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6 diapositives16:02EN
Matthew Berman· 1 avr. 2025Runway Gen-4 Examples: Cinematic Motion, Style and Visible ErrorsMatthew Berman · Forward FutureMatthew Berman reviews early generated clips, praising their visual detail while identifying awkward interactions and inconsistent physics.Vision et vidéoGenerative media
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Matthew Berman· 31 mars 2025Inside 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 researchModèles et entraînementAI Safety+1
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Matthew Berman· 29 mars 2025AI News in March 2025: GPT-4o, Gemini, DeepSeek and MCPMatthew Berman · Forward FutureMatthew Berman reviews model updates, the ARC-AGI-2 benchmark, image generators and early adoption of Model Context Protocol.Foundation ModelsBenchmarksMCP+2
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Cognitive Revolution "How AI Changes Everything"· 29 mars 2025PodcastAlways Bet on the Models: How Shortwave's Andrew Lee Shipped Tasklet as Agents All the Way DownAnime : 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.AgentsIngénierie d’agentsIngénierie du contexte+3
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Unsupervised Learning: With Jacob Effron· 28 mars 2025PodcastOpen-source models are 5% of enterprise use — and GPT wrappers wonAnime : Jacob EffronLatent Space's Swyx and Alessio join Redpoint to map what actually has product-market fit in AI, and why the application layer is the fight that matters.Entreprise et stratégieProduct-Market FitAI Strategy+3
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Matthew Berman· 28 mars 2025Matthew Berman Explores GPT-4o Image Generation and Its LimitsMatthew Berman · Forward FutureFrom animated trailer remakes to infographics and interface mockups, early examples show creative possibilities alongside persistent errors.Generative mediaVision et vidéoCreativity+2
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Matthew Berman· 27 mars 2025NVIDIA NIM Microservices Bring Packaged AI Models to RTX PCsMatthew Berman · Forward FutureIn an NVIDIA-sponsored short, Matthew Berman introduces local AI microservices, compatible applications and the planned PDF-to-podcast workflow.Infrastructure et déploiementLocal inferenceAI agents
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Cognitive Revolution "How AI Changes Everything"· 27 mars 2025PodcastHe Hasn’t Typed a Line of Code in Months. Here’s How Augment Reads a Million-Line RepoAnime : Nathan LabenzGuy Gur-Ari, co-founder and chief scientist at Augment, tells Nathan Labenz how coding agents actually work inside messy enterprise codebases.Agents de codeIngénierie du contexteGénération augmentée par récupération+3
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Matthew Berman· 26 mars 2025Gemini 2.5 Pro Experimental: Coding Demos and Launch BenchmarksMatthew Berman · Forward FutureIn March 2025, Matthew Berman tests Google’s experimental model on interactive simulations and reviews its launch benchmarks, including their limits.GeminiAgents de codeBenchmarks+2
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Lex Fridman· 26 mars 2025PodcastDemocrats still think politics runs on money. It runs on attention.Anime : Lex FridmanEzra Klein and Derek Thompson tell Lex Fridman why the left keeps authorizing billions it cannot build, and why DOGE is a fight over control rather than efficiency.Political PhilosophyGeopoliticsLeadership
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Cognitive Revolution "How AI Changes Everything"· 23 mars 2025PodcastA Year to Grow a Brain Organoid, an Hour to Simulate ItAnime : Nathan LabenzStanford postdoc Siyu He tells Nathan Labenz how Squidiff and CORAL move single-cell and spatial experiments into the computer — and where the models still cannot go.Modèles et entraînementAI for scienceComputational Biology+3
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Matthew Berman· 21 mars 2025Claude Adds Web Search: A First LookMatthew Berman · Forward FutureMatthew Berman enables Claude’s web search and tries a query about his latest YouTube video in March 2025.AnthropicSearch & retrievalDeveloper productivity
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Cognitive Revolution "How AI Changes Everything"· 19 mars 2025PodcastThe Fake Five-Second Hold: Voice AI Is Already Negotiating With TruckersAnime : Nathan Labenza16z partners Olivia Moore and Anish Acharya walk Nathan Labenz through what is working in voice AI — call centers, coaches, companions — and what still is not.Produit et UXIA vocaleProduct Strategy+3
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Unsupervised Learning: With Jacob Effron· 17 mars 2025PodcastA Million Tokens per Dollar: Why Noam Shazeer Thinks Inference Compute Is Still UntappedAnime : Jacob EffronThe Transformer co-inventor and Gemini researcher Jack Rae walk through test-time compute, Ilya Sutskever's AGI critique, and a four-year-old who now lectures his teacher about lizards.Modèles et entraînementReasoning & test-time computeScaling Laws+3
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Cognitive Revolution "How AI Changes Everything"· 15 mars 2025PodcastTechnology Opens the Door. Competition Pushes Us Through.Anime : Nathan LabenzAllan Dafoe on technological determinism, why alignment is not enough, and how DeepMind is trying to evaluate dangerous capabilities before they arrive.SécuritéSécurité et gouvernanceAI Strategy+3
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Cognitive Revolution "How AI Changes Everything"· 12 mars 2025PodcastAnt's $320 Billion IPO Was Stopped at the Eleventh Hour: Angela Zhang on China's Tech TightropeAnime : Nathan LabenzA USC law professor walks through the dynamic pyramid that governs Chinese tech, from Didi's listing to DeepSeek's price war, and why she thinks the United States is starting to look more like China.Entreprise et stratégieAI StrategySécurité et gouvernance+3
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Cognitive Revolution "How AI Changes Everything"· 8 mars 2025Podcasto3 took ARC from 20% to 87%. Nathan Labenz sketches early superintelligenceAnime : 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.Modèles et entraînementReinforcement LearningDistributed training & inference+3
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Matthew Berman· 7 mars 2025QwQ-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.Reasoning & test-time computeReinforcement LearningOpen Source+2
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Matthew Berman· 6 mars 2025Mercury Coder and Diffusion Language Models: Speed, Demos and LimitsMatthew Berman · Forward FutureMatthew Berman explores Inception’s 2025 coding model, comparing iterative text refinement with autoregressive generation and examining speed claims.Modèles et entraînementInferenceAgents de code+2
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Cognitive Revolution "How AI Changes Everything"· 6 mars 2025PodcastThirty Years of Research, Collapsed into One SentenceAnime : Nathan LabenzImmunologist Derya Unutmaz on writing a medical patent in half an hour, treating o1 Pro as a professor-level collaborator, and why he no longer trusts his own expertise until he asks the model.AI for scienceAI in healthcareHuman-AI Collaboration+3
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Unsupervised Learning: With Jacob Effron· 5 mars 2025PodcastMike Schroepfer: AI’s Bottleneck Is Electricity, and One Tanker of Fusion Fuel Could Power the U.S. for a YearAnime : Jacob EffronMeta’s former CTO tells Redpoint why hyperscaler demand is the climate story, why Llama was an access play, and why tomorrow’s CTO still lives or dies on a priority queue.Infrastructure et déploiementAI StrategyOpen-weight models+3
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Matthew Berman· 5 mars 2025Vibe Coding With Cursor and Windsurf: Berman’s 2025 WorkflowMatthew Berman · Forward FutureMatthew Berman shares project rules, testing habits and version-control practices from early experiments with coding agents.Agents de codeWorkflows de développement et testsHuman-AI Collaboration+2
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Cognitive Revolution "How AI Changes Everything"· 1 mars 2025PodcastChip Controls Are Meant to Buy Ten Years, Not Win the AI RaceAnime : Nathan LabenzEconomist Noah Smith tells Nathan Labenz that U.S. export controls are a piece of conventional deterrence against China — not a plan to kneecap DeepSeek.SécuritéGeopoliticsAI Strategy+2
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Cognitive Revolution "How AI Changes Everything"· 27 févr. 2025PodcastThe Attacker Goes Second: Why Nicholas Carlini Keeps Breaking AI DefensesAnime : Nathan LabenzA Google DeepMind security researcher on simple loss functions, 70% robust accuracy, and why the fix has to live in the system, not the model.SécuritéAI securitySécurité et gouvernance+3
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