This right here is also the reason why AI fanboys get angry when they are told that LLMs are not intelligent or even thinking at all. They don't understand that in order for rational intelligence to exist, the LLMs should be able to have an internal, referential inner world of symbols, to contrast external input (training data) against and that is also capable of changing and molding to reality and truth criteria. No, tokens are not what I'm talking about. I'm talking about an internally consistent and persistent representation of the world. An identity, which is currently antithetical with the information model used to train LLMs. Let me try to illustrate.

I don't remember the details or technical terms but essentially, animal intelligence needs to experience a lot of things first hand in order to create an individualized model of the world which is used to direct behavior (language is just one form of behavior after all). This is very slow and labor intensive, but it means that animals are extremely good, when they get good, at adapting said skills to a messy reality. LLMs are transactional, they rely entirely on the correlation of patterns of input to itself. As a result they don't need years of experience, like humans for example, to develop skilled intelligent responses. They can do it in hours of sensing training input instead. But at the same time, they can never be certain of their results, and when faced with reality, they crumble because it's harder for it to adapt intelligently and effectively to the mess of reality.

LLMs are a solipsism experiment. A child is locked in a dark cave with nothing but a dim light and millions of pages of text, assume immortality and no need for food or water. As there is nothing else to do but look at the text they eventually develop the ability to understand how the symbols marked on the text relate to each other, how they are usually and typically assembled one next to the other. One day, a slit on a wall opens and the person receives a piece of paper with a prompt, a pencil and a blank page. Out of boredom, the person looks at the prompt, it recognizes the symbols and the pattern, and starts assembling the symbols on the blank page with the pencil. They are just trying to continue from the prompt what they think would typically follow or should follow afterwards. The slit in the wall opens again, and the person intuitively pushes the paper it just wrote into the slit.

For the people outside the cave, leaving prompts and receiving the novel piece of paper, it would look like an intelligent linguistic construction, it is grammatically correct, the sentences are correctly punctuated and structured. The words even make sense and it says intelligent things in accordance to the training text left inside and the prompt given. But once in a while it seems to hallucinate weird passages. They miss the point that, it is not hallucinating, it just has no sense of reality. Their reality is just the text. When the cave is opened and the person trapped inside is left into the light of the world, it would still be profoundly ignorant about it. When given the word sun, written on a piece of paper, they would have no idea that the word refers to the bright burning ball of gas above them. It would know the word, it would know how it is usually used to assemble text next to other words. But it won't know what it is.

LLMs are just like that, they just aren't actually intelligent as the person in this mental experiment. Because there's no way, currently, for these LLMs to actually sense and correlate the real world, or several sources of sensors into a mentalese internal model. This is currently the crux and the biggest problem on the field of AI as I understand it.

I fucking hate how OpenAi and other such companies claim their models "understand" language or are "fluent" in French. These are human attributes. Unless they made a synthetic brain, they can take these claims and shove them up their square tight corporate behinds.

It's a nascent stage technology that reflects the world's words back at you in statistical order by way parsing user generated prompts. It's a reactive system with no autonomy to deviate from a template upon reset. It's no Rokos Basilisk inherently, just because

Its not just a calculator though.

Image generation requires no fact checking whatsoever, and some of the tools can do it well.

That said, LLMs will always have limitations and true AI is still a ways away.

Some problems lend themselves to "guess-and-check" approaches. This calculator is great at guessing, and it's usually "close enough".

The other calculator can check efficiently, but it can't solve the original problem.

Essentially this is the entire motivation for numerical methods.

People who suggest, let's say, firing employees of crisis intervention hotline and replacing them with llms...

The part that's being ignored is that it's a problem, not the existence of the hallucinations themselves. Currently a lot of enthusiasts are just brushing it off with the equivalent of ~~boys will be boys~~ AIs will be AIs, which is fine until an AI, say, gets someone jailed by providing garbage caselaw citations.

And, um, you're greatly overestimating what someone like my technophobic mother knows about AI ( xkcd 2501: Average Familiarity seems apropos). There are a lot of people out there who never get into a conversation about LLMs.

It's easily the worst problem of Lemmy. Sometimes one guy has an issue with something and suddenly the whole thread is about that thing, as if everyone thought about it. No, you didn't think about it, you just read another person's comment and made another one instead of replying to it.

I never heard anyone complain about the term "hallucination" for AIs, but suddenly in this one thread there are 100 clonic comments instead of a single upvoted ones.

I get it, you don't like "hallucinate", just upvote the existing comment about it and move on. If you have anything to add, reply to that comment.

I don't know why this specific thing is so common on Lemmy though, I don't think it happened in reddit.

that's not fun and dramatic and clickbaity though

I think you're giving a glorified encyclopedia too much credit. The difference between us and "AI" is that we can approach knowledge from a problem solving position. We do approximate the laws of physics, but we don't blindly take our beliefs and run with it. We put we come up with a theory that then gets rigorously criticized, then come up with ways to test that theory, then be critical of the test results and eventually we come to consensus that based on our understandings that thing is true. We've built entire frameworks to reduce our "hallucinations". The reason we even know we have blind spots is because we're so critical of our own "hallucinations" that we end up deliberately looking for our blind spots.

But the "AI" doesn't do that. It can't do that. The "AI" can't solve problems, it can't be critical of itself or what information its giving out. All our current "AI" can do is word vomit itself into a reasonable answer. Sometimes the word vomit is factually correct, sometimes it's just nonsense.

You are right that theoretically hallucinations cannot be solved, but in practicality we ourselves have come up with solutions to minimize it. We could probably do something similar with "AI" but not when the AI is just a LLM that fumbles into sentences.

Their real power is their ability to understand language and context.

...they do exactly none of that.

So if you type cats but the item is called pets get no results. Now the ai can find context based matches in the auto complete list.

Google added context search to Gmail and it's infuriating. I'm looking for an exact phrase that I even put in quotes but Gmail returns a long list of emails that are vaguely related to the search word.

Yes and no. I've had to insert a LOT of meaning to get a story worth any substance, and I've had to do a lot of editing to get good images. It's really good at giving me a figure that's 90% done, but that last 10% touching up still often takes me a day or so of work.

Searching with synonym matching is almost.decades old at this point. I worked on it as an undergrad in the early 2000s.and it wasn't new then, just complicated. Google's version improved over other search algorithms for a long time.and then trashed it by letting AI take over.

hallucination refers to a specific bug (AI confidently BSing) rather than all bugs as a whole

It's not a bug, it's a natural consequence of the methodology. A language model won't always be correct when it doesn't know what it is saying.

Because hallucinations pretty much exactly describes what's happening? All of your suggested terms are less descriptive of what the issue is.

The definition of hallucination:

A hallucination is a perception in the absence of an external stimulus.

In the case of generative AI, it's generating output that doesn't match it's training data "stimulus". Or in other words, false statements, or "facts" that don't exist in reality.

https://en.m.wikipedia.org/wiki/Hallucination_(artificial_intelligence)

The term "hallucinations" originally came from computer researchers working with image producing AI systems. I think you might be hallucinating yourself 😉