P5 Health Ventures

P5 invests in early to mid-stage cos that translate research & technology into platforms that provide everyday life saving, preventive and accessible solutions

[Kevin O'Leary aka Mr. Wonderful @kevinolearytv]

We uncovered something far bigger than I ever expected. After seeing coordinated false attacks against the Utah data center project, we brought in an advanced data science team to trace where the content was coming from and the results were shocking. What we found led back to organized networks, political activist groups, and funding trails tied to massive international entities. We dug through IRS 990 filings, tracked IP data from around the world, and uncovered what appears to be a coordinated campaign targeting energy and data center projects across multiple regions.

I shared 90 pages of evidence with federal law enforcement and raised concerns directly with contacts at the White House. This isn’t speculation. The filings, funding records, dates, and connections are documented. There’s a coordinated PR war happening around energy infrastructure and data centers, and we’re not going to ignore it.

[COATUE @coatuemgmt]

Memory is the new bottleneck.

Nick Gagnet, Coatue Sector Head, on the AI infrastructure shift and why memory demand could 5x in 5 years.

[P5 Health Ventures @P5Health]

I listened to (morning runs) and simultaneously read (when back at my desk) Read Write Own when it first came out. That week forced me to reprioritize my mornings. I am slow to blockchain but a big believer in it as the foundational technology. I viewed and still view the book as foundational knowledge for politicians, at least for those who can read and understand context. Many of the young guns don’t or “can’t.”That delays, but it doesn’t stop the inevitable. @cdixon is taking the time to teach the world and without him I would have been hunting for “my teacher.” So thank you! My three sons each immediately got their own copy. After all, they were trading NFTs during the Covid lockdown. So now I deep dive back in after building other companies and I know where to start and https://t.co/6qaDLcWmh0 and Substack enable me to collate and pull information - with Grok, Claude and Perplexity getting and organizing the research for me…. After all, the long game eventually has many short games inside it, and I see those emerging.

[Chris Dixon @cdixon]

https://t.co/zAHyO5TJ0c

[Arthur MacWaters @ArthurMacwaters]

Let me get this straight:

> the top 1% earners in CA pay a cumulative $40-$50b/yr in income tax

> yet CA Medicaid alone loses $50b/yr in fraud

So, you can work your whole life to be incredibly successful, and bureaucrats in CA will redistribute it to fraudsters

The Bolscheviks working to pass an asset seizure cannot be trusted.

[Steve Jurvetson @FutureJurvetson]

Tesla Dojo on top, in my updated long-term version of Moore's Law.

Note: this is a semi-log graph, so a straight line is an exponential; each y-axis tick is 100x. This graph covers a 10,000,000,000,000,000,000x improvement in computation/$ over 125 years.

The computational frontier has shifted across many technology substrates over the past 125 years, most recently from the CPU to the GPU to ASICs optimized for neural networks (the majority of new compute cycles). The ASIC approach is being pursued by scores of new companies and Google TPUs, as well as the Mythic analog ASIC. Google is currently spending $25B on TPU 5 chips.

Of all of the depictions of Moore’s Law, this is the one, originally by Ray Kurzweil, I find to be most useful, as it captures what customers actually value — computation per $ spent.

Humanity’s capacity to compute has compounded for as long as we can measure it, exogenous to the economy, and starting long before Intel co-founder Gordon Moore noticed a refraction of the longer-term trend in the belly of the fledgling semiconductor industry in 1965.

Why the transition within the integrated circuit era? Intel lost to NVIDIA for neural networks because the fine-grained parallel compute architecture of a GPU maps better to the needs of deep learning. There is a poetic beauty to the computational similarity of a processor optimized for graphics processing and the computational needs of a sensory cortex, as commonly seen in neural networks today. A custom chip (like the Tesla D1 ASIC) optimized for neural networks extends that trend to its inevitable future in the digital domain. Further advances are possible in analog in-memory compute, an even closer biomimicry of the human cortex. The best business planning assumption is that Moore’s Law, as depicted here, will continue for the next 20 years as it has for the past 120.

For those unfamiliar with this chart, here is a more detailed description:

• Moore's Law is both a prediction and an abstraction

Moore’s Law is commonly reported as a doubling of transistor density every 18 months. But this is not something the co-founder of Intel, Gordon Moore, has ever said. It is a nice blending of his two predictions; in 1965, he predicted an annual doubling of transistor counts in the most cost effective chip and revised it in 1975 to every 24 months. With a little hand waving, most reports attribute 18 months to Moore’s Law, but there is quite a bit of variability. The popular perception of Moore’s Law is that computer chips are compounding in their complexity at near constant per unit cost. This is one of the many abstractions of Moore’s Law, and it relates to the compounding of transistor density in two dimensions. Others relate to speed (the signals have less distance to travel) and computational power (speed x density).

Unless you work for a chip company and focus on fab-yield optimization, you do not care about transistor counts. Integrated circuit customers do not buy transistors. Consumers of technology purchase computational speed and data storage density. When recast in these terms, Moore’s Law is no longer a transistor-centric metric, and this abstraction allows for longer-term analysis.

What Moore observed in the belly of the early IC industry was a derivative metric, a refracted signal, from a longer-term trend, a trend that begs various philosophical questions and predicts mind-bending futures.

Ray Kurzweil’s abstraction of Moore’s Law shows computational power on a logarithmic scale, and finds a double exponential curve that holds over 120 years! A straight line would represent a geometrically compounding curve of progress.

Through five paradigm shifts – such as electro-mechanical calculators and vacuum tube computers – the computational power that $1000 buys has doubled every two years. For the past 35 years, it has been doubling every year.

Each dot is the frontier of computational price performance of the day. One machine was used in the 1890 Census; one cracked the Nazi Enigma cipher in World War II; one predicted Eisenhower’s win in the 1956 Presidential election. Many of them can be seen in the Computer History Museum.

Each dot represents a human drama. Prior to Moore’s first paper in 1965, none of them even knew they were on a predictive curve. Each dot represents an attempt to build the best computer with the tools of the day. Of course, we use these computers to make better design software and manufacturing control algorithms. And so the progress continues.

Notice that the pace of innovation is exogenous to the economy. The Great Depression and the World Wars and various recessions do not introduce a meaningful change in the long-term trajectory of Moore’s Law. Certainly, the adoption rates, revenue, profits and economic fates of the computer companies behind the various dots on the graph may go though wild oscillations, but the long-term trend emerges nevertheless.

Any one technology, such as the CMOS transistor, follows an elongated S-shaped curve of slow progress during initial development, upward progress during a rapid adoption phase, and then slower growth from market saturation over time. But a more generalized capability, such as computation, storage, or bandwidth, tends to follow a pure exponential – bridging across a variety of technologies and their cascade of S-curves.

In the modern era of accelerating change in the tech industry, it is hard to find even five-year trends with any predictive value, let alone trends that span the centuries. I would go further and assert that this is the most important graph ever conceived.

• Why do I think this the most important graph in human history?

A large and growing set of industries depends on continued exponential cost declines in computational power and storage density. Moore’s Law drives electronics, communications and computers and has become a primary driver in drug discovery, biotech and bioinformatics, medical imaging and diagnostics. As Moore’s Law crosses critical thresholds, a formerly lab science of trial and error experimentation becomes a simulation science, and the pace of progress accelerates dramatically, creating opportunities for new entrants in new industries. Boeing used to rely on the wind tunnels to test novel aircraft design performance. Ever since CFD modeling became powerful enough, design moves to the rapid pace of iterative simulations, and the nearby wind tunnels of NASA Ames lie fallow. The engineer can iterate at a rapid rate while simply sitting at their desk.

Every industry on our planet is going to become an information business. Consider agriculture. If you ask a farmer in 20 years’ time about how they compete, it will depend on how they use information, from satellite imagery driving robotic field optimization to the code in their seeds. It will have nothing to do with workmanship or labor. That will eventually percolate through every industry as IT innervates the economy.

Non-linear shifts in the marketplace are also essential for entrepreneurship and meaningful change. Technology’s exponential pace of progress has been the primary juggernaut of perpetual market disruption, spawning wave after wave of opportunities for new companies. Without disruption, entrepreneurs would not exist.

Moore’s Law is not just exogenous to the economy; it is why we have economic growth and an accelerating pace of progress. At Future Ventures, we see that in the growing diversity and global impact of the entrepreneurial ideas that we see each year. The industries impacted by the current wave of tech entrepreneurs are more diverse, and an order of magnitude larger than those of the 90’s — from automobiles and aerospace to energy and chemicals.

At the cutting edge of computational capture is biology; we are actively reengineering the information systems of biology and creating synthetic microbes whose DNA is manufactured from bare computer code and an organic chemistry printer. But what to build? So far, we largely copy large tracts of code from nature. But the question spans across all the complex systems that we might wish to build, from cities to designer microbes, to computer intelligence.

• Reengineering engineering

As these systems transcend human comprehension, we will shift from traditional engineering to evolutionary algorithms and iterative learning algorithms like deep learning and machine learning. As we design for evolvability, the locus of learning shifts from the artifacts themselves to the process that created them. There is no mathematical shortcut for the decomposition of a neural network or genetic program, no way to "reverse evolve" with the ease that we can reverse engineer the artifacts of purposeful design. The beauty of compounding iterative algorithms (evolution, fractals, organic growth, art) derives from their irreducibility. And it empowers us to design complex systems that exceed human understanding.

• Why does progress perpetually accelerate?

All new technologies are combinations of technologies that already exist. Innovation does not occur in a vacuum; it is a combination of ideas from before. In any academic field, the advances today are built on a large edifice of history. . This is why major innovations tend to be 'ripe' and tend to be discovered at the nearly the same time by multiple people. The compounding of ideas is the foundation of progress, something that was not so evident to the casual observer before the age of science. Science tuned the process parameters for innovation, and became the best method for a culture to learn.

From this conceptual base, come the origin of economic growth and accelerating technological change, as the combinatorial explosion of possible idea pairings grows exponentially as new ideas come into the mix (on the order of 2^n of possible groupings per Reed’s Law). It explains the innovative power of urbanization and networked globalization. And it explains why interdisciplinary ideas are so powerfully disruptive; it is like the differential immunity of epidemiology, whereby islands of cognitive isolation (e.g., academic disciplines) are vulnerable to disruptive memes hopping across, much like South America was to smallpox from Cortés and the Conquistadors. If disruption is what you seek, cognitive island-hopping is good place to start, mining the interstices between academic disciplines.

It is the combinatorial explosion of possible innovation-pairings that creates economic growth, and it’s about to go into overdrive. In recent years, we have begun to see the global innovation effects of a new factor: the internet. People can exchange ideas like never before Long ago, people were not communicating across continents; ideas were partitioned, and so the success of nations and regions pivoted on their own innovations. Richard Dawkins states that in biology it is genes which really matter, and we as people are just vessels for the conveyance of genes. It’s the same with ideas or “memes”. We are the vessels that hold and communicate ideas, and now that pool of ideas percolates on a global basis more rapidly than ever before.

In the next 6 years, three billion minds will come online for the first time to join this global conversation (via inexpensive smart phones in the developing world). This rapid influx of three billion people to the global economy is unprecedented in human history, and so to, will the pace of idea-pairings and progress.

We live in interesting times, at the cusp of the frontiers of the unknown and breathtaking advances. But, it should always feel that way, engendering a perpetual sense of future shock.

[Doge Tipping @Dogetothemoon]

@pmarca probably because people realize mainstream media is full of BS

[🇺🇸ColonelMAGAMark🇺🇸 @ColonelMark4]

@pmarca Mark Twain and newspapers:

[Isabel Brown @theisabelb]

Teenagers are sharing photos of their AP U.S. Government textbooks, and the sheer amount of indoctrination is wildly disturbing.

Apparently, Barack Obama is ideologically a right wing authoritarian.

Hillary Clinton and George W Bush are entirely indistinguishable politically.

Donald Trump is of course virtually the same as Hitler.

@tedcruz is apparently more radically authoritarian than Fidel Castro AND Joseph Stalin..??!!??

@Linda_McMahon — can we expedite some major changes to American public education?

[Hillel Fuld @HilzFuld]

What Israel’s then female prime minister, Golda Meir said over five decades ago is almost a prophecy.

Every word is still relevant and highly accurate.

[Elon Musk @elonmusk]

Wow

[Gavin Baker @GavinSBaker]

Most interesting chart I’ve seen in quite some time. From @eglyman

[StockMarket.News @_Investinq]

Sam Altman told the world exactly what skills will matter when AI takes over 30 to 40 percent of the global economy.

He was asked what his own kids should do to survive it.

His answer was surprisingly human.

He said the single most valuable thing anyone can build right now is the meta-skill of learning how to learn.

Not a degree or a certification but the raw ability to adapt when everything around you changes.

He also said learning to understand what other people actually want and building useful things for them will be more valuable than almost any technical knowledge.

That skill has never been automated and is not close to being automated.

He said human creativity and the desire to express it are, in his words, limitless.

Every major technological revolution increased the demand for creative, curious, and socially intelligent people, not decreased it.

The Industrial Revolution is the clearest parallel.

Machines replaced physical labor and people were terrified.

The next generation took those machines and built industries, art forms, and institutions nobody had conceived of before.

The people who thrived were not the ones who competed with the machines. They were the ones who learned to direct them toward something new.

That dynamic is already playing out right now with AI.

The practical implication is this, depth in a single rigid skill is becoming less valuable.

The ability to move across domains, pick up new tools quickly, and apply judgment in ambiguous situations is becoming more valuable.

Altman also pointed to something most career advice ignores entirely, learning how to interact with the world, build relationships, and earn trust from other people.

Those are things AI can simulate but cannot replace.

The honest opportunity in this moment is not to outrun AI. It is to focus on the things that make you irreducibly human.

Curiosity, judgment, empathy and the ability to ask the right question before anyone knows what the right question is.

The people who will matter most in an AI-driven economy are not necessarily the ones who understand the technology deepest.

They are the ones who can figure out what the technology should actually be used for.

Altman has spent his career betting on human potential in the face of technological disruption.

Based on every historical precedent, that is still the right bet to make.

[Mor Edge Insight @MorEdge_Insight]

One of the best interviews you’ll watch this week. The phenomenal @visegrad24 interviews the brilliant @Imamofpeace. I encourage you to watch all of it. You can thank me later. Or better yet, thank @visegrad24. Exceptional 🔥

[Ricardo @Ric_RTP]

Jensen Huang just called out every CEO who’s been firing people “because of AI.”

Jim Cramer asked him why companies are laying people off if AI is supposed to make everyone MORE productive.

Jensen's answer:

"For companies with imagination, you will do more with more. For companies where the leadership is just out of ideas, they have nothing else to do. They have no reason to imagine greater than they are. When they have more capability, they don't do more."

Read that again.

The man who built the most important tech company on Earth just told you that if your CEO is using AI to cut headcount, it means one thing:

They have no imagination.

They have no vision for what comes next.

They got handed the most powerful tool in human history and their FIRST instinct was to fire people.

This is the CEO of NVIDIA. The company whose chips power every AI system on the planet.

If anyone on Earth has the right to say "AI replaces workers," it's Jensen Huang.

And he said the OPPOSITE.

He said every carpenter could become an architect. Every plumber could become an architect. AI elevates capability. It doesn't eliminate it.

But here's where it gets really interesting...

During the same interview, Jensen revealed something nobody's talking about:

He said AI startups like OpenAI and Anthropic are seeing their revenues increase by one to two billion dollars a WEEK. And he wishes these companies were public so the world could see what he sees.

One to two billion per week.

That's a $50 to $100 BILLION annualized run rate.

For companies that most people think are burning cash and making nothing.

The entire Wall Street narrative that "AI companies aren't profitable" might be completely wrong.

Jensen sees their numbers. He sees their compute orders. He sees their growth. And he's saying the revenue is real.

So if the money IS real, why are other companies firing people?

Because they're not building AI products. They're not creating new revenue streams. They're not using AI to expand into new markets.

They're using AI as an EXCUSE to cut costs because they ran out of ideas 3 years ago and need something to tell the board.

Jensen's company added $500 billion in new orders in 5 months. He expects $1 trillion in cumulative revenue through 2027 from just two product lines.

That number doesn't include the new chips, systems, or partnerships announced this week.

And he's not cutting people. He's hiring.

Because when you have imagination, more capability means MORE opportunity. Not less headcount.

Meanwhile Salesforce cut thousands. Meta cut thousands. Amazon cut thousands. All blaming "AI efficiency."

Jensen's response: You're out of imagination.

He also said something that stuck with me.

Cramer asked if he ever thought he'd build a $10 to $20 trillion company while waiting tables at Denny's.

His answer: "I was just trying to make it through the shift."

Biggest tip he ever got? Two, three dollars.

Now he's building tech that increased computing demand by one million times in two years.

He announced OpenClaw, which he says is as big as ChatGPT.

And he's got 21 months of new business that isn't even counted in the trillion dollar figure yet.

When asked how long he plans to keep working?

"I'm hoping to die on the job. And I'm not hoping to die anytime soon."

This is a man who believes every single thing he's building.

And his message to every CEO using AI to justify layoffs is simple...

You're not innovating. You're surrendering.

The technology wasn't built to shrink companies.

It was built to make them limitless.

If your leadership can't see that, the problem isn't AI.

It's THEM.

[P5 Health Ventures @P5Health]

I try to keep politics out of P5 as it is about healthcare and building companies. But this is in my feed and I cannot ignore it. This young man was a beast. No way he committed what they accused him of. They used him as a warning to their people. No caring about human life or justice. Beyond… May he rest in peace - which should have come after a long life well lived.

[Eric Daugherty @EricLDaugh]

🚨 WOW. The Iranian Islamic regime just publicly hanged 19-year-old champion wrestler Saleh Mohammadi as part of the crackdown on protests

"His execution was a blatant political m*rder."

Iranians who rise up are on the right side.

Rest in peace 🙏🏻

[NDTV @ndtv]

"Israel acted alone against gas compound": Israeli Prime Minister Benjamin Netanyahu clarifies after Donald Trump's rebuke

[Camus @newstart_2024]

Dr. Thomas Seyfried (cancer researcher) drops a stark warning: Cancer is primarily a mitochondrial metabolic disorder—not just genetic.

The key to slashing risk? Keep your mitochondria healthy so cells can't go dysregulated and ferment.

His practical advice:

- Live in semi-nutritional ketosis (like traditional/hunter-gatherer lifestyles where cancer is rare).

- Track your Glucose Ketone Index (GKI) — aim to keep it below 20 (ideally much lower, e.g., 1-2 range for strong metabolic therapy per his research).

- GKI = [glucose (mmol/L)] / [ketones (mmol/L)]. Lower = healthier mitochondria, remote cancer probability.

- Modern life (processed carbs, obesity, inactivity, stress, screen addiction) damages mitochondria → obesity epidemic, childhood obesity as "canary in coal mine," rising young-adult cancers.

If you binge and spike into red zone? Act fast to return to green—prevents cancer, diabetes, heart disease, dementia—all tied to mitochondrial dysfunction.

Parents: Morbidly obese kids are on path to lifelong mitochondrial stress—knowledge gap is the real neglect.

What's one step you're taking to protect your mitochondria (keto, fasting, exercise, etc.)?

[P5 Health Ventures @P5Health]

Best ever

[Vala Afshar @ValaAfshar]

This may be the most important life advice from one of the greatest thinkers of all time

[Noa Tishby @noatishby]

I’m in the bomb shelter again. Rocket sirens continue to ring across Israel as the Islamic regime in Iran launches ballistic missiles at millions of innocent civilians. This evil regime cannot have a nuclear weapon. That’s why we have to take action now.