The best first step towards building a complex end-to-end system is to build a basic end-to-end system -- not to build a submodule of what you think the complex system should look like
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I wonder if this is because you can only get gradient with an end-to-end system - it’s hard to learn more complex behavior if you only have a submodule that doesn’t do the final task, and thus can’t get feedback on performance.
Gradient is not a good metaphor because we're not talking about continuous optimization at all. But it is indeed about information discovery and grounding the meaning of the task
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Isn’t the evolution of a system (towards greater complexity) due to a process of continuous optimization? It’s true, though, that gradient isn’t a perfect analogy.
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Incremental change != Continuous optimizationhttps://en.m.wikipedia.org/wiki/Continuous_optimization …
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The simple system is an information-collection device about the end-to-end problem (which is critical for success), and because it is useful & meaningful on its own you'll be motivated to work on it and iterate.
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I wonder how to describe this mechanism more formally - i.e. the process by which information is used to iterate on the system.
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