Physical 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'.

The most successful AI company you’ve never heard of | Qasar Younis

The most successful AI company you’ve never heard of | Qasar Younis

Qasar Younis, CEO of Applied Intuition, discusses the future of AI, arguing its most significant near-term impact will be in physical industries like farming, mining, and construction. He shares his philosophy on building a company quietly, the importance of early traction, and the core values that drive Applied Intuition, while also offering a nuanced perspective on China's AI capabilities and how to develop leadership taste.

Why Physical AI Needs a new Data Set | Rerun CEO

Why Physical AI Needs a new Data Set | Rerun CEO

Nikolaus West, CEO of Rerun, explains how their data logging and visualization platform, built on an Entity Component System (ECS) inspired by gaming, is unlocking new capabilities in physical AI. He discusses the rapid progress in robot manipulation through imitation learning, the gap between impressive demos and real-world products, and the critical need for better data tooling to handle complex, multi-rate sensor data in robotics and AR/VR.

Building the "App Store" for Robots: Hugging Face's Thomas Wolf on Physical AI

Building the "App Store" for Robots: Hugging Face's Thomas Wolf on Physical AI

Thomas Wolf, co-founder of Hugging Face, details the LeRobot project, aiming to replicate the success of Transformers in the robotics domain. He discusses the vision of creating a massive open-source community, tackling data scarcity, and the future of physical AI hardware, arguing that we are at a key inflection point for robotics similar to where LLMs were years ago.