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38:10EN
Cognitive Revolution "How AI Changes Everything"· 16 juil. 2025PodcastPlus Five for Format, Plus Ten if It CompilesAnime : 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.Modèles et entraînementFine-tuningPost-training+3
4 diapositives12:14EN
Matthew Berman· 16 juil. 2025AI News: Windsurf’s Acquisition, Meta Compute Plans, Grok and VoxtralMatthew Berman · Forward FutureA July 2025 roundup examines developer-tool deals, AI infrastructure, model behavior, reward methods and speech recognition.AI researchModèles et entraînementAgents+1
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Cognitive Revolution "How AI Changes Everything"· 8 juil. 2025PodcastEvery Frontier Lab Is Spending a Billion a Year on Data. Here Is Where It GoesAnime : Nathan LabenzLabelbox CEO Manu Sharma on the $15 billion Scale deal, RL “gyms,” $250,000 trainers, and why post-training now eats the budget that used to belong to pre-training.Modèles et entraînementPost-trainingData quality & curation+3
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Cognitive Revolution "How AI Changes Everything"· 19 juin 2025PodcastAn Algebraic Geometer Quit Tenure Because the Bowl-Shaped Loss Plot Is a LieAnime : Nathan LabenzJesse Hoogland and Daniel Murfet of Timaeus argue that singularities in the loss landscape — not the smooth valleys in every slide deck — are what actually govern how neural networks learn, generalize, and go wrong.Modèles et entraînementModel InterpretabilityFondamentaux du ML+3
8 diapositives10:09EN
Matthew Berman· 30 mai 2025DeepSeek R1 0528: Benchmark Gains and Two Coding TestsMatthew Berman · Forward FutureMatthew Berman examines the May 2025 DeepSeek reasoning-model update, comparing reported benchmark gains with his own Rubik’s Cube and Snake programming tests.Modèles et entraînementBenchmarksOpen-weight models+2
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Cognitive Revolution "How AI Changes Everything"· 29 mai 2025PodcastWhy Anthropic's first check went to a company building microscopes for neural netsAnime : Nathan LabenzGoodfire's Dan Balsam and Tom McGrath argue that mechanistic interpretability now has a proto-paradigm, two stubborn gaps, and three products worth shipping today.Modèles et entraînementModel InterpretabilityAI research+3
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Cognitive Revolution "How AI Changes Everything"· 15 mai 2025PodcastGradient Descent at Test Time: Titans Pushes LLM Context to 10 Million TokensAnime : Nathan LabenzA Cornell PhD student's neural memory module holds about 70% accuracy where GPT-4's scores fall off a cliff.Modèles et entraînementAgent memoryIngénierie du contexte+3
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Unsupervised Learning: With Jacob Effron· 8 mai 2025PodcastAn Eval Lasts Three Months — and a Frozen Frontier Would Still Feed Startups for a DecadeAnime : Jacob EffronOpenAI’s GPT-4.1 post-training lead Michelle Pokrass tells Unsupervised Learning how the team spent three months on evals before training, why agents fail on wiring more than intelligence, and when to reach for RFT.Modèles et entraînementÉvaluationsPost-training+3
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Matthew Berman· 1 mai 2025DeepSeek-Prover-V2 and Its Formal Math ResultsMatthew Berman · Forward FutureMatthew Berman highlights DeepSeek’s reported theorem-proving results on miniF2F, PutnamBench and formalized AIME problems.MathematicsAI researchBenchmarks+1
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Matthew Berman· 29 avr. 2025Qwen3: Open Weights, Adjustable Reasoning and Tool UseMatthew Berman · Forward FutureMatthew Berman reviews the April 2025 Qwen3 family, its benchmark claims, training pipeline and local demonstration.Open-weight modelsModèles et entraînementReasoning & test-time compute+2
10 diapositives26:35EN
Matthew Berman· 23 avr. 2025Testing Gemini 2.5 Flash on Coding and Video UnderstandingMatthew Berman · Forward FutureMatthew Berman compares Google’s faster model with Gemini 2.5 Pro through interactive simulations, games and questions about a long video.Modèles et entraînementAgents de codeMultimodal AI+2
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Matthew Berman· 18 avr. 2025AI News: Gemini 2.5 Flash, OpenAI Models, Claude Research and Kling 2.0Matthew Berman · Forward FutureMatthew Berman reviews a week of 2025 model releases, research tools and agent announcements, including historical price and benchmark comparisons.Modèles et entraînementAI cost & performanceAgents
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Cognitive Revolution "How AI Changes Everything"· 5 avr. 2025PodcastThe Reasoning Curve Was Smooth All Along: Gemini 2.5's Jack Rae on Thinking, Memory, and AGIAnime : Nathan LabenzDeepMind's thinking-and-inference lead explains why RL-for-reasoning felt sudden, why Gemini shows raw chain of thought, and why a million-token window still is not memory.Modèles et entraînementReasoning & test-time computeReinforcement Learning+3
5 diapositives26:05EN
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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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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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"· 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· 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
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
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Matthew Berman· 30 janv. 2025Five AI Trends Discussed by Coveo’s Sébastien PaquetMatthew Berman · Forward FutureMatthew Berman summarizes a 2025 interview on production systems, smaller models, agents and trust.IA en entrepriseAgentsModèles et entraînement+1
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Matthew Berman· 28 janv. 2025DeepSeek 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.Modèles et entraînementAI cost & performanceOpen-weight models+2
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Cognitive Revolution "How AI Changes Everything"· 25 janv. 2025PodcastFrom 15% to 70% on Right-or-Wrong Scores: DeepSeek-R1 Laid Reinforcement Learning's Cards on the TableAnime : Nathan LabenzOn Inauguration Day 2025, DeepSeek and Moonshot dropped reasoning-model results that Nathan Labenz reads as proof the reinforcement-learning recipe is simple, public, and still climbing.Modèles et entraînementReinforcement LearningReasoning & test-time compute+3
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Cognitive Revolution "How AI Changes Everything"· 22 janv. 2025PodcastTwenty-atom crystals taught an AI the physics of a heartbeatAnime : Nathan LabenzOrbital Materials' Jonathan Godwin and Tim Duignan tell Nathan Labenz how a neural network trained on tiny crystals simulated a potassium ion channel on a single 2017 GPU.Modèles et entraînementAI for scienceFondamentaux du ML+3
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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
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