Robotics startup Covariant's founders and some employees were hired by Amazon
Amazon has entered into a significant agreement with AI robotics company Covariant, licensing their robotic foundation models and acquiring key talent to enhance its warehouse automation capabilities and advance the state of AI-powered robotics.
Amazon's interest in driving innovation in supply chain, logistics, and warehouse automation is widely known. Recently, Amazon announced a new commercial agreement with Covariant, a leading Bay Area-based AI robotics company working on developing foundation models for robotics, inspired by the foundation model approach to language modeling.
Amazon will receive a non-exclusive license to Covariant's robotic foundation model as part of the agreement. Moreover, the startup's co-founders Pieter Abbeel, Peter Chen, and Rocky Duan, along with a team of research scientists and engineers, will join Amazon's Fulfillment Technologies & Robotics Team to support the integration of Covariant's technology into Amazon's operations. Covariant will continue serving its customers and develop its technology under the leadership of Ted Stinson and Tianhao Zhang. Stinson, previously Covariant's COO, has been named the company's new CEO.
For Amazon, the agreement with Covariant is part of a wider effort to expand its AI and robotics team in the Bay Area. With it, the company plans to build on its already extensive experience building useful robotics systems that streamline its employees' workflows, enabling them to serve customers better. Amazon expects that integrating Covariant's technology will unlock new methods to generalize how Amazon's robotic systems learn, which will uncover opportunities to ensure safety and efficiency in its operations.
Ellie Ramirez-Camara is the News Editor at Data Phoenix, where she writes the daily AI newsdesk — covering model releases, research, funding rounds, and policy across the AI and machine-learning industry. She tracks announcements from labs and startups alike and distills them into clear, source-linked reporting for practitioners.
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