絞り込み結果
7 件並び順
47:22EN
Sequoia Capital· 2026年8月4日ポッドキャストFrom One in a Thousand to 15 Percent: Chai Discovery Treats Drug Design as a Scaling ProblemJoshua Meier and Matthew McPartlon tell Sequoia’s Training Data why antibody design is an engineering problem, not a bespoke science, and why they sell a molecular CAD suite instead of their own drugs.
58:27ENSequoia Capital· 2026年3月24日ポッドキャストEven a dumber AI can win science if it never leaves the labGinkgo Bioworks CEO Jason Kelly tells Sequoia why autonomous labs, not smarter models, will change how experimental science gets done.
41:13ENSequoia Capital· 2025年7月11日ポッドキャストFrom 49 Multiplications to 48: DeepMind’s AI Rewrites a Fifty-Year Math RecordPushmeet Kohli explains how AlphaEvolve couples Gemini with evaluators to invent algorithms, prove old conjectures, and change which scientific problems are even worth attempting.
55:40ENSequoia Capital· 2025年4月29日ポッドキャストTo Solve All Diseases, Isomorphic Labs Needs a Half-Dozen AlphaFoldsMax Jaderberg on turning DeepMind's game-playing research into a general AI engine for drug design—and why prediction alone cannot search a 10^60 molecular universe.
58:11ENSequoia Capital· 2025年4月15日ポッドキャストPatrick Hsu Wants an App Store for Biology, Not Just Better DrugsThe Arc Institute co-founder argues that Evo 2, trained on genomes rather than proteins, should underpin tools for every step of the scientific method.
41:42ENSequoia Capital· 2024年10月22日ポッドキャストNeural Networks Are Still Waiting for Their ThermodynamicsOpenAI researcher Dan Roberts on why physicists keep migrating into AI, and why the field still lacks the equivalent of the ideal gas law.
39:45ENSequoia Capital· 2024年9月24日ポッドキャストHarmonic’s Bet: Teach AI Math Directly, and the Riemann Hypothesis Falls by 2029Robinhood’s Vlad Tenev and Harmonic co-founder Tudor Achim tell Sequoia why math is reasoning, why Lean is the verifier, and why they refuse to wait for mathematical skill to emerge from scale.