causal claim
Karpathy argues that agents trained by unguided keyboard and mouse interaction receive rewards too sparsely to learn effectively, potentially wasting vast computing resources without yielding a functional system.
Andrej Karpathy · Andrej Karpathy — AGI is still a decade away · 17 Oct 2025
In their words
The transcript segments this claim was taken from
“tracked with you know the actual digital world that can do knowledge work and it just so turns out that this was extremely early way too early so early that we shouldn't have been working on that you know because if you're just stumbling your way around and keyboard mashing and mouse clicking and trying to get rewards in these environments your reward is too sparse and you just won't learn and you're going to burn a forest computing and you're never actually going to get something off the ground and so what you're missing is this power of”Play from 5:42Report a misattribution
90%how strongly it was put, not whether it is true
90%importance to the conversation
96%confidence the claim was read correctly