Ken Goldberg is a professor at UC Berkeley in the Industrial Engineering & Operations Research department.
How media typically covers Ken Goldberg
Directly quoted in these articles
UC Berkeley roboticist Ken Goldberg argues that a "100,000-year data gap" will prevent humanoid robots from gaining real-world skills like those claimed by tech leaders, debunking near-term timelines for surgical robots or in-home butlers.
“UC Berkeley roboticist who published two papers in Science Robotics explaining why robots are not gaining real-world skills as quickly as AI chatbots.”
Referenced in coverage
“Co-authored the ASPIRE paper on robot learning framework.”
Training a robot foundation model equivalent to language model scale (2 trillion tokens) requires 70,000+ robot-years of data, but scaling fleets, simulation, and human video data combined could make this feasible with substantial investment.
“Gave a talk about the huge question of the 'robot data gap' in training robot foundation models.”