In my view this is one of the most serious misconceptions about the entire field of machine learning. Sure, if you zoom out far enough, everything is a number or vector or matrix, but it’s rare that such a representation is the most convenient or precise one for formulating the learning problem.
In my view this is one of the most serious misconceptions about the entire field of machine learning. Sure, if you zoom out far enough, everything is a number or vector or matrix, but it’s rare that such a representation is the most convenient or precise one for formulating the learning problem.
Yeah, it shows how a reductionist viewpoint tends to dead end. But so hard to represent stuff in analog...