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2:11:15ENA 50% Chance of Extinction — and a $50 GPT-4 for EveryoneHost Nathan LabenzEmad Mostaque tells Nathan Labenz why he puts p(doom) at even odds, why a five-watt model changes the energy debate, and how the Intelligent Internet would fund universal basic AI with a Bitcoin-like token.
42:21ENThey Cooled 5,000 Watts per Square Centimeter in Space. Now Diamond Goes on AI ChipsHost Sarah Guo, Elad GilAkash Systems founders Felix Ejeckam and Ty Mitchell tell Sarah Guo why heat is the real limiter on AI, and how lab-grown diamond bonded to semiconductors is their answer.
48:18ENNoam Brown: There's No Hard Wall—Just Eight Orders of Magnitude of HeadroomHost Jacob EffronA ChatGPT query costs about a penny. The problems society cares about most, he says, are worth a million dollars.
36:49ENJensen Huang: NVIDIA Is No Longer Building Computers. It Is Building AI FactoriesHost Sarah Guo, Elad GilOn No Priors, NVIDIA’s CEO walks through hyper Moore’s law, NVLink, a 100,000-GPU cluster stood up in weeks, and why tokens are the new commodity.
55:16ENGemini’s API Grew 14× in Six Months. Google’s PMs Explain the Catch-Up.Host Nathan LabenzLogan Kilpatrick and Shrestha Basu Mallick walk through search grounding, Gemini Flash’s price-latency quadrant, and why a near-tied leaderboard still leaves Google third in most developers’ queues.
2:24:18ENMMLU Stays at Chance Until Late Training. Loss Is Only an Alarm.Host Nathan LabenzZyphra’s training lead walks through Zamba 2’s hybrid architecture, the evals that actually matter, and the trade secrets small labs still have to rediscover.
42:42ENEthereum Once Held Two Thousand GPT-3 Clusters of GPUsHost Sarah Guo, Elad GilFoundry CEO Jared Quincy Davis on idle H100s, why today's AI cloud is still colocation, and how compound systems move work off giant interconnected clusters.
1:51:00ENStart With Ten Gold Examples: A Three-Step Playbook for AI AutomationHost Nathan LabenzThe day after OpenAI opened GPT-4o fine-tuning, Nathan Labenz unpacks a three-year method for choosing work, extracting tacit judgment, and raising model performance.
50:33ENThe 40% data-center save started with an email that ended in a question markPhaidra founder Jim Gao tells Sequoia how an AlphaGo-inspired bet at Google became reinforcement learning that runs billion-dollar plants.
39:18ENOpen and Closed Will Tie at the Same Size: PyTorch's Former Lead on Fast InferenceA six-month library swap at Meta became a five-year rebuild. Lin Qiao wants the rest of the industry to get that stack in five weeks.
1:21:53ENHippoRAG Matches Iterative Retrieval at One-Tenth the Online CostHost Nathan LabenzA hippocampus-inspired knowledge graph lets multi-hop questions skip the brute-force document crawl.
1:00:28ENScaling Laws Aren't Done. Don't Lock Yourself Into Yesterday's Architecture.Microsoft CTO Kevin Scott on why the exponential is still compounding, why inference will dwarf training, and why a language model is the world's crappiest database.
36:20ENA Hundred Million Tokens in Context Would Cost $10 Million. Tengyu Ma Runs the RAG MathHost Sarah Guo, Elad GilThe Stanford professor and Voyage AI founder argues that retrieval, not a giant context window, is how enterprises should manage private knowledge.
1:10:07ENSame Intelligence, 1% of the Price: Logan Kilpatrick on Gemini FlashHost Nathan LabenzA former OpenAI developer-relations lead, now the product manager for Google AI Studio, walks through what Gemini 1.5 Flash actually changes for builders.
29:09ENThe Hyperscalers Are Spending $200 Billion — and the Next Bottleneck Is a Power PlantHost Sarah Guo, Elad GilSarah Guo and Elad Gil walk through music models, on-device LLMs, long context, and why AI capex now sits beside oil and broadband.
1:42:17ENThe Cheapest Inference Provider Is the Most DangerousHost Nathan LabenzFireworks AI cofounders Lin Qiao and Dmytro Ivchenko explain why subsidized GPU bills vanish, how LoRA serving can cut cost a hundredfold, and why OpenAI is the rival that actually matters.
26:03ENGPT-4-Class Models Will Be Cheap. The Frontier Will Still Need a Patron.Host Sarah Guo, Elad GilSarah Guo and Elad Gil walk through Mosaic’s Law, Microsoft’s Inflection hire, where the real money sits, and why the first AI wave looks consumer.
38:33ENSpeed Is the Thing You Can Buy: Baseten’s Bet on InferenceHost Sarah Guo, Elad GilTuhin Srivastava tells Sarah Guo and Elad Gil why a six-person chatbot company running a billion tokens a day should not be building its own serving stack.
39:03ENMI300 Leads Inference by 2x: AMD's CTO on Winning Chip Competition Without a Walled GardenHost Sarah Guo, Elad GilWhen Mark Papermaster became AMD's CTO in fall 2011, nearly all of the company's revenue sat on PCs and gaming, Moore's Law was slowing, and everyone knew it needed a turnaround.
1:43:07ENAn Agent Posted Five Tweets — and 5,000 People Didn't NoticeHost Nathan LabenzMultiOn founder Div Garg walks Cognitive Revolution through what web agents can actually do in early 2024, what they cost, and why guardrails have to sit outside the model.
1:17:20ENHume wants well-being in the objective function, measured 53 emotions at a timeHost Nathan LabenzAlan Cowen tells Nathan Labenz how Hume AI reads face, voice, and language, sells custom models at $1.66 an hour, and wants long-horizon well-being to override every other AI goal.
1:17:09ENGPT-4 as Teacher, GPT-3.5 as Student: A Nine-Tenths Cost Cut and an AI Bundle Nobody Will StartHost Nathan LabenzNathan Labenz reports that chain-of-thought traces from GPT-4 train a cheaper, faster 3.5, then argues for flooring the app accelerator, tapping the brake on GPT-5, and bundling a hundred AI tools for a hundred dollars.
30:03ENA Dinner-Plate Chip Cut Training From 60 Days to 3.5Host Sarah Guo, Elad GilCerebras CEO Andrew Feldman tells No Priors why wafer-scale silicon, not another GPU, is the answer to the compute crunch — and why most production models will stay at 13 billion parameters or below.
52:48ENOpenAI Cut Fine-Tuning 90 Percent, and Founders Crossed Llama 2 Off the ListHost Nathan LabenzNathan Labenz and Erik Torenberg walk through GPT-3.5 Turbo fine-tuning, why self-hosting still loses on total cost, and what is actually working in code, school, and medicine.
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