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1:29:30EN2,500 Compounds and a 51 Percent Hit Rate: How a Small Graph Net Found New AntibioticsHost 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.
57:52ENThey Aimed for 1%. The Lab Hit 20%. Chai Discovery Moved Antibody Design Onto the Computer.Host 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.
2:02:27ENShe set out to build mirror life. Then she talked the field into stoppingHost Nathan LabenzUniversity of Minnesota geneticist Kate Adamala tells Nathan Labenz why every known organism shares one chemical alphabet — and why flipping that alphabet would be a branch of synthetic biology better left unexplored.
1:12:29ENGoogle's AI Co-Scientist Solved a Phage Puzzle Humans Missed for YearsHost 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scientists José Penadés and Tiago Costa told the Podovirus podcast how a still-unreleased Google system recovered their unpublished answer: tailless capsids that pick up stray phage tails.
1:43:54ENA Year to Grow a Brain Organoid, an Hour to Simulate ItHost Nathan LabenzStanford postdoc Siyu He tells Nathan Labenz how Squidiff and CORAL move single-cell and spatial experiments into the computer — and where the models still cannot go.
1:33:01ENRare Diseases Are Common: How a Harvard Gene Hunter Uses o1-pro on the Cases Sequencing Already MissedHost Nathan LabenzDr. Catherine Brownstein of Boston Children's Hospital explains why cheap genomes made her job harder, why data sharing still beats any model, and where ChatGPT Pro actually gives her hours back.
1:13:23ENAn AI Found a GABA-Cancer Link. The Next Step Is Talking to the Cells.Host Nathan LabenzMichael Levin and Leo Pio Lopez on a multilayer embedding that predicted melanoma, a cancer with no mutations, and why biology's real interface is cognitive.
1:18:32ENA DNA Model That Can Tell Which Genes You Cannot TouchHost Nathan LabenzStanford's Brian Hie walks through hybrid architectures, a genome-scale language model trained only on DNA, and an antibody that binds 25 times tighter than nature.
1:30:37EN64 Bytes of Random Code, and Computational Life Showed Up AnywayHost Nathan LabenzGoogle researchers Ettore Randazzo and Luca Versari show that self-replicators can arise from a soup of random strings with no fitness function at all.
1:59:15ENA Protein Backbone in a Minute: The Real Progress, Bottlenecks, and Risks of AI BiologyHost Nathan LabenzThe White House set a thousand-fold lower reporting bar for biological models than for language models—and this conversation shows why that gap already looks prescient.
1:25:09ENTwo-Headed Worms, Regenerated Legs, and a Sort That Learned to WaitHost Nathan LabenzTufts biologist Michael Levin tells Cognitive Revolution why anatomy is rewritable software, and why he stopped a paper that might have made AI more alive.
1:03:59ENBuilding a World Model of Life: Biohub's Alex Rives on Why Better Measurement Must Come Before Virtual CellsHost Nathan LabenzBiohub's head of science explains why today's virtual cell models fall short, how a $1.8 billion data push aims to fix it, and what a five-year information-level model of the cell could unlock.
1:45:55ENFrom Static Structures to Moving Molecules: Where AI for Protein Design Stands After AlphaFold 3Host Nathan LabenzComputational biochemist Amelie Schreiber walks Nathan Labenz through six months of progress in structure prediction, molecular dynamics, peptide and antibody models, and early agent-driven design workflows.









