The post appended the raw data provided by GPT, allowing you to verify the integrity of the data. This makes the post trustworthy from a methodological pov.
> I don’t trust anything published on the Internet after Llms went mainstream.
You always had to verify the integrity of the data and methods used in any publication, regardless of the medium. The responsibility of both authors and readers hasn't changed. If you took things for granted before LLMs, you shouldn't have, and if you don't trust trustworthy authors post LLMs, you should.
> This makes the post trustworthy from a methodological pov.
A post is not trustworthy if it’s reposting trash, even if it shows the source.
> you took things for granted before LLMs, you shouldn't have, and if you don't trust trustworthy authors post LLMs, you should.
The nature of how LLMs hallucinate is different from how garbage used to appear on the internet. Before LLMs there was a relatively good inverse correlation between quality and blatant bullshit. Not enough to pass the verification rigor required for an academic publication by any means, but enough that you didn’t have to second guess every single statement on every web page listing something as simple as book authors.
Here's my radical take: humans hallucinate as much or more than the top LLMs. Heck, depending on the human, nearly everything they think and say is functionally a hallucination according to the metrics in use here.
When it comes to what LLM's write, I find that LLM hallucinations are like self-driving car crashes. We are hyper-aware of the machine doing something that we ourselves do every single day and consider a normal defect of biological conscious.
> Here's my radical take: humans hallucinate as much or more than the top LLMs.
I can't believe that. LLMs always talk in the same confident tone, entirely regardless of what they're saying is true or not. What is true in the real world literally doesn't come into the equation.
Whereas at least some of the time, humans will say that they're not sure and might be wrong, or otherwise sound less confident. And that's related to how true the thing they're saying is.
> humans will say that they're not sure and might be wrong
Is that so? https://innocenceproject.org/dna-exonerations-in-the-united-... These people were convicted by people who were 100% convinced their memory was correct. The DNA evidence, which is "harder" evidence, said otherwise, and in these cases, was exonerating. (There are hundreds, possibly thousands, of other cases like this by the way, where the imprisoned innocent is NOT yet exonerated, all based on overconfident eyewitness testimony that yet managed to convince a judge/jury.)
There is also the well-known Dunning-Kruger effect, the cognitive bias where individuals with limited knowledge or expertise in a particular area tend to overestimate their competence and confidently assert their opinions. We've literally seen this countless times just since the 2016 US election, just watch literally any Jordan Klepper interview https://www.youtube.com/watch?v=LoZ2Lt_aCo8 (honestly, this is a little too political for me to use as an example, but I ran out of time seeking out unbiased examples... Mandela Effect? Misplaced keys being common?)
I'm afraid you're a little off, here, on your faith in humans not hallucinating memories and knowledge.
Ironically, if you agree with pmarreck above, scarblac's comment can be seen as an example of a human hallucinating with confidence, precisely what they were arguing is less likely to occur in the organic side of the internet.
That “if” is doing a good bit of lifting though. Nobody is talking about the hallucination rate.
How many times have innocent people been wrongly convicted? The innocence project found 375 instances in a 31 year period.
How often do LLMs give false info? Hope it never gets used to write software for avionics, criminology, agriculture, or any other setting that could impact huge amounts of people…
I think this is overall a good criticism of the current generation of LLM's- They can't seem to tell you how sure (or not) they are about something. A friend mentioned to me that when it gave ChatGPT a photo of a Lego set with an Indiana Jones theme earlier today and asked it to identify the movie reference, it meandered on for 2 paragraphs arguing different possibilities when it could have just said "I'm not sure."
I think this is a valid area of improvement, and I think we'll get there.
They never did human always do it, rather that they do “some of the time”. Whereas I’ve yet to see an LLM do that.
Also experts tend to be much more accurate at evaluating how knowledgable they are (this is also part of the D-K effect). So Id much prefer to have a 130 IQ expert answer my question than an LLM
Fair enough, but given that access to a 130IQ expert on the subject matter at hand may be either expensive or impossible to obtain in the moment, and ChatGPT is always available 24/7 at very nominal cost, what do you think is the better option overall?
They do, but they are better at verifying what they've already said. So a simple prompt asking them to verify the facts they've presented often improves the accuracy. There are also other techniques like chain of thought and tree of thought that further improves accuracy.
oh here we go. You're one of those people conveniently restricting this accusation to a machine that scores a 130 IQ (https://www.reddit.com/r/singularity/comments/11t5bhh/i_just...), instead of also including humans, who notably will send someone to prison 1000% sure that they witnessed that person doing the thing, when in fact, later DNA evidence exonerates them (https://innocenceproject.org/dna-exonerations-in-the-united-...). Fucking LOL. Get out of here, doomer, the rest of us have AI-enhanced work to do.
Of course humans also hallucinate, but we didn’t have to take that into account every single time we read a piece of information on the internet. Humans have well-documented cognitive biases. Also, usually, a human’s attempt to deceive has some motivation. With LLMs, the most basic of information they provide could be totally false.
I don't dispute this. What I chafe at is the default-dismissive attitude about any utility of these. "It emits inaccuracies, therefore useless" would invalidate literally every human.
That said, overall utility of anything plummets drastically as reliability goes below 100%. If a particular texting app or service only successfully sent 90% of your messages, or a person you depended on only answered 90% of your calls, you'd probably stop relying on those things.
Those are both excellent points. And I know I’m guilty of being somewhat anti-LLM just because it’s the new hotness and I’m kind of a contrarian by nature. Which is an example of bias right there! And being in academia when it blew up - I do worry about our future cohorts of computer scientists jf academia doesn’t adapt. Which it almost surely won’t. But that’s not a problem inherent to LLMs.
Did you fully read the post you blew up at? I didn’t doubt the usefulness of LLMs. It was a very specific complaint about posting LLM generated content on the Internet without specifying it as the off-the-cuff trash it usually is.
> If you took things for granted before LLMs, you shouldn't have, and if you don't trust trustworthy authors post LLMs, you should.
Blaming LLMs for everything is becoming the preferred excuse for people who like to reject what they read and substitute their own beliefs instead.
It’s true that LLMs hallucinate and are definitely not correct all the time, but the way people are using that as an opening to reject everything on the internet and elevate their own prior beliefs to the top is strange.
Most people don't know humans hallucinate daily. Right now your brain is removing visual information by clipping out the image of your nose and replacing it with what the scene behind it theoretically looks like.
One could argue that whereas once it was necessary to verify the source, now it is necessary to verify not just the source but also the LLM derivation of it, (which may be subtly mangled) - and the source may no longer be readily apparent.
I think this is a good thing. In the past you would remind people, hey, after you find your wiki article, "please" go verify. But wiki was "good" enough most of the time, that people found verification to be often time redundant.
But now with LLMs everywhere, people will realize it is necessary to verify.
The post appended the raw data provided by GPT, allowing you to verify the integrity of the data. This makes the post trustworthy from a methodological pov.
> I don’t trust anything published on the Internet after Llms went mainstream.
You always had to verify the integrity of the data and methods used in any publication, regardless of the medium. The responsibility of both authors and readers hasn't changed. If you took things for granted before LLMs, you shouldn't have, and if you don't trust trustworthy authors post LLMs, you should.