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What can LLMs never do?

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Re: What can LLMs never do?

#301

Post by LivenessModel »

scoot wrote: post #291
Al-Khwarizmi wrote: post #264

Earlier quoted context omitted.

An LLM doesn't even see individual letters at all, because they get encoded into tokens before they are passed as input to the model. It doesn't make much sense to require reasoning with things that aren't even in the input as a requisite for intelligence. That would be like an alien race that could see in an extra dimension, or see the non-visible light spectrum, presenting us with problems that we cannot even see a…

And yet ChatGPT 3.5 can tell me the nth letter of an arbitrary word…

And yet GPT4 still can't reliably tell me if a word contains any given letter.

Re: What can LLMs never do?

#302

Post by jncfhnb »

PopePompus wrote: post #276
jncfhnb wrote: post #269

Earlier quoted context omitted.

Active for a period is still continuous during that period. As opposed to “active when called”. A function, being called repeatedly over a length of time is reasonably “continuous” imo

I don't see what the difference between "continuous during that period" and "active when called" is. When an AI runs inference, that calculation takes time. It is active during the entire interval during which it is responding to the prompt. It is then inactive until the next prompt. I don't see why a system can't be considered intelligent merely because its activity is intermittent.

The calculation takes time but the inference is from a single snapshot so it is effectively a single transaction of input to output. An intelligent entity is not a transactional machine. It has to a working system.

That system might be as simple as calling the transactional machine ever few seconds. That might pass the threshold. But then your AGI is the broader setup, not just the LLM.

But the transactional machine is certainly not an intelligent entity. Much like a brain in a jar or a cryostasis’d human.

Suppose we could perfectly simulate a human mind in a way that everyone finds compelling. We would still not call that simulated human mind an intelligent entity unless it was “active”.

Re: What can LLMs never do?

#303

Post by jncfhnb »

naasking wrote: post #283
jncfhnb wrote: post #281

Earlier quoted context omitted.

State is a function of accumulated past. That does not mean that having some past written down makes you stateful. A stateful thing has to incorporate the ongoing changes.

Which is what I described: some successful prompt-replies are fed back into subsequent training runs.

No… that implies the model never has active state and is being replaced with a different, stateless model. This is similar to the difference between

Actor.happy = True

And

Actor = happier(Actor)

Re: What can LLMs never do?

#304

Post by jncfhnb »

card_zero wrote: post #294
jncfhnb wrote: post #273

Earlier quoted context omitted.

Then for at least eight hours a day you don’t qualify as a generally intelligent system.

If I spend some amount of the day bathing, some amount of it scratching, some amount of it thinking vaguely about racoons without any clear conclusions, and a lot of it drinking tea, I wonder how many seconds remain during which I qualified as generally intelligent.

I feel you qualify during all of those waking seconds

Re: What can LLMs never do?

#305

Post by layer8 »

furyofantares wrote: post #300
layer8 wrote: post #296

Earlier quoted context omitted.

The idea is, instead of five-letter-words, play the game with five-token-words.

That was my original interpretation, and while all it sees are tokens, roughly none of its training data is metadata about tokenizing. It knows far less about the positions of tokens in words than it does about the positions of letters in words.

I’m not sure that training data about that would be required. Shouldn’t the model be able to recognize that `["re", "cogn", "ize"]` represents the same sequence of tokens as `recognize`, assuming those are tokens in the model?

More generally, would you say that LLMs are generally unable to reason about sequences of items (not necessarily tokens) and compare them to some definition of “valid” sequences that would arise from the training corpus?

Re: What can LLMs never do?

#306

Post by Al-Khwarizmi »

scoot wrote: post #291
Al-Khwarizmi wrote: post #264

Earlier quoted context omitted.

An LLM doesn't even see individual letters at all, because they get encoded into tokens before they are passed as input to the model. It doesn't make much sense to require reasoning with things that aren't even in the input as a requisite for intelligence. That would be like an alien race that could see in an extra dimension, or see the non-visible light spectrum, presenting us with problems that we cannot even see a…

And yet ChatGPT 3.5 can tell me the nth letter of an arbitrary word…

I have just tried and it indeed does get it right quite often, but if the word is rare (or made up) and the position is not one of the first, it often fails. And GPT-4 too.

I suppose if it can sort of do it is because of indirect deductions from training data.

I.e. maybe things like "the third letter of the word dog is d", or "the word d is composed of the letters d, o, g" are in the training data; and from there it can answer questions not only about "dog", but probably about words that have "dog" as their first subtoken.

Actually it's quite impressive that it can sort of do it taking into account that, as I mention, characters are just outright not in the input. It's ironic that people often use these things as an example of how "dumb" the system is when it's actually amazing that it can sometimes work around that limitation.

Re: What can LLMs never do?

#307

Post by cess11 »

naasking wrote: post #299

> They have been trained on more information than a human being can hope to even see in a lifetime. Assuming a human can read 300 words a min and 8 hours of reading time a day, they would read over a 30,000 to 50,000 books in their lifetime. Most people would manage perhaps a meagre subset of that, at best 1% of it. That’s at best 1 GB of data. This just isn't true. Human training is multimodal to a degree far beyond…

Some people seem to be unaware that reality is analog, possibly fractal.

Re: What can LLMs never do?

#308

Post by card_zero »

jncfhnb wrote: post #304
card_zero wrote: post #294

Earlier quoted context omitted.

If I spend some amount of the day bathing, some amount of it scratching, some amount of it thinking vaguely about racoons without any clear conclusions, and a lot of it drinking tea, I wonder how many seconds remain during which I qualified as generally intelligent.

I feel you qualify during all of those waking seconds

Racoons are said to be intelligent because they're good at opening locks. On the other hand, when they have food and are within ten feet of a pool of water, they will dip the food in the water and rub it between their paws for no reason. They can reason about the locks, but not about the food. Meanwhile, I in theory can reason about anything, but in practice I wouldn't count on it. Whereas an LLM can't reason, but it's very sharp and always ready to react appropriately.

Re: What can LLMs never do?

#309

Post by kromem »

fragmede wrote: post #293
kromem wrote: post #239

Earlier quoted context omitted.

We may be talking about different logic puzzles? The only model I've seen that didn't need some rather extreme adjustments to eventually solve it was Mistral large.

what's your puzzle? mines the river crossing puzzle

Mine is also the river crossing puzzle. What's your variation?

Re: What can LLMs never do?

#310

Post by cs702 »

naasking wrote: post #299

> They have been trained on more information than a human being can hope to even see in a lifetime. Assuming a human can read 300 words a min and 8 hours of reading time a day, they would read over a 30,000 to 50,000 books in their lifetime. Most people would manage perhaps a meagre subset of that, at best 1% of it. That’s at best 1 GB of data. This just isn't true. Human training is multimodal to a degree far beyond…

I agree with you, but your comment strikes me as unfair nitpicking, because the OP is referring to information that has been encoded in words.
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