And yet It Understands
This article lines up well with my feelings on the matter. In general, people seem to understate the emergent behaviours of ML models, while overstating the uniqueness of human intelligence. I think a lot of this is down to the fact that although both systems exhibit a form of intelligence, they’re very different. LLMs deliver mastery of natural language that would normally be a signal for a highly intelligent human. While in other ways they’re less intelligent than a cat.<p>So it’s not ‘human like intelligence’ but it is a form of intelligence and the reality is no one would have predicted the behaviours we are seeing. So it seems silly to pretend we can know for certain how it achieves its results.<p>For human intelligence, do we assume cave men had theory of mind at the level of modern day humans? Or did language have to develop first? Our intelligence is built on previous generations, and most of us just ‘interpolate’ within that to a large extent. We behave on occasion like ‘stochastic parrots’ too, mindlessly repeating some new term or phrase we’ve started hearing on Hacker News (why? It just felt like the ‘right thing’ to say).<p>Human intelligence is the working example that combinations of atoms built into large networks have emergent properties. I’m sure our artificial networks won’t behave qualitatively like the human one as they continue to develop, but I think the burden of proof is on those that suggest we can know what ultimately is and isn’t possible.