Teaching robots like humans: 1000 tasks in 24 hours

Teaching robots like humans: 1000 tasks in 24 hours

From TechFirst with John Koetsier by John Koetsier

March 10, 2026 · 24 min

About this episode

In this episode, John Koetsier interviews Edward Johns about a breakthrough in robot learning that enables robots to learn 1,000 tasks in 24 hours through efficient imitation learning.

Imagine teaching a robot 1000 tasks in just 24 hours. Imagine teaching robots just like you teach humans. In fact, what if teaching a robot were as easy as showing it once? Humans can learn new skills almost instantly by watching, trying, or receiving a quick explanation. Robots, historically, haven’t been so lucky. Training them often requires huge datasets with real or virtual data, massive engineering effort, and weeks or months of experimentation. But that may be changing. In this episode of TechFirst, host John Koetsier talks with Edward Johns, Director of the Robot Learning Lab at Imperial College London, about a breakthrough in efficient imitation learning that allowed a robot to learn 1,000 different tasks in just 24 hours. Instead of collecting huge datasets, Johns’ team combines simulation training, clever algorithm design, and single demonstrations to dramatically speed up how robots learn. We discuss: • How robots can learn from just one demonstration • Why breaking tasks into “reach” and “interact” phases makes learning faster • The role of simulation data in robotics AI • Why robotics doesn’t have the same data advantage as large language models • The future of…

People in this episode

Host: John Koetsier

Guest: Edward Johns

Topics covered

  • robot learning
  • imitation learning
  • artificial intelligence
  • robotics

Keywords

  • efficient learning
  • simulation training
  • algorithm design
  • humanoid robots

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