Patrick van Hoof
2.9K posts
@patvanhoof
Human-Centric Innovation: Computation, Intelligence, Consciousness, Health & Experience (Quantum, AI, Bio/Neuro, Robotics, 3D/4D, Space). Mens et Manus.
@PGC1a_RB Am I missing out by not taking CoQ10 with it?
Cognition, executive function, indeed existence itself, are whole-mind/body experiences. The answer is not inward, it is outward, and in the world.
Alex Karnal (@alex_karnal) is the most talented bio and healthcare investor I've ever met. He's spent 20 years in the industry and says 2025 was the single most exciting year he's seen. The start of a once-in-a-lifetime, trillion-dollar revolution in public health. He explains how few people realize we already have the medicines to prevent our deadliest diseases. The problem is that almost no one takes them. There's a population of people born with a mutation that means their bodies don't produce a protein called PCSK9. Their lifetime risk of cardiovascular disease is 88% lower than yours. Pharma turned that genetic advantage into a drug. It's been approved for years, but the number of people taking it is still vanishingly small. Partly because high cholesterol is a silent killer. You feel nothing, right up until you have a heart attack. And partly because the health system makes it punishingly hard to stay on a preventive drug like a PCSK9 inhibitor. In other words, the medicine works, but the system around it doesn't. That's what's starting to change, and in this episode, Alex explains why. We discuss the "health stack" he believes can add a decade to most lives, why oral GLP-1s are breaking every adoption record in pharma, peptides and citizen pharmacology, and what AI is doing to drug discovery. I wish I had an "Alex" for every interesting topic. We've been having versions of this conversation for over five years, and every single one is as clear and as useful as this one. Enjoy! Timestamps: 0:00 Intro 1:00 The State of Modern Medicine 5:00 Designing the Modern Health Stack 12:17 The GLP-1 Inflection Point 19:18 The Biological Mechanisms of GLP-1 30:36 Overcoming Frictions in Healthcare 34:19 Cardiovascular Disease 44:04 Addressing Alzheimer's 47:04 The Future of Cancer 57:33 Drug Discovery 1:05:25 AI and Scientific Super Intelligence 1:14:40 Citizen Pharmacology and the Peptide Movement 1:18:13 Background and Career Journey 1:31:09 Braidwell's Investment Approach 1:33:30 The Kindest Thing
@FT It’s not ceding sovereignty, it’s an inability to compete
each one of his companies is philanthropic at the core
Yann LeCun was right the entire time. And generative AI might be a dead end. For the last three years, the entire industry has been obsessed with building bigger LLMs. Trillions of parameters. Billions in compute. The theory was simple: if you make the model big enough, it will eventually understand how the world works. Yann LeCun said that was stupid. He argued that generative AI is fundamentally inefficient. When an AI predicts the next word, or generates the next pixel, it wastes massive amounts of compute on surface-level details. It memorizes patterns instead of learning the actual physics of reality. He proposed a different path: JEPA (Joint-Embedding Predictive Architecture). Instead of forcing the AI to paint the world pixel by pixel, JEPA forces it to predict abstract concepts. It predicts what happens next in a compressed "thought space." But for years, JEPA had a fatal flaw. It suffered from "representation collapse." Because the AI was allowed to simplify reality, it would cheat. It would simplify everything so much that a dog, a car, and a human all looked identical. It learned nothing. To fix it, engineers had to use insanely complex hacks, frozen encoders, and massive compute overheads. Until today. Researchers just dropped a paper called "LeWorldModel" (LeWM). They completely solved the collapse problem. They replaced the complex engineering hacks with a single, elegant mathematical regularizer. It forces the AI's internal "thoughts" into a perfect Gaussian distribution. The AI can no longer cheat. It is forced to understand the physical structure of reality to make its predictions. The results completely rewrite the economics of AI. LeWM didn't need a massive, centralized supercomputer. It has just 15 million parameters. It trains on a single, standard GPU in a few hours. Yet it plans 48x faster than massive foundation world models. It intrinsically understands physics. It instantly detects impossible events. We spent billions trying to force massive server farms to memorize the internet. Now, a tiny model running locally on a single graphics card is actually learning how the real world works.
Alex Karnal (@alex_karnal) is the most talented bio and healthcare investor I've ever met. He's spent 20 years in the industry and says 2025 was the single most exciting year he's seen. The start of a once-in-a-lifetime, trillion-dollar revolution in public health. He explains how few people realize we already have the medicines to prevent our deadliest diseases. The problem is that almost no one takes them. There's a population of people born with a mutation that means their bodies don't produce a protein called PCSK9. Their lifetime risk of cardiovascular disease is 88% lower than yours. Pharma turned that genetic advantage into a drug. It's been approved for years, but the number of people taking it is still vanishingly small. Partly because high cholesterol is a silent killer. You feel nothing, right up until you have a heart attack. And partly because the health system makes it punishingly hard to stay on a preventive drug like a PCSK9 inhibitor. In other words, the medicine works, but the system around it doesn't. That's what's starting to change, and in this episode, Alex explains why. We discuss the "health stack" he believes can add a decade to most lives, why oral GLP-1s are breaking every adoption record in pharma, peptides and citizen pharmacology, and what AI is doing to drug discovery. I wish I had an "Alex" for every interesting topic. We've been having versions of this conversation for over five years, and every single one is as clear and as useful as this one. Enjoy! Timestamps: 0:00 Intro 1:00 The State of Modern Medicine 5:00 Designing the Modern Health Stack 12:17 The GLP-1 Inflection Point 19:18 The Biological Mechanisms of GLP-1 30:36 Overcoming Frictions in Healthcare 34:19 Cardiovascular Disease 44:04 Addressing Alzheimer's 47:04 The Future of Cancer 57:33 Drug Discovery 1:05:25 AI and Scientific Super Intelligence 1:14:40 Citizen Pharmacology and the Peptide Movement 1:18:13 Background and Career Journey 1:31:09 Braidwell's Investment Approach 1:33:30 The Kindest Thing
