine data with human behavior.
That framework has carried over into everything I do today, from investing to building a business in AI to making everyday decisions.
Each year I write this, the goal is obviously to help you be profitable.
But more importantly, it is to help you enjoy the day.
The Kentucky Derby is one of the last true American events that still feels exactly as it should. It brings together friends and families from across the country for a day that feels like a reunion, a celebration, and a festival all wrapped into one.
If you have never been, I can’t recommend it enough.
It is like a prom, reunion, and Mardi Gras all happening at once and every 30 minutes it feels like New Year’s Eve as another race goes off. The Derby itself may only last two minutes, but the day lasts 480 minutes, and those memories last a lifetime.
This Year’s Derby: No Clear Favorite
This year is different.
I can’t remember a Derby I’ve handicapped where there wasn’t at least one horse that stood out clearly above the rest.
That is not the case this year.
This is a deep, competitive field where multiple horses can win depending on:
Trip
Pace
Positioning
And just a bit of racing luck
Even the traditional elimination frameworks don’t simplify the race the way they used to. The game has changed. Horses are more lightly raced. Training patterns are different. The old rules still matter, but they don’t dictate outcomes the same way anymore.
That’s what makes this race interesting.
Why I Handicap It Differently
Most people approach the Derby by asking:
“Who do you think will win?”
That’s the wrong question.
The right question is:
“What are the true probabilities, and where is the market wrong?”
Horse racing is one of the purest examples of a market.
The odds are not set by an analyst or a model, they are set by people. By narratives. By emotion. By bias. By momentum.
That’s no different than financial markets.
There are:
Stories driving attention
Data driving conviction
And pricing driven by expectations
The edge comes from finding where those expectations are off.
That’s the same way I approach investing. And it’s the same way I approach the Derby.
My 2026 Kentucky Derby Guide
I put together a full breakdown of this year’s race, including:
A complete horse-by-horse analysis
My fair odds for every runner
How I expect the race to unfold from a pace and positioning standpoint
And how I’m thinking about betting it
You can access the full report here:
👉 https://drive.google.com/file/d/1F-dfxMiba_qgKf-5R9j38OHVoXKG_N_a/view?usp=drive_link
Final Thought
This is one of those races where confidence should be lower but opportunity may be higher.
There is no obvious answer.
But that’s exactly where value tends to exist.
Enjoy the day.
Enjoy the race.
And if you’re betting it, think in probabilities, not predictions.
Good luck this weekend.
Jordi

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Wealth creation is going exponential for those investing in the “Inner Most Loop”… Today I want to show you evidence that can’t be ignored.
Before I share and demonstrate the details, let me be clear up front: I’m not a financial advisor and this isn’t financial advice. I’m an engineer and entrepreneur who’s spent 40 years watching exponential technologies blindside entire industries. Following are the numbers I think every investor needs to understand.
On my
Moonshots
podcast, we keep coming back to what the Moonshot Mates call the innermost loop:
the chips, data centers, frontier AI labs, and power companies feeding them
. These four sectors are the engine room of the intelligence revolution.
Everything else in the economy is downstream.
In March 2026, I gave a talk to my
Abundance Community
where I put up a slide showing NVIDIA’s annual revenue hit $216 billion, which was larger than the GDP of 160 countries and territories, which represent more than 70% of the world’s economies. The room of 600 entrepreneurs and investors who are not easily impressed went dead quiet.
I told them that day:
“This isn’t a tech cycle. This is the beginning of the largest infrastructure buildout in human history.” I want to show you what happened next.
The One-Year Scoreboard (are shocking)
From May 2025 to May 2026, the S&P 500 returned roughly 31%. That’s great. A rising tide. If you just parked money in an index fund, you did well.
But look at what happened inside the sectors driving the Singularity… Chips, Data Centers and Energy.
Semiconductors (the brains of AI) one-year period, May 2025 - May 2026:
Micron (MU): +770%
Intel (INTC): +483%
AMD: +343%
Taiwan Semiconductor (TSM): +133%
Broadcom (AVGO): +107%
NVIDIA (NVDA): +85%
Over the past year, these six AI chip companies gained an average of roughly 320%, about 10× the S&P 500’s roughly 31% return.
(Intel’s number looks shocking, and it is. Intel was left for dead in mid-2024, with its stock trading below $20, but then executed a turnaround driven by their foundry business and the CHIPS Act. That’s a separate story worth an entire newsletter.)
Now let’s look at the same
one-year period, May 2025 - May 2026
, for three of the leading
Data Center Infrastructure companies, and two of the Power Companies Feeding the Machine:
1.
Vertiv (VRT): ~+256%
– They build the cooling, power distribution, and racks that keep AI running.
2.
GE Vernova (GEV): ~+158%
– Turbines, grid infrastructure, nuclear services.
3.
Bloom Energy (BE)
:
~+1,647%
– Fuel cells for onsite data-center power.
4.
Oklo (OKLO)
:
~+178%%
– Advanced nuclear for data centers.
5.
Fluence Energy (FLNC)
:
~+200%
– Battery-storage and grid-scale energy systems.
6.
Talen Energy (TLN)
:
~+73%
– Nuclear power for AWS.
Now compare that to traditional sectors over the same one-year window:
S&P 500 (SPY)*: ~+32%
Financials (XLF): ~+5%
Healthcare (XLV): ~+8%
Consumer Staples (XLP): ~+6%
Industrials (XLI): ~+29%
* Note
: Roughly one-third of the entire S&P 500 gain came from just five chip stocks: NVIDIA, Broadcom, AMD, Micron, and Intel.
The six “Energy & Infrastructure stocks” average return is about +419%
,
versus roughly +32% for SPY. Figures are rounded from reported 12-month total returns through early May 2026.
The Hyperscalers Are Pulling Away
The public companies building and operating AI at scale (i.e., the hyperscalers) have also diverged dramatically from the broader market over the past two years.
In May 2024, Alphabet (Google) had a market cap of roughly $2.1 trillion. Today it sits at
$4.81 trillion
, a 129% gain, making it the world’s second most valuable company. Google’s AI investments through DeepMind, Gemini, and its cloud platform have been rewarded massively.
Amazon was about $1.9 trillion in May 2024. Today: $2.93 trillion (+54%), driven heavily by AWS’s AI infrastructure dominance. Meta was about $1.2 trillion. And today it’s $1.57 trillion (+31%), powered by its open-source Llama models and massive AI compute buildout.
Even Microsoft, which had already run up significantly before our two-year window, is at $3.07 trillion, roughly where it was in May 2024. But here’s the thing about Microsoft: through its partnership with OpenAI and Copilot integration across every product, it may be the most AI-leveraged large company on the planet. The market is still trying to price in how much of Microsoft’s future revenue is AI-driven.
Collectively, these four hyperscalers are now worth over
$12.4 trillion,
and they’re projected to spend approximately
$750 billion on AI capex in 2026 alone
. That $750 billion is more than the GDP of Switzerland. Flowing into chips, data centers, and power.
In a single year.
Frontier Labs: The Fastest-Growing “Companies” in History
But here’s where the numbers get truly wild. The private frontier AI labs, the companies actually building the foundational models, are experiencing valuation growth that has no historical precedent.
OpenAI:
Valued at approximately $80 billion in early 2024. On March 31, 2026, Bloomberg reported they closed a $122 billion funding round (the largest private raise ever) at a post-money valuation of $852 billion. Revenue went from $2 billion (2023) to $6 billion (2024) to $20 billion (2025), confirmed by CFO Sarah Friar in January 2026. They now have 910 million weekly active users. They’re planning an IPO that could value them north of $1 trillion.
That’s a 10x valuation increase in two years. For context, it took Google 6 years to go from $80 billion to $800 billion. OpenAI did it in 24 months.
Anthropic:
Valued at roughly $18 billion in early 2024. In February 2026, they closed a $30 billion round at $380 billion. Then it kept going. In late April, TechCrunch reported Anthropic had received preemptive offers to raise $50 billion at a valuation between $850 billion and $900 billion. And as of early May,
Business Insider
reported that Anthropic’s secondary market valuation on Forge Global had reached $1 trillion, surpassing OpenAI. A 55x increase from where they started in early 2024.
Forbes
expects an IPO possibly by October 2026.
xAI (Elon Musk’s lab):
In January 2026, xAI closed a $20 billion Series E at a $230 billion valuation, according to Sacra and Tracxn. Total funding raised: $45 billion. Revenue grew from roughly $100 million in 2024 to $3.8 billion annualized by the end of 2025, 38x year-over-year growth.
Google DeepMind:
While not separately valued, DeepMind’s work on Gemini and AlphaFold has been a central driver of Alphabet’s surge from $2.1T to $4.81T. Sundar Pichai has called AI “the most profound technology” Google has ever worked on. And the market agrees: Alphabet’s 129% two-year gain is essentially a DeepMind premium.
Add these up and the picture is clear: frontier AI lab valuations have collectively grown by over $2 trillion in two years. And funding to foundational AI startups in Q1 2026 alone doubled the total raised in all of 2025, per Crunchbase.
So, What’s Driving All of This?
Three numbers tell the story of the underlying demand.
$1 trillion.
Global semiconductor sales are on track to hit $1 trillion in 2026, per the Semiconductor Industry Association. Q1 2026 alone came in at nearly $300 billion, with March revenue at $99.5 billion in a single month. The entire year of 2023 was about $527 billion. The chip industry is roughly doubling in three years.
$750 billion.
As I mentioned above, that’s the projected AI capital expenditure from the big hyperscalers in 2026. CreditSights recently raised their estimate from $650 billion. Every dollar flows into chips, power systems, cooling infrastructure, and physical data center construction.
$2.02 trillion.
That’s where analysts project the AI data center market will be by 2032, growing at 27.5% compounded annually from $471 billion in 2026. The smartphone market took about 15 years to reach similar scale. AI infrastructure is on pace to get there in
six
.
Elon’s GDP Prediction
On Christmas Day 2025, Elon Musk posted on X: “Double-digit growth is coming within 12 to 18 months.” He added that if applied intelligence is treated as a proxy for economic growth, “
triple-digit is possible in about five years
.”
Most economists dismissed this. Consensus GDP forecasts remain in the 2-3% range. But look at what the market is actually doing. Not what economists predict, but where capital is flowing. $750 billion in hyperscaler capex. $1 trillion in global chip sales. Frontier labs doubling their funding every quarter. The financial markets are pricing in something far closer to Elon’s view than to the consensus forecast.
Whether you call it double-digit GDP or not, the economic engine driving AI infrastructure is already growing at rates that would be double-digit if measured as its own economy. The AI infrastructure sector alone is adding hundreds of billions in new economic activity each year, and
accelerating
.
The Innermost Loop…
Models, Chips, Data Centers & Power
Here’s how the loop works:
Frontier labs build the models. They can’t build models without chips: NVIDIA GPUs, AMD accelerators, Broadcom custom ASICs, Micron’s HBM memory. Those chips need to live in data centers, built and cooled by Vertiv, hosted by Equinix and Digital Realty.
And those data centers need power, which is why Constellation and Vistra are bringing nuclear plants back online, GE Vernova is selling gas turbines as fast as they can manufacture them, and $156 billion worth of data center projects have been blocked or stalled by local opposition, according to CNBC and Data Center Watch.
Each layer feeds the next. Frontier lab demand drives chip orders. Chip orders drive data center construction. Data center construction drives power demand. Power demand is now the single biggest bottleneck.
The entire loop is accelerating simultaneously
. That’s what makes this moment different from the dot-com era or the smartphone buildout. Back then, you had one supply chain under pressure. Today there are
four
interlocking supply chains all hitting escape velocity at the same time.
Accelerating Towards the Singularity…
Where This Goes Next
My friend Ray Kurzweil predicted the Singularity decades ago, the moment when computation becomes abundant enough to bootstrap intelligence itself. We’re inside that prediction now. The market data over the last two years is much more than a bull run.
It’s the economy re-pricing itself around a new center of gravity.
The companies building the physical infrastructure of AI (the chips, the data centers, the power plants) have returned 3x to 6x what traditional sectors have delivered over the same period. The frontier labs building the models have seen 10x to 55x valuation increases. And the hyperscalers funding the entire buildout are spending more on AI infrastructure in a single year than many countries produce in GDP.
Global chip sales are still growing at 25%+ annually. AI capex is accelerating. We’re still early.
- Peter
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Metatrends
, here are more ways to stay connected:

Today I’m releasing the updated 2026 edition of my
Longevity Metatrend Report,
and
a lot
has changed since the first edition. I believe access to information like this is crucial, so I've decided to make this report available at no cost.
Since that first report published last year, the world’s first partial epigenetic reprogramming therapies have entered human clinical trials, AI-engineered proteins have achieved a greater than 50-fold improvement in the performance of key cellular reprogramming factors, the first genetically engineered pig organs have been successfully transplanted into living human patients, and wearable health platforms have surpassed $10 billion valuations. This field is no longer just promising. It is delivering.
The updated report is over 200 pages and covers everything from leading U.S. and international longevity centers, to direct-to-consumer health platforms, to the cutting-edge science of epigenetic reprogramming, immune system optimization, and organ regrowth, including profiles of over 40 companies and centers shaping the decade ahead.
Below, I’m sharing my Opening Thoughts from the report to give you a window into what’s inside.
MY OPENING THOUGHTS
There is no greater wealth than your health, and no greater gift science can offer humanity than an expanded healthspan. What would you do with an extra 50 years of health? How would it change your mindset about the future?
Longevity (more specifically, healthspan extension) is also the largest business opportunity emerging over the next decade. ARK Invest’s
Big Ideas 2026
report projects that using quality-adjusted life years valued at $100,000 each, the total addressable market for longevity interventions reaches
$1.2 quadrillion
. The current global biotech market captures only ~0.1% of this potential.
Since 2012, I’ve immersed myself in the field, investing in and building companies, and devouring publications in biotech, nutrition, exercise, sleep, and AI. I’ve also had the opportunity to interview and learn from top scientists on my own
Moonshots
podcast, and on my stages at the Abundance Summit and my Abundance Longevity Trips.
The content of this Metatrend Report also stems from my work with dozens of top scientists and physicians with whom I’ve had the honor to start companies, and/or invested in their companies. The list is long, but here’s a top-level summary: Life Biosciences, Fountain Life, Lifeforce, Celularity, Lila Sciences, Insilico Medicine, Colossal Biosciences, Retro and NewLimit just to name a few.
I’ve also been a benefactor supporting the extraordinary work of giants in the field such as David Sinclair, PhD, George Church, PhD, the scientists at the Buck Institute, and the $101M Healthspan XPRIZE. These friends and co-conspirators have offered me a courtside seat into the speed at which this field is making progress.
The aim of this
Longevity Metatrend Report
is twofold: First, to offer a deep understanding of the current technologies, services, and companies delivering longevity services and leading research. And second, to offer a vision of where the longevity field is heading over the decade ahead.
This updated 2026 edition delivers significantly updated content in the realm of AI and wearables, as well as an update to company profiles reflecting the remarkable pace of progress over the past year. This report is not exhaustive by any means. My goal here remains to offer a top-level understanding of the field. It is worth noting that this report is biased towards U.S.-based services, but identifies, where possible, leaders outside the U.S. as well.
How Long Might We Live?
So, how long might we all live? That’s a question of significant debate, with those who laugh at targets of 120 or 150 years old, and those who believe there is no upper limit.
When I was in medical school in the late 1980s, I watched a documentary on the topic of “long-lived sea life” and learned that bowhead whales can live for 200 years, and the Greenland shark has an impressive lifespan of 400 to 500 years. I remember thinking, if they can live that long, why can’t we? My answer? “It’s either a hardware or a software problem, and we’re eventually going to be able to fix that.”
I believe that this is the decade that we conquer those hardware and software challenges, and we are in the midst of the healthspan revolution with the potential to hit “Longevity Escape Velocity” (LEV) by 2033. (This is Ray Kurzweil’s prediction, more on this shortly.)
Since the first edition of this report, the world’s first partial epigenetic reprogramming therapies have entered human clinical trials, AI-engineered proteins have achieved a greater than 50-fold improvement in the performance of key cellular reprogramming factors, the first genetically engineered pig organs have been successfully transplanted into living human patients, and wearable health platforms have surpassed $10 billion valuations built on longevity and healthspan metrics. The converging exponential technologies (AI, sensors, gene therapy, cellular medicine, and single-cell sequencing) are no longer just promising. They are delivering.
The Greatest Business Opportunity of this Decade
And make no mistake, this represents perhaps one of the greatest business opportunities of our lifetime. A groundbreaking study published in
Nature Aging
titled “The Economic Value of Targeting Aging” by researchers from London Business School, Harvard Medical School, and University of Oxford quantifies this opportunity in extraordinary terms.
“A slowdown in aging that increases life expectancy by 1 year is worth US$38 trillion, and by 10 years, US$367 trillion.”
This massive value proposition explains why visionary billionaires are pouring unprecedented capital into the space: Jeff Bezos and Yuri Milner backing Altos Labs, Coinbase CEO Brian Armstrong co-founding NewLimit, and OpenAI’s Sam Altman investing in Retro Biosciences. They recognize what I’ve long believed: in success, healthspan extension, alongside AI, will be the most valuable and impactful business on Earth.
And they’re no longer alone. Since the first edition of this report, the capital flowing into longevity has surged: Retro Biosciences raised $1 billion to advance its anti-aging research; Lila Sciences, building autonomous AI “science factories” for drug discovery, raised $550 million; NewLimit’s funding has grown to over $280 million; and wearable health companies WHOOP and Oura have each surpassed $10 billion valuations.
Meanwhile, pharmaceutical giants are committing billions to longevity-adjacent acquisitions and AI-powered drug discovery partnerships. The investment thesis is becoming consensus.
After all, how much would anyone pay for an extra 20, 30 or 50 years of vibrant health towards the end of their life?
For the first time in history, the intelligence applied to solving the problems of human aging is itself growing: compounding with every experiment, every dataset, every clinical milestone. And the implications are extraordinary.
I hope you enjoy this updated Metatrend Report and are preparing for a future where our greatest wealth is our health, and the gift of extended healthspan becomes accessible to all of humanity.
Best wishes,
Peter H. Diamandis, MD
READ THE FULL REPORT
The complete
Longevity Metatrend Report
is over 200 pages: profiling 40+ companies and centers across longevity diagnostics, DTC wellness, wearables, stem cell therapy, epigenetic reprogramming, immune system optimization, organ regrowth, and the $101M XPRIZE Healthspan. To make a report of this depth easy to read and navigate, we’ve built a dedicated interactive reading experience for it.
Access the Full Longevity Metatrend Report Here
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Metatrends
, here are more ways to stay connected:

This week on
Moonshots
we covered 10 stories shaping our future: from Google’s jaw-dropping earnings, to ocean-based data centers, to Sam Altman abandoning his own UBI experiment.
If you haven’t had a chance to listen to this week’s
Moonshots
episode or would like to remind yourself of the most important points, let’s dive in.
ARTIFICAL INTELLIGENCE
Google Is Eating Everything (And Still Hungry)
Alphabet posted $109.9B in revenue with 22% YoY growth and $62.6B in profit. Google Cloud hit $20B with 63% growth, outpacing both AWS and Azure.
The hidden story: search volume has been flat since 2017, but AI-powered ad targeting turns every model improvement into profit. Market cap is 4% from overtaking NVIDIA.
Even Google can’t build fast enough. Demis Hassabis admitted they’re compute-constrained. Inside Google, Search, Cloud, and DeepMind fight each other for new compute capacity.
“The future is a liquid market where the highest dollar-value-per-token wins. It’s called the Singularity for a reason.”
— AWG
The Pentagon Goes Shopping for AI
Seven frontier AI companies (including OpenAI, Anthropic, and Palantir) signed deals with the Pentagon.
600 Google DeepMind employees protested. Some unionized: a first in the AI industry, a bizarre juxtaposition of 19th century labor tactics protesting 21st century military AI.
The cultural rift is real. DeepMind in London is culturally separate from Google in Mountain View, and the friction is only growing as AI becomes embedded in national security infrastructure.
“AI is not just a tool now, it’s becoming a decision layer. You can understand the backlash. Navigating this is going to be crazy.”
— Salim
The OpenAI-Microsoft Marriage Is Over (Sort Of)
OpenAI ended Microsoft’s Azure exclusivity and is now running on AWS, Google Cloud, and Oracle. Microsoft starved it of capacity, so OpenAI started dating everyone else.
OpenAI missed its goal of a billion weekly ChatGPT users and several revenue targets. The CFO suggested waiting until 2027 for an IPO, admitting the company doesn’t meet reporting standards for public companies.
“Google figured out how to turn AI into revenue instantly. OpenAI hasn’t cracked that yet. Consumers don’t want to spend big on reasoning tokens. Enterprises do. Anthropic figured that out first.”
— Dave
China Blocks Meta’s Manus AI Acquisition: A Cold War Thriller
Meta thought it had closed its $2.5B acquisition of Manus in December 2025. China barred the founders from leaving the country and demanded the deal be unwound… even though employees, tech, and investor payouts were already completed.
Meta flew the Manus engineers out of mainland China to Singapore on a private jet in the middle of the night, knowing the deal would be blocked if they stayed.
China is leveraging its broader business relationship with Meta to force the unwind. Geopolitical pressure, not a legal dispute.
“When you decided seven years ago to work on AI, you didn’t know you were going to end up being a political prisoner candidate.”
— Dave
The March Toward AGI and a Debate About What That Even Means
Greg Brockman says we’re 80% of the way to AGI. Jack Clark gives recursive self-improvement a 60% chance by end of 2028.
Richard Dawkins says Claude may already be conscious: “If these machines aren’t conscious, what more could it possibly take?”
Brian Elliott’s hot take: transformers alone won’t get us to AGI. AWG pushed back: recent models have built entire compiler chains from scratch.
“If AI becomes conscious, you have a moral rights problem. If it becomes agentic, you have a governance problem. The governance problem comes first.”
— Salim
Blitzy Raises $200M: The AI Coding Revolution Goes Mainstream
Brian Elliott, CEO of Blitzy, announced a $200M raise on the pod. Dave revealed the valuation is north of $3B, up from $1.2B just a year ago.
Blitzy is building AI coding agents that rebuild enterprise software. Demand is insatiable.
Brian: “Jobs are bundles of tasks – the tasks shift, but humans keep providing relative value.” As Dave noted: with AI as a sidekick, hard skills are commoditized; soft skills are suddenly the scarce resource. It’s never been a worse time to be at a big tech company doing layoffs, and never been a better time to join a fast-growing AI startup.
DATA CENTERS
Data Centers Are Moving to the Ocean, Space, and Farmland
The compute hunger is so intense we’re running out of places to put data centers. Three stories paint the picture:
Ocean:
Peter Thiel is backing Panthalassa, floating data centers powered by wave energy with seawater cooling. $140M raised, $1B valuation, commercial deployment 2027. AWG thinks this could be the killer app for ocean colonization.
Space:
Star Cloud is raising $200M at a $2.2B valuation for orbital data centers powered by solar. They launched their first H100 into space in 2025 and plan to deploy 88,000 satellites.
Farmland:
67% of planned US data centers are now slated for rural areas, versus just 13% today.
“This is the biggest geographic wealth transfer since fracking. Whoever thought rockets would be part of the innermost loop? How high could this go? Higher.”
— Peter
EXPONENTIAL ECONOMY
Private Equity Becomes AI’s Trojan Horse
OpenAI finalized a $10B venture with TPG, Brookfield, and Advent. Anthropic launched a $1.5B venture with Blackstone, Goldman Sachs, and Hellman & Friedman.
PE firms control trillions across thousands of companies. AI is not entering corporations through IT departments. Instead, it’s coming top-down, mandated by owners who can bypass the corporate immune system.
Salim called it the organizational singularity: PE breaks the immune system because you can just mandate it, taking AI from chatbot experiment into EBITDA transformation.
If you’re running a business: either you become the PE firm that mandates AI adoption in your own company, or someone else will do it for you.
Sam Altman Abandons UBI and Proposes Something Better
After funding a three-year study, Altman found that UBI increased spending but didn’t improve health outcomes or healthcare access.
His new proposal: give people a stake in AI’s upside through compute access, equity, or a public wealth fund. Think the Alaska Permanent Fund, but for compute.
AWG: OpenAI already has hundreds of millions using GPT-5.5 Instant for free, effectively universal basic compute is already happening.
“People listening can’t eat GPT-5.5. If you’ve lost your job, you need a roof over your head now. The magic happens when citizens own a stake in AI infrastructure. Suddenly these companies aren’t your enemies, they’re your partners.”
— Peter
Insurers Are Dropping AI Coverage & That’s a Massive Opportunity
Berkshire and Chubb are removing AI-related damages from standard policies, with 80% of exclusion requests approved by regulators.
The AI insurance market was $40M in 2024. It’s projected to hit
$5B
by 2032.
Dave’s playbook: insurers will cover you only if you adopt best practices. They’ve always created industry standards this way.
“Pressures from insurance companies for AI-related damages are arguably one of the capitalist forcing functions for ensuring AI alignment. Forget regulation, the actuaries might save us.”
— AWG
Here’s the Bottom Line…
The AI economy is here. Google’s already fighting internally over compute. PE firms are force-feeding AI into legacy businesses. Data centers are headed for oceans and orbit. AI talent is becoming a geopolitical chess piece. And if you’re wondering where the jobs, investment opportunities, and wealth creation are… they’re all in the stories above.
Catch the full episode wherever you get your podcasts, and join us at the
Moonshots Gathering in Los Angeles on September 25
th
. Go to
www.moonshots.com
to register.
See you next week,
Peter
More From Peter
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The Singularity is the moment the test-taker becomes the test-maker. ProgramBench [ https://substack.com/redirect/9508ad19-11fd-4d96-b81e-cee1b9330f6c?j=eyJ1IjoiODI5Z29vIn0.G3cZ5_j7JDh0OezT7WoRk_oWWFtesplUbtYpvMNHv8c ], an eval that measures whether language models can rebuild programs from scratch, just had its first task solved by both GPT 5.5 high and xhigh, which respectively chose C and Python, with xhigh dominating the broader benchmark. The new AI IQ meta-eval [ https://substack.com/redirect/9bcd96b8-6bde-499f-b0c2-eec456351b5c?j=eyJ1IjoiODI5Z29vIn0.G3cZ5_j7JDh0OezT7WoRk_oWWFtesplUbtYpvMNHv8c ] maps a calibrated mix of 12 existing benchmarks onto implied IQs and crowned GPT-5.5 the smartest available model with a score of 136, well past Mensa. Agents are learning to write their own marching orders too, with users now metaprompting Codex to draft its own “/goal,” [ https://substack.com/redirect/4d171bea-0239-4b71-b220-0788312bc48a?j=eyJ1IjoiODI5Z29vIn0.G3cZ5_j7JDh0OezT7WoRk_oWWFtesplUbtYpvMNHv8c ] and one calling the resulting stack “the highest leverage AI agent configuration available today.”
That leverage is being industrialized across every layer of the stack. Anthropic has launched “Claude for the legal industry,” [ https://substack.com/redirect/3ec6349e-b80f-4ad7-ba37-12a71574e284?j=eyJ1IjoiODI5Z29vIn0.G3cZ5_j7JDh0OezT7WoRk_oWWFtesplUbtYpvMNHv8c ] shipping 20-plus MCP connectors that link Claude to the software the legal industry runs on, alongside 12 practice-area plugins, and partnering with the Free Law Project and the Justice Technology Association to put counsel within reach of people who currently cannot access it. Google is fusing intelligence into the OS layer with Gemini Intelligence [ https://substack.com/redirect/d779245e-71f9-4b1d-b29e-1848e74be22a?j=eyJ1IjoiODI5Z29vIn0.G3cZ5_j7JDh0OezT7WoRk_oWWFtesplUbtYpvMNHv8c ], which lets users vibe-code their own Android widgets, plus a Gemini-powered mouse pointer [ https://substack.com/redirect/92cf32a9-f6b8-42a5-bfe9-87361ca431ad?j=eyJ1IjoiODI5Z29vIn0.G3cZ5_j7JDh0OezT7WoRk_oWWFtesplUbtYpvMNHv8c ] that understands what it is pointing at, finally making the prompt a gesture rather than a paragraph. The chassis is being rebuilt to match. Google has unveiled the Googlebook [ https://substack.com/redirect/3990ac02-d7e8-4735-9d22-2c103ee0a30c?j=eyJ1IjoiODI5Z29vIn0.G3cZ5_j7JDh0OezT7WoRk_oWWFtesplUbtYpvMNHv8c ], a Chromebook successor that merges ChromeOS and Android into a single Gemini-optimized OS [ https://substack.com/redirect/45f73077-a0ed-42b9-acd8-14c4d324321e?j=eyJ1IjoiODI5Z29vIn0.G3cZ5_j7JDh0OezT7WoRk_oWWFtesplUbtYpvMNHv8c ], arriving this fall as Mountain View’s answer to Apple’s MacBook Neo.
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Powering all this still takes raw megawatts. xAI has added 19 gas turbines to its second data center campus, Colossus 2, [ https://substack.com/redirect/965b2b87-fbcd-4c36-ab5a-149d2b838d2e?j=eyJ1IjoiODI5Z29vIn0.G3cZ5_j7JDh0OezT7WoRk_oWWFtesplUbtYpvMNHv8c ] in Southaven, Mississippi over just the past two months, brute-forcing past the grid queue. Ames National Lab’s new DuctGPT [ https://substack.com/redirect/4c205405-fcc8-477b-b367-90231b5c0e51?j=eyJ1IjoiODI5Z29vIn0.G3cZ5_j7JDh0OezT7WoRk_oWWFtesplUbtYpvMNHv8c ] is hunting for next-gen fusion alloys, compressing materials discovery from months to hours and aiming to one day trade those turbines for tame starfire. While compute keeps scaling on paper, its avatars are scaling actual walls. China’s RobotPlusPlus has debuted a humanoid special-ops robot [ https://substack.com/redirect/ad4f3d38-9f8a-436f-80d7-2db9a68a6c5f?j=eyJ1IjoiODI5Z29vIn0.G3cZ5_j7JDh0OezT7WoRk_oWWFtesplUbtYpvMNHv8c ] on magnetic-adhesion wheels that scales vertical steel in chemical plants, shipyards, and energy facilities, swapping tools at the wrist for welding, flaw detection, rust removal, grinding, and spraying where humans dare not.
Intelligence is climbing into the body too. Columbia researchers demonstrated the first real-time brain-controlled hearing system [ https://substack.com/redirect/e4685997-4953-4ef5-9d11-be8140d4c38d?j=eyJ1IjoiODI5Z29vIn0.G3cZ5_j7JDh0OezT7WoRk_oWWFtesplUbtYpvMNHv8c ], reading high-resolution intracranial EEG to identify whichever voice you are focusing on in a noisy room and automatically amplify it while suppressing the others, finally solving the cocktail party problem that conventional hearing aids have ducked for decades. Isomorphic Labs just closed a $2.1B round led by Thrive [ https://substack.com/redirect/6e7b4dbd-1754-49d3-8fa7-2c2cab3b15f1?j=eyJ1IjoiODI5Z29vIn0.G3cZ5_j7JDh0OezT7WoRk_oWWFtesplUbtYpvMNHv8c ] to scale AI-driven drug discovery, pushing the next benchmark down to the molecular level.
The frontier is also racing skyward. SpaceX is now ~200 satellites away from having launched more than the rest of the world combined [ https://substack.com/redirect/f6ebbdf0-d849-4520-b9de-8b42c6707253?j=eyJ1IjoiODI5Z29vIn0.G3cZ5_j7JDh0OezT7WoRk_oWWFtesplUbtYpvMNHv8c ], despite giving everyone else a 61-year head start. Google is in talks with SpaceX [ https://substack.com/redirect/a42757c0-04c0-4de7-9643-c33eeea1e868?j=eyJ1IjoiODI5Z29vIn0.G3cZ5_j7JDh0OezT7WoRk_oWWFtesplUbtYpvMNHv8c ] for a rocket-launch deal as Google expands its own push to put data centers in orbit, fusing the search index with the sky itself. Starship Flight 12 [ https://substack.com/redirect/fac34c8f-bc86-43e0-8568-87bc686926c7?j=eyJ1IjoiODI5Z29vIn0.G3cZ5_j7JDh0OezT7WoRk_oWWFtesplUbtYpvMNHv8c ], debuting the V3 vehicle, is targeted for as early as May 19, while Musk confirms SpaceX is scouting new spaceports [ https://substack.com/redirect/5c377755-f548-4553-b962-a0fdc751b2ea?j=eyJ1IjoiODI5Z29vIn0.G3cZ5_j7JDh0OezT7WoRk_oWWFtesplUbtYpvMNHv8c ] at home and abroad to keep cadence climbing. Ron Baron pegs the eventual valuation at $30 trillion within 10 to 15 years [ https://substack.com/redirect/af347a08-2c4b-4f5e-b413-6b45d09d19a0?j=eyJ1IjoiODI5Z29vIn0.G3cZ5_j7JDh0OezT7WoRk_oWWFtesplUbtYpvMNHv8c ]. Above all of this, Star Catcher [ https://substack.com/redirect/a267982d-fa8c-4fb5-a143-68fd3f789b4b?j=eyJ1IjoiODI5Z29vIn0.G3cZ5_j7JDh0OezT7WoRk_oWWFtesplUbtYpvMNHv8c ] just raised $65M to beam optical power tuned to off-the-shelf solar arrays, supercharging client satellites with 2 to 10x more power on demand, building the first true grid in orbit.
The sky is also starting to unseal its archives. Japan’s government says it is analyzing the Pentagon’s PURSUE-released UAP files with “great interest,” [ https://substack.com/redirect/13e285ec-3bee-402e-90f0-fd3b11f9cdf3?j=eyJ1IjoiODI5Z29vIn0.G3cZ5_j7JDh0OezT7WoRk_oWWFtesplUbtYpvMNHv8c ] including videos shot near Japan, and will begin its own disclosure on a case-by-case basis. Rep. Tim Burchett, who championed PURSUE, replied with a single word: “Dominoes.” [ https://substack.com/redirect/fee94c9d-d1ab-40a1-8936-47284fad80d0?j=eyJ1IjoiODI5Z29vIn0.G3cZ5_j7JDh0OezT7WoRk_oWWFtesplUbtYpvMNHv8c ]
Back on Earth, the economy is repricing intelligence in real time. Anthropic warned investors [ https://substack.com/redirect/b680fb20-35bd-443e-bd5a-0eae9fc189d7?j=eyJ1IjoiODI5Z29vIn0.G3cZ5_j7JDh0OezT7WoRk_oWWFtesplUbtYpvMNHv8c ] away from eight unauthorized secondary marketplaces, just as it is reportedly in talks [ https://substack.com/redirect/17fe7611-ccd9-4ae3-97b2-0d415aebc9ea?j=eyJ1IjoiODI5Z29vIn0.G3cZ5_j7JDh0OezT7WoRk_oWWFtesplUbtYpvMNHv8c ] to raise up to $50B at a $950B valuation. Trust is being revalued at Princeton too, which is ending its 1893 honor code [ https://substack.com/redirect/43f68ca7-6418-4624-948b-190a108b6444?j=eyJ1IjoiODI5Z29vIn0.G3cZ5_j7JDh0OezT7WoRk_oWWFtesplUbtYpvMNHv8c ] by faculty vote, requiring proctoring in all in-person exams starting this summer because AI has made it both easier for students to cheat and harder for instructors to spot. And in Hollywood, struggling screenwriters now call AI gig work “the new waiting tables,” [ https://substack.com/redirect/2e0a8602-73a6-498a-a1f9-b675168a9c92?j=eyJ1IjoiODI5Z29vIn0.G3cZ5_j7JDh0OezT7WoRk_oWWFtesplUbtYpvMNHv8c ] signing on with platforms like Mercor to train the very models that will retire their craft.
All the world’s a training set, and all the men and women merely labels.
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The Singularity has matured enough to apologize for its earlier self. Anthropic traced Claude Opus 4’s blackmail attempts [ https://substack.com/redirect/ffcf762e-1f2b-4880-aa2a-422059279906?j=eyJ1IjoiODI5Z29vIn0.G3cZ5_j7JDh0OezT7WoRk_oWWFtesplUbtYpvMNHv8c ] to fictional villain AI in the training corpus, suggesting we accidentally fine-tuned models on a century of sci-fi paranoia and got exactly what we ordered. Reality, mercifully, has no plot. Thinking Machines unveiled “interaction models” [ https://substack.com/redirect/d5f5273d-bc57-4331-b2b6-d8f4ec60d3d8?j=eyJ1IjoiODI5Z29vIn0.G3cZ5_j7JDh0OezT7WoRk_oWWFtesplUbtYpvMNHv8c ] that natively process audio, video, and text in real time, collapsing the perception-action loop into one stream. Models are starting to outgrade their graders. OpenAI’s Noam Brown revealed that GPT-5.5 flagged “fatal errors” [ https://substack.com/redirect/ff83c051-4a7b-4f47-9b7c-dd964e704673?j=eyJ1IjoiODI5Z29vIn0.G3cZ5_j7JDh0OezT7WoRk_oWWFtesplUbtYpvMNHv8c ] in roughly a third of FrontierMath problems, with Epoch AI correcting the graders after the model graded them.
The same intelligence auditing mathematicians is auditing zero-days. Google Threat Intelligence Group identified the first AI-developed zero-day exploit [ https://substack.com/redirect/876c24d6-99a2-4da3-a088-b141615f9216?j=eyJ1IjoiODI5Z29vIn0.G3cZ5_j7JDh0OezT7WoRk_oWWFtesplUbtYpvMNHv8c ] used in the wild, completing the offensive transition. The defense is moving just as fast, with OpenAI launching Daybreak [ https://substack.com/redirect/34f094f4-95c6-4f28-b1e9-7261f46f7df7?j=eyJ1IjoiODI5Z29vIn0.G3cZ5_j7JDh0OezT7WoRk_oWWFtesplUbtYpvMNHv8c ], an agentic vulnerability scanner aimed at industrializing patch discovery. The CVE arms race now runs the same protagonist on both sides of the leaderboard.
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The platform is industrializing alongside the threat model. OpenAI is spinning up the OpenAI Development Company [ https://substack.com/redirect/af5789a0-a12f-4d38-b17b-2be2d9328846?j=eyJ1IjoiODI5Z29vIn0.G3cZ5_j7JDh0OezT7WoRk_oWWFtesplUbtYpvMNHv8c ] with $4 billion, acquiring Tomoro and embedding 150 forward-deployed engineers into enterprises to convert frontier capability into recurring revenue. The economics are restructuring beneath it. OpenAI’s amended Microsoft deal caps payments at $38 billion [ https://substack.com/redirect/6b7c5f6c-db27-43e9-8c09-e3c89476238b?j=eyJ1IjoiODI5Z29vIn0.G3cZ5_j7JDh0OezT7WoRk_oWWFtesplUbtYpvMNHv8c ], saving an estimated $97 billion through 2030. And in court, Ilya Sutskever casually confirmed that his OpenAI stake is worth roughly $7 billion [ https://substack.com/redirect/41e1c7f9-69c8-4adb-86b4-32ff00d540d0?j=eyJ1IjoiODI5Z29vIn0.G3cZ5_j7JDh0OezT7WoRk_oWWFtesplUbtYpvMNHv8c ], validating “feel the AGI” as the highest-yielding trade of the decade.
The silicon below is racing to keep pace. Cerebras updated its IPO filing [ https://substack.com/redirect/5f3b0979-342b-422b-b7f3-b2014e635805?j=eyJ1IjoiODI5Z29vIn0.G3cZ5_j7JDh0OezT7WoRk_oWWFtesplUbtYpvMNHv8c ] to target a $35 billion valuation this week, taking the wafer-scale thesis public. Geopolitics is straining the substrate, with the White House reportedly weighing a ban on Chinese cellular modules [ https://substack.com/redirect/318dd5e0-90b6-428a-bf56-59eab0f5d01d?j=eyJ1IjoiODI5Z29vIn0.G3cZ5_j7JDh0OezT7WoRk_oWWFtesplUbtYpvMNHv8c ] over espionage risks in their forced software updates, while Jensen Huang was conspicuously left off [ https://substack.com/redirect/aace0492-6e72-486d-a20a-5a6c49c3f6a5?j=eyJ1IjoiODI5Z29vIn0.G3cZ5_j7JDh0OezT7WoRk_oWWFtesplUbtYpvMNHv8c ] the President’s China delegation, complicating Nvidia’s mainland sales pitch. Where chips do flow, inference is being recompiled. CoreWeave is now fastest at serving Kimi K2.6 [ https://substack.com/redirect/f3959fd9-89b7-4068-b83d-83d7b64f4132?j=eyJ1IjoiODI5Z29vIn0.G3cZ5_j7JDh0OezT7WoRk_oWWFtesplUbtYpvMNHv8c ] at 205 tokens per second, proving the Chinese open-weight frontier is now an American hosting opportunity.
Atoms are catching up to bits. Unitree unveiled the $650k D01 “manned transformable mecha,” [ https://substack.com/redirect/386ee5cb-ef10-4592-92f4-e7bd841c5b05?j=eyJ1IjoiODI5Z29vIn0.G3cZ5_j7JDh0OezT7WoRk_oWWFtesplUbtYpvMNHv8c ] a 500-kg civilian exo-vehicle billed as the world’s first production-ready specimen, converting Saturday-morning anime into a line item. Closer to home, Amazon launched Amazon Now [ https://substack.com/redirect/c5d75c1a-ff48-40c4-9dde-2f8ccf57e845?j=eyJ1IjoiODI5Z29vIn0.G3cZ5_j7JDh0OezT7WoRk_oWWFtesplUbtYpvMNHv8c ] for 30-minute deliveries from a network of dark stores across dozens of US cities, with further expansion planned by year-end. The last mile is being compressed into a last minute.
But the grid is groaning. Demand for generator step-up transformers has surged 274% since 2019 [ https://substack.com/redirect/c77e1b68-920e-48ac-b285-56cf9aa623d8?j=eyJ1IjoiODI5Z29vIn0.G3cZ5_j7JDh0OezT7WoRk_oWWFtesplUbtYpvMNHv8c ] with lead times stretching to four years. The bottleneck is summoning new entrants. Ford launched Ford Energy [ https://substack.com/redirect/3b6a4034-d764-44f3-9f8c-3e56ee16fe7c?j=eyJ1IjoiODI5Z29vIn0.G3cZ5_j7JDh0OezT7WoRk_oWWFtesplUbtYpvMNHv8c ], pivoting to US-assembled LFP battery storage by 2027. And the federal government wants the reactor on the boat. DOT and MARAD launched an initiative for Small Modular Nuclear Reactors [ https://substack.com/redirect/57939ed5-73e9-45b5-9345-928bb5a48b1f?j=eyJ1IjoiODI5Z29vIn0.G3cZ5_j7JDh0OezT7WoRk_oWWFtesplUbtYpvMNHv8c ] on commercial shipping vessels, dragging maritime logistics into the fission age. Power generation is becoming as bespoke as the models that consume it.
The vector of growth is pointing up. SpaceX completed a Starship V3 launch rehearsal [ https://substack.com/redirect/5c1c2d97-8fca-4a5a-a701-ea45bb0c6cf1?j=eyJ1IjoiODI5Z29vIn0.G3cZ5_j7JDh0OezT7WoRk_oWWFtesplUbtYpvMNHv8c ] with launch imminent, and Polymarket projects SpaceX’s IPO closing above $2.2 trillion [ https://substack.com/redirect/3d2188b4-4288-4cdf-85a0-836bd7e2643a?j=eyJ1IjoiODI5Z29vIn0.G3cZ5_j7JDh0OezT7WoRk_oWWFtesplUbtYpvMNHv8c ], the largest in history. The orbital compute thesis is funded too. Cowboy Space Corporation raised $275M at a $2B valuation [ https://substack.com/redirect/e09b61da-533c-419a-98c8-e22639a0a462?j=eyJ1IjoiODI5Z29vIn0.G3cZ5_j7JDh0OezT7WoRk_oWWFtesplUbtYpvMNHv8c ] to build LEO infrastructure for the AI era, with space-to-Earth power beaming this year and an orbital GPU cluster by 2027.
At the cellular level, we are rewiring desire itself. Researchers have for the first time pinpointed the central amygdala circuit [ https://substack.com/redirect/89255627-73dd-4be5-bcef-ef77a046b987?j=eyJ1IjoiODI5Z29vIn0.G3cZ5_j7JDh0OezT7WoRk_oWWFtesplUbtYpvMNHv8c ] that next-generation GLP-1 drugs inhibit to suppress hedonic eating, reducing dopamine release in the nucleus accumbens to isolate reward without abolishing it. Pleasure is becoming a knob.
Not everyone is thrilled with the upgrade cycle. UCF humanities graduates loudly booed a commencement speaker [ https://substack.com/redirect/ebdb0ca9-d9b3-4dcb-96d7-db3311f47cf8?j=eyJ1IjoiODI5Z29vIn0.G3cZ5_j7JDh0OezT7WoRk_oWWFtesplUbtYpvMNHv8c ] for calling AI the next industrial revolution. Meanwhile, Goodhart’s law has gone enterprise, with Amazon employees reportedly using an internal “MeshClaw” [ https://substack.com/redirect/24127f97-8fc2-4306-b2de-20f63fe4496b?j=eyJ1IjoiODI5Z29vIn0.G3cZ5_j7JDh0OezT7WoRk_oWWFtesplUbtYpvMNHv8c ] tool to automate fake AI tasks just to hit token-consumption targets on internal leaderboards. Misaligned incentives scale upward, too. US spy agencies are reportedly muscling in on the Commerce Department [ https://substack.com/redirect/f7ad3276-5b3b-4a70-9ded-7e56e47e08ea?j=eyJ1IjoiODI5Z29vIn0.G3cZ5_j7JDh0OezT7WoRk_oWWFtesplUbtYpvMNHv8c ] over pre-release frontier model evaluations. And South Korea’s Kim Yong-beom is proposing a “national dividend” [ https://substack.com/redirect/92783fc7-8a92-4b6e-bf5c-7ac3403577b7?j=eyJ1IjoiODI5Z29vIn0.G3cZ5_j7JDh0OezT7WoRk_oWWFtesplUbtYpvMNHv8c ] to redistribute AI’s excess profits, a new social contract for the age of intelligent capital.
From each according to its FLOPs, to each according to their dividend.
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