DeepMind and Biohub Panel: AlphaFold Is Just the Start for Biological AI

1 reports archived0 independent sourcesupdated 10/10/2026, 08:31:26

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Pushmeet Kohli from Google DeepMind and Sal Candido from Biohub discuss the future of AI in biology. They argue that AlphaFold's structural prediction is merely a starting point, as scaling compute alone cannot solve all protein folding mysteries. The panel highlights the need to move beyond individual proteins toward cellular system modeling and discover new scaling laws in biological data.

LATEST/Pushmeet Kohli from Google DeepMind and Sal Candido from Biohub discuss the future of AI in biology. They argue that AlphaFold's structural prediction is merely a starting point, as scaling compute alone cannot solve all protein folding mysteries. The panel highlights the need to move beyond individual proteins toward cellular system modeling and discover new scaling laws in biological data.

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Latent SpaceT1·Oct 10, 08:3168 pts
DeepMind and Biohub Panel: AlphaFold Is Just the Start for Biological AI
- AlphaFold's success hasn't ended the protein folding problem; current models still lack complete understanding of complex biological systems.
- AI applications in biology are seeking breakthroughs by balancing general-purpose architectures with scientific intuition, requiring specific scaling laws for biological data.
- Future biological AI models must move beyond single-protein prediction toward predictive models of living systems capable of simulating cells and disease mechanisms.
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