Building adaptive AI models that can learn and complete tasks in the physical world requires precision but these AI robots could completely change manufacturing and logistics processes. Peter Chen, the co-founder and CEO of Covariant, leads the team that is building robots that will increase manufacturing efficiency, safety, and create warehouses of the future.

Today on No Priors, Peter joins Sarah to talk about how the Covariant team is developing multimodal models that have precise grounding and understanding so they can adapt to solve problems in the physical world. They also discuss how they plan their roadmap at Covariant, what could be next for the company, and what use case will bring us to the Chat-GPT moment for AI robots.

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Show Notes:

(0:00) Peter Chen Background

(0:58) How robotics AI will drive AI forward

(3:00) Moving from research to a commercial company

(5:46) The argument for building incrementally

(8:13) Manufacturing robotics today

(12:21) Put wall use case

(15:45) What’s next for 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

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