4 ms·
The "deep learning is a black box" meme is about 5 years past it's due date. It's not as tight as for convex models but we do understand what's going on inside,
by igorkraw 5y ago
The "deep learning is a black box" meme is about 5 years past it's due date. It's not as tight as for convex models but we do understand what's going on inside, just not perfectly yet.
- habitue 5y agoI think we're talking about different levels of understanding. For things like convex optimization, we have optimality results. For deep learning we have "try to stop training early because it tends to get overfit if you run it too long", "increase the number of parameters in the transformer to magically get uncanny impressions of written text out". These are not the same kind of understanding. If I hand you a 175B parameter language model, are you really contending we know what's going on in there? At a mechanical level, sure, it's tensor products and activation functions, but that's like saying we know how human brains work because the standard model is very predictive.
- igorkraw 5y agoWell, the thing is, we do know how human brains work, just not perfectly. A black box is something you can't look inside and don't understand, which we left behind years ago. We can even interpret parts of it. And if you hand me a 175B parameter language model without skip connections I can tell you exactly what will happen because we understand what role they play and how attention decays rank. Note I'm not saying we perfectly understand everything, or that our understanding is as solid as that involving convex models or linear regression. But "black box" just isn't true anymore and just adding unnecessary mystique. We are somewhere between Newton and the Lord Kelvin and Faraday era of physics, no longer in the ancient alchemist days
- l33t2328 5y agoIs it actually tensor products? I thought it was some multilinear map that factors through the tensor product, but my knowledge is limited.