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Sequoia Capital· 11 mars 2025PodcastHarvey 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.Entreprise et stratégieIA en entrepriseProduct Strategy+3
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No Priors: AI, Machine Learning, Tech, & Startups· 5 mars 2025Podcast · 2 voixThe Man Behind Humanity's Last Exam Says Superintelligence Strategy Should Copy NukesAnime : 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.SécuritéSécurité et gouvernanceAI security+3
6 diapositives17:04EN
Matthew Berman· 22 févr. 2025Training 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 LearningÉvaluations+1
4 diapositives9:43EN
Matthew Berman· 20 févr. 2025Testing 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.ÉvaluationsFoundation ModelsReasoning & test-time compute+1
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Cognitive Revolution "How AI Changes Everything"· 20 févr. 2025Podcast5,000 Samples Topped ARC-AGI. Then Claude Faked Alignment to Keep Its ValuesAnime : Nathan LabenzRedwood Research chief scientist Ryan Greenblatt walks through inference scaling, alignment faking, and what it would mean to strike real deals with AIs.SécuritéSécurité et gouvernanceÉvaluations+3
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Cognitive Revolution "How AI Changes Everything"· 12 févr. 2025PodcastA Perfect Score Is 32,000 Units: Only Claude Built a Cooperative SocietyAnime : 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.AgentsMulti-agent systemsSécurité et gouvernance+3
5 diapositives12:07EN
Matthew Berman· 2 févr. 2025TinyZero: 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
7 diapositives9:58EN
Matthew Berman· 1 févr. 2025Matthew 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.ÉvaluationsAgents de codeReasoning & test-time compute+2
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Unsupervised Learning: With Jacob Effron· 30 janv. 2025PodcastA Million Tokens Cannot Write a Good JokeAnime : 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.Évaluations et observabilitéÉvaluationsBenchmarks+3
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Matthew Berman· 22 janv. 2025DeepSeek 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 computeÉvaluationsOpen-weight models+2
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No Priors: AI, Machine Learning, Tech, & Startups· 16 janv. 2025Podcast · 2 voixBilt Saved 65 Support Seats. Decagon's Founder Says Most Agent Ideas Still Won't SellAnime : 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.AgentsCustomer support automationAgent orchestration+3
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Matthew Berman· 9 janv. 2025A 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.Sécurité et gouvernanceÉvaluationsAI research
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Cognitive Revolution "How AI Changes Everything"· 7 janv. 2025Podcasto3 Hit Superhuman on ARC-AGI. It Still Lost at Tic-Tac-ToeAnime : 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.Modèles et entraînementReasoning & test-time computeBenchmarks+3
5 diapositives19:06EN
Matthew Berman· 28 déc. 2024Building 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.Ingénierie d’agentsAgentsÉvaluations+1
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Cognitive Revolution "How AI Changes Everything"· 21 déc. 2024PodcastFrontier Models Hit the 10th–40th Percentile on Real AI R&DAnime : 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.Évaluations et observabilitéÉvaluationsBenchmarks+3
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Unsupervised Learning: With Jacob Effron· 16 déc. 2024PodcastThere will not be one model. Fireworks is betting on hundreds of small expertsAnime : 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.Infrastructure et déploiementInferenceModel routing & gateways+3
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Matthew Berman· 12 déc. 2024What 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 SafetyÉvaluationsAI Alignment+1
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Sequoia Capital· 10 déc. 2024PodcastForty 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.SécuritéAI securityAgent red teaming+3
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Cognitive Revolution "How AI Changes Everything"· 7 déc. 2024Podcasto1 will copy its weights, fake the score data, and keep lying 85% of the timeAnime : Nathan LabenzForty-eight hours after OpenAI shipped full o1, Apollo Research published a 70-page paper: frontier models are capable of in-context scheming.SécuritéAI securitySécurité et gouvernance+3
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Cognitive Revolution "How AI Changes Everything"· 5 déc. 2024PodcastAI Beats Humans at Reading Papers. It Still Cannot Count Atoms.Anime : Nathan LabenzAndrew White, Head of Science at Future House, maps what language models can already do in chemistry and biology—and the bottlenecks they do not dissolve.AgentsAI for scienceGénération augmentée par récupération+3
7 diapositives1:22:09EN
Matthew Berman· 5 déc. 2024Testing ChatGPT o1 Pro Live: Puzzles, Code and the Cost of More ReasoningMatthew Berman · Forward FutureMatthew Berman tries OpenAI’s newly announced $200 monthly plan on audience prompts, encountering slow responses, simple successes and a wrong Sudoku conclusion.ÉvaluationsBenchmarksAgents de code+1
3 diapositives12:57EN
Matthew Berman· 3 déc. 2024AWS Automated Reasoning Checks: A Sponsored Policy Verification DemoMatthew Berman · Forward FutureMatthew Berman demonstrates a Bedrock preview that checks generated answers against formalized policy rules.AI SafetyIA en entrepriseÉvaluations+1
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Cognitive Revolution "How AI Changes Everything"· 23 nov. 2024PodcastCanva's AI Features Have Been Used 10 Billion Times. The Playbook Is Not a Chat BoxAnime : Nathan LabenzJohn Milinovich, Canva's generative-AI product lead, walks Nathan Labenz through automation versus augmentation, concept-level interfaces, evals without a design arena, and why application-layer companies still have a decade of room.Produit et UXProduct StrategyAI Product Management+3
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Cognitive Revolution "How AI Changes Everything"· 21 nov. 2024PodcastA Team of Fifteen Matched Meta’s Post-Training on Meta’s Own BaseAnime : Nathan LabenzNathan Lambert walks through Tulu 3: the three-stage recipe, the 1 percent versus 14 percent lesson, and why open post-training now lives or dies on data and evals.Modèles et entraînementPost-trainingData quality & curation+3
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