Tim Cook…go take your meds and watch Price is Right
Saying anything else would be lying
Stupid headline, it’s like Tim Cook saying he’s not 100% sure Apple can stop batteries in their devices from exploding. You do as much as you can to prevent it but it might happen anyway because that’s just how it is.
Of course you are getting downvoted, because you are right and not being a reactionary douche like your average lemmizen.
It’s kind of funny how AI has the exact same problems some humans have.
I always thought AI wouldn’t have that kind of problems, because they would be carefully fed accurate information.
Instead they are taught from things like Facebook and the thing formerly known as Twitter.
What an idiotic timeline we are in. LOLThere’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.
They learn how to pretend
True, and they are so darn good at it, that it can be somewhat confusing at times.
But the current AIs are not the ones we read about in SciFi.I’d argue that referring to it as “AI” is a stretch since it’s all A and no I.
This is why I strictly refer to these things as LLMs. That’s what they are.
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…
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.
-
Hands. Are your hands… Hands? Do they make sense?
-
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
-
How did I get here? Where was I before this? Does the transition make sense?
-
Mirrors. Are they accurate?
-
Displays on digital devices. Do they look normal?
-
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.
Also, check your cell phone. Despite how ubiquitous they are in our daily lives, I don’t think I’ve seen a single cell phone in my dreams. Or any other phone, for that matter.
And now that I think about it, I’ve definitely had a dream of being in my living room where there’s a TV, but I don’t remember the TV actually being in the dream.
Weird.
-
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.
Not in the case of the google search AI. It quotes directly from unreliable sources.
Exactly, which is why I’ve objected in the past to calling Google Overview’s mistakes “hallucinations.” The AI itself is performing correctly, it’s giving an accurate overview of the search result it’s being told to create an overview for. It’s just being fed incorrect information.
Right? In all science fiction, artificial intelligence starts out better than us, and the only question is whether it can capture some idiosyncratic element of “being human.” Instead, AI has started out dumber than us, and we’re all standing around saying “uh what is this good 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.
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.
Yeah it’s the old garbage in, garbage out problem, the AI algorithms don’t really understand what they are outputting.
I think at this point voice recognition and text generation AI would be more useful as something like a phone assistant. You could tell it complex things like “Mute my phone for the next 2 hours” or “Notify me if I receive an email from John Smith.” Those sort of things could be easily done by AI algorithms that A) Understand your voice and B) Are programmed to know all the features of the OS. Hopefully with a known dataset like a phone OS there shouldn’t be hallucination problems, the AI could just act as an OS concierge.
Seems Siri and Alexa could already do things like that without needing LLMs trained on Facebook shit.
The narrow purpose models seem to be the most successful, so this would support the idea that a general AI isn’t going to happen from LLMs alone. It’s interesting that hallucinations are seen as a problem yet are probably part of why LLMs can be creative (much like humans). We shouldn’t want to stop them, but just control when they happen and be aware of when the AI is off the tracks. A group of different models working together and checking each other might work (and probably has already been tried, it’s hard to keep up).
Yeah the hallucinations could be very useful for art and creative stepping stones. But not as much for factual information.
They can’t. AI has hallucinations. Google has shown that AI can’t even rely on external sources, either.
At least LLMs will. The only real fix we’ve seen was running it through additional specialized LLMs to try to massage out errors, but that just increases costs and scale for marginally low results.
I don’t know why they’re trying to shove AI down our throats. They need to take their time, allow it to evolve.
Because it’s all a corporation and a huge part of the corporate capitalist system is infinite growth. They want returns, BIG ones. When? Right the fuck now. How do you do that? Well AI would turn the world upside down like the dot-com boom. So they dump tons of money into AI. So… it’s the AI done? Oh no no no, we’re at machine leaning AI is pretty far down the road actually, what we’re firing the AI department heads and releasing this machine leaning software as 100% all the way done AI?
It’s all the same reasons section 8 housing and low cost housing don’t work under corporate capitalism. It’s profitable to take government money, it’s profitable to have low rent apartments. That’s not the problem, the problem is THEY NEED THE GROWTH NOW NOW NOW!!! If you have a choice between owning a condo where you have high wage renters, and you add another $100 to rent every year, you get more profit faster. No one wants to invest in a 10% increase over 5 years if the can invest in 12% over 4 years. So no one ever invests in low rent or section 8 housing.
If you want to have good AI, you need to spend money and send your AI to college. Have real humans interact with it, correct it’s logic, make sure it understands sarcasm and logical fallacies.
Or, you can go the cheap route: train it on 10 years of Reddit sh*tposts and hope for the best.
Of course they can’t. Any product or feature is only as good as the data underneath it. Training data comes from the internet, and the internet is full of humans. Humans make and write weird shit so so the data that the LLM ingests is weird, this creates hallucinations.
Well yeah, its using the same dataset as MS copilot.
Spitting out inaccurate (I wish the media would stop feeding into calling it something that sounds less bad like hallucinations) answers is nothing something that will go away until the LLM gains the ability to decern context.
If Apple can stop AI hallucination, any other AI company can also stop AI hallucination. Which is something they could have already done instead of making AI seem a joke on purpose. AI hallucinations are a sort of phenomena that nobody has control over. Why would Tim Cook have unique control over it?
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
Yeah. When Apple says it’s coming into a market, they mean they have already perfected it.
(Or let other companies polish up a feature/concept for a few years, slap a coat of Space Gray on it, and release it as a revolutionary “new” feature for apple)
Like the revolutionary space gray USB-C port?
eh. I don’t think Apple’s gonna be a pioneer in AI. If anybody can do it, it would be openai figuring it out first. Happy to be proven wrong tho.
Oh I’m not suggesting the will or are able to, I’m coming from a strategic standpoint
I’m sure Tesla can do it within the decade! /s
You mean xAI?
I doubt anyone can for as long as “AI” is synonymous with LLMs. LLMs are just inherently unreliable because of how they work.
I’m not exaggerating when I say there’s only like a dozen true experts for generative AI on the planet and even they’re not completely sure what’s going on in that blackbox. And as far as I’m aware Tim Cook isn’t even one of them. How would he know?
I would expect that Apple has hired some of those experts and they told him.
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.
Everything these AIs output is a hallucination. Imagine if you were locked in a sensory deprivation tank, completely cut off from the outside world, and only had your brain fed the text of all books and internet sites. You would hallucinate everything about them too. You would have no idea what was real and what wasn’t because you’d lack any epistemic tools for confirming your knowledge.
That’s the biggest reason why AIs will always be bullshitters as long as their disembodied software programs running on a server. At best they can be a brain in a vat which is a pure hallucination machine.
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.
I’m 100% sure he can’t. Or at least, not from LLMs specifically. I’m not an expert so feel free to ignore my opinion but from what I’ve read, “hallucinations” are a feature of the way LLMs work.
One can have an expert system assisted by ML for classification. But that’s not an LLM.
You mean we can’t teach a bullshit machine to stop bullshitting? I’m shocked.
What you can do is try to filter out the garbage, but it’s basically trying to find gold in food waste.
