Recursive Meta Learning
The discussion delves into the evolution of meta learning, emphasizing the need for recursive learning processes. Insights reveal that while traditional meta learning focuses on one-time adaptations, there's potential for more complex, multi-level learning strategies. Notably, the concept of learning optimizers that can optimize themselves sparks intrigue, alongside the idea of learning at different timescales to better understand the world.In this clip
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The Robot Brains Podcast
S3 E2 Stanford Prof Chelsea Finn: How to build AI that can keep up with an always changing world
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