What exactly are you trying to argue? Yes, I wasn't incredibly precise, a book isn't literal knowledge, but I didn't think that somebody would nitpick this hard. Do you really think this is in any way a productive line of argumentation?

Knowledge is something possessed by an actor capable to employ it.

Technically this is not correct, as e.g. a fully paralyzed and mute person can't employ their knowledge, yet they still possess it.

™One way I can employ a textbook about Quantum Mechanics is by throwing it at you, for which any book would suffice, but I can't put any of the knowledge represented within into practice.

Why can't you put any of the knowledge represented in the book into practice? You can still pick the book up and extract the knowledge.

See how these are technically correct arguments, yet they are absolutely stupid?

This gets the question...how do we think? Are we not just language (and other inputs as well) processors? I'm not sure the answer is "no."

I also listened to an interesting podcast, I believe it was this American life or some other npr one, about whether ai has intelligence. To avoid the just "compressed knowledge" they came up with questions that the ai almost certainly would not have found in the web. Early ai models were clearly just predicting the next word, and the example was asking it to stack a list of objects. And it just said to stack them one on top of another, in a way that would no way be stable.

However when they asked a new model to do the same, with the stipulation that it explain it's reasoning, it stacked the objects in a way that would likely be stable. Even noting that the nail on top should be placed on the head so it doesn't roll around, and laying eggs down in a grid between a book and a plank of wood so they wouldn't roll out.

Another experiment they did was take a language model and asked it to use some obscure programming language to draw a picture of a unicorn. Now this is a language model, not trained on any images.

And you know what it did? It produced a picture of a unicorn. Just in rough shapes, but even when they moved the horn and flipped it around, it was able to put it back. Without even ever seeing a unicorn, or anything even, it was able to draw a picture of one.

I don't think the answer is as simple and clear as you want it to be. And the fact that it "fucked up" on a vague prompt doesn't really prove anything. Even humans do stupid shit like this if they learn something incorrectly.

A cognizant ai would have recognized that the Nazis it was creating looked historically inaccurate, based on its training data.

Do you understand that the model is specifically prompted to create "historically inaccurate looking Nazis"? Models aren't supposed to inject their own guidelines and rules, they simply produce output for your input. If you tell it to produce black Hitler it will produce a black Hitler. Do you expect the model to instead produce white Hitler?

It definitely is lacking for now, but the question is: are these differences in degrees, or fundamental differences? I haven't seen research suggesting that it's the latter so far.

Exactly. They have very strong feelings that they are right, and won't be moved - not by arguments, research, evidence or anything else.

Just look at the guy telling me "they can't reason!". I asked whether they'd accept they are wrong if I provide a counter example, and they literally can't say yes. Their world view won't allow it. If I'm sure I'm right that no counter examples exist to my point, I'd gladly say "yes, a counter example would sway me".

Yall actually have any research to share or just gonna talk about it?