Alpha fold

Why AlphaFold Didn't Solve Protein Folding — Pushmeet Kohli, Google DeepMind & Sal Candido, Biohub

Why AlphaFold Didn't Solve Protein Folding — Pushmeet Kohli, Google DeepMind & Sal Candido, Biohub

A panel with Google DeepMind's Pushmeet Kohli and Biohub's Sal Candido, moderated by Brandon Anderson, examines how AI should be built for biology. Topics include scaling laws and data quality, the bitter lesson applied to data, AlphaFold's handcrafted design and its limits, protein dynamics, cryo-EM as a richer data source, trust and calibration versus interpretability, and why curing disease requires 10x breakthroughs.

Chai Discovery's Bitter Lesson: Drug Design Is Another Scaling Problem

Chai Discovery's Bitter Lesson: Drug Design Is Another Scaling Problem

Chai Discovery is revolutionizing drug discovery by treating biology as an engineering problem, leveraging AI—particularly diffusion models and the "bitter lesson" of scaling—to design molecules rather than merely discover them. Their approach has boosted antibody design hit rates from 0.1% to 16%, aiming for a "Molecular CAD" suite that collapses discovery timelines from months to days. They partner with pharma, building infrastructure and creating a data flywheel to develop higher-quality, more targeted medicines for previously undruggable diseases.

Demis Hassabis on Building DeepMind, AlphaFold, and the Final Stretch to AGI

Demis Hassabis on Building DeepMind, AlphaFold, and the Final Stretch to AGI

Demis Hassabis, CEO of Google DeepMind, outlines the path to AGI, which he predicts by 2030. He discusses the profound impact of AI on science, particularly in revolutionizing drug discovery with systems like AlphaFold, and posits that AI will enable new forms of simulation-based science. Hassabis also delves into the philosophical underpinnings of his work, viewing information as the universe's most fundamental quantity and advocating for developing AGI as a powerful tool before tackling the deeper questions of consciousness.

How to Build the Future: Demis Hassabis

How to Build the Future: Demis Hassabis

Demis Hassabis, CEO of Google DeepMind, outlines the remaining challenges on the path to AGI, including memory, continual learning, and true reasoning. He discusses how learnings from AlphaGo are shaping agent development, the strategic importance of powerful small models like Gemma, and his vision for AI as the ultimate tool for scientific discovery, offering a framework for identifying breakthrough opportunities and advice for founders building in the age of AI.

The future of intelligence | Demis Hassabis (Co-founder and CEO of DeepMind)

The future of intelligence | Demis Hassabis (Co-founder and CEO of DeepMind)

Google DeepMind CEO Demis Hassabis discusses the path to AGI, focusing on the scientific frontiers of the next decade. He covers the importance of solving 'root node' problems like fusion energy, the challenge of 'jagged intelligence' in current models, and the promise of world models and simulations like Genie and SimA. The conversation also explores the balance between scientific rigor and commercial competition, and the profound societal and philosophical questions AGI will force us to confront.

Faster Science, Better Drugs

Faster Science, Better Drugs

Erik Torenberg, Patrick Hsu (Arc Institute), and Jorge Conde (a16z) discuss Arc's moonshot to create 'virtual cells' using foundation models to simulate biology. They cover why science is slow, how AI can accelerate drug discovery by predicting cellular perturbations, and the remaining bottlenecks in clinical trials and capital intensity that the biotech industry faces.