John Yang

A First Step Towards Interpretable Protein Structure Prediction With SAEFold, we enable mechanistic interpretability on ESMFold, a protein structure prediction model, for the first time. Watch @NithinParsan demo a case study here w/ links for paper & open-source code 👇

Anthropic CEO predicts cancer, Alzheimer's, heart disease, mental illness will be cured in less than 10 years ACCELERATE

Genomes are long but redundant. Not great for pretraining. To fix that, we've developed a lossless tokenization strategy that shortens sentence length by >2000x. For pretraining, we achieve a 0.55 validation CE on All of Us. Public replication on 1KG linked below.

Genomes are long but redundant. Not great for pretraining. To fix that, we've developed a lossless tokenization strategy that shortens sentence length by >2000x. For pretraining, we achieve a 0.55 validation CE on All of Us. Public replication on 1KG linked below.

Massive failure at Novartis to improve cardiovascular outcomes by lowering Lp(a). What went wrong? What now? Is Lp(a) useful? lifespan.com/blogs/magazine/…

Congratulations to @kiranmusunuru & @AhrensNicklas for not only pioneering individualized gene editing for Baby KJ, but also helping shape the regulatory pathway for the patients who will follow, with implications far beyond one patient or one disease. The FDA's new draft guidance (in reply) is an important advance, recognizing that multiple patient-specific variants of a gene-editing therapy can be evaluated within a common regulatory framework, while maintaining rigorous standards for safety and efficacy. This is how science and regulation should work together.inquirer.com/health/fda-guid…

Pretty striking how much better 5.2 is at Pfam classification. It's clear that models are already natively reasoning over biological inputs and may soon exceed the capabilities of specialized models. We're going to need a lot of scalable, broad expt capacity in the next few years.

this Peter Thiel backed startup says its AI can find a 14 point IQ gap between your embryos it's called Nucleus and their tagline is literally "have your best baby" here's how it happens: > you do a round of IVF and end up with a bunch of embryos > you send Nucleus the DNA data for each one, up to 20 embryos > its AI reads more than 7 million spots in each embryo's DNA and compares them to what it learned from more than a million people > then each embryo gets scored on things like IQ, disease risk, hair color and eye color > you pick the one you want implanted scoring your embryos starts at about $6,000 every one of these embryos is naturally yours btw, with zero gene editing involved America's main medical genetics group says this is moving too fast with too little evidence but that hasn't slowed Nucleus down at all when the founder announced this new AI, he wrote "AI is rapidly getting smarter... Now, humanity can too." they even put ads on the NYC subway that said "IQ is 50% genetic" lol personally i feel kinda uneasy about this but IVF got called playing god too, and now nobody blinks at it so for better or for worse, i think this will soon be accepted as normal

Couples with a family history of severe autism have been reaching out, hoping we could find a genetic cause to screen for. But the genetic signal was always sparse. Now our new work on rare variants & GPN-star has increased performance by over 50%. Another step towards ending genetic disease.

Just published our state-of-the-art polygenic scoring results. We're emphasizing our benchmarking methods, especially how we split. medrxiv.org/content/10.64898…

Introducing Kino: make videos end-to-end with Claude Code and Codex. Drop your footage, get highlights, edit together, send links for feedback, and let your agents cook. AI is becoming a great creative partner. Kino is a new home for your team and agents to collaborate.