If every problem is bounded by a bunch of data points on a multi-dimensional plane, and some sort of clustering is done on them that reflects the problem domain, then isn't running through the samples during training equivalent to memorizing them and associating them and allowing for a small margin of error making it look like the model is able to generalize.
In short, doesn't that just boil down to how good we made our samples and setting the whole process in a way to memorize those samples ?
I wonder what motivates people to add links to HN ? I have added many of my blogs in the hope that people will read / discuss about it.
But for those who add links to HN is it the discussion from the community the only thing?
And most times the comments are very interesting to read, but beyond that does it really translate into commerce and connections for people ?
