- They will not work in any environment outside of XLand (unless that environment looks very very similar to XLand).
In particular, I reject the idea that these agents have learned “general strategies for problem solving” or something like that, such that we should expect them to work in other contexts as well, perhaps with a little finetuning. I think they have learned general strategies for solving a specific class of games in XLand.
Strongly agree with this, although with the caveat that it’s deeply impressive progress compared to the state of the art in RL research in 2017, where getting an agent to learn to play ten games with a noticeable decrease in performance during generalization was impressive. This is generalization over a few million related games that share a common specification language, which is a big step up from 10 but still a fair way off infinity (i.e. general problem-solving).
It may well be worth having a think about what AI that’s human level on language understanding, image recognition and some other things, but significantly below human on long-term planning would be capable of, what risks it may present. (Is there any existing writing on this sort of ‘idiot savant AI’, possibly under a different name?)
It seems to be the view of many researchers that long-term planning will likely be the last obstacle to fall, and that view has been borne out by progress on e.g. language understanding in GPT-3. I don’t think this research changes that view much, although I suppose I should update slightly towards long-term planning being easier than I thought.
Strongly agree with this, although with the caveat that it’s deeply impressive progress compared to the state of the art in RL research in 2017, where getting an agent to learn to play ten games with a noticeable decrease in performance during generalization was impressive. This is generalization over a few million related games that share a common specification language, which is a big step up from 10 but still a fair way off infinity (i.e. general problem-solving).
It may well be worth having a think about what AI that’s human level on language understanding, image recognition and some other things, but significantly below human on long-term planning would be capable of, what risks it may present. (Is there any existing writing on this sort of ‘idiot savant AI’, possibly under a different name?)
It seems to be the view of many researchers that long-term planning will likely be the last obstacle to fall, and that view has been borne out by progress on e.g. language understanding in GPT-3. I don’t think this research changes that view much, although I suppose I should update slightly towards long-term planning being easier than I thought.