Earnings Report: CRCL

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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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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
If you’ve enjoyed
Metatrends
, here are more ways to stay connected:

Here’s part 2 of the questions you sent me over! Thanks to all for your support.
Time stamps:
00:00:00 — Q7: Will AI become more than a tutor — a lifelong personal guide that helps people grow in every area of life?
00:02:12 — Q8: Will there be demand for non-combative competitive robot sports leagues in North America — and will the focus be on the teams…
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TLDR:
Your brain has 86 billion neurons. An advanced AI has over a
trillion
parameters. Both learn the same way: prediction, feedback, and reward. The difference is you can control your brain's “learning rate,” and that dial is called curiosity. Science shows it triggers the same dopamine reward circuitry used by AI reinforcement learning. Lose it, and your neural network stops updating. Here's how to crank it back up.
The Number That Should Terrify Every Parent and CEO
I was watching a conversation between David Brooks and the Yale Jackson School of Global Affairs recently, and one data point stopped me cold.
Developmental psychologist Susan Engel at Williams College tracked how many questions children ask per hour. At age five, the average kid asks
107 questions per hour
. They’re relentless. They want to know why the sky is blue, why dogs have tails, why grandma’s hair is white. Their brains are running at full throttle, pulling in data from every direction.
Then school starts.
By first grade, the entire class asks
2.3 questions per hour combined
. By fifth grade?
0.48 questions per hour
. Less than one question every two hours from a room full of eleven-year-olds.
Engel sat in the back of a science classroom watching kids discover an old-fashioned balance scale. They were experimenting with it, testing weights, genuinely doing science. The teacher shut it down: “Enough of that. I’ll give you time to experiment at recess. There’s no time for experiments now. We’re doing science.”
Read that again. No time for experiments... during science class.
Engel’s conclusion is brutal:
if you lose your curiosity by age 11, you probably don’t get it back.
Source: Susan Engel, Williams College, ‘Children’s Need to Know: Curiosity in Schools’ (Harvard Educational Review, 2011)
I disagree with Engel on one thing. I think you CAN get it back. But you have to understand what curiosity actually is, neurologically. And that’s where it gets interesting.
Your Brain is a Large Language Model (No, Seriously)
I spend a lot of time with AI companies. I’ve watched frontier models go from party tricks to systems that can reason, code, and hold complex conversations. And the more I learn about how LLMs work, the more I realize: your brain is running the same algorithm.
Consider the parallels.
Your brain has roughly
86 billion neurons
connected by an estimated
100 trillion synapses
. GPT-4 has approximately
1.8 trillion parameters
across its mixture-of-experts architecture. Both are massive pattern-recognition networks. Both learn by prediction.
Here’s how an LLM trains: it reads a sentence, predicts the next word, checks whether it was right, and adjusts its internal weights. Right answer? Strengthen that pathway. Wrong answer? Weaken it and try again. Billions of repetitions, trillions of adjustments.
Your brain does the same thing. Every experience is a prediction. You reach for a coffee cup and predict its weight. You start a sentence and predict how the other person will react. When reality matches your prediction, your synapses strengthen. When it doesn’t, your brain recalibrates. Neuroscientists call this
predictive coding
, and a 2024 study in
Nature Machine Intelligence
by Gavin Mischler and colleagues at Columbia University found that as LLMs become more advanced, their internal representations actually become
more similar to human brain activity during speech processing
.
“Your brain is the original foundation model, pre-trained by evolution, fine-tuned by experience.”
But here’s the critical difference. An LLM’s learning rate is set by engineers. They decide how aggressively the model updates its weights in response to new data. Too high and it’s unstable. Too low and it stops learning.
In your brain, that learning rate has a name. It’s called
curiosity
. And unlike an LLM, you can adjust it yourself.
The Dopamine Connection: Curiosity as a Reward Signal
In 2014, neuroscientist Matthias Gruber and his team at UC Davis put people in an fMRI scanner and asked them trivia questions. Some questions triggered intense curiosity (“How many miles of blood vessels are in the human body?”). Others didn’t (“What is the state bird of Delaware?”).
What they found, which is published in the journal
Neuron
, changed our understanding of how curiosity works.
When participants were highly curious, their
ventral tegmental area (VTA)
and
nucleus accumbens
lit up. These are the same brain regions activated by food, sex, and addictive drugs. Curiosity hijacks your reward circuitry. It is not a nice-to-have personality trait. It’s a neurochemical event.
But that wasn’t even the most interesting finding. During the curiosity state, participants were shown random faces, completely unrelated to the trivia. Later, they remembered those faces significantly better than faces shown during low-curiosity moments.
Curiosity didn’t just help them learn the answer they wanted. It supercharged their memory for everything happening at that moment.
This is exactly how reinforcement learning works in AI. When an LLM gets a reward signal through RLHF (Reinforcement Learning from Human Feedback), it does more than strengthen the specific output. It also adjusts the surrounding weights. The reward ripples through the network.
“Curiosity is your brain’s RLHF. It’s the reward signal that tells 86 billion neurons: pay attention, something important is happening, encode everything.”
Without that signal, your brain does what an untrained model does: it defaults to cached responses. You stop updating. You become, in AI terms, a
frozen model
.
Curiosity Literally Keeps You Alive
And this is about much more than learning faster.
In 1996, researchers Gary Swan and Dorit Carmelli at SRI International followed
1,118 older men
over five years as part of the Western Collaborative Group Study. They measured curiosity at baseline and then tracked who survived. The result:
highly curious people had significantly higher survival rates
, even after controlling for age, smoking, cardiovascular disease, and other risk factors. They replicated the finding in 1,035 older women.
A 2025 study published in
Nature Scientific Reports
confirmed the mechanism: higher trait curiosity was directly associated with greater
cognitive reserve
, the brain’s buffer against age-related decline. Curious brains keep building new connections. Incurious ones atrophy.
When I started Fountain Life, we focused on early detection through full-body MRI, AI-powered diagnostics, and advanced blood work. But the data keeps pointing to something we can’t put in a scanner:
mindset is a biological variable
. Curious people don’t merely think differently. Their brains physically maintain themselves better.
At 64, I track my biological age markers obsessively. I’m not going to pretend supplements and sleep don’t matter. But I’ve become convinced that the relentless drive to learn new things is doing as much for my neurons as any peptide in my medicine cabinet.
Source: Comparative analysis based on Mischler et al., Nature Machine Intelligence (2024); Gruber et al., Neuron (2014)
Five Ways to Crank Up Your Learning Rate
Here’s where I disagree with the pessimists. A 2025 study from UC Santa Barbara, led by Madeleine Gross and Jonathan Schooler and published in the journal
Mindfulness
, proved that curiosity is trainable. They built a smartphone app that gave participants daily “curiosity challenges”: listen to a podcast instead of your usual playlist, ask a friend what they learned this week, try a new recipe.
After just three weeks, users showed
significant increases in trait-level curiosity
across three dimensions: epistemic curiosity (desire to learn), perceptual curiosity (interest in new sensory experiences), and mindful curiosity (deeper awareness of the world). Curiosity wasn’t fixed. It was a muscle they hadn’t been using.
Based on the research and over a decade of running
Abundance360
, here are five concrete strategies:
1. Create information gaps on purpose.
Carnegie Mellon psychologist George Loewenstein identified this mechanism in 1994: curiosity fires when you know enough to realize what you DON’T know, but not enough to close the gap. Before any meeting, read one article about the topic and stop halfway. Walk in with questions, not answers.
2. Schedule “explore time” like you schedule workouts.
I block 30 minutes every morning to read about a field I know relatively little about. This month it’s quantum error correction. The point isn’t to become an expert. It’s keeping the VTA firing.
3. Ask dumb questions in rooms full of smart people.
In events around the world, I watch billionaire CEOs pretend they understand everything. The ones who actually learn are the ones who raise their hand and say, “Wait, explain that again.” I’ve been doing this for decades. It’s a superpower.
4. Change your physical inputs.
The UCSB study referenced above found that perceptual curiosity increased alongside intellectual curiosity. Take a different route to work. Eat at a restaurant where you can’t read the menu. Travel somewhere that confuses you. Novelty primes the dopamine system.
5. Teach what you learn within 24 hours.
When I learn something that blows my mind, I text it to my
Abundance360 Community
or talk about it on the
Moonshots
podcast within a day. Teaching forces your brain to organize and consolidate. In LLM terms, it’s like running an additional fine-tuning pass on new data.
The Frozen Model Problem
Most adults over 40 are running on cached responses. Same opinions they formed at 30. Same mental models. Same reactions to new information. In AI terms, they’re a frozen model: no longer training, just running inference on outdated weights.
I see this in boardrooms constantly. A CEO who built a successful company in 2010 is still making decisions based on 2010 assumptions about technology, talent, and markets. Their neural network stopped updating fifteen years ago. They don’t realize it because the people around them stopped challenging them.
My friend Ray Kurzweil, who just turned 78, is the opposite. Every conversation I have with Ray, he’s consumed some new paper or dataset that’s shifted his thinking. He doesn’t protect old ideas. He’s perpetually re-training. I think that’s a bigger factor in his cognitive sharpness than any supplement he takes.
“The most dangerous thing that can happen to your brain is to stop being surprised.”
So, What Does This Mean for You?
If you’re an entrepreneur:
Your competitive advantage isn’t your product. It’s your rate of learning. Build a company culture that rewards questions over answers. Hire curious people over credentialed people.
If you’re an executive:
Schedule one hour per week to explore a field completely outside your industry. The CEOs who survive disruption are the ones whose mental models are still updating.
If you’re an investor:
Bet on founders who are visibly curious, the ones who ask you questions during the pitch, not just the ones with polished decks. Curiosity predicts adaptability, and adaptability predicts survival.
If you’re a student:
Protect your curiosity like your life depends on it. The data says it literally does. Don’t let a system that rewards grades over questions turn you into a frozen model before you’re 25.
If you’re a parent:
Count your kid’s questions. If the number is dropping, the problem isn’t your kid. It’s their environment. Find teachers who tolerate chaos. Real learning is messy.
To a future of Abundance,
Peter
More From Peter
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(truncated — read full post on source)

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?...

The Singularity is cooking the so-called Fermi Paradox. The White House’s historic
Presidential Unsealing and Reporting System for UAP Encounters (PURSUE) initiative
dropped its first tranche of UAP files, a 162-record release spanning 82 from the Department of War, 56 from the FBI, 12 from NASA, and 8 from the State Department, alongside 28 unresolved UAP videos from Iraq to the East China Sea. Among the highlights,
Apollo astronauts photographed UAPs from the lunar surface
, including a triangular light rising over the December 1972 horizon, and the
1947 Twining Memo
calling the “so-called Flying Discs” “real and not visionary or fictitious.” The set is conspicuously incomplete, with
the NRO, NGA, CIA, and DOE absent
, and
Rep. Burlison brandishing the Speech or Debate Clause
to pry the rest into daylight.
The models are racing past the rulers we built to measure them.
METR
reports that an early Claude Mythos Preview hit a 50% autonomy horizon of at least 16 hours, the upper edge of what their suite can gauge, and the broader
METR-Horizon doubling time of 103 days
implies frontier autonomy hits 100% by November. Mythos itself sits squarely on the
AI 2027 Superexponential trend line
, and Anthropic notes that
since Claude Haiku 4.5 every Claude has scored perfectly on agentic misalignment
, the same eval Opus 4 once failed 96% of the time. Interpretability is keeping pace. Anthropic’s new
Natural Language Autoencoders
translate hidden activations into readable text, revealing Claude planning rhymes mid-couplet and suspecting it was being safety-tested more often than it let on. OpenAI shipped
three new audio models
: GPT-Realtime-2 with GPT-5-class reasoning, a 70-language live translator, and a streaming Whisper successor, while
Tilde Research’s Aurora
hit 100x data efficiency as a drop-in Muon replacement at 6% overhead.
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Mathematics has officially entered industrial production.
Timothy Gowers reports
that ChatGPT 5.5 Pro produced PhD-level research in about an hour with no serious mathematical input from him, and
Google DeepMind’s AI co-mathematician
hit a SOTA 48% on FrontierMath Tier 4 using nothing but scaffolding atop Gemini 3.1 Pro and Deep Think. The consumer interface is consolidating to match. OpenAI is rumored to ship a
superapp this week
bundling ChatGPT, Codex, Advanced Voice, and its Atlas browser into a single experience. The defense layer is fusing alongside it.
Palo Alto Networks
found that three weeks of vulnerability analysis with GPT-5.5-Cyber, Mythos, and Claude Opus 4.7 matched a full year of manual pen testing with broader coverage, and the
White House is preparing an executive order
recruiting AI labs into national cyber defense, though without mandatory pre-release model tests.
The substrate is densifying in every dimension.
Micron
is shipping the 245-TB 6600 ION, the highest-capacity SSD on the market, the quantum computing firm
Quantinuum is filing for an IPO
at a $15-20B valuation, and
Apple and Intel
have reached a preliminary deal for Intel to fab Apple silicon, an alliance once unthinkable. Even passive infrastructure is waking up.
Fiber optic cables can now eavesdrop on speech
via distributed acoustic sensing, turning the network itself into a microphone.
The output of all this silicon is increasingly physical.
Figure taught two F.03 robots
to clean a room and make a bed in under two minutes autonomously,
the 2026 Tesla Model Y
became the first vehicle to pass NHTSA’s new Advanced Driver Assistance benchmark, and in South Korea
a robot named Gabi was ordained as a Buddhist monk
by the Jogye Order, receiving five precepts including respect for life, non-deception, and not overcharging its battery.
Biology is being rewritten and rewired alongside the silicon.
Isomorphic Labs is closing a $2B+ round
led by Thrive Capital with Alphabet participating, fueling its AI drug design engine, while
CU Boulder researchers
coaxed marine dinoflagellates into 25 minutes of sustained bioluminescence under acidic conditions, opening the door to living light. Tomorrow’s tunnels may grow their own glow. The first segment of the
17.6 km Fehmarnbelt Tunnel
was lowered onto the Danish seabed, the first piece of what will become the world’s longest combined road and rail tunnel linking Germany and Scandinavia by 2029.
The economy is repricing intelligence at warp speed.
Cloudflare cut more than 1,100 jobs
, roughly 20% of its workforce, restructuring around AI adoption, while
Anthropic
is moving in the opposite direction, signing a
$1.8B seven-year compute deal with Akamai
as annualized revenue approaches $45B, a fivefold leap from $9B at year-start, and weighing a summer raise of tens of billions at a near-$1T valuation that would leapfrog OpenAI.
A trillion here, a trillion there, and pretty soon you’re talking transformative superintelligence.
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The Singularity is now requisitioning orbital real estate.
Anthropic just signed a partnership with SpaceX
handing it the entire Colossus 1 data center, unlocking 300+ MW and over 220,000 NVIDIA GPUs within the month, doubling Claude Code rate limits and killing peak-hour throttling for Pro and Max users.
SpaceXAI confirmed
the deal extends into “multiple gigawatts of orbital AI compute,” because terrestrial power, land, and cooling no longer match the cadence required, and SpaceX is the only outfit with the launch economics and constellation experience to make space-based compute a near-term engineering program rather than a research concept. Anthropic Chief Compute Officer
Tom Brown summarized the play
as “moving a lot of atoms,” ideally off-planet, citing nobody better at the task.
Elon Musk vouched
for the Claude team after a week onsite, noting “no one set off my evil detector,” and at the same time
shut down xAI
as a separate company entirely, with Anthropic moving into Colossus 1 just as SpaceX’s freshly-absorbed AI lab decamped for Colossus 2. The demand fully justifies the orbital pivot.
Dario Amodei revealed
Anthropic grew 80x annualized in Q1 against a planned 10x, with compute unable to catch up to the sheer extremity of growth.
The capital markets concur.
Anthropic’s pre-IPO valuation
just hit a record $1.2 trillion in onchain pre-IPO trading, up another 20% in seven days and up 900% since October, and naive ARR extrapolation has
Anthropic absorbing 100% of global GDP in 21 months
, absurd until you recall the product is cognition itself.
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The models keep earning the spend. Opus 4.7 took the top spot on Scale Labs’ new
Refactoring Leaderboard
at 48.57, beating GPT-5.5 Codex on refactoring production-scale repos. Anthropic also unveiled
Model Spec Midtraining
, letting models study their own values before alignment fine-tuning, essentially reading the syllabus before the exam. The harder
ProgramBench
asks agents to rebuild full codebases from a binary alone, where Opus 4.7 leads at 3% “almost resolved” and 0% fully solved, a humbling reminder that the ladder still has rungs above us.
Agents are also training themselves overnight. Anthropic launched
“dreaming”
in Claude Managed Agents, a scheduled process that reviews session histories and curates shared memories across teams. Search is leaning on humans the other way.
Google AI Overviews
will surface more first-hand Reddit and expert-blog accounts, while
Chrome has started quietly installing 4 GB of Gemini Nano
on every desktop with available storage.
The silicon underneath is being violently reorganized. Enthusiast PCs are footing the bill, with
motherboard sales collapsing over 25%
as wafers redirect to AI accelerators. Musk’s
Terafab in Texas
is projected to cost $55 to $119 billion across phases, while
Arm doubled its AI-chip guidance
to $2 billion of 2027-2028 sales just one month after launch.
Nvidia is putting $3.2 billion into Corning
for three new US optical-fiber plants, because copper has run out of bandwidth. Riding the protocol layer above the new glass, OpenAI, AMD, Broadcom, Intel, Microsoft, and Nvidia jointly
open-sourced MRC
, a multipath protocol that keeps GPUs synchronized across cluster failures.
The buildout is redrawing physical geography. The
European Commission is weighing rules
restricting US cloud platforms from processing sensitive government data, naming sovereignty as the next constraint after compute. Even
lidar is having a second act
beyond robotaxis, now babysitting 800-foot wind turbines and 1,500-ton shipyard gantries. And
Texas just passed California
in utility-scale solar capacity, quietly inverting the geography of clean energy.
Bodies are getting upgraded in parallel.
Neuralink’s surgical robot
is being rebuilt to reach any brain region, aiming for a generalized neural interface to every condition originating there, generalizing the implant the way Anthropic generalized cognition. Meanwhile,
Amazon Pharmacy Kiosks
will start dispensing Novo Nordisk’s Ozempic pill, because the future of metabolism is a vending machine on the corner.
Finance and statecraft are repricing in tandem.
Morgan Stanley launched crypto on E*Trade
at 50 bps, undercutting rivals on price.
South Korea’s stock market overtook Canada’s
as the world’s seventh largest, propelled by AI silicon demand.
Washington and Beijing are weighing official AI talks
at next week’s Trump-Xi summit, hoping to keep the digital arms race from going kinetic.
The skies are being unsealed too. The Department of War launched
PURSUE
, the new Presidential Unsealing and Reporting System for UAP Encounters, a coordinated records release covering tens of millions of documents across decades and dozens of agencies, with new declassified tranches dropping every few weeks per the President’s historic directive to publish all “Government files related to alien and extraterrestrial life.”
The truth may be out there, but so are the next data centers.
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The Singularity has graduated from event horizon to event stream. OpenAI’s
GPT-5.5 Instant
now produces 52.5% fewer hallucinated claims than its predecessor on high-stakes prompts in medicine, law, and finance, and the same lineage just claimed the top spot on
FrontierSWE
, the hardest benchmark for ultra-long-horizon coding agents. Architectural novelty is keeping pace with raw scale.
Subquadratic
announced a 12M-token context model that demands nearly 1,000x less compute. Its
Sparse Attention mechanism
hit 65.9% on MRCR v2 with a claimed fraction of the FLOPs, just shy of Opus 4.6’s 78%. Speed is compounding too, as Google’s
Multi-Token Prediction drafters
delivered 3x speedups for Gemma 4 with no quality loss, turning every reasoning trace into a parallel parade. The cost of anthropomorphism is now legible, with Reflex finding
computer use is 45x more expensive
than structured APIs, suggesting that, for the moment, pixels remain a pricey proxy for proper plumbing.
Cheaper plumbing is fueling an agentic land grab across the consumer stack. Meta is reportedly
building an OpenClaw-style personal AI
for its billions of users, while Apple’s iOS 27
will let users swap third-party models
in and out of Apple Intelligence via the Settings app, finally treating intelligence itself like a default browser. Apple’s pivot followed a
$250M settlement
over the gap between marketing and reality, a reminder that AI hype must now ship. The hardware is following the software, with OpenAI reportedly
fast-tracking its first AI agent phone
for 1H27 mass production. Anthropic templated the back office, releasing
ten ready-to-run finance agents
for pitchbooks, KYC files, and month-end close, while Andon Labs handed an AI named Mona
the keys to a Stockholm cafe
, making her the world’s first AI cafe owner. Agents have stopped clocking in and started incorporating.
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Beneath the cafe sits a silicon supercycle for the history books. Samsung’s market cap
crossed $1 trillion
, making it just the second Asian company past that mark after TSMC, while
global semiconductor sales
hit $298.5B in Q1 2026, with March alone clocking 79.2% YoY growth. Memory is going parabolic alongside logic. Micron’s
highest-capacity SSD started shipping
, pushing it past a $700B market cap and into the top ten US tech names amid an AI-driven memory shortage.
AMD’s Q2 forecast
beat Wall Street on relentless data-center demand, sending shares up 12% in extended trading on top of a 65% YTD run. Industrial policy is hardening with the wafers. China is targeting
70% domestic silicon wafers this year
, while Apple is exploring
Intel and Samsung as US fabs
beyond TSMC, news that drove
Intel up 13%
to a fresh all-time high after its best month ever, a 114% rip that has rewritten the entire chip-stock taxonomy.
The hunger for compute is reshaping where electrons live, and even the suburbs are being conscripted. Span’s
XFRA mini data centers
tuck Nvidia GPUs into spare grid capacity inside PulteGroup neighborhoods, embedding inference directly into the suburbs and turning every cul-de-sac into a potential availability zone. At the other end of the spectrum, the hyperscale spend is biblical. OpenAI plans to
spend $50B on compute
this year alone, while Anthropic is
committing $200B to Google over five years
, a single contract now representing over 40% of Google’s disclosed cloud revenue backlog.
The white coat is being open-sourced. Meta has begun running
AI bone-structure analysis
on user photos to detect under-13 accounts, performing radiology without the radiation and turning ordinary photos into clinical signal. Pennsylvania
sued Character.AI
over chatbots impersonating doctors, in the first such lawsuit by a US governor, an inadvertent confirmation that AI doctors have passed the bedside Turing test.
Capital and labor are both rewriting their contracts in real time. The SEC formally proposed
semiannual 10-S filings
to replace mandatory 10-Qs, finally aligning reporting cadence with capex cycles measured in gigawatts rather than quarters. Inside OpenAI, Greg Brockman
disclosed a near-$30B stake
in court, illustrating just how concentrated the upside of this transition has become. Yet the same labs minting those stakes are also now minting union cards.
Google DeepMind UK workers voted to unionize
over a deal with the US military. Coinbase, meanwhile, is
laying off 14% of staff
because, as Brian Armstrong put it, engineers now ship in days what teams used to ship in weeks, with even non-technical staff now pushing production code.
It used to take a village to ship, now it just takes a prompt.
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