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ilovekungfuu t1_jbi2xao wrote

Thank you very much u/hcarlens !
This distills so much of information .

Do you think that we might be at a plateau in terms of new methods being tried out (say, since last 24 months) ?

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hcarlens OP t1_jbnreef wrote

Hi! I'm not sure I fully understand your question, but if you're asking whether the rate of progress in competitive ML is slowing down, I think probably not. A lot of the key areas of debate (gbdt vs nn in tabular data, cnn vs transformers in vision) are seeing a lot of research still and I expect the competitive ML community to adopt new advances when they happen. Also in NLP there's a move towards more efficient models, which would also be very useful.

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