Apr 27, 2026

The $15B Physical AI Company: Simulation, Autonomy OS, Neural Sim, & 1K Engineers—Applied Intuition

Qasar Younis and Peter Ludwig, founders of Applied Intuition, discuss the shift from autonomy tooling to a comprehensive physical AI platform. They explain why physical AI is more than just LLMs on wheels, highlighting the critical bottleneck of deploying models onto constrained hardware. The conversation covers their three-pillar tech stack—simulation, operating systems, and AI models—and makes the case for an 'Android for every moving machine' to solve the fragmentation in safety-critical systems like cars, trucks, and robots.

Apr 23, 2026

Why Most Robot Demos Are Fake

Changan Chen, co-founder of Rhoda AI, discusses their vision-first approach to building foundation models for robotics. The conversation covers their unique training pipeline, the distinction between policy and world models, and the path to deploying data-efficient, reliable robots in real-world industrial settings.

Apr 08, 2026

From Neural Networks to Digital Brains: The Next Leap in AI • Daniel Lütgehetmann • GOTO 2025

Daniel Lütgehetmann of inait introduces "digital brains," biologically accurate computational models of real brains, as a solution to current AI's limitations in physical world interaction. Unlike traditional AI that struggles with dynamic environments and skill accumulation, these digital brains leverage biologically inspired learning rules to achieve dramatically faster learning in robotics and complex systems, demonstrating potential for real-world adaptability and efficiency.

Mar 20, 2026

Andrej Karpathy on Code Agents, AutoResearch, and the Loopy Era of AI

Andrej Karpathy discusses the paradigm shift to AI agent-driven development, the future of engineering and research with his AutoResearch project, the impact on jobs, and the evolving landscape of open-source models, robotics, and education.

Mar 19, 2026

This Technology Scares OpenAI (Here's Why)

Jeff Hawke, CTO at Odyssey, provides a deep dive into the emerging field of "world models"—AI systems that generate continuous, interactive simulations. He draws parallels to the "GPT-2 era" of LLMs, outlining the current state, core research challenges like coherence and control, and the immense potential for applications in gaming, robotics, and content creation. Hawke also clarifies the confusing terminology, distinguishing canonical world models from spatial intelligence and generative video models like Sora.

Jan 27, 2026

Beyond AI implementation: Introducing JDLA's initiatives

This presentation by the Japan Deep Learning Association (JDLA) details Japan's strategy for accelerating AI adoption. It covers the government's strong pro-AI stance driven by demographic challenges, the critical need for corporate AI governance, and the rise of physical AI in robotics. JDLA's core initiatives are highlighted, including the G- and E-Certificate programs for talent development, which are increasingly becoming corporate standards, and the establishment of the AI Robot Association (AIROA) to build a foundational data infrastructure for robotics.