Scott Alexander at Astral Codex Ten:
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 networks
1967: Multi-layer perceptron
2010: Modern deep learning
2017: Transformer, LLM
2022: RLHF, chatbots
2024: Chain of thought / test-time compute
We 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?
More here.
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