> I don't see "Automatic design of novel algorithms" in this list. Can AutoML produce something as novel as a GAN, CapsNet, WaveNet, Transformer, Neural ODE, etc? Is that even considered to be one of its goals. In my opinion, there's a clear separation between a group of people trying to improve AutoML so that it's more useful in doing all those tasks on the list, and a group of people trying to invent next gen ML algorithms or DL architectures.

I agree with you from the view of the current state of the art methods and the current state of the AutoML / fundamental ML research communities. Current methods are very limited, but I can not think of a reason why a sufficiently general searchspace of architectures/pipelines could not produce something like a GAN or a WaveNet.

I do not think that designing algorithms as novel as the ones you listed is currently a goal of AutoML, as that is not something we have an attack for. However, I do think that with increasing capabilities, the field of AutoML will seek to automate every step of the machine learning pipeline - including the design of algorithms. E.g., once/if there are attacks to apply NAS for yielding truly novel architectures, I think NAS researchers will be happy to do just that -- wouldn't you call that AutoML then?