He won a Nobel here for AlphaFold. Then he left. - John Jumper

This episode is sponsored by Notion. Learn more about Notion's Developer Platform today at notion.com/mlstProtein folding stalled biology for fifty years. A sequence of amino acids dictates a three-dimensional shape, but reading that shape meant a year and roughly $100,000 of crystallography per structure. Then AlphaFold 2 won CASP14 so decisively the organizers called the problem essentially solved.In this documentary cut, John Jumper, who shared the 2024 Nobel Prize in Chemistry and has since left DeepMind for Anthropic, walks Tim Scarfe through what the system did and, more interestingly, what it did not. The architecture gets a proper dissection: MSAs, the Evoformer, invariant point attention, the FAPE loss, and Jumper's correction of the equivariance story, which ablations valued at roughly 2.5 of 30 GDT points rather than the whole win. He is blunt about the limits. AlphaFold predicts one experiment extraordinarily well; it is not a model of the cell, it does not capture dynamics, and on a given drug target it is "wrong nine times out of ten."From there: the AlphaFold Database of 200M+ predicted structures, AlphaFold 3 and ligands, Isomorphic Labs, and Jumper's quarrel with the bitter lesson, where finite data and human hypotheses still matter. Emmanuel Nji of BioStruct Africa closes the film on what changes when work that took years now takes months, and on training the next thousand structural biologists across Africa.---TIMESTAMPS:00:00:00 Cold open: predicting nature with a button press00:01:03 The protein folding bottleneck and CASP00:04:39 The Nobel, the database, and the move to Anthropic00:07:39 Sponsor and framing: what AlphaFold does not claim00:07:39 Proteins as self-assembling nanomachines00:12:24 From structures to biology: drug discovery and Midnolin00:17:37 The humility of AlphaFold: a narrow predictor00:22:18 Inside the architecture: Evoformer, IPA and FAPE00:30:20 Ruthless empiricism: ablations and 100x in data00:35:20 Predict, control, understand00:40:00 Against the bitter lesson; AlphaFold 3 as diffusion00:45:07 Intelligence, representations and AGI00:49:23 Epilogue: AlphaFold in Africa00:52:16 Closing: the case for hybrid science models---REFERENCES:organization:[00:01:55] Critical Assessment of Structure Prediction (CASP)https://predictioncenter.org/[00:04:39] The Nobel Prize in Chemistry 2024https://www.nobelprize.org/prizes/chemistry/2024/summary/[00:05:18] BioStruct Africahttps://www.biostructafrica.org/[00:18:03] Isomorphic Labshttps://www.isomorphiclabs.com/paper:[00:03:09] AlphaFold Protein Structure Databasehttps://doi.org/10.1093/nar/gkab1061[00:17:25] Accurate structure prediction of biomolecular interactions with AlphaFold 3https://www.nature.com/articles/s41586-024-07487-w[00:22:18] Highly accurate protein structure prediction with AlphaFoldhttps://www.nature.com/articles/s41586-021-03819-2[00:23:10] Midnolin promotes degradation of substrates independent of ubiquitinationhttps://doi.org/10.1126/science.adh5021[00:27:00] Improved protein structure prediction using potentials from deep learninghttps://www.nature.com/articles/s41586-019-1923-7tool:[00:03:09] AlphaFold Protein Structure Database (EBI)https://alphafold.ebi.ac.uk/[00:45:55] AlphaEvolve: a coding agent for designing advanced algorithmshttps://deepmind.google/blog/alphaevolve-a-gemini-powered-coding-agent-for-designing-advanced-algorithms/other:[00:39:40] The Bitter Lessonhttp://www.incompleteideas.net/IncIdeas/BitterLesson.html---ReScript: https://app.rescript.info/share/d8cde5c221fb71e2c0f5aafe94f90dfa