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1:08:51ENChip Controls Are Meant to Buy Ten Years, Not Win the AI Race진행자 Nathan LabenzEconomist Noah Smith tells Nathan Labenz that U.S. export controls are a piece of conventional deterrence against China — not a plan to kneecap DeepSeek.
2:33:39ENThe Attacker Goes Second: Why Nicholas Carlini Keeps Breaking AI Defenses진행자 Nathan LabenzA Google DeepMind security researcher on simple loss functions, 70% robust accuracy, and why the fix has to live in the system, not the model.
22:32ENThe $5.5 Million Was Only the Last Mile진행자 Sarah Guo, Elad GilOn No Priors' 100th episode, Sarah Guo and Elad Gil separate DeepSeek's paper cost from the compute behind it, then walk through OpenAI's Deep Research, Stargate, and their bets for 2025.
5:06:18ENDeepSeek's $5 million training claim and the five-year bet on compute진행자 Lex FridmanDylan Patel and Nathan Lambert walk Lex Fridman through DeepSeek-V3 and R1, export controls, TSMC, megaclusters, and who actually makes money in the AI race.
1:48:20ENFrom 15% to 70% on Right-or-Wrong Scores: DeepSeek-R1 Laid Reinforcement Learning's Cards on the Table진행자 Nathan LabenzOn Inauguration Day 2025, DeepSeek and Moonshot dropped reasoning-model results that Nathan Labenz reads as proof the reinforcement-learning recipe is simple, public, and still climbing.
1:24:57ENA 50,000-GPU cap and a 1,700-chip loophole진행자 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.
1:00:05ENIf Someone Builds a Better Spark Product, We Deserve to LoseIon Stoica on how Databricks turned academic open source into a data-and-AI company — and which problems he thinks will matter more tomorrow than today.
3:53:49ENWith One-Twelfth the Data, an Open-Source Vision Model Beat GPT-4o진행자 Nathan LabenzWill Hardman of Veratai walks Nathan Labenz through two years of vision-language models, from ViT and CLIP to InternVL, BLINK, and Transfusion.
1:57:00ENLess Than 1%: Why OpenAI's roon Thinks the Good Guys Get AGI First진행자 Nathan LabenzDoom Debates host Liron Shapira presses OpenAI technical staffer roon on extinction odds, alignment-by-default, and a plan that even he admits is balancing on razor wire.
27:07ENAfter adding $100 billion a month, Jensen Huang says NVIDIA is selling the data center진행자 Sarah Guo, Elad GilSarah Guo and Elad Gil clip their favorite 2024 No Priors conversations into a year-end reel of NVIDIA, Karpathy, Sierra, Sora, Waymo, Figma, and Scale.
1:49:41ENA Team of Fifteen Matched Meta’s Post-Training on Meta’s Own Base진행자 Nathan LabenzNathan Lambert walks through Tulu 3: the three-stage recipe, the 1 percent versus 14 percent lesson, and why open post-training now lives or dies on data and evals.
2:24:18ENMMLU Stays at Chance Until Late Training. Loss Is Only an Alarm.진행자 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.
26:08ENFewer Than 3% of Deals Get Investigated. Selling to the Monopolist Is What Triggers the FTC.진행자 Sarah Guo, Elad GilChair Lina Khan tells No Priors how merger review actually works in AI markets, why open-weight models matter, and why the agency banned most non-competes.
42:59ENAWS Is a $100 Billion Cloud. Matt Garman Still Sees a 10x Migration Ahead진행자 Sarah Guo, Elad GilAmazon Web Services’ new CEO tells No Priors why 85 percent of workloads are still on-prem, how Bedrock was built from three bets, and why startups remain the company’s growth engine.
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.
42:08ENMeta Trained a 405B Teacher on 16,000 GPUs — Then Told the World to Distill ItTwo days after Llama 3.1 405B shipped, Meta's generative-AI product lead walks Sequoia through why the most expensive model in the family is free, and why he thinks the frontier itself is heading toward commodity.
1:54:01ENA Tiny Network Grew a Salt Crystal the Training Data Never Showed진행자 Nathan LabenzTim Duignan trained tens of thousands of parameters on salt water. The model invented a crystal — and a continuum solvent theory he had spent a PhD failing to write by hand.
1:42:17ENThe Cheapest Inference Provider Is the Most Dangerous진행자 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.
2:47:17ENIf You Want Human-Level AI, Abandon Generative Models게스트 Yann Lecun · 진행자 Lex FridmanYann LeCun tells Lex Fridman why autoregressive LLMs cannot plan, remember, or understand the physical world — and why open source is the only democratic answer.
19:10ENThe World's Only Capped-Profit Company진행자 Sarah Guo, Elad GilNo Priors looks back at 2023 through eight conversations on money, intelligence, jobs, and who should put the guardrails on a model.
2:16:27ENSuperhuman Go Has a Blind Spot. Balaji Bets on a War of the Gods진행자 Nathan LabenzBalaji Srinivasan tells Nathan Labenz why adversarial inputs, missing actuators, and cryptography make a single runaway AI god less likely than a contest among many that still need priests.
32:57ENA 7-billion-parameter model on a MacBook: Mistral's CEO reruns the cost of AI진행자 Sarah Guo, Elad GilArthur Mensch tells No Priors why Chinchilla made small models valuable, why open-sourcing Mistral 7B is not a bioweapon risk, and why guardrails belong on the application.
1:14:36ENZulu Bypasses GPT-4, and a Hundred Examples Undo the Guardrails진행자 Nathan LabenzNathan Labenz reads seven papers — four hopeful, three not — on whether anyone can actually keep a language model under control.
1:04:38ENHundreds of Miles Apart, Zuckerberg and Fridman Sat Close Enough to See the Wrinkles게스트 Mark Zuckerberg · 진행자 Lex FridmanLex Fridman sat in a dark room in Austin wearing a Quest headset; Mark Zuckerberg sat in another conference room, also wearing one, and it did not feel like a video call.
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