Tristan Farmer

If Hantavirus mutated into a global threat, it would unleash AI + biotech unlike anything we've ever seen. > genome sequenced and public in 4 hours > AlphaFold maps every protein target > AI screens 10,000 drugs in 24 hrs > 50 vaccine candidates designed simultaneously > AI designed antibodies in days > risk of death computed instantly > decentralized trials launch globally > enroll from home > 20 countries manufacturing at once > first doses in three weeks > real-time dose characterization > your genome + biomarkers determine your protocol > variant map updates every hour No one would wait for governments.

The most underrated trait in science is the willingness to change your mind when the facts change.

Next time a VC tells you your company is not VC-scale, send them this

Today we're announcing ESMFold2, an open scientific engine to power prediction, design, and discovery across protein biology. The new model delivers state of the art performance on protein interactions, especially antibodies, a critical modality for therapeutics. We have designed and validated miniprotein binders and single chain antibodies across five therapeutic targets that are important in cancer and immunology. We are seeing very high success rates, and affinities at levels consistent with therapeutic activity. We’re also releasing an atlas of 6.8 billion proteins, and 1.1 billion predicted structures. ESMFold2 is built on a state of the art language model that has been trained on billions of protein sequences. A world model of protein biology emerges through language modeling. We’ve used the techniques of mechanistic interpretability developed to understand large language models to understand the concepts ESM uses to represent proteins. The model’s representation space has a compositional organization of features across scales, levels of complexity, and abstraction, that reflects and mirrors the understanding of protein biology developed through a century of empirical science. This understanding emerges without prior knowledge, just from language modeling of protein sequences. Language models are becoming a powerful substrate to understand and program biology. The design of protein interactions is one of the most fundamental problems in biophysics, and has critical implications for the discovery of new medicines. A simple gradient based search with the model was able to discover high-affinity protein binders. I'm excited by the potential this has to accelerate basic science and the understanding of proteins. And especially for the new avenues it opens up for therapeutic design and medicine.

Steven Bartlett says a few glasses of wine ruined the next 3 days of his life “It's one of those areas where you don't understand the hidden cost until you really give it up for a while. I stopped drinking at 30 years old. I'm now 33. When I was 31, I thought, I'll have a drink again because now I could really A/B test it. I had a year of not drinking, decided to have a drink again” “It ruined three days of my life. I had a couple of glasses of wine, didn't get drunk. It ruined three days of my life because of the domino effect it caused” “I got worse sleep that night, and then because I got worse sleep that night, I ate more poorly the next day because my dopamine system or whatever, the cortisol system was all messed up. I podcasted worse. I didn't go to the gym that day or the day after because I felt really bad. I then slept worse, and I could track all of this on my Whoop”