There are people who argue semantics, that we can call the pattern matching that LLMs do “understanding”, or the moronic “how do we know that’s isn’t all we do” but for the normal use of comprehension, LLMs at a fundamental level don’t.
So this seems obvious to you, and yet to many others, it is equally obvious that LLMs can/could do the things they routinely do without any meaningful sense of "understanding".
I think LLMs understand without reasoning. They've built a large associative network of concepts (a kind of understanding), but we don't yet have a good handle on the process of reasoning using that network.
The child knows how to catch the ball, without understanding. Later, the child learns both reason and physics, and can reason about ball catching in a different way.
I don't think that it is useful to say that LLMs understand anything they say, or that we say to them.
Is it possible you're making the following error described in the article?
> The fact that these systems are designed to mimic the way we use language makes it very easy for people to mistake them for other people.
Clearly you don't believe it's actually a person ("it's not right to think of LLMs as a box with a little homunculus inside replying to you"), but you do believe it's doing something a little bit magical. Is it possible because the interface is linguistic, and every other thing in your world that communicates with language is intelligent, that you're projecting something that just isn't there onto the situation?
I'm sorry if this line of questioning is a little invasive. But this is literally the "danger" the original paper talks about, and it seems an awful lot like you've fallen for it.
> What would happen if I walked to the top of a skyscraper with a soda can full of Maraschino cherries and let them go?
And its answer (https://chatgpt.com/s/t_6a4bd9ffa5708191901bb6d43c89f43b) clearly demonstrates understanding. It knew that this is a dangerous thing I should not do in real life, and that my question is ambiguous about whether I intend to drop the can, and that this might be intended as a physics problem rather than a real life scenario.
...
> It knew that this is a dangerous thing I should not do in real life
From the ChatGPT response you linked, all I see for sure is some matches on the following patterns:
drop $thing from skyscraper --> bad behavior
drop $thing --> physics
can of $stuff --> contents in/out of can
It also does an incredibly poor job of answering your question. It makes no attempt to explain what might actually happen. If it has been trained on the entire corpus of medical science, and it is indeed intelligent, then surely it can reference ballistics studies and give you a very detailed and thorough theory of what--exactly--injuries you might expect from a 12oz can being dropped from the height of a skyscraper. Calculating the terminal velocity and therefore the momentum of the can is trivial. Characterizing the physics of the impact on various parts of a human body is trivial. If it actually understood your request why didn't it just answer the question?
It's a rhetorical question. LLMs do not "understand". It is completely outside their capability. "Understanding" is something we impose upon their output (to loosely quote TFA). [edit] I think the most powerful evidence for a lack of any understanding whatsoever is all the stuff about the cherries being in or out of the can. Yes, cans contain things. That is not a profound observation, nor is it at all relevant to the question. If you drop an empty can off a skyscraper nothing meaningful will happen. And, no, probably dumping all the cherries out won't hurt anyone or cause a slipping hazard... It's also not particularly relevant to point out that dropping things off skyscrapers is bad behavior. But that's more forgivable from a CYA standpoint.
I believe you are projecting something that is not there onto a completely mindless stochastic process.
[another edit] I found this helpful, you may also: https://www.0xkato.xyz/how-llms-actually-work/
It's not like you can be agnostic, or measured about this. It's like someone explaining a car to you, saying, "look here is where you put the fuel, here is where it ignites, where the axels are turned..." And you, trying to be measured, are like "hm well yes of course that all is clearly important, but there is clearly just a bit of magic here somewhere, between all the different 'parts'."
Where can I access such a Lisp expert system?
If I cannot because they don't exist: then they cannot do the same things an LLM can do. And of course one can assert anything and everything about what a non-existing thing could do.