A simple path forward, is to go from classifying single elements of training data, to classifying multiple elements and their relationship in the training data.
Training data already has multiple labels.
Slightly less simple, is to gather orders of magnitude more data, by just hooking the input to an IRL robot.
An entire point of the paper and video is that massive increases in training set size are showing diminishing returns.
Another step, is for the NN to control the robot and decide which parts of the data require refinement, and focus on that.
🤡
vrighter@discuss.tchncs.de 6 months ago
this has “draw the rest of the fucking owl” to it. especially step 3
jarfil@beehaw.org 6 months ago
It’s a “push as much data as a baby gets to train its NN” step, which is several orders of magnitude more, and more focused, than any training dataset in existence right now.
Even with diminishing returns, it’s bound to get better results.
vrighter@discuss.tchncs.de 6 months ago
that’s not how asymptotes work.
jarfil@beehaw.org 6 months ago
That’s not how watching the video or reading the paper works either.
Whatever.