[rcme]

> No, the number of fingers is absolutely critical, you simply fail to understand what understanding a concept means. ChatGPT is, in this sense (and I know it’s probably a gross simplification, sorry OpenAI), a fancy markov chain. It can sample data that, by sheer correlation in the training data, reflects many features a typical drawing that matches the prompt would have. But it doesn’t understand what a human hand is, it lacks the ability to abstract, so it cannot deduce that there are (almost) always exactly 5 fingers.

Yet it correctly understands that faces typically have two eyes, one mouth, one nose, etc. So clearly this "lack of understanding that hands have five fingers" is unlikely to be inherent to the model.

Let's say I ask you to draw a lady bug. You'll draw a red shell with some black dots haphazardly strewn about. However, the most common lady bug in Europe always has 7 spots. It's unlikely that your drawing will reflect that. Why? Because you lack understanding of Coccinella septempunctata. But does that you mean you lack understanding in general? Of course not. Lady bugs simply aren't important to you.

So again, why are we elevating hands to be the litmus test of understanding? Yes, hands are important to humans. But this algorithm is not a human, so hands are no more important to it than anything else it can do. Like let's say if could draw perfect hands 100% of the time. Does that mean you would concede that it has understanding? I doubt it. You'd pick some other thing it didn't do well and say "See, it can't accurately draw eggs stacked in a pyramid, therefore it lacks understanding." The issue with your argument is that is a slippery slope without a specific reason why the correct rendering of hands is important.

And I'm not arguing that GPT-3 or Stable Diffusion are omnipotent. Clearly they're not. But that doesn't mean that can't understand things in their domain. As others have mentioned in adjacent comments, the only test we have for understanding, in humans or ML models, is measuring the correctness of an output for a given input. Essentially, your argument is that "It's an algorithm, it can't understand like a human," which is begging the question.

I'm not claiming that ChatGPT or any other ML algorithm is "generally intelligent." Just that it has an understanding of certain concepts.

[Noneofya]

>Yet it correctly understands that faces typically have two eyes, one mouth, one nose, etc. So clearly this "lack of understanding that hands have five fingers" is unlikely to be inherent to the model.

It is, we just don’t know it’s exact features. It might very well be optimized for recognizing faces (and therefore to identify the features that make up a face). A general AI doesn’t have to be retrained on specifics. Sure, you „can“ (in a very generous hypothetical sense of the word) train a model like this on all pictures and movies in existence and then some, so that it has seen everything and never fails to give the wrong answer for any prompt that only involves things that were depicted at some point in time. You don’t have to show a child all hands on the planet for it to recognize hands have 5 fingers. You don’t even have to show children pictures of every body part once for every skin color. They only need to see 1-2 different skin colors once to make the deduction that every body part can come in different skin colors. That‘s understanding, a general intelligence. Try this with a model like ChatGPT and you get a racist model.

>And I'm not arguing that GPT-3 or Stable Diffusion are omnipotent. Clearly they're not. But that doesn't mean that can't understand things in their domain. As others have mentioned in adjacent comments, the only test we have for understanding, in humans or ML models, is measuring the correctness of an output for a given input. Essentially, your argument is that "It's an algorithm, it can't understand like a human," which is begging the question. I'm not claiming that ChatGPT or any other ML algorithm is "generally intelligent." Just that it has an understanding of certain concepts.

We can also inspect the model. And even the ouputs are obviously different from what a human would be able to output, so it fails even that test.

If you argue that’s still intelligence, just on a lower level, you can absolutely do that. But at that point you’re basically saying everything is intelligent/conscious just on varying levels. In the sense that consciousness is what consciousness does. Which is a stance I generally agree with, but it’s also unfalsifiable and therefore meaningless in a scientific discussion.