This episode is sponsored by Notion. Learn more about Notion's Developer Platform today at https://notion.com/mlst Protein 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 press 00:01:03 The protein folding bottleneck and CASP 00:04:39 The Nobel, the database, and the move to Anthropic 00:05:50 Sponsor (Notion) and framing: what AlphaFold does not claim 00:07:39 Proteins as self-assembling nanomachines 00:12:24 From structures to biology: drug discovery and Midnolin 00:17:37 The humility of AlphaFold: a narrow predictor 00:22:18 Inside the architecture: Evoformer, IPA and FAPE 00:30:20 Ruthless empiricism: ablations and 100x in data 00:35:20 Predict, control, understand 00:40:00 Against the bitter lesson; AlphaFold 3 as diffusion 00:45:07 Intelligence, representations and AGI 00:49:23 Epilogue: AlphaFold in Africa 00:52:16 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 2024 https://www.nobelprize.org/prizes/chemistry/2024/summary/ [00:05:18] BioStruct Africa https://www.biostructafrica.org/ [00:18:03] Isomorphic Labs https://www.isomorphiclabs.com/ paper: [00:03:09] AlphaFold Protein Structure Database https://doi.org/10.1093/nar/gkab1061 [00:17:25] Accurate structure prediction of biomolecular interactions with AlphaFold 3 https://www.nature.com/articles/s41586-024-07487-w [00:22:18] Highly accurate protein structure prediction with AlphaFold https://www.nature.com/articles/s41586-021-03819-2 [00:23:10] Midnolin promotes degradation of substrates independent of ubiquitination https://doi.org/10.1126/science.adh5021 [00:27:00] Improved protein structure prediction using potentials from deep learning https://www.nature.com/articles/s41586-019-1923-7 tool: [00:03:09] AlphaFold Protein Structure Database (EBI) https://alphafold.ebi.ac.uk/ [00:45:55] AlphaEvolve: a coding agent for designing advanced algorithms https://deepmind.google/blog/alphaevolve-a-gemini-powered-coding-agent-for-designing-advanced-algorithms/ other: [00:39:40] The Bitter Lesson http://www.incompleteideas.net/IncIdeas/BitterLesson.html --- ReScript: https://app.rescript.info/share/d8cde5c221fb71e2c0f5aafe94f90dfa Disclaimer - not sponsored, editorial with us - we filmed it at GDM, London