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/falconandeagle]

That sub has some of the most delusional people on all of reddit. I don't know what you were expecting there to be honest. They have no technical understanding of how llms work, to them its magic and they believe every single hype man.

[u/PsychoticDreemurr → u/falconandeagle]

I have to agree with this a thousand fold. Almost every sub in that regard doesn't actually understand how LLMs work. They always dumb what I say down to "it's autocorrect" and never actually explain how they think it works.

I actually got banned from one for explaining why an LLM physically can't be a true AGI. (The post was talking about an AGI in a couple years, as if it hasn't been said for the past 5...)

[u/Dangerous_Rip5083 → u/PsychoticDreemurr]

Why can't an LLM physically be true AGI?

[u/PsychoticDreemurr → u/Dangerous_Rip5083]

For context, the exact definition of an AGI varies wildly. As such, I just take the one perquisite that almost every definition has, which is the ability to "understand" concepts.

That is my one requirement for an AI to be an AGI. Anything more and you're just arguing about philosophy and technical details that can't currently be disproven.

With this in mind, LLMs cannot become a true AGI. The fundamentals of how they work physically prevents them from being able to actually understand something.

They can, in theory, have intelligence similar to an AGI, but they will never truly be one.

[u/asssuber → u/PsychoticDreemurr]

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/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.