We’re sharing a solution to the Navier-Stokes Millennium Prize Problem, one of the deepest problems at the frontier of mathematics. The proof was produced by a group of agents, using an OpenAI next-generation model significantly more capable than GPT-6 Astra. The problem concerns whether the description of smooth three-dimensional fluid motion modeled by the Navier-Stokes equations can break down. It has remained unresolved for roughly 90 years.

A buttload of developers are going through a tough time right now. Their identity has always been tied to their ability to write code, so now they feel threatened by this new era where *anyone* can write code. If they don't write code anymore, who are they? I'm very pragmatic, and yet I've struggled with this too, so I totally understand how tough it must be for others. You'll hear from these people everywhere. They are the ones fighting with everything they've got against AI-generated code. But they must understand this is an uphill battle. Manually writing code is destined to disappear. There's no going back.

I'm officially done reading AI-generated code. It's been two weeks since I looked at any of it. I think the IDE is officially on its way to the graveyard. The job is no longer about "writing code," so we need new tools that better reflect this new reality. While reviewing the code, I realized my only complaints were stylistic, and I wasn't finding any obvious bugs anymore. The more code I generated, the harder it became to keep track of every line. I found that my time is better spent designing ways to verify that the overall system works than looking at the code. State-of-the-art coding agents are better at writing code than I'd ever be, and I'm going to stop pretending otherwise. I still think these coding agents can't go too far without an experienced human guiding them, but we're past the point where we need to check every line of code.

🚨David Sinclair: “AI helped us do 160 years of biology work in two months.” ROGAN: “What?!” SINCLAIR: “We’re looking for molecules, a single molecule that can replace this cocktail... You need a molecule to do three or four activities in the cell. Finding one activity is what pharmaceutical companies do. It takes hundreds of millions, if not billions, to make a drug.” “My little lab of 20 people and students are trying to make one drug do three or four different things. That’s beyond the reach of pharmaceutical experience, at least five years ago.” “This funnel is full of a trillion molecules, and we have to come down to one. We don’t look for a trillion molecules at the bench. That would take 160 or thousands of years... so we do it inside the computer.” “We just use a lot of compute, and we dock each of these molecules against the enzymes that we now know how they work, thanks to Google DeepMind solving the problem of how all our proteins look, 20,000 of them.” 1 trillion candidate molecules. Filtered to 200. Two months. “Next week, we’re testing these 200 against human cells, and we’ve also got AI helping us tell if the human cells go from 92 years old back to 20. We can tell that just by looking at them, thanks to AI.” Dr. David Sinclair is a Harvard geneticist and one of the world's leading longevity researchers. Fascinating to hear how he's using AI to compress 160 years of biology work into two months. What other decades of work is about to become two months? @joerogan @davidasinclair

JUST IN: Telegram removed from the Apple App Store worldwide.

Noticer News has officially been banned from X for who knows what reason. @elonmusk this is literally the only news outlet in Australia accurately reporting about what’s going on in this country, the entire country needs this account restored immediately. So over this entire joke of a country

For years I've written that the entire economy is heading on-chain, and that the smart contract networks are the only rails it can possibly run on. Here's the thing people still haven't understood. Billions of AI agents are about to come online, and they're going to transact constantly... paying each other for compute, data, services, at a scale and speed no human market has ever seen. The existing financial system physically cannot carry them. It’s too slow. And it looks like institutions are catching on. Just last week: Franklin Templeton called AI agents the “use case that finally drives blockchain adoption” Coinbase's agent-payment rails got adopted by Google and Amazon. Samsung put stablecoins in the Galaxy wallet. David Solomon went against the rest of Wall Street to back the Clarity Act. And this is just one week. The rails are being laid, the machine economy is coming to run on them, and most people are still whinging over the daily price movements. We're about to onboard billions of agents onto a financial system that didn't exist twenty years ago. This is fucking wild.

POV: Vibe coder after hitting the daily usage limit.

Why does Anthropic do this? a) they need to show demand to keep growing b) they can train better models by getting more usage c) none of the above (comment why)