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Today we’re joined by return guest Ken Goldberg, a professor at UC Berkeley and the chief scientist at Ambi Robotics. It’s been a few years since our initial conversation with Ken, so we spent a bit of time talking through the progress that has been made in robotics in the time that has passed. We discuss Ken’s recent work, including the paper Autonomously Untangling Long Cables, which won Best Systems Paper at the RSS conference earlier this year, including the complexity of the problem and why it is classified as a systems challenge, as well as the advancements in hardware that made solving this problem possible. We also explore Ken’s thoughts on the push towards simulation by research entities and large tech companies, and the potential for causal modeling to find its way into robotics. Finally, we discuss the recent showcase of Optimus, Tesla, and Elon Musk’s “humanoid” robot and how far we are from it being a viable piece of technology.
The complete show notes for this episode can be found at twimlai.com/go/599.
By Sam Charrington4.7
419419 ratings
Today we’re joined by return guest Ken Goldberg, a professor at UC Berkeley and the chief scientist at Ambi Robotics. It’s been a few years since our initial conversation with Ken, so we spent a bit of time talking through the progress that has been made in robotics in the time that has passed. We discuss Ken’s recent work, including the paper Autonomously Untangling Long Cables, which won Best Systems Paper at the RSS conference earlier this year, including the complexity of the problem and why it is classified as a systems challenge, as well as the advancements in hardware that made solving this problem possible. We also explore Ken’s thoughts on the push towards simulation by research entities and large tech companies, and the potential for causal modeling to find its way into robotics. Finally, we discuss the recent showcase of Optimus, Tesla, and Elon Musk’s “humanoid” robot and how far we are from it being a viable piece of technology.
The complete show notes for this episode can be found at twimlai.com/go/599.

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