AI in the Real World with Foundation Capital

What robots can (& can't) do in 2025: Ken Goldberg, UC Berkeley & Ambi Robotics

Episode Notes

Welcome to AI in the Real World! In this episode, Foundation Capital Partner Joanne Chen sits down with Ken Goldberg, professor of engineering at UC Berkeley and co-founder of Ambi Robotics, a company applying AI-enabled robotics to transform the logistics industry.

Ken has spent more than four decades working at the intersection of robotics and AI, focusing on one of the most persistent challenges in the field: how machines perceive and manipulate the physical world.

Ken shares why tasks that seem trivial to humans, like picking up a glass or folding laundry, remain profoundly difficult for robots, and why the physical world introduces a level of uncertainty that can't be fully simulated.

Our conversation also covers:

• What it would take to reach a ChatGPT moment in robotics
• Why simulation data is not 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