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32:22ENQwen 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.
1:29:30EN2,500 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.
15:43ENHow AI Data Centers Work: Power, Cooling and Community TradeoffsMatthew Berman · Forward FutureMatthew Berman explains the physical infrastructure behind AI prompts, from accelerator racks and backup power to water use and local planning.
13:53ENTiny 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.
1:53:50ENA curriculum rewrite takes five years. AI does not wait.ホスト Nathan LabenzJohan Falk, a Swedish teacher-turned-analyst, argues that AI literacy and AI friends are more urgent than putting a tutor in every classroom.
1:37:25ENFin Climbed From 35% to 65% Resolution. Intercom Says the Models Only Did a Few Pointsホスト Nathan LabenzEoghan McCabe and Fergal Reid on production A/B tests, 99-cent outcome pricing, and why GPT-4 was already smart enough for most customer service.
28:27ENSora 2 in Practice: Cameos, Camera Direction and Video Generation ErrorsMatthew Berman · Forward FutureMatthew Berman surveys early Sora 2 clips, testing likenesses, hands, motion, graphics and physics while pointing out where the generated scenes break down.
1:01:49ENChatGPT'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.
26:17EN21 Practical AI Uses for Design, Work and ResearchMatthew Berman · Forward FutureMatthew Berman demonstrates ways to use image tools, ChatGPT and NotebookLM for visual concepts, research, everyday work and study.
2:20:35ENChatGPT Is a Thousand Days Old. Emad Mostaque Says We Have About a Thousand Left.ホスト Nathan LabenzThe Stability AI founder’s new economics argues that when intelligence is abundant, scarcity-based money and GDP stop making sense.
0:58ENMicrosoft’s Nebius GPU Infrastructure AgreementMatthew Berman · Forward FutureIn a sponsored video, Matthew Berman discusses a 2025 infrastructure agreement and Nebius’s AI services.
1:22:07ENEvery 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.
15:29ENBuilding a Multi-Agent Research Team with Strands AgentsMatthew Berman · Forward FutureMatthew Berman builds from a calculator agent to a multi-agent business-report demo, with examples of tools, model selection and orchestration.
1:02:05EN$100 Million Researchers and a $200 Billion xAI: An AI Roundtable Does the Mathホスト Jacob EffronDatology’s Ari Morcos and Radical Ventures’ Rob Toews argue over whether models are plateauing, whether RL-environment startups will last, and why Google is the lab they would pick.
1:28:17ENAdam Gleave's Three Capability Tiers: Attack Agents in 5–7 Years, Fully AI Companies Around Year 14ホスト Nathan LabenzFAR.AI and the UK AI Security Institute stacked adversarial attacks on frontier safeguard pipelines and found many breakthroughs were engineering failures, not a verdict against defense in depth.
14:47ENAI News in September 2025: OpenAI’s Programming Test, Meta’s REFRAG and New Agent ToolsMatthew Berman · Forward FutureMatthew Berman surveys competition results, efficient retrieval, agent payments, 3D worlds and model launches, alongside updates on Waymo and AI video. The episode distinguishes announcements, research claims and rumors from established outcomes.
16:29ENWhat Anthropic’s 2025 Economic Index Says About AI Adoption and WorkMatthew Berman · Forward FutureMatthew Berman explores Claude usage across tasks, countries and businesses, and considers what uneven adoption could mean for workers and inequality.
42:20ENA Name Invented at 2:30 a.m. Put Gemini on Top of the App Storeホスト Jacob EffronGoogle's Nicole Brichtova and Oliver Wang on Nano Banana, why image models got smart when language models did, and why a prompt still is not a finished product.
8:47ENWhy Identical LLM Prompts Can Produce Different Answers at Temperature ZeroMatthew Berman · Forward FutureMatthew Berman explains Thinking Machines Lab’s work on batch-invariant inference and what its reproducibility experiment actually showed.
18:05ENAI News: Qwen3-Max, OpenAI’s Restructuring and New Research ModelsMatthew Berman · Forward FutureMatthew Berman surveys September 2025 releases and reports, from silent speech and image generation to infrastructure and AI business deals.
1:32:47ENA transformer co-author wants a $160 million model no company ownsホスト Nathan LabenzIllia Polosukhin tells Nathan Labenz how NEAR turned a payments headache into a stack for private inference, shared-revenue training, and AI agents that still answer to a court.
1:44:35ENJoe Hudson: $500 Billion Went Into AI, and Nobody Defined 'Good for Humanity'ホスト Nathan LabenzSam Altman says the OpenAI coach's superpower is emotional clarity — and that it will be one of the most critical skills in a post-AGI world.
59:06ENInference Costs Fell 100x. Tri Dao Says There's Another 10x — and NVIDIA's 90% Won't Holdホスト Jacob EffronThe FlashAttention author and Together AI chief scientist on why hardware portability is a myth, how Claude Code made him 1.5x faster, and why workloads will split the chip market.
3:14:49ENNothing This Summer Jumped the Curve: Why Zvi Lengthened His AGI Timelinesホスト Nathan LabenzOn his tenth visit to The Cognitive Revolution, Zvi Mowshowitz argues that GPT-5 and IMO gold stayed on trend, while chip policy, energy, and reinforcement learning nudged his p(doom) slightly up.
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