絞り込み結果
111 件並び順
54:53ENA Free Voting Board Burned $2 Million. Then It Raised $100 Million.ホスト Jacob EffronDatabricks co-founder Ion Stoica explains why LMArena exists, why China is winning open-source models, and why reliability—not another scaling law—is still the thing holding AI back.
33:18ENZuckerberg and Nadella on AI Coding, Agents and the Next Software StackMatthew Berman, Mark Zuckerberg, Satya Nadella · Forward FutureMatthew Berman examines their 2025 LlamaCon conversation about AI-assisted development, open models and changing workflows.
1:30:57ENAnt's $320 Billion IPO Was Stopped at the Eleventh Hour: Angela Zhang on China's Tech Tightropeホスト Nathan LabenzA USC law professor walks through the dynamic pyramid that governs Chinese tech, from Didi's listing to DeepSeek's price war, and why she thinks the United States is starting to look more like China.
45:06ENMike Schroepfer: AI’s Bottleneck Is Electricity, and One Tanker of Fusion Fuel Could Power the U.S. for a Yearホスト Jacob EffronMeta’s former CTO tells Redpoint why hyperscaler demand is the climate story, why Llama was an access play, and why tomorrow’s CTO still lives or dies on a priority queue.
1:08:51ENChip Controls Are Meant to Buy Ten Years, Not Win the AI Raceホスト 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 Defensesホスト 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.
1:03:08ZH朱啸虎:DeepSeek 如何改变我对 AI 的判断ゲスト 朱啸虎 · ホスト 张小珺2025 年初,投资人回顾对开放模型、应用创业和人工智能的看法。
5:06:18ENDeepSeek's $5 million training claim and the five-year bet on computeホスト 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.
1:00:02ENJonathan Ross on DeepSeek, Open Models and AI Infrastructureゲスト Jonathan Ross · ホスト Harry StebbingsThe Groq CEO discusses reported training costs, inference demand, competitive strategy and the security concerns surrounding AI.
1:48:20ENFrom 15% to 70% on Right-or-Wrong Scores: DeepSeek-R1 Laid Reinforcement Learning's Cards on the Tableホスト 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 loopholeホスト 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-4oホスト 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 Firstホスト 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.
1:49:41ENA Team of Fifteen Matched Meta’s Post-Training on Meta’s Own Baseホスト 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.ホスト 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.
35:30ENReflection 70B: Its Creators Explain the Proposed Self-Correction MethodMatthew Berman, Matt Shumer, Sahil Chaudhary · Forward FutureA launch-day discussion with Matt Shumer and Sahil Chaudhary covers synthetic data, selective reflection and evaluation limits.
1:03:46ENZico Kolter on AI Safety, Scaling and the Limits of Open Modelsゲスト Zico Kolter · ホスト Harry StebbingsThe Carnegie Mellon researcher and OpenAI board member explains why prompt injection worries him, how he thinks about open weights, and why AI progress remains uncertain.
42:59ENAWS Is a $100 Billion Cloud. Matt Garman Still Sees a 10x Migration Aheadホスト 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.
1:02:39ZHKevin 和 Sophia:2023 年硅谷 AI 热潮中的产品、融资与竞争ゲスト Kevin Xu, Sophia · ホスト 张小珺GitHub 从业者与风险投资人回顾 ChatGPT 兴起后的硅谷,讨论模型、Copilot、算力和初创公司。
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.
44:08ENMark Zuckerberg on Llama 3.1, Open Models and Meta’s AI StrategyMatthew Berman, Mark Zuckerberg · Forward FutureMatthew Berman reacts to Zuckerberg’s 2024 interview on open-weight AI, safety, platform control and a future of personalized agents.
1:54:01ENA Tiny Network Grew a Salt Crystal the Training Data Never Showedホスト 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.
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