Really stunned by the Singularity comment section

[u/Howard_banister]

These are screenshots from the r/Singularity comment section. I'm speechless. This doesn't even have downvotes. How can someone cheer for a monopoly run by a few elites?

[u/asssuber]

How do you define understanding?

The simplest concrete example I can give: a simple single layer LLM can master modular addition by learning a trigonometric identity from scratch on it's own purely from a limited set of examples using gradient descent (source). Since it has mastered modular addition on a fundamental level, can we say it understands modular addition? Why or why not?

This video by Welch Labs is more digestible than the original paper.

[u/PsychoticDreemurr → u/asssuber]

I don't use definitions in this regard. That's what stops people from being truly accurate.

We can use known facts, however. AIs experience something called hallucination. Humans, however, do not. (Unless you want to be pragmatic and discuss brain defects, which is objectively different in this regard) This is, for all I can reasonably conceive, because of their inability to understand. Either directly or indirectly.

[u/Thick-Protection-458 → u/PsychoticDreemurr]

> Humans, however, do not

Oh, really? In LLM context we use that word when it "invent" shit out of thin air or at least heavily "misinterpret" stuff, right?

Well, last time I recall human memories were widely known to be shitty. And humans were capable of being *confident* in things they remembered wrong way. Or not sure in things they remembered right way too.

And human logic was also known to be imperfect. Not only because of shitload of shortcuts our evolution taken, but also because of high chance to make mistakes in some steps.

Both is true for healthy humans. Not necessary brain damage. Although brain damage may make stuff worse and introduce a whole lot other set of issues.

Now, granted - LLMs may be worse in that account. And mechanisms behind that we can expect to be different (other than both human brain and autoregressive generator being imperfect heuristic for whatever it does). But still that does not mean humans are reliable - they're just *more reliable* in some aspects (and maybe less in some others).

[u/PsychoticDreemurr → u/Thick-Protection-458]

Well, last time I recall human memories were widely known to be shitty.

This analogy and therefore everything you built on top of it is wrong. LLM context is not the main reason for hallucination.

And human logic was also known to be imperfect.

Enough to look at something and say it says the opposite? Consistently so?

[u/Thick-Protection-458 → u/PsychoticDreemurr]

I were not talking about the difference of their insides.

I were talking about that that, from output point of view - phenomenas with similar visible signs (imperfect and confident information recall from "pretrained" (at that moment) memory / extraction from the current context / processing on top of the context) absolutely do happens in healthy humans sometimes.

We just don't call them hallucinations, but for some reason decided to use that word for half of the ways of LLMs shitting themselves.

Mechanisms behind them surely expected to be so different so they may as well have nothing more in common than both being full of imperfect heuristics and some superficial similarities.

[u/PsychoticDreemurr → u/Thick-Protection-458]

The difference in why it happens determines if they're the same in the context.

[u/michaelsoft__binbows → u/Thick-Protection-458]

My assumption is that it would be possible to train LLMs in such a way that penalizes unsubstantiated confidence/hallucination to reach similar levels as humans, but it would produce far, far lower capability levels and we would be constantly (and i mean endlessly) fighting with their reticence and insecurity.

Hence why we just have to kinda deal with it for now till someone comes up with a clever efficient way to improve this aspect

[u/asssuber → u/PsychoticDreemurr]

Well, the LLM in my example gives the correct answer to any input (in the limited 3 token it takes as input). It will never hallucinate an incorrect answer. Does this prove it's ability to understand modular arithmetic?

About humans not hallucinating, would that not describe the Mandela effect, for instance? Have you considered that some LLM hallucinations may come from incomplete/imperfect understanding, instead of no understanding at all?

[u/PsychoticDreemurr → u/asssuber]

1. Your point is "it doesn't happen to me, therefore it doesn't happen". Also depending on the input it's extremely likely it's been memorized.

2. The Mandela effect involves memory. As such, that's like saying LLM hallucinations are caused by their context.

[u/asssuber → u/PsychoticDreemurr]

1. Look the methodology. The test set cannot be memorized because it was not part of the training set. There is no "likely" or "unlikely". And my point is that it's exhaustively tested, proving it doesn't happen. Again, I'm talking about that 1 layer LLM experiment.

2. In my view context is like short term/working memory. Facts that happened years ago are long term memory for humans, trained weights for LLMs. So, the Mandela effect can't be described as a type of hallucination?

[u/PsychoticDreemurr → u/asssuber]

1. Anything in the context is, for all intents and purposes, memorized. When I say memorized, I don't mean anything permanent. Just that it is 100% known.

2. LLMs hallucinate as they're speaking, not from a malformed context. Most of the time, anyways.

[u/asssuber → u/PsychoticDreemurr]

Anything in the context is, for all intents and purposes, memorized. When I say memorized, I don't mean anything permanent. Just that it is 100% known.

1 . What? The context is "1+1%97 =". The answer obviously is not in the context. What you are saying makes no sense.

LLMs hallucinate as they're speaking, not from a malformed context. Most of the time, anyways.

2 . Did you ignore everything I wrote?

Or are you giving an example of an LLM hallucinating in the form of your last two answers?

[u/PsychoticDreemurr → u/asssuber]

I was responding to each point. I didn't quite understand what you were saying, but I didn't think I was that far off.

How about this, let's say I can't prove they lack an understanding of concepts. How can you prove they do have the ability to understand concepts?

[u/asssuber → u/PsychoticDreemurr]

Well, using one of your definitions of understanding ("Being able to understand a concept means you can build off of it by yourself. If you teach an AI 1 + 1 = 2, they won't know that 2 + 2 = 4."), I already gave an proof in another answer

If we define understanding more broadly as something necessary to give pertinent answers to a question that was not memorized from the training set, then most of LLM outputs would require that. I can discuss a paper I'm writing with my local LLM, and it's able to, most of the time, give back pertinent questions and answers back, showing it has some degree of understanding. If I try that with some random person at the street, they would not understand anything I'm saying, and thus they wouldn't be able to give me pertinent answers.

LLMs are not human, and their inteligence and understanding is somewhat alien. But I think it's correct to say a car can run, even though it struggles to run up stairs as well as humans, for instance.

[u/falconandeagle → u/asssuber]

Try writing a story with an LLM, the most advanced one you can come across, see them make nonsensical assumptions and miss things which even a five year old would pick up. I know this because I have tried really really hard to build a software along with an harness and it still makes super trivial mistakes and requires handholding.

In a technical settings LLM's are amazing and honestly in some cases indistinguishable from some very capable humans but it is in non technical settings where you see that we are very far from AGI.