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1:24:57ENA 50,000-GPU cap and a 1,700-chip loopholeHost Jacob EffronSemiAnalysis founder Dylan Patel walks through the AI diffusion rule, China’s compute squeeze, and how xAI stood up a 100,000-GPU cluster in a closed Memphis appliance factory.
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.
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.
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.
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.
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.
1:10:07ENSame 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.
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.
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.
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.
1:23:40ENA $9 Tutor That Refuses to Give the AnswerHost Nathan LabenzHow Khan Academy spent five months of GPT-4 early access building Khanmigo, a Socratic tutor shipped on the model's launch day.
1:01:26ENAlexNet Used Two GPUs. GPT-4 Took Twenty Thousand. The Shortage Will Be Back.Host Nathan LabenzRun:ai CTO Ronen Dar on filling idle accelerators, why H100s can be cheaper per experiment, and why Llama 2 undercuts compute governance.
1:30:29ENGPT-4 Wins Ten Times More Bill Fights: DoNotPay's Robot-Lawyer WarHost Nathan LabenzGPT-3 thanked Comcast for twenty dollars off. GPT-4 said that was not enough — and the robot lawyer called it an arms race.
1:20:49ENA Wafer-Scale Chip So AI Stops Waiting on AmdahlHost Nathan LabenzAndrew Feldman, CEO of Cerebras, tells Nathan Labenz why one 2.5-trillion-transistor die, sparse linear algebra, and a 16-machine supercomputer are a better shape than a GPU cluster.
1:44:19ENTen People Versus Google’s $282 Billion Search MachineHost Nathan LabenzPerplexity founder Aravind Srinivas tells Nathan Labenz why citations, speed, and value per minute — not chat bubbles — are how a tiny team competes with Google.
1:53:14ENWorth Thousands, Priced at $20: Zvi Mowshowitz on OpenAI's Flurry, Gemini Bets, Deepfakes and a Compute CapHost Nathan LabenzZvi Mowshowitz and Nathan Labenz survey OpenAI's launch spree, AI pricing and bundling, data pollution, deepfakes, the reversal curse, calls to cap training compute, and Amazon's Anthropic deal.
1:00:10ENThe Long Leash and the Narrow Fences: Eric Ries and Jeremy Howard on Building AI’s Edison LabHost Jacob EffronEric Ries and Jeremy Howard discuss Lean Startup discipline in AI, Answer.AI’s for-profit R&D lab model, efficient fine-tuning, language-heavy applications, and AI safety regulation.
1:18:48ENData Movement, Not Math: How to Make Deep Learning Fit on Robots and PhonesHost Lex FridmanMIT professor Vivienne Sze explains why moving data dominates the energy cost of neural networks and how co-designing hardware and algorithms can cut it by orders of magnitude.
57:21ENGemini 2.0 Flash Goes to Production: Pricing, Model Lineup and What Developers Should Build NextHost Nathan LabenzGoogle DeepMind's Logan Kilpatrick walks through launch-day Gemini 2.0 releases, rate limits, model naming, and where he sees startup opportunities.
51:55ENThe Search Engine Under AI Apps: Why Bigger Context Windows Aren't EnoughHost Jacob EffronTurbopuffer CEO Simon on object-storage databases, vector-search trade-offs, and the AI features that will become SaaS table stakes.









