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It's a long list, since it's akin to describing the frontier of research. A few: 1) meta-learning requires too many tasks (and where do they come from?) 2) fine-tuning for transfer learning has no guarantees 3) RL requires a reward function, which is unrealistic for many tasks
yes, indeed, making such a list does indeed define the frontier of research, which was precisely the point of http://Rebooting.AI . Since our list doesn't overlap with yours, I will be curious to see which of those on our list you do and do not agree with. [+1 to yours.]
I’ll have to look at your book I suppose to answer that. Is it on arXiv? ;)
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