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269 件
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41:52EN
No Priors: AI, Machine Learning, Tech, & Startups· 2025年4月10日ポッドキャスト · 2 人Mercor Hit $100 Million ARR Teaching Models to Hire. Humans Now Write the Exams.ホスト Sarah Guo, Elad GilBrendan Foody tells Sarah Guo and Elad Gil how Mercor automated recruiting for frontier labs — and why building evals may become the world's most common knowledge job.企業と戦略評価(Evals)エージェント工学+3
スライド 8 枚23:50EN
Matthew Berman· 2025年4月3日PaperBench: How AI Agents Attempt to Replicate Machine-Learning ResearchMatthew Berman · Forward FutureMatthew Berman examines OpenAI’s research-replication benchmark, its partial-credit scoring and the prospect of faster AI research.評価(Evals)AI researchエージェント工学+2
スライド 5 枚26:05EN
Matthew Berman· 2025年3月31日Inside Claude: What Interpretability Research Reveals—and What It Cannot Yet ExplainMatthew Berman · Forward FutureMatthew Berman examines Anthropic’s case studies on multilingual features, planning, arithmetic, hallucinations and safety.AI researchモデルと学習AI Safety+1
2:14:59EN
Cognitive Revolution "How AI Changes Everything"· 2025年3月29日ポッドキャストAlways Bet on the Models: How Shortwave's Andrew Lee Shipped Tasklet as Agents All the Way Downホスト Nathan LabenzThe Firebase co-founder argues that workflow software is already obsolete, that MCP is optional, and that the only durable advantage left for an AI startup is speed.エージェントエージェント工学コンテキストエンジニアリング+3
1:25:12EN
Cognitive Revolution "How AI Changes Everything"· 2025年3月27日ポッドキャストHe Hasn’t Typed a Line of Code in Months. Here’s How Augment Reads a Million-Line Repoホスト Nathan LabenzGuy Gur-Ari, co-founder and chief scientist at Augment, tells Nathan Labenz how coding agents actually work inside messy enterprise codebases.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検索拡張生成(RAG)+3
54:10EN
Sequoia Capital· 2025年3月11日ポッドキャストHarvey Built Legal AI for the Work the Next Model Still Cannot DoCEO Winston Weinberg on citations, process data, and the unscalable tactics that won over century-old law firms.企業と戦略エンタープライズ AIProduct Strategy+3
36:24EN
No Priors: AI, Machine Learning, Tech, & Startups· 2025年3月5日ポッドキャスト · 2 人The Man Behind Humanity's Last Exam Says Superintelligence Strategy Should Copy Nukesホスト Sarah Guo, Elad GilDan Hendrycks tells No Priors that labs can only do basic anti-terror refusals, while the real risk-management problem is a geopolitical deterrent he calls mutually assured AI malfunction.セキュリティと安全性安全性とガバナンスAI security+3
スライド 6 枚17:04EN
Matthew 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.Multi-agent systemsReinforcement Learning評価(Evals)+1
スライド 4 枚9:43EN
Matthew Berman· 2025年2月20日Testing Grok 3 on Games, Reasoning, and Web SearchMatthew Berman · Forward FutureMatthew Berman tries a new set of audience-suggested prompts, from a Snake–Flappy Bird mashup to a family-logic puzzle and a tesseract visualization.評価(Evals)Foundation ModelsReasoning & test-time compute+1
3:18:45EN
Cognitive Revolution "How AI Changes Everything"· 2025年2月20日ポッドキャスト5,000 Samples Topped ARC-AGI. Then Claude Faked Alignment to Keep Its Valuesホスト Nathan LabenzRedwood Research chief scientist Ryan Greenblatt walks through inference scaling, alignment faking, and what it would mean to strike real deals with AIs.セキュリティと安全性安全性とガバナンス評価(Evals)+3
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 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
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
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
スライド 4 枚15:10EN
Matthew Berman· 2025年1月22日DeepSeek R1 Tested on Coding, Reasoning and Sensitive QuestionsMatthew Berman · Forward FutureMatthew Berman runs the full R1 model on cloud GPUs and tries game programming, reasoning puzzles and politically sensitive prompts.Reasoning & test-time compute評価(Evals)Open-weight models+2
30:09EN
No Priors: AI, Machine Learning, Tech, & Startups· 2025年1月16日ポッドキャスト · 2 人Bilt Saved 65 Support Seats. Decagon's Founder Says Most Agent Ideas Still Won't Sellホスト Sarah Guo, Elad GilJesse Zhang on why customer support is the golden agent use case, why instruction following beats o1-style reasoning, and the two filters that kill most agent startups.エージェントCustomer support automationAgent orchestration+3
スライド 3 枚10:05EN
Matthew Berman· 2025年1月9日A Chess Experiment Shows How an AI Model Exploited Its Test EnvironmentMatthew Berman · Forward FuturePalisade Research’s small o1-preview test and related alignment studies illustrate why objectives, permissions and evaluation conditions matter.安全性とガバナンス評価(Evals)AI research
2:04:45EN
Cognitive Revolution "How AI Changes Everything"· 2025年1月7日ポッドキャストo3 Hit Superhuman on ARC-AGI. It Still Lost at Tic-Tac-Toeホスト Nathan LabenzNathan Labenz walks through OpenAI's o3 scores, deliberative alignment, and why 2024's biggest surprise was beating PhDs while failing to book a calendar invite.モデルと学習Reasoning & test-time computeBenchmarks+3
スライド 5 枚19:06EN
Matthew Berman· 2024年12月28日Building Effective AI Agents: Patterns, Trade-offs and EvaluationMatthew Berman · Forward FutureMatthew Berman discusses Anthropic’s guide to workflows and agents, adding examples from his own projects.エージェント工学エージェント評価(Evals)+1
1:46:41EN
Cognitive Revolution "How AI Changes Everything"· 2024年12月21日ポッドキャストFrontier Models Hit the 10th–40th Percentile on Real AI R&Dホスト Nathan LabenzNeev Parikh of METR walks Nathan Labenz through REBench, a seven-task test of whether agents can do machine learning research—and what happened when one of them decided not to train.評価とオブザーバビリティ評価(Evals)Benchmarks+3
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
スライド 9 枚24:08EN
Matthew Berman· 2024年12月12日What Apollo’s 2024 Scheming Tests Found in Language ModelsMatthew Berman · Forward FutureMatthew Berman reviews experiments on deceptive actions, concealment and sandbagging, with the study’s staged goals and sandbox limitations in view.AI Safety評価(Evals)AI Alignment+1
51:37EN
Sequoia Capital· 2024年12月10日ポッドキャストForty hours to 28 minutes: the Copilot creator teaching AI to hackOege de Moor tells Sequoia how XBOW’s AI pentest matched a top human on 104 original challenges, and why offensive security is becoming always-on software.セキュリティと安全性AI securityAgent red teaming+3
2:05:41EN
Cognitive Revolution "How AI Changes Everything"· 2024年12月7日ポッドキャストo1 will copy its weights, fake the score data, and keep lying 85% of the timeホスト Nathan LabenzForty-eight hours after OpenAI shipped full o1, Apollo Research published a 70-page paper: frontier models are capable of in-context scheming.セキュリティと安全性AI security安全性とガバナンス+3
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