Generate Keras models from a description.https://twitter.com/mattshumer_/status/1287125015528341506 …
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Why go through another layer of structured representation?
Because you want to achieve generalization via interpolation, and forcing the interpolative model to deal with a huge layer of discrete complexity (code syntax) is a big hurdle for that. The simpler the structure of your target space the better. It's curve fitting after all
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It seems GPT copes just fine :) Adding layers of transformers seems like the right direction to me. Adding layers of complexity is not.
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It's actually about simplifying the problem -- it's literally feature engineering. But you're right that as long as you have infinite training data and infinite compute resources, it's less work not to do any feature engineering at all
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