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1,714 件
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スライド0:32EN
Matthew Berman· 2025年2月20日Figure’s Humanoid Robots and Natural-Language InstructionsMatthew Berman · Forward FutureMatthew Berman comments on a 2025 Figure Robotics demonstration and the potential for household chores.RoboticsAI agents
44:34EN
Unsupervised 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.エージェントエージェント工学Reinforcement Learning+3
スライド0:51EN
Matthew Berman· 2025年2月19日Mira Murati Announces Thinking Machines LabMatthew Berman · Forward FutureMatthew Berman reviews the new AI lab’s stated goals in its February 2025 announcement.AI startups & small teamsAI researchOpen-source ecosystems
1:29:02EN
Cognitive Revolution "How AI Changes Everything"· 2025年2月15日ポッドキャストShe Never Sees a Row of Your Data. The Answers Still Clear 95%.ホスト Nathan LabenzIllumex CEO Inna Tokarev Sela tells Nathan Labenz how a Platonic industry ontology, trained only on metadata, collapses enterprise software into one conversation.RAG とナレッジコンテキストエンジニアリングKnowledge graphs+3
スライド 4 枚8:04EN
Matthew Berman· 2025年2月14日OpenAI’s February 2025 GPT-5 Roadmap and the Case for a Unified InterfaceMatthew Berman · Forward FutureMatthew Berman explains the proposed model-routing experience, GPT-4.5 and GPT-5 plans, and the product choices that prompted them.Model routing & gatewaysOpenAIプロダクトと UX+1
スライド0:59EN
Matthew Berman· 2025年2月13日What Is Vibe Coding? Matthew Berman Explains His WorkflowMatthew Berman · Forward FutureBerman describes using voice input and an AI coding editor to build software, test it, and feed errors back without reading the code.Vibe Codingコーディングエージェント開発ワークフローとテスト
1:30:28EN
Cognitive Revolution "How AI Changes Everything"· 2025年2月12日ポッドキャストA Perfect Score Is 32,000 Units: Only Claude Built a Cooperative Societyホスト Nathan LabenzThe same donor game, run for ten generations, can bank 32,000 resource units if everyone cooperates—and three frontier models miss that ceiling by an order of magnitude.エージェントMulti-agent systems安全性とガバナンス+3
スライド 3 枚6:50EN
Matthew Berman· 2025年2月12日DeepScaleR: A Small Reasoning Model Tested on Competition MathMatthew Berman · Forward FutureMatthew Berman reviews a 1.5B model’s reported benchmark results and runs a quantized version locally on one AIME problem.Reinforcement LearningBenchmarksLocal inference+2
1:32:29EN
Cognitive Revolution "How AI Changes Everything"· 2025年2月9日ポッドキャスト17 Edits, Then 3 Prompts: Lovable Builds the Same App Twiceホスト Nathan LabenzAnton Osika and Isaak Sundeman live-build a shopping comparison tool and argue that opinionated defaults—not open-ended agents—are how non-coders actually ship software.コーディングエージェントVibe CodingProduct Strategy+3
1:24:29EN
Cognitive Revolution "How AI Changes Everything"· 2025年2月9日ポッドキャストStackBlitz Almost Shut Down. Then Bolt Hit $20 Million ARR in Eight Weeks.ホスト Nathan LabenzEric Simons tells Nathan Labenz how a seven-year browser operating system, Claude Sonnet 3.5, and a text box replaced the local toolchain.コーディングエージェントVibe CodingProduct Strategy+3
2:16:17EN
Cognitive Revolution "How AI Changes Everything"· 2025年2月5日ポッドキャストA 10B Model Trained Across Three Continents — and an H200 for $1.49 an Hourホスト Nathan LabenzPrime Intellect's founders lay out a four-step plan to turn spare global GPUs into collectively owned intelligence, and argue that reinforcement learning just made their job easier.インフラとデプロイDistributed training & inferenceAI 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
スライド 5 枚12:07EN
Matthew Berman· 2025年2月2日TinyZero: A $30 Reinforcement-Learning Experiment on a Small Arithmetic TaskMatthew Berman · Forward FutureMatthew Berman explains how a pretrained Qwen model learned to search and check answers in Countdown, and why the experiment does not recreate DeepSeek-R1.Reinforcement LearningReasoning & test-time computeAI research+2
5:06:18EN
Lex Fridman· 2025年2月2日ポッドキャストDeepSeek'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.企業と戦略Open-weight modelsPretraining & midtraining+3
スライド 7 枚9:58EN
Matthew Berman· 2025年2月1日Matthew Berman Tests o3-mini on Games, Puzzles and Web SearchMatthew Berman · Forward FutureA 2025 hands-on test finds working game prototypes and several successful answers alongside a delayed Tetris row, an ambiguous puzzle and a search configuration mistake.評価(Evals)コーディングエージェントReasoning & test-time compute+2
スライド 3 枚6:44EN
Matthew Berman· 2025年2月1日Testing DeepSeek Janus-Pro for Image Understanding and GenerationMatthew Berman · Forward FutureMatthew Berman tries the 7B multimodal model on diagrams, memes and image prompts using a sponsored cloud GPU demonstration.画像と動画Generative mediaMultimodal AI+2
スライド 4 枚9:58EN
Matthew Berman· 2025年1月31日OpenAI o3-mini Launch: Reasoning Effort, Benchmarks and a Snake TestMatthew Berman · Forward FutureIn January 2025, Matthew Berman reviews OpenAI’s reported results and tries two coding examples with different reasoning settings.OpenAIReasoning & test-time computeBenchmarks+1
57:11EN
Unsupervised Learning: With Jacob Effron· 2025年1月30日ポッドキャストA Million Tokens Cannot Write a Good Jokeホスト Jacob EffronPrinceton's Arvind Narayanan on why agent evals mislead, inference scaling hits a wall, and AI looks more like the internet than an overnight revolution.評価とオブザーバビリティ評価(Evals)Benchmarks+3
1:50EN
Matthew Berman· 2025年1月30日Five AI Trends Discussed by Coveo’s Sébastien PaquetMatthew Berman · Forward FutureMatthew Berman summarizes a 2025 interview on production systems, smaller models, agents and trust.エンタープライズ AIエージェントモデルと学習+1
スライド0:52EN
Matthew Berman· 2025年1月29日Genie 2 Generates Interactive Worlds for AI ResearchMatthew Berman · Forward FutureMatthew Berman explains why Google DeepMind’s image-conditioned world model could help researchers create environments for agents, while the early demonstrations have clear limits.World modelsGenerative mediaRobotics
56:07EN
Cognitive Revolution "How AI Changes Everything"· 2025年1月29日ポッドキャストBox Holds 100 Billion Files. Its CEO Says Enterprises Only Move for a 10xホスト Nathan LabenzAaron Levie tells Nathan Labenz why AI excitement in the enterprise already outruns the early cloud — and why 98% reliability, seat-based SaaS, and incremental savings still will not ship.企業と戦略エンタープライズ AIAI Strategy+3
スライド 3 枚5:27EN
Matthew Berman· 2025年1月29日Ways to Try DeepSeek R1: Hosted and Local Distilled ModelsMatthew Berman · Forward FutureMatthew Berman demonstrates DeepSeek chat, Groq’s hosted distill and a local model in LM Studio.Local inferenceOpen-weight modelsQuantization
スライド 4 枚20:34EN
Matthew Berman· 2025年1月28日DeepSeek R1 and the Debate Over AI Costs and ComputeMatthew Berman · Forward FutureMatthew Berman examines 2025 reactions to DeepSeek, from training efficiency and market losses to open weights, privacy and the possibility of a demand rebound.モデルと学習AI cost & performanceOpen-weight models+2
スライド16:45EN
Matthew Berman· 2025年1月27日DeepSeek-R1 and the Debate Over AI Costs and ComputeMatthew Berman · Forward FutureMatthew Berman examines the January 2025 reaction to an open-weight reasoning model, disputed cost claims and competing views of future demand for AI chips.Foundation ModelsReasoning & test-time computeOpen Source+1
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