aiqbench analysis
This discussion clarifies that AlphaFold's success was a milestone rather than the final solution to protein folding, highlighting the limits of pure scaling laws in complex biological systems. The speakers argue that future breakthroughs will require integrating scientific intuition with specialized architectures to model entire living systems rather than isolated proteins. Ultimately, the conversation underscores that solving disease demands 10x leaps in understanding biology, not just incremental improvements via general-purpose AI.
Why AlphaFold Didn't Solve Protein Folding — Pushmeet Kohli, Google DeepMind & Sal Candido, Biohub
From the Bitter Lesson of AI scaling to the unsolved mysteries of protein folding, Google DeepMind’s Pushmeet Kohli and Biohub’s Sal Candido are rethinking what it takes to build AI that truly understands biology.
From the Bitter Lesson of AI scaling to the unsolved mysteries of protein folding, Google DeepMind’s Pushmeet Kohli and Biohub’s Sal Candido are rethinking what it takes to build AI that truly understands biology. In this special panel moderated by Brandon Anderson, they explore why AlphaFold’s breakthrough was only the beginning, why scaling compute and data alone won’t solve biology, and how the next generation of AI models could transform our understanding of proteins, cells, and human disease. We go deep on the future of AI-driven biology: finding scaling laws in biological data, the tradeoffs between scientific intuition and general-purpose architectures, why protein structure prediction is far from solved, and what it would take to build predictive models of living systems. Pushmeet reflects on the lessons behind AlphaFold, the limits of human interpretability, and whether future frontier models could understand other AI systems better than we can. Sal explains why protein language models may already contain scientific knowledge we haven’t unlocked, how biological modeling must move beyond individual proteins, and why achieving Biohub’s mission to cure all disease requires thinking in terms of 10x breakthroughs rather than incremental improvements. X: https://x.com/pushmeet X: https://x.com/pushmeet LinkedIn: https://www.linkedin.com/in/pushmeet-kohli-4838994/ LinkedIn: https://www.linkedin.com/in/pushmeet-kohli-4838994/ Biohub: https://biohub.org/team/salvatore-candido/ Biohub:…
Excerpt shown under the publisher's RSS terms · 200 words · full text and figures are on the publisher's site
Related coverage
Introducing SynthID Bio
Google DeepMind · Sep 30, 2026

Humanity’s Last Invention — Richard Socher of Recursive
Latent Space · Sep 14, 2026
Accelerating the search for antimicrobial peptides with Google Antigravity
Google DeepMind · Oct 15, 2026
Synthesis Superintelligence: from Semiconductors to Superconductors — Periodic Labs’ Liam Fedus and Ekin Dogus Cubuk
Latent Space · Oct 8, 2026