Technology

I was wondering, are people working on networks that train to create a modular model of the world, in order to understand it / predict events in the world?

I imagine that that is basically what our brains do.

all we know about ourselves is what's in our memories. the way normal writing or talking works is just picking what words sound best in order

They do have internal concepts though: https://www.lesswrong.com/posts/yzGDwpRBx6TEcdeA5/a-chess-gpt-linear-emergent-world-representation

Probably not of what a human is, but thought process is needed for better text generarion and is therefore emergent in their neural net

An LLM once explained to me that it didn't know, it simulated an answer. I found that descriptive.

The AI is confidently wrong, that's the whole problem. If there was an easy way to know if it could be wrong we wouldn't have this discussion

These programs are averaging massive amounts of data into a massive averaging function. There's no way that a human could ever understand what's going on inside that kind function. Humans can't hold millions of weights/etc in their head and comprehend what it means. Otherwise, if humans could do this, there would be no point in doing this kind of statistics with computers.

I would expect that Apple has hired some of those experts and they told him.

I'm sure Tesla can do it within the decade! /s

Unless Apple became the first to figure out how, then they suddenly have a huge leg up on the rest. Which is kinda how Apple has been making their bread for most of their successes in my lifetime

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

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.

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.

Instead they are taught from things like Facebook and the thing formerly known as Twitter.

Imagine they would teach in our schools to inform yourself about all the important things, and therefore you should read as many toilet walls as newspapers...

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.