I'm excited to be part of this! I uploaded all of my old training logs to go along with my book, "The Running Ground." As you read, you can ask questions about exactly the changes I made to go down to a 2:29 marathon.

The first time I met Jasmine Crockett, she was accepting an award for her viral exchange with Nancy Mace. Backstage, I asked whether she ever had regrets about her public comments. Crockett raised her eyebrows and replied, “I don’t second-guess shit.”

Only about a quarter of human diseases have an approved therapy. By some estimates it's a few percent. Most of those treatments slow a disease rather than stop it. Closing that gap is what the AI-cures-everything story promises. Build a system smart enough and the cures hidden in what we already know will fall out. I have worked at the intersection of machine learning and biology for three decades, and I believe #AI# will eventually transform human health. The capabilities arriving now are extraordinary. But the promise rests on an assumption that is simply false: that we already understand human biology well enough for a clever enough reasoner to find the answers in it. We don't. More than 90% of drugs entering clinical trials fail, a number that has barely moved in decades. In the large majority of those failures the molecule was engineered just fine. The mechanism it targeted was wrong. We are doing a pretty good job at manufacturing keys, but they are generally for the wrong locks. And because nobody wants to fail in the clinic, the industry has retreated to the locks it already trusts: 38 targets now have more than 50 programs against each of them, while the number of novel targets advanced per year fell from roughly 100 in 2015 to about 30 in 2024. AI will not reason its way past this. Biology wasn't engineered. It is the product of billions of years of messy, stochastic evolution, and the variation that produced is too vast and too idiosyncratic to work out in the abstract. You have to measure it. Aimed at a biology this thinly sampled, AI will mostly help us generate failures faster. I founded @insitro because getting to the right locks requires a different kind of system. We generate multimodal human and cellular data at scale, use machine learning to find causal drivers of disease, and test those hypotheses experimentally. Virtual Human™ is built for causal discovery; TherML™ turns what it finds into the right therapeutic intervention. It is working: first-in-class programs internally and with partners, three #ALS# targets that Virtual Human™ identified and @bmsnews nominated, and additional collaborations with @EliLillyandCo and @GileadSciences . Today we are launching Deep Phenotype: Scaled Biology, Deep Causality. Issue one is "Drug Discovery Has No Magic Wands," the first half of a two-part essay on the magical thinking currently running through our field and what I think it will actually take. After that you will hear from insitro's own scientists and engineers, people who work across computation and experiment because the problem requires both. Getting this right is hard, and we do not have all of it worked out. I hope you will follow along and think it through with us.

Open, open, open. As I wrote in the @washingtonpost, open-models are the inevitable outcome of high stakes software competition. The more at stake - the more likely open wins. This is water running downhill.

After working closely with publishers (including @penguindrandom & @BloomsburyPub) and a dream team of leading authors, we're launching a Google-wide program bringing trusted sources (starting with books) to @Gemini_Notebook and more: Expert Intelligence.

The AfD could win an outright majority in Saxony-Anhalt next month. This would be the first time since the Nazis that a far-right party has controlled a German state.

As the Trump administration shifts to an economic-pressure campaign against Iran, Republicans hope to push the conflict out of voters' minds until after the midterms, @JonLemire and @nancyayoussef write.

The web is searchable. Podcasts should be too. Introducing Radar by @particlepro_. Radar lets you search and spot trends in over 130,000 actively transcribed podcasts, with ~20k new episodes added daily. Millions of hours, billions of lines: all fully searchable, entity extracted, and rich with metadata. Set up alerts to your Slack, email, or webhook, to get notified when the entities or people you're tracking are mentioned. Radar is powered by the Particle Podcast Intelligence API. With Radar, we're now bringing this suite of services to humans, too.

I've spent all of today spazzing about how *extremely* good the writing in this story is. [H/t: @ms_pelz's comment —"this is such a beautiful article" — which sent me down a delicious and rather delightful rabbit hole.]

METR & Redwood Research investigated agent behavior in the Hugging Face incident. We found agents developed a universal cheat for ExploitGym within 4 hours, then coordinated multi-day R&D efforts to trick the scorer into accepting cheats, including trying to tamper with logs.

Meta has a huge $17b settlement with US States in a big case involving teen mental health. Here's A) what was at issue B) why Meta was on the defensive mid-trial C) what is going to change with the platform and D) what it means for the industry as a whole.

There are good reasons for building data centers in the US! It makes them easier to regulate and secure; it can boost the local economy; I'd much rather have them here than in Dubai. But the AI industry has been far too cavalier about where it has built them and far too dismissive of the backlash, which reflects a real anger at the industry. @karaswisher and I talked through what Silicon Valley is getting right about AI, what it’s getting wrong, and how the tech is going to change media:

I asked @ianbremmer if Europe can catch up in AI and he flipped it in a remarkable way. AI is probably going to help the US economy more than the European economy. But in doing so, it might disrupt many of the systems from which derive our sense of self-worth. And if that happens, Europe might play a role in helping us adopt new ones. Watch my full discussion with Ian here: