Ergebnisse
72 ArtikelSortieren
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.
40:44ENGrant 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.
39:23ENThe Defenders' Window: Greg Brockman on AI-Generated Knowledge, Drug Discovery, and the New Physics of CybersecurityModeration: 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.
38:10ENFrom 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.
47:22ENFrom 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.
1:15:19ENAnj Midha on Anthropic, Compute Bottlenecks and Building Frontier AIGast: Anjney Midha · Moderation: Harry StebbingsThe AMP founder recounts Anthropic’s early fundraising and explains his investment thesis around scientific feedback, compute coordination and AI infrastructure.
32:22ENDemis Hassabis on AGI, Scientific Discovery and the Challenges AheadGast: Demis Hassabis · Moderation: Harry StebbingsThe Google DeepMind CEO discusses compute, continual learning, safety standards and his hopes for AI in science, medicine and energy.
58:27ENEven 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.
1:43:39ENFive Mutations Could Make a 60% Fatal Bird Flu Spread Between PeopleModeration: 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.
2:25:42ENThe experts argued through the coffee break — and never agreed whether AI can build AIModeration: 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.
1:34:42ENA $500 Kernel, a Ten-Month Village, and the Temper of AgentsModeration: 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.
1:04:51EN125 million cells took a decade. The next billion takes monthsModeration: 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.
48:14ENA New Drug Burns $2 Billion and 10 Years. Benchling's CEO Wants AI to Cut That to ThreeModeration: 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.
1:29:30EN2,500 Compounds and a 51 Percent Hit Rate: How a Small Graph Net Found New AntibioticsModeration: 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.
1:01:49ENChatGPT's Co-Creator Left to Put Nature in the Reward LoopModeration: 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.
1:55:02ENA hundred experiments a day, and the valley of death in materialsModeration: 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.
57:52ENThey Aimed for 1%. The Lab Hit 20%. Chai Discovery Moved Antibody Design Onto the Computer.Moderation: 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.
2:28:14ENNature Has Structure: Demis Hassabis on Learnable Reality and AGIGast: Demis Hassabis · Moderation: 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.
41:13ENFrom 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.
49:27ENFrom 0.1% to 20%: Chai-2 Turns Antibody Design Into Prompt EngineeringModeration: 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.
42:09ENAlphaEvolve found algorithms humans missed for 50 years — then sped up Gemini 23%Moderation: 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.
3:14:34ENIf ten things make a problem hard, Terence Tao turns nine of them offGast: Terence Tao · Moderation: Lex FridmanThe Fields Medalist walks Lex Fridman from the Kakeya needle and Navier-Stokes through Lean, Perelman, and why today's AI still cannot smell a dead-end proof.
1:12:29ENGoogle's AI Co-Scientist Solved a Phage Puzzle Humans Missed for YearsModeration: Nathan LabenzImperial College scientists José Penadés and Tiago Costa told the Podovirus podcast how a still-unreleased Google system recovered their unpublished answer: tailless capsids that pick up stray phage tails.
55:40ENTo 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.
Mehr laden24 von 72 angezeigt








