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Ken Goldberg is a professor of engineering at UC Berkeley and the co-founder of Ambi Robotics, a company applying AI-enabled robotics to the logistics industry. Ken has spent over four decades working on one of the hardest problems in robotics: how machines perceive and manipulate the physical world. We spoke about why tasks that seem effortless to humans - like picking up a glass or folding laundry - are still incredibly difficult for robots.
Our conversation also covers:
What it would take to reach a “ChatGPT moment” in robotics
Why simulation data isn't enough without real-world grounding
And why the next decade of robotics depends on combining cutting-edge models with good old-fashioned engineering
Chapters:
00:00 Cold open: Why robotics still needs good old-fashioned engineering
03:46 Hype cycles and winters in robotics
05:08 Why folding laundry is still hard for robots
10:38 What robots are good at today
15:00 Automation and the rise of warehouse robotics
19:39 Can LLMs and generative AI work for robotics?
26:52 The limits of simulation data and the sim-to-real gap
29:44 Why humanoids are still far from practical
36:34 What founders need to know about robotics timelines
37:08 Why robots need grounding and exploration
39:00 Combining the power of LLMs with traditional engineering
40:42 Why Ken is optimistic about the future of robotics