> many tasks considered "intellectual" can be done by systems that internally are simple, but very large There's plenty examples of such tasks even if we look

> many tasks considered "intellectual" can be done by systems that internally are simple, but very large There's plenty examples of such tasks even if we look back before the current proliferation of large language models. Translation used to be considered such a complex intellectual task, and had decades of research into more and more complicated systems to address various nuances and specific cases (e.g. transliteration of people's names, conversion of measurements) but in the end it turned out that this set of tasks is best solved by internally simple systems scaled up. Chess (and more recently, Go) is a historical example of what used to be considered an intellectually challenging task, but succumbs to simple-but-large solutions. Sure, GPT-4 can't do a lot of things well and a can't do a lot of things at all - however, it can do a bunch of tasks which we couldn't do before despite trying a lot with quite complicated, intelligent means, and it manages to beat that with a glorified autocomplete. Time and time again we want to consider some task as requiring "true intelligence" and then it eventually falls to brute force, reiterating Sutton's Bitter Lesson (http://incompleteideas.net/IncIdeas/BitterLesson.html http://incompleteideas.net/IncIdeas/BitterLesson.html) despite what most of us naturally would prefer to be true. Also, we do have some theoretical basis for equivalence of intellectual activity and "autocomplete", such as Hutter's proof that finding the optimal behavior of a rational agent is equivalent to compressing its observations.