Without discussion of grammars, I think you're lost in the sauce on this. > You need a system that has knowledge and a world model and common-sense reasoning,

Without discussion of grammars, I think you're lost in the sauce on this. > You need a system that has knowledge and a world model and common-sense reasoning, etc. When you're doing nothing but "predict the next token based on statistical patterns" then yeah, you're going to get hallucinations. Arguably, LLMs already have this. They can do impressive reasoning already. The problem may be that the way they encode all that is untenable. Imagine trying to describe a car in terms of its individual pieces (tires, suspension, engine). Then imagine trying to do that in terms of its molecules. Uh oh. Then its atoms. Even worse. > How much will it cost? To describe a car in terms of atoms? Infinite cost. We can barely even get a baby fruit fly's connectome (total brain schematic) read and stored somewhere. A car is much bigger. It may be that LLMs are structured such that they're trying to encode all that common sense reasoning in terms of atoms, and a fundamentally different grammar is necessary to go up to parts. Whether this is the case is still being debated. If it is the case, you'll see LLMs near a ceiling of diminishing returns. > How much will it cost? To figure out how to do LLMs with more expressive grammars? Unknown. I think that'd take a qualitative breakthrough in AI, and I think LLMs are just the result of a quantitative breakthrough (we're still doing the old, non-clever stuff; we're just doing it faster than ever before thanks to continued growth in GPU compute power; more monkeys on typewriters than ever before!). I don't think we've had much in the way of qualitative breakthroughs since the AI winter.