Episodes
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🔬 The Coolest Diffusion Research Isn't in LLMs — Evan Feinberg & Sergey Edunov, Genesis Molecular AI
Significant AI advances, especially diffusion models and high-precision structure prediction, are transforming drug discovery.
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⚡️ The Blueprint for Autonomous Work Agents | Gavriel Cohen, NanoClaw
Not summarized yet
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Why the Frontier Ecosystem must be Open — Matei Zaharia and Reynold Xin, Databricks
Databricks has evolved from a small meetup to a leading global AI and data platform with a strong community.
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Red-Teaming after Mythos — Zico Kolter & Matt Fredrikson, Gray Swan
AI security requires a specialized mindset distinct from traditional cybersecurity due to the unique vulnerabilities of large language models (LLMs).
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⚡️ Every product of the future will be a living system — Ronak Malde, Trajectory.ai
Not summarized yet
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The Professor of Outputmaxxing — Anjney Midha, AMP
High utilization of AI compute resources is critical to maximize efficiency and prevent wastage, both economically and in terms of resource sustainability.
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🔬 The Self-Driving Lab — Joseph Krause, Radical AI
AI in materials science faces unique challenges due to the complex variables involved, unlike molecular or biological models.
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⚡️ Making DeepSeek v4 outperform Opus 4.7 with Taste — @AhmadAwais , CommandCode.ai
Not summarized yet
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Reality: The Final Eval — Lukas Petersson and Axel Backlund of Andon Labs
Realistic AI evaluation goes beyond traditional benchmarks by measuring economic and operational capabilities relevant to real-world applications.
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🔬 Scaling Past Informal AI - Carina Hong, Axiom Math
Formal verification is transforming AI from regulatory checkbox into a tool for scaling and improving human-like brilliance.
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⚡️ Satya Nadella: No Priors x Latent Space Crossover Special at Microsoft Build
Viewing AI development as an ecosystem strategy allows broader participation and value creation across enterprises.
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GitHub's plan for Agents — Kyle Daigle, GitHub
AI is fundamentally transforming software development, leadership, and infrastructure at scale, enabling more automation and faster innovation.
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Why Video Agent models are next — Ethan He, xAI Grok Imagine
Rapid iteration speeds are crucial for cutting-edge AI development, often yielding more gains than algorithmic innovation.
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The Age of Async Agents — Cognition's Walden Yan & OpenInspect's Cole Murray
The development and deployment of autonomous background agents have accelerated significantly since December 2025, largely driven by improved model capabilities.
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🔬 ESM: The Bitter Lesson is Coming for Proteins - Alex Rives, BioHub
Large-scale unsupervised language models trained on extensive biological data can learn complex functional and structural properties of proteins, emerging capabilities as data and compute scale.
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⚡️ Google's Open AI Strategy — Omar Sanseviero, Google DeepMind
Not summarized yet
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⚡️ Why you should build Science Fiction — Sunil Pai, Cloudflare
Not summarized yet
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Giving Agents Computers — Ivan Burazin, Daytona
Daytona is built on bare metal hardware with its own scheduler, enabling ultra-fast startup times and high concurrency for AI workloads.
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Railway: The Agent-Native Cloud — Jake Cooper
Railway aims to simplify deployment by reducing activation energy, enabling fast iteration and evolution of applications without complex tooling.
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🔬 The Autonomous Drone Tech Stack & Economics of Drones — Yaroslav Azhnyuk, The Fourth Law & Guest Host Noah Smith, Noahpinion
The rapid proliferation and scale of drone manufacturing, especially in China, pose a significant strategic threat and could shift global military power.
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