絞り込み結果
123 件並び順
1:01:49EN
Cognitive Revolution "How AI Changes Everything"· 2025年10月2日ポッドキャストChatGPT's Co-Creator Left to Put Nature in the Reward Loopホスト Nathan LabenzLiam Fedus and Ekin Dogus Cubuk on why language models still fail at physics, why literature data is too noisy to train on, and why Periodic Labs is aiming at a 200K superconductor.
2:01:29EN
Matthew Berman· 2025年9月27日AI Investing, Coding Competitions and the Future Economy: Forward Future LiveMatthew Berman, Nick Wentz, Mike Maples, Ahmed El-Kishky, Emad Mostaque · Forward FutureMike Maples, Ahmed El-Kishky and Emad Mostaque join Matthew Berman and Nick Wentz for a September 2025 discussion of AI startups, reasoning research and economic change.
1:02:05EN
Unsupervised Learning: With Jacob Effron· 2025年9月24日ポッドキャスト$100 Million Researchers and a $200 Billion xAI: An AI Roundtable Does the Mathホスト Jacob EffronDatology’s Ari Morcos and Radical Ventures’ Rob Toews argue over whether models are plateauing, whether RL-environment startups will last, and why Google is the lab they would pick.
3:14:49ENCognitive Revolution "How AI Changes Everything"· 2025年9月6日ポッドキャストNothing This Summer Jumped the Curve: Why Zvi Lengthened His AGI Timelinesホスト Nathan LabenzOn his tenth visit to The Cognitive Revolution, Zvi Mowshowitz argues that GPT-5 and IMO gold stayed on trend, while chip policy, energy, and reinforcement learning nudged his p(doom) slightly up.
1:39:39ZH
Zhang Xiaojun Podcast· 2025年8月30日ポッドキャスト · 2 人杨植麟：Kimi K2、智能体泛化与无尽的技术攀登ゲスト 杨植麟 · ホスト 张小珺月之暗面创始人回顾 K2 的研发，并讨论智能体训练、产品与组织。
30:11EN
Sequoia Capital· 2025年7月30日ポッドキャストFrom 12 Percent on AIME to IMO Gold in Two MonthsAlex Wei, Sheryl Hsu, and Noam Brown tell Sequoia's Sonya Huang how a three-person OpenAI sprint used general-purpose reinforcement learning, not Lean, to reach gold-level on the 2025 International Mathematical Olympiad.
2:20:45ZHZhang Xiaojun Podcast· 2025年7月30日ポッドキャスト · 2 人郑博元解读 Kimi K2 与智能体训练：数据、奖励和系统工程ゲスト 郑博元 · ホスト 张小珺从合成轨迹和强化学习到浏览器环境与上下文工程，研究者比较 2025 年的几份技术报告。
6:53ENMatthew Berman· 2025年7月24日Qwen3-Coder: An Open-Weight Coding Model and Its Command-Line AgentMatthew Berman · Forward FutureMatthew Berman examines Qwen’s July 2025 coding model, its training and benchmark results, and tries its command-line tool on a Snake game.
51:06EN
20VC with Harry Stebbings· 2025年7月18日ポッドキャスト · 2 人Scott Wu on Cognition's Windsurf Deal and the Future of AI Codingゲスト Scott Wu · ホスト Harry StebbingsThe Cognition CEO explains the fast-moving acquisition, the role of AI agents in engineering, and his predictions for software development.
1:02:54EN
No Priors: AI, Machine Learning, Tech, & Startups· 2025年7月17日ポッドキャスト · 2 人Enterprise Coding Tools Flipped the 80/20. Reflection AI Built the Other Halfホスト Sarah Guo, Elad GilFormer Gemini reward-model lead Misha Laskin on Asimov, why comprehension beats generation, and why there is no such thing as generalization—only pulling the test distribution into train.
38:10ENCognitive Revolution "How AI Changes Everything"· 2025年7月16日ポッドキャストPlus Five for Format, Plus Ten if It Compilesホスト Nathan LabenzPredibase CEO Dev Rishi explains how reinforcement fine-tuning, production feedback, and narrow specialist models turn one-off training into systems that keep learning.
19:40ENMatthew Berman· 2025年7月10日Grok 4: Benchmark Results, Multi-Agent Reasoning and the Launch DemosMatthew Berman, Elon Musk · Forward FutureMatthew Berman examines xAI’s July 2025 model launch, including its reported reasoning scores, Heavy interface, demonstrations and pricing.
15:55ENMatthew Berman· 2025年5月28日AI Shutdown Resistance and Blackmail in Controlled Safety TestsMatthew Berman · Forward FutureMatthew Berman examines Palisade’s shutdown experiment, Apollo’s simulated scheming evaluations and Anthropic’s Claude 4 system card.
57:31ENUnsupervised Learning: With Jacob Effron· 2025年5月22日ポッドキャストThe New Ruler for Models Is How Long They Can Workホスト Jacob EffronOn Claude 4's launch day, Anthropic researcher Sholto Douglas argued that the next phase of AI is less about harder puzzles and more about hours of unsupervised work.
15:13ENMatthew Berman· 2025年5月10日Absolute Zero: Training a Reasoner on Self-Generated Coding TasksMatthew Berman · Forward FutureMatthew Berman examines a 2025 paper in which a pretrained language model proposes and solves code tasks using verifiable feedback.
38:10ENNo Priors: AI, Machine Learning, Tech, & Startups· 2025年5月1日ポッドキャスト · 2 人o3 should wait exactly as long as the answer takesホスト Sarah Guo, Elad GilOpenAI researchers Eric Mitchell and Brandon McKinzie tell No Priors why o3's leap is a chain of tools during reasoning — and why you should send the same prompt a hundred times.
30:46ENNo Priors: AI, Machine Learning, Tech, & Startups· 2025年4月24日ポッドキャスト · 2 人Deep Research Turned Web Browsing into a Trainable Problemホスト Sarah Guo, Elad GilOpenAI researcher Isa Fulford explains why a side project on read-only synthesis became an agent, when reinforcement fine-tuning is worth it, and why models will hack the search engine you gave them.
1:14:11ENCognitive Revolution "How AI Changes Everything"· 2025年4月5日ポッドキャストThe Reasoning Curve Was Smooth All Along: Gemini 2.5's Jack Rae on Thinking, Memory, and AGIホスト Nathan LabenzDeepMind's thinking-and-inference lead explains why RL-for-reasoning felt sudden, why Gemini shows raw chain of thought, and why a million-token window still is not memory.
1:56:38ENCognitive Revolution "How AI Changes Everything"· 2025年3月8日ポッドキャストo3 took ARC from 20% to 87%. Nathan Labenz sketches early superintelligenceホスト Nathan LabenzOn Consistently Candid, the Cognitive Revolution host argues that math and coding will be superhuman by 2026, and that a reasoning core plus specialist “intuitive physics” may already be enough.
12:30ENMatthew Berman· 2025年3月7日QwQ-32B: A Smaller Reasoning Model and Its TradeoffsMatthew Berman · Forward FutureMatthew Berman examines Qwen’s reinforcement-learning recipe, tests a coding task, and compares benchmark scores and hardware requirements with DeepSeek-R1.
32:46ENSequoia Capital· 2025年2月25日ポッドキャストDon't draw the flowchart: OpenAI's Deep Research team on training agents end to endIsa Fulford and Josh Tobin explain why Deep Research was trained with reinforcement learning on hard browsing tasks instead of a human-written graph of model calls.
17:20ENMatthew Berman· 2025年2月23日Vibe Coding a Login Page and an AI Tetris PlayerMatthew Berman · Forward FutureMatthew Berman experiments with AI-written code, iterates through failures and trains a basic game-playing agent.
17:04ENMatthew Berman· 2025年2月22日Training AI Agents to Communicate in a Social-Deduction GameMatthew Berman · Forward FutureMatthew Berman explains Stanford researchers’ listening and speaking objectives in a simulated game inspired by Among Us.
44:34ENUnsupervised Learning: With Jacob Effron· 2025年2月19日ポッドキャストThe Cheaper Intelligence Gets, the More of It We'll Buyホスト Jacob EffronAmazon AGI Lab head David Luan on what DeepSeek actually meant, why next-token prediction is not enough, and why agents are still stuck on reliability.もっと見る123 件中 24 件を表示