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1:29:02ENFrom 50 Designs a Day to 1,500: How AI Changed What Jaguar Land Rover Can ExploreAnime : Nathan LabenzNeural Concept’s Thomas von Tschammer on specialist physics models, engineering copilots, and why Formula 1 already runs thousands of designs overnight.
1:37:43ENCisco wants two extra network layers so agents can share intentAnime : Nathan LabenzVijoy Pandey of Outshift by Cisco argues that superintelligence has to scale out through networks of agents, not just up through bigger models.
2:06:23ENFive AI Employees Live on Five Mac MinisAnime : Nathan LabenzAfter selling her YC packaging company, Jesse Genet opened a terminal for the first time and built an OpenClaw staff that now plans lessons, logs learning, and keeps family evenings from sliding into slop.
1:57:56ENA Hundred Million Lines at Twenty Cents Each: Inside Blitzy's Enterprise Coding PipelineAnime : Nathan LabenzCEO Brian Elliott and CTO Sid Pardeshi tell Nathan Labenz how Blitzy turns a giant codebase into a map, then lets thousands of dynamically generated agents ship most of a multi-month project in days.
1:32:47ENA transformer co-author wants a $160 million model no company ownsAnime : Nathan LabenzIllia Polosukhin tells Nathan Labenz how NEAR turned a payments headache into a stack for private inference, shared-revenue training, and AI agents that still answer to a court.
1:29:02ENShe Never Sees a Row of Your Data. The Answers Still Clear 95%.Anime : Nathan LabenzIllumex CEO Inna Tokarev Sela tells Nathan Labenz how a Platonic industry ontology, trained only on metadata, collapses enterprise software into one conversation.
1:01:53ENHumans Wrote 1.3 Percent of the Tokens. The AI Lab Still Designed Working Nanobodies.Anime : Nathan LabenzStanford's James Zou describes a GPT-4o research group that invented a protein-design pipeline for under $100 — and a sparse autoencoder that pulled an undocumented motif out of ESM-2.
1:21:50ENA 16K Context Window Holds About 350 Rows. That's Why Tables Need an Agent.Anime : Nathan LabenzGretel AI founder Alex Watson tells Nathan Labenz why most company data is still a spreadsheet, why GPT-4 is the wrong tool for generating it, and how differential privacy lets a model learn a disease without learning a patient.
1:25:11EN105 lines of code, a million impressions, and a VC who refused to found the companyAnime : Nathan LabenzBabyAGI creator Yohei Nakajima tells Nathan Labenz how a weekend prototype set off the agent wave — and why he went back to writing checks.
1:45:46ENReplit's $10 AI Programmer Already Pays for Itself. The Ambition Is Bots Hiring BotsAnime : Nathan LabenzTyler Angert, Replit's first product designer, explains Ghostwriter, a virtual developer, and why the company calls itself the perfect substrate for AGI.
1:40:44ENGive the Model Time, Memory, and Tools: Nathan Labenz’s 2023 Field Guide to Using GPT-4Anime : Nathan LabenzPart two of the AI Scouting Report walks from H100 clusters and RLHF through chain-of-thought, retrieval, agents, and mixture-of-experts.
1:21:06ENEveryone Talks About RLHF. Almost Nobody Is Doing It.Anime : Nathan LabenzHumanloop CEO Raza Habib on why an LLM API is maybe five percent of a working product, and what actually fills the rest.








