Teachability Revolution
Nathan discusses a project emphasizing teachability, enabling robots to learn from human feedback and adjust their actions accordingly. The iterative process of training on different styles of reasoning and simulating multiple paths leads to performance improvement in decision-making.In this clip
From this podcast
The Cognitive Revolution: How AI Changes Everything
Robotics Research Update, with Keerthana Gopalakrishnan and Ted Xiao of Google DeepMind
Related Questions
Is the basic pattern of learning in the episode Robotics Research Update, with Keerthana Gopalakrishnan and Ted Xiao of Google DeepMind and the clip Teachability Revolution - fast repetitions, slow down for refinement, and then possibly speed up again for repetition including refinement?
Can AI learn from feedback like humans in the episode Robotics Research Update, with Keerthana Gopalakrishnan and Ted Xiao of Google DeepMind, and the clip Rapid Learning Feedback Loop? How does this relate to the concepts discussed in the episode 2024 in AI, with Nathan Benaich and the clip Open-Ended Systems?
Can AI learn from feedback like humans in the episode "Robotics Research Update" with Keerthana Gopalakrishnan and Ted Xiao of Google DeepMind and the clip "Rapid Learning Feedback Loop"?