
What's Your Problem?
Using AI to Build Better Robots
Feb 1, 2024
Peter Chen, Co-founder and CEO of Covariant, discusses the integration of AI in robotics and the challenges it faces. They explore the limitations of traditional robots and the role of AI in solving complex problems. The podcast also touches on building robot arms for business, the significance of ImageNet, robots in warehouse operations, AI models for robot arms, optimizing kitchens, GPT's impact, and transitioning from academia to industry.
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Quick takeaways
- Covariant aims to make AI breakthroughs work in robots by building a foundation model for robotics, similar to how GPT is a foundation model for language.
- Covariant's model uses multiple cameras and an understanding of physics to enable robots to interact with heterogeneous objects in a warehouse, making it adaptable and reliable for industrial use.
Deep dives
Building AI Breakthroughs in Robotics
Covariant, a robotics company, aims to make AI breakthroughs work in robots. The co-founder and CEO, Peter Chin, explains that traditional robotics focuses on hardware and control algorithms. However, AI is needed to solve complex tasks that cannot be reduced to repeated motion, such as folding towels. Covariant's approach involves building a foundation model for robotics, similar to how GPT is a foundation model for language. By training the model on large robotics datasets, Covariant aims to create smarter and more capable robots for various industries.
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