Back in 2017, when we founded Covariant, our key insight was that the future of AI and robotics lies in foundation models — versatile models that learn from vast datasets, enabling them to be highly adaptable.

To build these foundation models in the physical world, we needed data, so we embarked on a journey to create fleets of robots that provide value to customers and also generate the necessary dataset for advancing AI in the real world.

Peter Chen joined Sarah Guo on the No Priors podcast to discuss Covariant's pioneering role in building advanced AI that powers useful, commercial robotic applications.

Get the full scoop:

  • 00:00 Peter's background
  • 00:58 How robotics AI will drive AI forward
  • 03:00 Moving from research to a commercial company
  • 05:46 The argument for building incrementally
  • 08:13 Manufacturing robotics today
  • 12:21 AI-powered Robotic Putwall
  • 15:45 What’s next for the Covariant Brain
  • 18:42 Covariant’s customers
  • 19:50 Grounding concepts in AI
  • 25:47 How scaling laws apply to Covariant
  • 29:21 Covariant’s driving thesis
  • 32:54 The Chat-GPT moment for robotics
  • 35:12 Manufacturing center of the future
  • 37:02 Safety in AI Robotics
Related What’s Your Problem Podcast: Using AI to build better robots