New Paradigms Won't Save You

One popular objection to AI concerns is to declare that LLMs can never be AGI. You need a “new paradigm”. Therefore, AGI is so far in the future that it’s not worth worrying about.A common counterargument is to claim that no, LLMs can become AGI. But even without that counterargument, I think the “therefore” fails on its own terms. The key question is: how much of a new paradigm do we need?The landmark discoveries on the road to modern LLMs are something like:1950s: Neural networks1967: Multi-layer perceptron2010: Modern deep learning2017: Transformer, LLM2022: RLHF, chatbots2024: Chain of thought / test-time computeWe can think of this as an “evolutionary tree”, where a given LLM (let’s say Claude Opus 4.7) shares a recent “common ancestor” with all other chatbots, and only a very distant “common ancestor” with everything else descended from the multi-layer perceptron. If AGI needs a “new paradigm”, what common ancestor can we expect AGI and LLMs to share?AGI will very likely use…