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I consider the fact that these systems appear to create a very complex human-like internal model to be one of the, quite suddenly, most pressing philosophical p
by retrac 4y ago
I consider the fact that these systems appear to create a very complex human-like internal model to be one of the, quite suddenly, most pressing philosophical problems of our time. If we had introspection into ML models, would they be sensible, like how humans think and model in the abstract? Is there a "carry the one" weight somewhere, that's linked to numbers that triggers when GPT is given a pattern that invokes that subnetwork, it adds almost like humans do with pen and paper? Or is it entirely different?
I'm not sure we can say whether it "understands" until some questions like that have a start of an answer. Perhaps it's possible to model and predict something, even abstractly reason, without understanding that can be related in a way a human would comprehend. That would be unsettling in its own way.
- famouswaffles 4y agoFor me, if the output can consistently demonstrate understanding then it understands. The reason LLMs are able to be plugged into everything under the sun is that general intelligence and understanding. It's not a parlor trick. At this point you can say, it's only mimicking understanding but that's just a circular argument. If mimicry understanding is such an important distinction over true understanding then it should be obvious. I should be able to test for it. If you can't test for it then it's just an arbitrary distinction you think is important but paradoxically isn't affecting the output at all. Not saying LLMs understand exactly like humans. Maybe they do. Maybe not. But they understand.