Comment by tsukikage
17 hours ago
Your “and then” is doing a lot of work there. The steps between may or may not include some form of “learn to understand humans”, but you can’t just hide them behind “and then” if what we are doing is claiming some particular thing is not in the list.
Through training on human text, we are building implicitly in the weights a statistical model of what humans might write in response when presented with arbitrary pieces of text. It turns out that we can make these incredibly accurate.
If building an accurate internal model of something then using it to predict that thing’s behaviour is different to gaining understanding of that thing, we will need to pin down exactly what “understanding” means, or we are forever doomed to talk at cross purposes.
My "and then" simply implies order of operations. When it's fully "trained" then (and only then) can it generate text.
And I will reassert that even if it "understands" the text it was trained on, that is not the same as understanding humans. I mean really, we ARE humans and we barely understand humans.
The thing LLMs model and "predict" is simply, what words in what order are statistically common given these input words in this order.
You can write (non-ai) software to model and predict things using the laws of physics. I'd wager it would do a better job than any LLM at predicting where a rocket will go through space. Does that mean the program is conscious and "understands" physics? No