There have been a lot of announcements in the last few weeks about AI, so many that I decided to take a week off the app to slow down the pace of inbound takes for myself. I think making and breaking Millennium problems for various fields is good, I think it's good that frontier labs are pouring money into biology. Everything helps, and hopefully we hit an exponential on those returns. However, I also feel like there are so many low hanging fruit problems that are relevant to humans that affect billions of people today. A handful of diseases seriously impact the quality of life of so many Americans and I'd love to see progress towards tackling these. In medical training many of these diseases are somewhat disregarded as lifestyle or manageable with mild medications, but the truth is many of them have really poor medication adherence rates largely because they don't help much, so people opt to not take them and instead choose to deal with troublesome symptoms. So I am proposing a Boring Health Targets list! If you are at an AI lab please consider picking up some of these diseases and making them an area of interest! Many people are benefited from work on cancer or brain aging, but also a ton of resources are spent on addressing those through federal and venture funding. Not a lot of attention and talent are aimed at these (w/ roughly how many Americans you'd help): - GERD (~60M) - Chronic Kidney Disease (~35M) - COPD (~15M) - Peripheral neuropathy (from chemo, diabetes, aging etc) (20-30M) - Post-concussive syndrome (1-3M, mostly skewed younger) - Migraines (40-50M) - Endometriosis (~6.5M) - Urinary incontinence (~80-100M) - Peripheral artery disease (~6.5M) For many of the above conditions there are only palliative options, like vessels grafts for PAD or gabapentin for neuropathy, or terrible options like dialysis for CKD. Posting this for my friends at @AnthropicAI and @OpenAI !

Earlier this year, while at a philosophy festival, i met 3 performing clowns who told me they had all met at Ecole Phillipe Gaulier, the renowned French clown school, during their annual summer course every year i try and do one skill-based course in some domain that is totally foreign to me, and after hearing about clown school i signed up for the summer course this past june, and took two friends with me to rural France for it unlike how the wsj headline makes it appear, there was nobody in the course who wasn't a professional theater or improv artist, apart from my friends and i, who were very much the worst people in class fwiw clown school was v intense. the teachers put you on stage in front of everyone and give orders such as 'stay here until you make people laugh, but you cant speak unless it's to make the sound of an electrical item'. and if you did badly the teachers would heckle you and even make some people cry the experience was much more introspective than i thought it would be. i have no dreams of being a performer, but to be forced to stay in the realm of the awkward and to make the most out of a 'flop' helped me learn the edges of my own comfort levels and push them slightly. i notice now in social situations i feel more at ease, and my fiance said i came back from clown school with improved poise and presence. it for sure made public speaking far less scary would i recommend it to others? yes and no. yes, if you're in a position where you perform/ speak publicly often and no if you're not. clown school is pretty serious and my lack of skills in this domain felt somewhat disrespectful to the rest of the attendees

What if the proteome encodes more biology than we can see from proteins alone? What if protein degradation is not simply cellular disposal, but also a source of biological function? Every cell is continuously breaking down and remodeling proteins, generating a vast and dynamic pool of peptide fragments. We propose that some of these fragments are not inert byproducts, but bioactive molecules with important roles in biology. In our new Essay in @PLOSBiology, “Encrypted immunity mediated by peptides,” Zhenrun J. Zhang, @YMerbl, and I explore this idea through the emerging framework of encrypted immunity: bioactive peptides hidden within larger proteins that can be released through proteolysis and contribute to antimicrobial defense, immune signaling, inflammation, and potentially broader aspects of physiology. AI and machine learning are helping us explore this hidden molecular space at a scale that was previously inaccessible, uncovering candidate peptides in humans, microbes, archaea, venoms, and even extinct organisms. But identifying sequences is only the beginning. The deeper questions are biological: Which peptides are actually produced in vivo? When and where are they generated? How is their release regulated? What functions do they perform? And how do we distinguish meaningful biological signals from the background of protein turnover? Answering these questions will require computation and experimentation to advance together. To me, this points to a broader opportunity for AI in biology: using machines not simply to predict biology, but to help us uncover its hidden organizing principles—and ultimately learn how to engineer them for human health. If this framework holds, it could deepen our understanding of how biological information is encoded and deployed, while opening new directions for therapeutics and diagnostics. Much remains to be learned, and I’m excited about what comes next. Weizmann Institute of Science, @Penn, @CBE_Penn, @PennBioeng, @PennEngineers, @PennMedicine, @PennChemistry, @PennMicro, @PennPsych, @PennSAS. journals.plos.org/plosbiolog…

There is a child with a rare disease who is currently suffering and struggling to manage his symptoms. Rare as this is, you can directly help him. Today we are launching the "Rare Disease, Real Kid" Hackathon, and there are $50,000 in prizes from @AnthropicAI and @awscloud. We (@huggingface & @Sagebio) are helping this child open his genome and clinical data to the community, so that we can find what's caused his disease and what currently-approved drugs could help him. I doubt I need to motivate this much further or explain how rare it is for a family to share their child's genome and clinical data, but if you're not sure, consider this: Until very recently, it wasn't feasible for patients like this to get treatment because their disease was so rare that the economics could never justify the investment. Now, as we've seen, people with rare diseases are starting to be able to find the answers themselves (with the help of AI tools, cheaper sequencing, etc). This kid is not able to do that for himself and neither are his parents, so we're asking you for help. Both for this kid and to prove that it's possible for everyone else suffering from a rare disease. More details in 🧵. sagebio-rare-disease-real-ki…

I need to hear success stories. For those of who you fully healed from their mysterious chronic health issues, what did you do?

we look for novel behavior in AI and overlook how much nature is bursting with complex behavior that we still only shallowly understand

JUST IN: Scientists warn of “urgent” biosecurity concerns after AI successfully designs 16 new viruses capable of replicating inside cells.

It was a big mistake attacking Sid, cancer. You created a very dangerous enemy.

BREAKING: A helicopter carrying President Trump reportedly came within one mile of colliding with a jet in Washington, DC, in what officials are calling a major security incident, per NYT

Today we announced a landmark partnership with @EliLillyandCo to use our AI models to design recombinases for genetic medicine—a collaboration valued at up to $2.25 billion before royalties. The goal: use Profluent's AI models to design recombinase editors capable of inserting long stretches of DNA at precise locations in the genome. Read the press release for more: businesswire.com/news/home/2…

Demis Hassabis: If you know the structure of a protein, the real question becomes—where will your drug bind, and what will it actually do? That’s where the next wave of AI comes in. Not just predicting structures, but modeling interactions, outcomes, and real biological impact. At Isomorphic Labs, this is already happening—with 17 active drug programs and partnerships with giants like Eli Lilly and Novartis. The goal? Scale that to 100. This is a fundamental shift in how medicine gets built. Instead of slow, expensive trial-and-error in wet labs, AI allows researchers to run thousands of hypotheses in silico—hundreds to thousands of times more efficiently. The wet lab becomes validation, not exploration. Drug discovery is turning into a computational problem. Faster cycles, smarter predictions, and potentially massive breakthroughs in human health.

How outcomes in relapsed/refractory multiple myeloma changed, from 1986 to 2026

So, there’s a $1.5 billion judgement against Anthropic for including 480,000 books in training their AIs. Five of my books are among them. Word is, there might be $1,500 payout per book, according to my agent Max Brockman. I wrote him the following:

Excited to openly release E1. We use E1 for protein design and now you can too.

Another banger from @rivatez... was gonna use the flame emoji but that seemed insensitive. thespectator.com/topic/slow-…