I thought the main issue was that AI don't really know how to say I don't know or second guess themselves, as it would take a lot more robust architecture with multiple feedback loops. Like a brain.

Anyway, LLM's aren't the only AI that do this. So them being trained on Facebook data certainly isn't the whole issue.

The problem with AI hallucinations is not that the AI was fed inaccurate information, it's that it's coming up with information that it wasn't fed in the first place.

As you say, this is a problem that humans have. But I'm not terribly surprised these AIs have it because they're being built in mimicry of how aspects of the human mind works. And in some cases it's desirable behaviour, for example when you're using an AI as a creative assistant. You want it to come up with new stuff in those situations.

It's just something you need to keep in mind when coming up with applications.

What weirds me out is that the things it has issues with when generating images/video are basically a list of things lucid dreamers check on to see if they're awake or dreaming.

1. Hands. Are your hands... Hands? Do they make sense?

2. Written language. Does it look like normal written language?

(3. Turn the lights off/4. Pinch your nose and breath through it) - these two not so much

5. How did I get here? Where was I before this? Does the transition make sense?

6. Mirrors. Are they accurate?

7. Displays on digital devices. Do they look normal?

8. Clocks. Digital and analog... Do they look like they're telling time? Even if they do, look away and check again.

(9. Physics, try to do something physically impossible, like poking your finger through your palm. 10. Do you recognize people/do they recognize you) - on two more that aren't relevant.

But still... It's kinda remarkable.

Also, Nvidia launched their earth 2 earth simulator recently. So, simulation theory confirmed, I guess.

There's also the fact that they can't tell reality apart from fiction in general, because they don't understand anything in the first place.

LLMs have no way of differentiating fantasy RPG elements from IRL things. So they can lose the plot on what is being discussed suddenly, and for seemingly no reason.

LLMs don't just "learn" facts from their training data. They learn how to pretend to be thinking, they can mimic but not really comprehend. If there were facts in the training data, it can regurgitate them, but it doesn't actually know which facts apply to which subjects, or when to not make some up.

It's not the exact same problems humans have. It's completely different. Marketers and hucksters just use anthropomorphic terminology to hype their dysfunctional programs.

What you can do is try to filter out the garbage, but it’s basically trying to find gold in food waste.

Remember the game people used to play that was something like "type my girlfriend is and then let your phone keyboards auto suggestion take it from there?" LLMs are that.

Yeah, I try to make this point as often as I can. The notion that AI hallucinates only wrong answers really misleads people about how these programs actually work. It couches it in terms of human failings rather than really getting at the underlying flaw in the whole concept.

LLMs are a really interesting area of research, but they never should have made it out of the lab. The fact that they did is purely because all science operates in the service of profit now. Imagine if OpenAI were able to rely on government funding instead of having to find a product to sell.

First of all I agree with your point that it is all hallucination.

However I think a brain in a vat could confirm information about the world with direct sensors like cameras and access to real-time data, as well as the ability to talk to people and determine things like who was trustworthy. In reality we are brains in vats, we just have a fairly common interface that makes consensus reality possible.

The thing that really stops LLMs from being able to make judgements about what is true and what is not is that they cannot make any judgements whatsoever. Judging what is true is a deeply contextual and meaning-rich question. LLMs cannot understand context.

I think the moment an AI can understand context is the moment it begins to gain true sentience, because a capacity for understanding context is definitionally unbounded. Context means searching beyond the current information for further information. I think this context barrier is fundamental, and we won't get truth-judging machines until we get actually-thinking machines.

One can have an expert system assisted by ML for classification. But that's not an LLM.

Yeah, just pull the plug. The amount of time we waste talking about this shit for these assholes to play another round of monopoly is unbelievable

I mean companies world wide just jumped in the AI bandwagon like a lot of people did with the NFT one. Mostly because AI actually has solid use cases and can make a big difference in broad situations.

Just since people are just slapping AI in everything it's gonna end up being another fad to raise stock prices, like firing people last year.

Let's just hope when all of the hype blows over and the general public thinks of AI as the marketing buzzword that never works quite right we'll keep AI in the things it's actually useful for