> The architecture might just be wrong for AGI. LeCun’s been saying this for years: LLMs trained on text prediction are fundamentally limited. They’re mimicking human output without human experience. Yes, and most with a background in linguistics or computer science have been saying the same since the inception of their disciplines. Grammars are sets of rules on symbols and any form of encoding is very restrictive. W…
Why would language restrict LLMs? "Language" is an input/output interface. It doesn't define the internals that produce those inputs and outputs. And between those inputs and outputs sits a massive computational process that doesn't operate on symbols or words internally. And, what "clearer milestones" do you want exactly? To me, LLMs crushing NLU and CSR was the milestone. It was the "oh fuck" moment, the clear sign…
Humans create new words and grammatical constructs all the time in the process of building/discovering new things. This is true even in math, where new operators are created to express new operations. Are LLMs even capable of this kind of novelty?
There's also the problem that parts of human experience are inexpressible in language. A very basic example is navigating 3D space. This is not something that had to be explained to you as a baby, your brain just learned how to do it. But this problem goes deeper. For instance, intuition about the motion of objects in space. Even before Newton described gravitation every 3 year old still knew that an object that's dropped would fall to the ground a certain way. Formalizing this basic intuition using language took thousands of years of human development and spurred the creation of calculus. An AI does not have these fundamental intuitions nor any way to obtain them. Its conception of the world is only as good as the models and language (both mathematical and spoken) we have to express it.