> AFAIK this is a fundamental principle of ML that has been proven mathematically and which is inescapable. Well, the human brain manages to master several com

> AFAIK this is a fundamental principle of ML that has been proven mathematically and which is inescapable. Well, the human brain manages to master several complex tasks using much smaller data sets than current machine learning algorithms. Natural language acquisition, for example, seems to require fewer than 10 million spoken words per year, and even academically successful 12-year-olds might be reading 1 to 4 million words per year. These are not exactly tiny data sets, but they don't require Google's scale to recreate, either. Sure, the human genome probably "knows" what set of models to try when building the brain, which gives it an advantage. But I can't think of any reason why machine learning couldn't ultimately try similar techniques with similarly-sized data sets, and get competitive results.