Simulation

Why Physical AI Is the Next Frontier | The a16z Show

Why Physical AI Is the Next Frontier | The a16z Show

Applied Intuition discusses the emergence of physical AI, its mission to put intelligence on a billion machines, and its latest platform, Dana, designed to democratize autonomous system development. The conversation covers the vast scope of physical AI beyond automotive, the unique challenges of real-world deployment (safety, data, hardware), the current state and future of self-driving cars and trucks, and the transformative potential of humanoids and world models. They also touch upon the geopolitical landscape of AI and the global ambitions of Applied Intuition.

Robotics' End Game: Nvidia's Jim Fan

Robotics' End Game: Nvidia's Jim Fan

Jim Fan of Nvidia outlines the endgame for robotics, arguing it will mirror the successful playbook of Large Language Models. He introduces "The Great Parallel," a roadmap where World Models replace Language Models, and data collection shifts from limited teleoperation to scalable egocentric video, culminating in a future of physical APIs and automated research.

Demis Hassabis on Building DeepMind, AlphaFold, and the Final Stretch to AGI

Demis Hassabis on Building DeepMind, AlphaFold, and the Final Stretch to AGI

Demis Hassabis, CEO of Google DeepMind, outlines the path to AGI, which he predicts by 2030. He discusses the profound impact of AI on science, particularly in revolutionizing drug discovery with systems like AlphaFold, and posits that AI will enable new forms of simulation-based science. Hassabis also delves into the philosophical underpinnings of his work, viewing information as the universe's most fundamental quantity and advocating for developing AGI as a powerful tool before tackling the deeper questions of consciousness.

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

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.

Agentic Engineering & PINNs: AI for Simulation Engineers - James Shaw | Podcast #172

Agentic Engineering & PINNs: AI for Simulation Engineers - James Shaw | Podcast #172

James Shaw, a mechanical engineer and Ansys channel partner, delves into the current and future impact of agentic AI and physics-informed neural networks (PINs) on simulation workflows. He explores how AI is revolutionizing aspects from tech support and model setup to the solver itself, particularly in CFD. The discussion also covers the implications for the engineering job market, the 'senior-junior inversion crisis', and the continued irreplaceability of skilled engineers due to the inherent physicality of the world, emphasizing the need for robust, trustworthy data to train AI.

Physics Gets a Vote: Nominal Cofounders on Hardware Development in an AI World

Physics Gets a Vote: Nominal Cofounders on Hardware Development in an AI World

Nominal's co-founders discuss the new age of reindustrialization and the critical need for a modern data infrastructure in hardware engineering. They explain how their platform acts as a 'GitHub for hardware data,' providing a system of record for testing that bridges the gap between simulation and reality, and serves as the essential verification layer for the future of 'Physical AI'.