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355 件
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スライド 6 枚13:40EN
Matthew Berman· 2025年10月23日AI News in October 2025: Gemini Tools, M5 and a Quantum Echoes ExperimentMatthew Berman · Forward FutureMatthew Berman reviews an app-building demo, robot footage, model rumors, hardware claims, research debates and Meta’s AI reorganization.AI researchプロダクトと UXQuantum Mechanics+2
スライド 7 枚32:22EN
Matthew Berman· 2025年10月16日Qwen Image Edit Plus Compared With Nano Banana, Seedream and GPT Image 1Matthew Berman · Forward FutureMatthew Berman compares four image-editing models across compositing, precise edits, style transfer, object removal and weather effects.モデルと学習評価(Evals)
1:29:30EN
Cognitive Revolution "How AI Changes Everything"· 2025年10月14日ポッドキャスト2,500 Compounds and a 51 Percent Hit Rate: How a Small Graph Net Found New Antibioticsホスト Nathan LabenzMIT's Jim Collins tells Nathan Labenz how a bootlegged 2018 project, a binary growth-inhibition label, and Chemprop graph networks pulled novel antibiotics out of chemical space that labs could never screen by hand.モデルと学習AI for scienceDrug Discovery+3
スライド 6 枚13:53EN
Matthew Berman· 2025年10月10日Tiny Recursive Models and the Limits of Puzzle Benchmark ComparisonsMatthew Berman · Forward FutureMatthew Berman examines a small recursive network that reports strong ARC and Sudoku results, and what its experimental setup means.AI researchBenchmarksReasoning & test-time compute+1
36:58EN
No Priors: AI, Machine Learning, Tech, & Startups· 2025年10月9日ポッドキャスト · 2 人STaR's Author Wants Models With EQ, Not Just More IQホスト Sarah Guo, Elad GilEric Zelikman, the Stanford and xAI researcher behind STaR and Quiet-STaR, launches humans& on the bet that three years of IQ scaling left models emotionally unintelligent.モデルと学習Post-trainingReinforcement Learning+3
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.モデルと学習AI for scienceReinforcement Learning+3
スライド 2 枚0:58EN
Matthew Berman· 2025年9月26日Microsoft’s Nebius GPU Infrastructure AgreementMatthew Berman · Forward FutureIn a sponsored video, Matthew Berman discusses a 2025 infrastructure agreement and Nebius’s AI services.インフラとデプロイAI cost & performanceモデルと学習
1:22:07EN
Cognitive Revolution "How AI Changes Everything"· 2025年9月25日ポッドキャストEvery payment is a frame in a movie. Stripe’s foundation model took card-testing detection from 59% to 97%ホスト Nathan LabenzEmily Sands, Stripe’s head of data and AI, explains how a domain-specific payments model, shared embeddings, and mixed rules turn a $1.4 trillion network into compounding advantage.モデルと学習金融 AIEmbeddings+3
2:02:17EN
Cognitive Revolution "How AI Changes Everything"· 2025年8月27日ポッドキャストSAEs Find the Nouns. Parameter Decomposition Looks for the Verbsホスト Nathan LabenzGoodfire's Lee Sharkey argues that sparse autoencoders recover a network's variables, not the algorithms those variables run, and shows how stochastic parameter decomposition tries to recover the computations themselves.モデルと学習Model InterpretabilityAI research+3
スライド 4 枚13:30EN
3Blue1Brown· 2025年8月17日How AlphaGeometry Combines Logical Proof with Creative ConstructionAleph0Aleph0 explains how a symbolic geometry solver gets surprisingly far without AI, and how a language model supplies the auxiliary constructions that take it to Olympiad level.MathematicsReasoning & test-time computeAI research+2
57:52EN
Unsupervised Learning: With Jacob Effron· 2025年8月13日ポッドキャストThey Aimed for 1%. The Lab Hit 20%. Chai Discovery Moved Antibody Design Onto the Computer.ホスト Jacob EffronJoshua Meier on three waves of AI drug discovery, why Chai-2 behaves like Photoshop for molecules, and why a 1% hit rate was supposed to be enough to change the industry.モデルと学習AI for scienceComputational Biology+3
スライド 7 枚15:08EN
Matthew Berman· 2025年8月8日GPT-5 at Launch: Routing, Coding, Benchmarks and ReliabilityMatthew Berman · Forward FutureMatthew Berman reviews OpenAI’s 2025 GPT-5 release, its unified ChatGPT experience, benchmark claims and the limitations of model evaluations.OpenAIモデルと学習Benchmarks+2
40:32EN
Matthew Berman· 2025年8月7日Mark Chen on GPT-5, Synthetic Data and the Future of AI ResearchMatthew Berman, Mark Chen · Forward FutureOpenAI’s head of research discusses training, agents, open-weight releases and evaluation with Matthew Berman in August 2025.OpenAIモデルと学習Synthetic data+2
スライド 3 枚10:28EN
Matthew Berman· 2025年8月5日OpenAI’s gpt-oss Models: Open Weights, Benchmarks and SafetyMatthew Berman · Forward FutureMatthew Berman reviews the 120b and 20b models, local deployment claims, selected evaluations and the scope of OpenAI’s safety testing.モデルと学習AI research評価(Evals)+1
スライド3:13EN
Matthew Berman· 2025年8月5日Claude Opus 4.1: Anthropic’s August 2025 Benchmark UpdateMatthew Berman · Forward FutureMatthew Berman reviews the model’s reported coding, reasoning and tool-use results, including one benchmark that declined.モデルと学習評価(Evals)コーディングエージェント
スライド 9 枚15:30EN
Matthew Berman· 2025年7月31日Qwen3 Tested: Coding Demos, Long Context and Response BehaviorMatthew Berman · Forward FutureMatthew Berman tests generated simulations, political and safety prompts, hand tracking and word puzzles using a hosted Qwen3 model.Open-weight modelsコーディングエージェント評価(Evals)+2
スライド 6 枚11:28EN
Matthew Berman· 2025年7月30日GLM-4.5: Coding Demos, Model Sizes and Z.ai’s BenchmarksMatthew Berman · Forward FutureMatthew Berman tests interactive applications built with GLM-4.5 and examines Z.ai’s reported comparisons with leading models in July 2025.Open-weight modelsコーディングエージェントBenchmarks+2
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.モデルと学習Reasoning & test-time computeBenchmarks+3
スライド 4 枚6:53EN
Matthew 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.コーディングエージェントOpen-weight modelsモデルと学習+2
スライド 16 枚23:39ZH
跟李沐学AI· 2025年7月23日李沐:给文本大模型加入一千万小时语音,开源 Higgs Audio李沐 · Boson AI李沐介绍团队如何在文本大语言模型的训练里加入大量语音数据,做成能听能说的 AudioLLM,并把 Higgs Audio 开源。他讲了架构取舍、token 压缩、数据从哪来,以及怎么在 3090 上跑起来。音声 AIMultimodal AIモデルと学習+2
1:07:41EN
20VC with Harry Stebbings· 2025年7月21日ポッドキャスト · 2 人Edwin Chen on Building Surge and the Data Behind AI Modelsゲスト Edwin Chen · ホスト Harry StebbingsThe Surge founder discusses a bootstrapped business, training-data quality and the limits he sees in AI benchmarks and synthetic data.Data quality & curationCompany Buildingモデルと学習+2
47:05EN
Matthew Berman· 2025年7月21日Logan Kilpatrick on AI Developers, Interfaces, and the Future of ModelsMatthew Berman, Logan Kilpatrick · Forward FutureIn a July 2025 conversation, Google’s Logan Kilpatrick discusses Windsurf, agent interfaces, coding skills, Veo, and the shifting boundary between models and application scaffolding.AI researchコーディングエージェントエージェント+2
49:55EN
Matthew Berman· 2025年7月17日Aravind Srinivas on Comet, AI Browsers and the Future of WorkMatthew Berman, Aravind Srinivas · Forward FuturePerplexity’s CEO explains why the company built a browser, how it evaluates models and why he expects AI to disrupt jobs.エージェントProduct StrategyAI Strategy+2
38:10EN
Cognitive 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.モデルと学習ファインチューニングPost-training+3
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