Chiang makes some insightful points, e.g. about what we mean by magic. Then I come to > [LLMs] can get better at reproducing patterns found online, but they don’t become capable of actual reasoning; it seems that the problem is fundamental to their architecture. and wonder how an intelligent person can still think this, can be so absolute about it. What is "actual" reasoning here? If an AI proves a theorem is it only…
But I don't believe that. That a machine that can produce convincing human-language chains of thought says nothing about its "intelligence". Back when basic RNNs/LSTMs were at the forefront of ML research, no one had any delusions about this fact. And just because you can train a token prediction model on all of human knowledge (which the internet is not) doesn't mean the model understands anything.
It's surprising to me that the people most knowledgeable about the models often appear to be the biggest believers - perhaps they're self-interestedly pumping a valuation or are simply obsessed with the idea of building something straight from the science fiction stories they grew up with.
In the end though, the burden of proof is on the believers, not the deniers.