SPEAKER_00 argues that reinforcement learning without constraints or prior information must relearn everything from scratch.

“which is very applied. Uh so I actually did some project which are actually applied reinforcement learning. And this is a big problem in reality that effectively information can be very expensive. And in fact I would say most information is very very expensive. And reinforcement, if you completely say well constraints don't matter, uh I I don't need any prior information, I don't want to encode anything in the”

“thing in there. Uh assuming this even possible uh that co could being completely like unconstr uh unconstr etcetera and completely like without prior knowledge, I assume all of this the case, we”

“We still have the problem of now needing to actually relearn everything from scratch, and the reality is that we want to be gathering as much information that we already have paid for and gathered with our blood, sweat and tears, we want to put all of that in the model first,”