3 ms·
We are. Plateauing doesnt mean you don't book progress. Arguably that is what you would call "plateaud". The argument of plateauing is not that AI is fundament
by ArnoVW 2y ago
We are. Plateauing doesnt mean you don't book progress. Arguably that is what you would call "plateaud".
The argument of plateauing is not that AI is fundamentally impossible. The argument is that just dumping more data and more compute on the problem, using the same approach, has diminishing returns.
It's that statistical inference is not how the human mind works (not exclusively) and thus that we are not guaranteed to be able to replicate all traits of human intelligence by brute forcing.
Of course we can and will still improve the algorithms. But the question remains whether tweaks like these, as cool and useful they may be to solve certain issues, will be enough by themselves.
Since it remains statistical in nature, my position is "no".
- logicchains 2y ago> that we are not guaranteed to be able to replicate all traits of human intelligence by brute forcing. We know from complexity theory that transformers with chain of thought are guaranteed to be able to reproduce a significant fraction of human reasoning, anything in the complexity class PTIME: https://arxiv.org/abs/2310.07923 https://arxiv.org/abs/2310.07923
- fl0id 2y agoI don’t think this paper says what you claim. It says chain of reasoning and its length can improve transformer performance. Not that this represent a significant fraction of human reasoning or that it’s even reasoning
- logicchains 2y agoIt says it can represent all programs in P, i.e. all reasoning that produces an output in no more than polynomial time with respect to the amount of inputs. Most human reasoning is presumably in P, not NP, because we generally don't find ourselves needing to think exponentially long about things.