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129 件
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2:12:00EN
Cognitive Revolution "How AI Changes Everything"· 2025年5月15日ポッドキャストGradient Descent at Test Time: Titans Pushes LLM Context to 10 Million Tokensホスト Nathan LabenzA Cornell PhD student's neural memory module holds about 70% accuracy where GPT-4's scores fall off a cliff.モデルと学習Agent memoryコンテキストエンジニアリング+3
1:14:36EN
20VC with Harry Stebbings· 2025年3月24日ポッドキャスト · 2 人Andrew Feldman on AI Chips, Inference and Competing With Nvidiaゲスト Andrew Feldman · ホスト Harry StebbingsThe Cerebras CEO explains wafer-scale computing, argues inference demand will grow and discusses the limits of his industry’s infrastructure.SemiconductorsAI cost & performanceInference+2
スライド 6 枚12:10EN
Matthew Berman· 2025年3月6日Mercury Coder and Diffusion Language Models: Speed, Demos and LimitsMatthew Berman · Forward FutureMatthew Berman explores Inception’s 2025 coding model, comparing iterative text refinement with autoregressive generation and examining speed claims.モデルと学習Inferenceコーディングエージェント+2
45:06EN
Unsupervised Learning: With Jacob Effron· 2025年3月5日ポッドキャストMike 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.インフラとデプロイAI StrategyOpen-weight models+3
1:18:09EN
20VC with Harry Stebbings· 2025年2月24日ポッドキャスト · 2 人Steeve Morin on AI Inference, Chips and the Cost of Switching Hardwareゲスト Steeve Morin · ホスト Harry StebbingsThe ZML founder explains the difference between training and production inference and offers a competitive view of the AI hardware market.インフラとデプロイInferenceAI cost & performance+2
22:32EN
No Priors: AI, Machine Learning, Tech, & Startups· 2025年2月7日ポッドキャスト · 2 人The $5.5 Million Was Only the Last Mileホスト 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.モデルと学習AI StrategyAI cost & performance+3
スライド 5 枚10:01EN
Matthew Berman· 2025年2月5日DeepSeek R1 Code Optimization and a $3 Visual Counting ExperimentMatthew Berman · Forward FutureMatthew Berman examines a human-guided coding improvement and a small reinforcement-learning experiment, then considers their implications for AI research.Reinforcement LearningGPU programming & kernelsAI research+2
1:00:02EN
20VC with Harry Stebbings· 2025年1月29日ポッドキャスト · 2 人Jonathan 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.InferenceAI cost & performanceGeopolitics+2
1:08:12EN
20VC with Harry Stebbings· 2025年1月22日ポッドキャスト · 2 人George Sivulka on Hebbia, Enterprise AI and the Future of Workゲスト George Sivulka · ホスト Harry StebbingsThe Hebbia founder discusses document analysis, inference scaling, enterprise adoption and his forecasts for models and employment.エンタープライズ AIAI agentsInference+2
1:24:57EN
Unsupervised Learning: With Jacob Effron· 2025年1月21日ポッドキャストA 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.インフラとデプロイAI RegulationGeopolitics+3
23:37EN
No Priors: AI, Machine Learning, Tech, & Startups· 2025年1月9日ポッドキャスト · 2 人A Hundred GPUs in Seconds: Why Modal Threw Out Docker and Kubernetesホスト Sarah Guo, Elad GilErik Bernhardsson tells Elad Gil that AI inference is too bursty for year-long GPU contracts, and that the cloud should feel as fast as a laptop.インフラとデプロイInferenceAI cost & performance+3
スライド 2 枚30:29EN
Matthew Berman· 2025年1月3日How Researchers Think o1-Style Reasoning Models WorkMatthew Berman · Forward FutureMatthew Berman explains a research survey of policy initialization, rewards, search and reinforcement learning, and the open questions behind reasoning models.Reinforcement Learningモデルと学習AI research+1
55:50EN
Unsupervised Learning: With Jacob Effron· 2024年12月16日ポッドキャストThere will not be one model. Fireworks is betting on hundreds of small expertsホスト Jacob EffronPyTorch veteran Lin Qiao argues that inference is a compound system hyperscalers cannot buy their way through, and that the products with real traction still keep a human in the loop.インフラとデプロイInferenceModel routing & gateways+3
42:21EN
No Priors: AI, Machine Learning, Tech, & Startups· 2024年12月12日ポッドキャスト · 2 人They Cooled 5,000 Watts per Square Centimeter in Space. Now Diamond Goes on AI Chipsホスト 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.インフラとデプロイAI cost & performanceSemiconductors+1
44:16EN
No Priors: AI, Machine Learning, Tech, & Startups· 2024年11月21日ポッドキャスト · 2 人Cohere's Aidan Gomez: The Model Curve Is Flattening, and $20 Million Now Buys GPT-4ホスト Sarah Guo, Elad GilThe Attention Is All You Need co-author tells No Priors why enterprises should stop waiting for the next model and start putting today's models into production.企業と戦略エンタープライズ AIAI Strategy+3
36:49EN
No Priors: AI, Machine Learning, Tech, & Startups· 2024年11月7日ポッドキャスト · 2 人Jensen Huang: NVIDIA Is No Longer Building Computers. It Is Building AI Factoriesホスト 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.インフラとデプロイAI cost & performanceInference+3
スライド 6 枚10:39EN
Matthew Berman· 2024年10月29日Zamba2-7B: A Hybrid Mamba–Transformer Model Tested on Coding and ReasoningMatthew Berman · Forward FutureMatthew Berman compares Zyphra’s efficiency claims with his own informal tests, including Python games, spatial puzzles and simple word tasks.モデルと学習Open-weight modelsBenchmarks+2
スライド 5 枚9:38EN
Matthew Berman· 2024年10月15日Liquid Foundation Models: Company Benchmarks and a Hands-On TestMatthew Berman · Forward FutureMatthew Berman reviews Liquid AI’s 2024 model and memory claims, then tries the 40B preview on coding, logic, and instruction-following prompts.Foundation Models評価(Evals)Benchmarks+2
2:29:04EN
Lex Fridman· 2024年10月6日ポッドキャスト · 2 人Keep the Programmer in the Driver's Seat: Cursor's Founders on Tab, Agents, and Zero-Entropy Editingゲスト Cursor Team · ホスト Lex FridmanMichael Truell, Aman Sanger, Sualeh Asif, and Arvid Lunnemark tell Lex Fridman why they forked VS Code, how Tab and Apply actually work, and why most programming still needs a human iterating in real time.コーディングエージェント開発ワークフローとテストAI interface design+3
スライド0:54EN
Matthew Berman· 2024年9月16日OpenAI’s o1 Preview: A First Look at Longer ReasoningMatthew Berman · Forward FutureMatthew Berman introduces the o1-preview and o1-mini models and tries a Python game prompt.モデルと学習Inference
37:47EN
No Priors: AI, Machine Learning, Tech, & Startups· 2024年8月30日ポッドキャスト · 2 人Working Backwards from AGI: Magic's Five-Million-Token Betホスト Sarah Guo, Elad GilEric Steinberger wants a coding colleague you trust like a teammate — and a world that is still a good place thirty years after AGI.コーディングエージェントコンテキストエンジニアリングInference+3
スライド 6 枚18:37EN
Matthew Berman· 2024年8月29日GameNGen Simulates Doom as AI Coding, Safety and Inference News AccelerateMatthew Berman · Forward FutureMatthew Berman reviews a 2024 game-simulation paper, Cursor, robotics, AI safety debates and new enterprise tools.World modelsコーディングエージェントAI Safety+2
スライド0:44EN
Matthew Berman· 2024年8月29日NVIDIA Adds Multi-LoRA Serving to Its RTX AI ToolkitMatthew Berman · Forward FutureIn an NVIDIA-partnered video, Matthew Berman describes using multiple adapters with one base model and a vendor-reported throughput gain.ファインチューニングInferenceインフラとデプロイ
42:59EN
No Priors: AI, Machine Learning, Tech, & Startups· 2024年8月29日ポッドキャスト · 2 人AWS 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.インフラとデプロイエンタープライズ AIAI Strategy+3
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