The thing with recursive self-improvement in AI, is that if it were going to happen, it would already be happening
Much like AutoML is the first thing ML people start working on after reaching proficiency, I assume the answer is yes
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AutoML not meant to recursively self improve I thought. How about learning to learn by gradient by gradient descent? https://arxiv.org/abs/1606.04474
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It's a pretty good case study on why exponential self-improvement isn't a thing -- self-improvement, when it occurs, is typically sigmoidal
End of conversation
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