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You'd be surprised how many people are on the "nothing to see here" bandwagon despite how obviously false that is. It feels so ridiculous when someone says GPT

You'd be surprised how many people are on the "nothing to see here" bandwagon despite how obviously false that is. It feels so ridiculous when someone says GPT doesn't reason or understand because I and many others can clearly show output demonstrating this. When presented with this, the next thing is to double down. "Oh forget what you're seeing, it's not "true understanding" TM". This just makes the conversation even more bizzare. Either your dog fetches what you throw at it or it doesn't. The idea of "pretend fetching" is so obviously silly and it's exactly what these people argue. I'm supposed to believe in this mysterious special distinction that nobody can apparently properly define nevermind test for. General understanding isn't binary. You can understand some things and not understand other things. And it's not like everything encoded in language is encoded at the same level. GPT-4's spatial understanding is much better but that doesn't mean GPT-3 didn't understand anything at all. It just means it didn't understand space.

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 ago
  For 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.

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 ago
For 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.