Episodi

  • Attention Is All You Need — The Paper That Changed Everything

    Attention Is All You Need — The Paper That Changed Everything
    Feb 11 2026
    In our inaugural episode, we dive deep into Attention Is All You Need — the 15-page paper from June 2017 that introduced the Transformer architecture and reshaped all of artificial intelligence. We break down how it works, why the title is a Beatles joke, and where all eight authors ended up — from Google Gemini to RNA therapeutics to blockchain.
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    16 min
  • Generative Modeling via Drifting — One-Step Image Generation

    Generative Modeling via Drifting — One-Step Image Generation
    Feb 12 2026
    Researchers from MIT and Harvard propose Drifting Models, a new paradigm for generative modeling that achieves state-of-the-art image generation in a single forward pass. Instead of iterating at inference time like diffusion models, Drifting Models evolve the generated distribution during training using an elegant attraction-repulsion mechanism. The result: one-step image generation with FID 1.54 on ImageNet 256x256, beating even multi-step diffusion models. From the lab of Kaiming He, the creator of ResNet.
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    13 min
  • DreamDojo — Teaching Robots to Dream

    DreamDojo — Teaching Robots to Dream
    Feb 13 2026
    Researchers from UC Berkeley, NVIDIA, and UT Austin introduce DreamDojo, a framework that teaches robots physical skills by learning from large-scale human videos. Instead of expensive robot-specific data, DreamDojo distills 5 years of human video into a generalist world model that runs in real time. We break down how it works, why the team composition matters, and what it means for the future of robotics.
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    21 min
  • The Week China Open-Sourced The Frontier

    The Week China Open-Sourced The Frontier
    Feb 14 2026
    In a 48-hour span, three Chinese AI labs independently released frontier-class open-weight models. Step 3.5 Flash from StepFun delivers frontier intelligence with just 11 billion active parameters. MiniMax M2.5 offers comparable performance at one-twentieth the cost of Western alternatives. And GLM-5 from Zhipu AI trained a 744-billion parameter model entirely on Huawei Ascend chips — zero NVIDIA hardware. We break down the architectures, the benchmarks, the researchers behind them, and what it means when the frontier becomes a public good.
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    20 min
  • From Blood Sacrifice to Universal Translator

    From Blood Sacrifice to Universal Translator
    Feb 15 2026
    In July 2024, a French nonprofit's open-source voice AI went viral for demanding human sacrifice mid-conversation. Seven months later, the same team used the same architecture to build a real-time speech translator that runs on your phone. This is the story of Kyutai Labs — how Moshi became the Blood God, how Hibiki became a universal translator, and why transparency beats secrecy every time.
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    21 min
  • Building a Robot Mind in the Open

    Building a Robot Mind in the Open
    Feb 16 2026
    Alibaba DAMO Academy built a complete embodied AI system in six months — eyes, hands, imagination, unified brain — and open-sourced everything. Seven model checkpoints, Apache 2.0, zero gating. This is the story of RynnBrain.
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    15 min
  • ΔBelief-RL: Rethinking How AI Learns to Act

    ΔBelief-RL: Rethinking How AI Learns to Act
    Feb 17 2026
    We explore a bold new framework that rethinks reinforcement learning from the ground up — replacing reward maximization with belief updating, and asking whether AI agents should learn the way scientists do.
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    21 min
  • SkillRL: Don't Give Agents Memories, Give Them Skills

    SkillRL: Don't Give Agents Memories, Give Them Skills
    Feb 18 2026
    SkillRL from UNC Chapel Hill achieves 89.9% on ALFWorld with a 7B model — beating GPT-4o by 41.9 points. The secret: distilling raw experience into compact, reusable skills instead of storing verbose trajectory memories.
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    20 min