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Self-driving cars, arms that can learn ow to pick up objects, machines that can have conversations, etc. I understand how neural nets work. But I really don't know much about how neural nets are combined to form intelligent systems. Is it all rule-based above a few base nets for tasks like e.g. image recognition? Or are there meta-nets that do deep learning on the outputs from base nets?

Things to read/references would be super-helpful!

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Neural networks can be combined together in a variety of ways. One promising direction is Mixture-of-Experts (MoE), where different neural networks learn different parts of the problem space and are combined together.

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