絞り込み結果
77 件並び順
45:08ENSam Altman on AI Discovery, Consciousness, Compute and a Human-Centered FutureMatthew Berman, Sam Altman · Forward FutureIn a conversation with Matthew Berman, Altman discusses scientific progress, personal assistants, recursive self-improvement and the importance of human agency.
40:44EN
3Blue1Brown· 2026年10月16日Grant Sanderson: There's never been a better time to go into mathGrant Sanderson, Constantin Kogler · 3Blue1BrownStudents fear AI has solved mathematics. Grant Sanderson argues the opposite: even if machines prove theorems better than we do, the institution of math stays valuable—and this is a rare moment when newcomers can reshape it.
39:23EN
No Priors: AI, Machine Learning, Tech, & Startups· 2026年10月15日ポッドキャスト · 2 人The Defenders' Window: Greg Brockman on AI-Generated Knowledge, Drug Discovery, and the New Physics of Cybersecurityホスト Sarah Guo, Elad GilOpenAI's president explains why solving open math problems is a proof point for science, how proactive agents change product form, and why security spending must exceed software spending.
38:10EN
Google DeepMind· 2026年10月1日From deepfakes to DNA: how SynthID watermarks AIHannah Fry, Pushmeet Kohli, Jeremy Ratcliffe · Google DeepMindHannah Fry sits down with Pushmeet Kohli and Jeremy Ratcliffe to explain SynthID: a mathematical watermark now used on text, images and video, and being extended to protein sequences so DNA synthesis companies can tell AI-designed molecules from nature.
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.
1:15:19EN
20VC with Harry Stebbings· 2026年4月14日ポッドキャスト · 2 人Anj Midha on Anthropic, Compute Bottlenecks and Building Frontier AIゲスト Anjney Midha · ホスト Harry StebbingsThe AMP founder recounts Anthropic’s early fundraising and explains his investment thesis around scientific feedback, compute coordination and AI infrastructure.
32:22EN20VC with Harry Stebbings· 2026年4月7日ポッドキャスト · 2 人Demis Hassabis on AGI, Scientific Discovery and the Challenges Aheadゲスト Demis Hassabis · ホスト Harry StebbingsThe Google DeepMind CEO discusses compute, continual learning, safety standards and his hopes for AI in science, medicine and energy.
29:26ENNo Priors: AI, Machine Learning, Tech, & Startups· 2026年4月3日ポッドキャスト · 2 人ChatGPT Almost Became a Meeting Bot. Its Co-Creator Is Now Rearranging Atomsホスト Sarah Guo, Elad GilLiam Fedus tells No Priors how Periodic Labs is connecting language models to experiments so materials science can run in a closed loop.
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.
1:43:39EN
Cognitive Revolution "How AI Changes Everything"· 2026年3月11日ポッドキャストFive Mutations Could Make a 60% Fatal Bird Flu Spread Between Peopleホスト Nathan LabenzJohns Hopkins assistant professor Jassi Pannu argues for locking down only the sliver of functional data that teaches models how to make pandemic viruses — and keeping the rest of biology open.
2:25:42ENCognitive Revolution "How AI Changes Everything"· 2026年2月14日ポッドキャストThe experts argued through the coffee break — and never agreed whether AI can build AIホスト Nathan LabenzOn a marathon Cognitive Revolution live show, a cancer-AI researcher, a former OpenAI board member, and a national-security analyst each hit a different wall in the boom.
1:34:42ENCognitive Revolution "How AI Changes Everything"· 2026年2月13日ポッドキャストA $500 Kernel, a Ten-Month Village, and the Temper of Agentsホスト Nathan LabenzJames Zou, Sam Hammond, and Shoshannah Tekofsky on science agents, America's knowledge-work bet, and what models actually do when you leave them alone.
0:47ENGPT-5 and an Automated Laboratory: A Scientific WorkflowMatthew Berman · Forward FutureMatthew Berman describes an OpenAI and Ginkgo Bioworks demonstration connecting an AI model to laboratory automation.
1:04:51ENCognitive Revolution "How AI Changes Everything"· 2026年2月1日ポッドキャスト125 million cells took a decade. The next billion takes monthsホスト Nathan LabenzMark Zuckerberg and Priscilla Chan on pairing a frontier biology lab with a frontier AI lab so models train on data that was designed for them.
48:14ENNo Priors: AI, Machine Learning, Tech, & Startups· 2025年11月13日ポッドキャスト · 2 人A New Drug Burns $2 Billion and 10 Years. Benchling's CEO Wants AI to Cut That to Threeホスト Sarah Guo, Elad GilMost medicines fail in years seven to ten, after hundreds of millions have already gone into the clinic—and Sajith Wickramasekara thinks sending things to space may already be easier.
1:29:30ENCognitive Revolution "How AI Changes Everything"· 2025年10月14日ポッドキャスト2,500 Compounds and a 51 Percent Hit Rate: How a Small Graph Net Found New Antibioticsホスト Nathan LabenzMIT's Jim Collins tells Nathan Labenz how a bootlegged 2018 project, a binary growth-inhibition label, and Chemprop graph networks pulled novel antibiotics out of chemical space that labs could never screen by hand.
1:01:49ENCognitive Revolution "How AI Changes Everything"· 2025年10月2日ポッドキャストChatGPT's Co-Creator Left to Put Nature in the Reward Loopホスト Nathan LabenzLiam Fedus and Ekin Dogus Cubuk on why language models still fail at physics, why literature data is too noisy to train on, and why Periodic Labs is aiming at a 200K superconductor.
1:55:02ENCognitive Revolution "How AI Changes Everything"· 2025年8月30日ポッドキャストA hundred experiments a day, and the valley of death in materialsホスト Nathan LabenzRadical AI’s co-founders tell Nathan Labenz how a closed loop of frontier models and a self-driving lab is meant to collapse a forty-year materials cycle into less than a decade.
13:30EN3Blue1Brown· 2025年8月17日How AlphaGeometry Combines Logical Proof with Creative ConstructionAleph0Aleph0 explains how a symbolic geometry solver gets surprisingly far without AI, and how a language model supplies the auxiliary constructions that take it to Olympiad level.
57:52EN
Unsupervised Learning: With Jacob Effron· 2025年8月13日ポッドキャストThey Aimed for 1%. The Lab Hit 20%. Chai Discovery Moved Antibody Design Onto the Computer.ホスト Jacob EffronJoshua Meier on three waves of AI drug discovery, why Chai-2 behaves like Photoshop for molecules, and why a 1% hit rate was supposed to be enough to change the industry.
2:28:14EN
Lex Fridman· 2025年7月23日ポッドキャスト · 2 人Nature Has Structure: Demis Hassabis on Learnable Reality and AGIゲスト Demis Hassabis · ホスト Lex FridmanThe Google DeepMind CEO argues that evolution-shaped systems can be modeled by classical learning, and that interactive world models sit on the path to AGI.
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.
49:27ENNo Priors: AI, Machine Learning, Tech, & Startups· 2025年7月3日ポッドキャスト · 2 人From 0.1% to 20%: Chai-2 Turns Antibody Design Into Prompt Engineeringホスト Sarah Guo, Elad GilChai Discovery co-founders Joshua Meier and Jack Dent tell Sarah Guo how a generative model now designs antibodies that bind on the first 24-well plate.
42:09ENNo Priors: AI, Machine Learning, Tech, & Startups· 2025年6月26日ポッドキャスト · 2 人AlphaEvolve found algorithms humans missed for 50 years — then sped up Gemini 23%ホスト Sarah Guo, Elad GilGoogle DeepMind’s Pushmeet Kohli and Matej Balog tell No Priors how an evolutionary coding agent searches algorithm space the way AlphaGo searched Go.もっと見る77 件中 24 件を表示