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2:59:44ENTwo Endangered Languages Broke Transformers. Nested Learning Gave Models a Sleep Button.Presenta: Nathan LabenzGoogle researcher Ali Behrouz tells Nathan Labenz how stacking update frequencies — not just layers — and an offline sleep phase could give language models genuine continual learning.
1:13:23ENAn AI Found a GABA-Cancer Link. The Next Step Is Talking to the Cells.Presenta: 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.
1:59:47ENBCI Would Take 30 Years. This Studio Pivoted to Alignment InsteadPresenta: Nathan LabenzJudd Rosenblatt and Mike Vaiana of AE Studio describe two biologically inspired results that do not need interpretability breakthroughs to work.
1:29:14EN55% of People Have Had a Lucid Dream. Prophetic AI Wants the Rest to Have One Every NightPresenta: Nathan LabenzProphetic AI co-founders Eric Wollberg and Wesley Berry tell Ate-a-Pi how a headband of EEG and focused ultrasound, steered by a neural transformer, is meant to light up the prefrontal cortex during REM.
2:09:50ENHe stayed up all night playing Civilization 6 with his mindPresenta: Nathan LabenzDean W. Ball surveys EEG, ultrasound stimulation, and Neuralink with Nathan Labenz, and argues that merging with machines started decades ago.
1:34:11ENFrom forty hours in a scanner to one: reconstructing what you see from a shared brain spacePresenta: Nathan LabenzPaul Scotti explains how MindEye2 maps a new person's fMRI into CLIP with an hour of data, and why a linear layer plus better image generators changed the cost of reading minds.
1:25:09ENTwo-Headed Worms, Regenerated Legs, and a Sort That Learned to WaitPresenta: 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.
1:58:43ENA Worm With 302 Neurons Already Makes Trade-offs. AI Is Still on the Same Ladder.Presenta: Nathan LabenzMax Bennett maps 600 million years of brain evolution onto five breakthroughs — and asks which rungs today's models have actually reached.
1:18:18ENFifteen Thousand Brain Numbers Were Enough to Reconstruct What Someone SawPresenta: Nathan LabenzTanishq Mathew Abraham walks through MindEye, the fMRI-to-image system that maps a handful of voxel values onto CLIP and diffusion models.
45:31ENYou Are Your Own Existence Proof: Karl Friston on Free Energy, Life, and Self-AwarenessPresenta: Lex FridmanKarl Friston explains how the free energy principle reframes existence, life, planning, and self-awareness as inference problems.
25:06ENLiving Inside the Brain's Story: Joscha Bach on Simulation, Self and ConsciousnessPresenta: Lex FridmanIn a clip from his conversation with Lex Fridman, Joscha Bach argues that consciousness, identity and even God are software-like patterns, and that we exist inside a narrative our brain generates.
11:51ENBuilding a Brain: Paola Arlotta on the Choreography of Human Brain DevelopmentPresenta: Lex FridmanA Harvard stem cell biologist walks through how the embryo builds the cerebral cortex, why order and environment matter, and why development continues into our twenties.
15:41ENAbolishing Involuntary Death: Ben Goertzel on Immortality, Pain and the Meaning of LifePresenta: Lex FridmanIn a clip from Lex Fridman's podcast, AI researcher Ben Goertzel argues that death and pain should be optional, and sketches what it would take to fund a serious attack on aging.
11:26ENThe Cookie Your Brain Bakes: Joscha Bach on Happiness, Cells and the Meaning of GodPresenta: Lex FridmanIn a short clip, Joscha Bach moves from why happiness is not the point to the cell as a cosmic probe and a naturalistic reading of God as civilization.
20:50ENGlitches as Features: What John Hopfield Says Artificial Neural Networks Are MissingPresenta: Lex FridmanIn a short conversation with Lex Fridman, physicist and neural-network pioneer John Hopfield compares evolved brains with today's artificial networks and explains why he expects AI to borrow from biology generation after generation.









