> And it must do this based entirely on context and how likely one is to appear in the same place as another. That takes a massive amount of data in practice an

> And it must do this based entirely on context and how likely one is to appear in the same place as another. That takes a massive amount of data in practice and could be one reason why humans appear to learn from much sparser data and faster. That, and another thing: A LLM fundamentally boils down to a statistical repetition engine. That means, if it has never seen the input - say, some random large numbers -, it will hallucinate garbage if you ask it a question ("multiply 245358943543548 by 438574589675486789654"), whereas a human would recognize where the boundaries of the numbers are and plug it into a calculator (or, some particularly big brained people would actually do it in their mind) to figure out the result. Some AI or pseudo-AI (dunno what Wolfram Alpha uses under the hood) has to have a "front" AI to recognize such questions and redirect them to a calculator, but in my eyes that's just cheating for a very specific case and not enabling general intelligence.