The author searches for a midpoint between "AIs are useless and do not actually think" and "AIs think like humans," but to me it seems almost trivially true that both are possible.
What I mean by that is that I think there is a good chance that LLMs are similar to a subsystem of human thinking. They are great at pattern recognition and prediction, which is a huge part of cognition. What they are not is conscious, or possessed of subjective experience in any measurable way.
LLMs are like the part of your brain that sees something and maps it into a concept for you. I recently watched a video on the creation of AlexNet [0], one of the first wildly successful image-processing models. One of the impressive things about it is how it moves up the hierarchy from very basic patterns in images to more abstract ones (e. g. these two images' pixels might not be at all the same, but they both eventually map to a pattern for 'elephant').
It's perfectly reasonable to imagine that our brains do something similar. You see a cat, in some context, and your brain maps it to the concept of 'cat', so you know, 'that's a cat'. What's missing is a) self-motivated, goal-directed action based on that knowledge, and b) a broader context for the world where these concepts not only map to each other, but feed into a sense of self and world and its distinctions whereby one can say: "I am here, and looking at a cat."
It's possible those latter two parts can be solved, or approximated, by an LLM, but I am skeptical. I think LLMs represent a huge leap in technology which is simultaneously cooler than anyone would have imagined a decade ago, and less impressive than pretty much everyone wants you to believe when it comes to how much money we should pour into the companies that make them.
What I mean by that is that I think there is a good chance that LLMs are similar to a subsystem of human thinking. They are great at pattern recognition and prediction, which is a huge part of cognition. What they are not is conscious, or possessed of subjective experience in any measurable way.
LLMs are like the part of your brain that sees something and maps it into a concept for you. I recently watched a video on the creation of AlexNet [0], one of the first wildly successful image-processing models. One of the impressive things about it is how it moves up the hierarchy from very basic patterns in images to more abstract ones (e. g. these two images' pixels might not be at all the same, but they both eventually map to a pattern for 'elephant').
It's perfectly reasonable to imagine that our brains do something similar. You see a cat, in some context, and your brain maps it to the concept of 'cat', so you know, 'that's a cat'. What's missing is a) self-motivated, goal-directed action based on that knowledge, and b) a broader context for the world where these concepts not only map to each other, but feed into a sense of self and world and its distinctions whereby one can say: "I am here, and looking at a cat."
It's possible those latter two parts can be solved, or approximated, by an LLM, but I am skeptical. I think LLMs represent a huge leap in technology which is simultaneously cooler than anyone would have imagined a decade ago, and less impressive than pretty much everyone wants you to believe when it comes to how much money we should pour into the companies that make them.
[0] https://www.youtube.com/watch?v=UZDiGooFs54