You've missed something about the Chinese Room. The solution to the Chinese Room riddle is that it is not the person in the room but rather the room itself that is communicating with you. The fact that there's a person there is irrelevant, and they could be replaced with a speaker or computer terminal.

Put differently, it's not an indictment of LLMs that they are merely Chinese Rooms, but rather one should be impressed that the Chinese Room is so capable despite being a completely deterministic machine.

If one day we discover that the human brain works on much simpler principles than we once thought, would that make humans any less valuable? It should be deeply troubling to us that LLMs can do so much while the mathematics behind them are so simple. Arguments that because LLMs are just scaled-up autocomplete they surely can't be very good at anything are not comforting to me at all.

You might just love Blind Sight. Here, they're trying to decide if an alien life form is sentient or a Chinese Room:

"Tell me more about your cousins," Rorschach sent.

"Our cousins lie about the family tree," Sascha replied, "with nieces and nephews and Neandertals. We do not like annoying cousins."

"We'd like to know about this tree."

Sascha muted the channel and gave us a look that said Could it be any more obvious? "It couldn't have parsed that. There were three linguistic ambiguities in there. It just ignored them."

"Well, it asked for clarification," Bates pointed out.

"It asked a follow-up question. Different thing entirely."

Bates was still out of the loop. Szpindel was starting to get it, though.. .

(damn, wish we had a tool that did exactly this back in August of 1996, amirite?)

Wait, what was going on in August of '96?

That's a very long answer to my snarky little comment :) I appreciate it though. Personally, I find LLMs interesting and I've spent quite a while playing with them. But after all they are like you described, an interconnected catalogue of random stuff, with some hallucinations to fill the gaps. They are NOT a reliable source of information or general knowledge or even safe to use as an "assistant". The marketing of LLMs as being fit for such purposes is the problem. Humans tend to turn off their brains and to blindly trust technology, and the tech companies are encouraging them to do so by making false promises.

a much simpler and dumber machine that was designed to handle this basic input question could have come up with the answer faster and more accurately

The human approach could be to write a (python) program to count the number of characters precisely.

When people refer to agents, is this what they are supposed to be doing? Is it done in a generic fashion or will it fall over with complexity?

Yes but have you considered that it agreed with me so now i need to defend it to the death against you horrible apes, no matter the allegation or terrain?

Imagine asking a librarian "What was happening in Los Angeles in the Summer of 1989?" and that person fetching you ... That's modern LLMs in a nutshell.

I agree, but I think you're still being too generous to LLMs. A librarian who fetched all those things would at least understand the question. An LLM is just trying to generate words that might logically follow the words you used.

IMO, one of the key ideas with the Chinese Room is that there's an assumption that the computer / book in the Chinese Room experiment has infinite capacity in some way. So, no matter what symbols are passed to it, it can come up with an appropriate response. But, obviously, while LLMs are incredibly huge, they can never be infinite. As a result, they can often be "fooled" when they're given input that semantically similar to a meme, joke or logic puzzle. The vast majority of the training data that matches the input is the meme, or joke, or logic puzzle. LLMs can't reason so they can't distinguish between "this is just a rephrasing of that meme" and "this is similar to that meme but distinct in an important way".

AGI is only a benchmark because it gets OpenAI out of a contract with Microsoft when it occurs.

If you want an even older example, the ghosts in Pac-Man could be considered AI as well.

Hey now, that's unfair and queerphobic.

These models are from 1950, with juiced up data sets. Alan turing personally sid a lot of work on them, before he cracked the math and figured out they were shit and would always be shit.

Machine learning algorithm from 2017, scaled up a few orders of magnitude so that it finally more or less works, then repackaged and sold by marketing teams.