Uploaded June 2026 | Updated September 2026, 1 week ago
This episode is sponsored by Notion. Learn more about Notion's Developer Platform today at 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)
predictioncenter.org
[00:04:39] The Nobel Prize in Chemistry 2024
nobelprize.org/prizes/chemistry/2024/summary
[00:05:18] BioStruct Africa
biostructafrica.org
[00:18:03] Isomorphic Labs
isomorphiclabs.com
paper:
[00:03:09] AlphaFold Protein Structure Database
doi.org/10.1093/nar/gkab1061
[00:17:25] Accurate structure prediction of biomolecular interactions with AlphaFold 3
nature.com/articles/s41586-024-07487-w
[00:22:18] Highly accurate protein structure prediction with AlphaFold
nature.com/articles/s41586-021-03819-2
[00:23:10] Midnolin promotes degradation of substrates independent of ubiquitination
doi.org/10.1126/science.adh5021
[00:27:00] Improved protein structure prediction using potentials from deep learning
nature.com/articles/s41586-019-1923-7
tool:
[00:03:09] AlphaFold Protein Structure Database (EBI)
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
incompleteideas.net/IncIdeas/BitterLesson.html
---
ReScript: app.rescript.info/share/d8cde5c221fb71e2c0f5aafe94f90dfa
Disclaimer - not sponsored, editorial with us - we filmed it at GDM, London
This episode is sponsored by Notion. Learn more about Notion's Developer Platform today at 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)
predictioncenter.org
[00:04:39] The Nobel Prize in Chemistry 2024
nobelprize.org/prizes/chemistry/2024/summary
[00:05:18] BioStruct Africa
biostructafrica.org
[00:18:03] Isomorphic Labs
isomorphiclabs.com
paper:
[00:03:09] AlphaFold Protein Structure Database
doi.org/10.1093/nar/gkab1061
[00:17:25] Accurate structure prediction of biomolecular interactions with AlphaFold 3
nature.com/articles/s41586-024-07487-w
[00:22:18] Highly accurate protein structure prediction with AlphaFold
nature.com/articles/s41586-021-03819-2
[00:23:10] Midnolin promotes degradation of substrates independent of ubiquitination
doi.org/10.1126/science.adh5021
[00:27:00] Improved protein structure prediction using potentials from deep learning
nature.com/articles/s41586-019-1923-7
tool:
[00:03:09] AlphaFold Protein Structure Database (EBI)
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
incompleteideas.net/IncIdeas/BitterLesson.html
---
ReScript: app.rescript.info/share/d8cde5c221fb71e2c0f5aafe94f90dfa
Disclaimer - not sponsored, editorial with us - we filmed it at GDM, London
