> They do it by iteratively predicting the next token.

You don't know that. It's how the llm presents, not how it does things. That's what I mean by it being the interface.

There's ever only one word that comes out of your mouth at a time, but we don't conclude that humans only think one word at a time. Who's to say the machine doesn't plan out the full sentence and outputs just the next token?

I don't know either fwiw, and that's my main point. There's a lot to criticize about LLMs and, believe or not, I am a huge detractor of their use in most contexts. But this is a bad criticism of them. And it bugs me a lot because the really important problems with them are broadly ignored by this low-effort, ill-thought-out offhand dismissal.

Have you read the literature? Do you have a background in machine learning or statistics?

Yes. We know that LLMs can be trained by predicting the next token. This is a fact. You can look up the research papers, and open source training code.

I can't work it out, are you advocating a conspiracy theory that these models are trained with some elusive secret and that the researchers are lying to you?

Being trained by predicting one token at a time is also not a criticism??! It is just a factually correct description...

> Have you read the literature? Do you have a background in machine learning or statistics?

Very much so. Decades.

> Being trained by predicting one token at a time is also not a criticism??! It is just a factually correct description...

Of course that's the case. The objection I've had from the very first post in this thread is that using this trivially obvious fact as evidence that LLMs are boring/uninteresting/not AI/whatever is missing the forest for the trees.

"We understand [the I/Os and components of] LLMs, and what they are is nothing special" is the topic at hand. This is reductionist naivete. There is a gulf of complexity, in the formal mathematical sense and reductionism's arch-enemy, that is being handwaved away.

People responding to that with "but they ARE predicting one token at a time" are either falling into the very mistake I'm talking about, or are talking about something else entirety.

Do you have, by chance, a set of benchmarks that could be administered to humans and LLMs both, and used to measure and compare the levels of "consciousness, self-awareness and volition" in them?

Because if not, it's worthless philosophical drivel. If it can't be defined, let alone measured, then it might as well not exist.

What is measurable and does exist: performance on specific tasks.

And the pool of tasks where humans confidently outperform LLMs is both finite and ever diminishing. That doesn't bode well for human intelligence being unique or exceptional in any way.

> Because if not, it's worthless philosophical drivel.

The feeling is mutual:

> ... that doesn't bode well for human intelligence being unique or exceptional in any way.

My guess was that you argued that we "don't understand" these systems, or that our incomplete analysis matters, specifically to justify the possibility that they are in whatever sense "intelligent". And now you are making that explicit.

If you think that intelligence is well-defined enough, and the definition agreed-upon enough, to argue along these lines, the sophistry is yours.

> If it can't be defined, let alone measured

In fact, we can measure things (like "intelligence") without being able to define them. We can generally agree that a person of higher IQ has been measured to be more intelligent than a person of lower IQ, even without agreeing on what was actually measured. Measurement can be indirect; we only need accept that performance on tasks on an IQ test correlates with intelligence, not necessarily that the tasks demonstrate or represent intelligence.

And similarly, based on our individual understanding of the concept of "intelligence", we may conclude that IQ test results may not be probative in specific cases, or that administering such a test is inappropriate in specific cases.

Well, you could do the funny thing, and try to measure the IQ of an LLM using human IQ tests.

Frontier models usually get somewhere between 90 and 125, including on unseen tasks. Massive error bars. The performance of frontier models keeps rising, in line with other benchmarks.

And, for all the obvious issues with the method? It's less of a worthless thing to do than claiming "LLMs don't have consciousness, self-awareness and volition, and no, not gonna give definitions, not gonna give tests, they just don't have that".