If the bitter lesson were true we'd be getting sota results out of two layer neural networks using tanh as activation functions.
It's a lazy blog post that should be thrown out after a minute of thought by anyone in the field.
It's a lazy blog post that should be thrown out after a minute of thought by anyone in the field.
You need a ton of specialized knowledge to use compute effectively.
If we had infinite memory and infinite compute we'd just throw every problem of length n to a tensor of size R^(n^n).
The issue is that we don't have enough memory in the world to store that tensor for something as trivial as mnist (and won't until the 2100s). And as you can imagine the exponentiated exponential grows a bit faster than the exponential so we never will.