181–190 of 652 posts
This course mentions the famous Apple advertisement. Unfortunately it slightly oversells and while I'm sure that's not because this fragment was written by an LLM it is exactly the sort of over-simplification which leads to LLMs generating wild bullshit when they interpolate this "fact" with other "facts" they've been fed, and we ought to strive to do better when writing for humans. "Describe how prior to 1984, there…
This website is so important! Now ask yourself why AI companies don't want to be regulated or scrutinized. So many companies (users and providers) jump on the AI hype train because of FOMO. The end result might be just as destructive as this mythical "AGI". Edit: I am not saying to not use the technology. I am just on the side of caution and constant validation. The technology has to serve society. But I fear this hy…
This course mentions the famous Apple advertisement. Unfortunately it slightly oversells and while I'm sure that's not because this fragment was written by an LLM it is exactly the sort of over-simplification which leads to LLMs generating wild bullshit when they interpolate this "fact" with other "facts" they've been fed, and we ought to strive to do better when writing for humans. "Describe how prior to 1984, there…
Earlier quoted context omitted.
Two university professors in data science and computational biology are not just “somebody”.
People that find professors and similar in high esteem usually haven't spent enough time in or around academia and academics and for that reason still maintain some innocent aura of mystique and prestige around it in their mind. Quite literally anyone with a bit of persistence could become a professor (and this by far isn't even a top university either). They are quite literally just a somebody with an opinion just l…
While we shouldn't trust academics just because they are academics, these people specialize in relevant fields and also back their claims with citations throughout the course. They are not just postulating.
Organic produce was the first metaphor the came to mind: it's probably more healthy for you even if it isn't as pretty, but many people aren't willing to pay a premium it and I suspect economics isn't often the reason. Is that a straw-man for live music? I don't know that it is because plenty of people are content to listen to recorded music -- sure, they might enjoy going to a live concert but they'll still listen to the radio on the drive to work.
Then I got to thinking about something more crass: while breast implants and other cosmetic body surgery may be as much for the benefit of the subject self-image I imagine there are plenty of people that find it very attractive despite what is often obviously fake.
So do we crave authenticity? I think I do but I'm not sure if that's a safe generalization to make.
"The LLMs have no ground truth" claim (around chapter 2) that's core to the "bullshit machines" argument is itself wrong. Of course LLMs have ground truth. What do the authors think here, that the text in training corpus is random ? Hint: it isn't. Real conversations are anything but random. There's a lot of information hidden in "statistical ordering of the words", because the distribution is not arbitrary . Statist…
> Statistical ground truth isn't any worse than explicitly given one There are multiple kinds of truths. 'Statistical truth' is at best 'consensus truth', and that's only when LLM doesn't hallucinate.
When a kid at school is being taught, say, Newton's laws of motion, or what happened in 476 CE, they're not experiencing the empirical truth about either. They're only learning the consensus truth, i.e. the correct answer to give to the teacher, so they get good grade instead of bad grade, and so their parents praise them instead of punishing them, etc.
This covers pretty much everything any human ever learns. Few are in position to learn any particular things experimentally. Few are in position to verify most of what they've learned experimentally afterwards.
We live in a "consensus reality", but that works out fine, because establishing consensus is hard, and one of the strongest consensus-forcing forces that exist is "close enough to actual reality".
I was thinking how this article claims that people crave the authenticity of live music and that bullshit-generators will never be able to supply that. At first, I saw this as a reason for optimism, but then I got to thinking about evidence that people may not necessarily want authenticity after all. Organic produce was the first metaphor the came to mind: it's probably more healthy for you even if it isn't as pretty…
This website is so important! Now ask yourself why AI companies don't want to be regulated or scrutinized. So many companies (users and providers) jump on the AI hype train because of FOMO. The end result might be just as destructive as this mythical "AGI". Edit: I am not saying to not use the technology. I am just on the side of caution and constant validation. The technology has to serve society. But I fear this hy…
Fully agree, in recent weeks I've also started to consider LLMs in a wider context, which is to destroy all trust in the web. The enshittification of search engines, making social media verification meaningless, locking down APIs that used to be public, destroying public datasets, spreading lies about legacy media, the easiness of deploying bots that can sound human in short bursts of text... it's all leading towards…
Genuine question - how so? If I want to find stuff out I go to wikipedia, nyt, guardian, hn, linked sites and so on. I'm not aware of that lot being noticeably less trustable than in the past? If anything I find getting information more trustable than before in that there are a lot of long from interviews from all sorts of people on youtube where you can get their thoughts directly rather than editorialised and distorted.
I mean the web was never a place where things were vetted - you've always been able to put any sort of rubbish on it and so have had to be selective if you want accuracy.
Earlier quoted context omitted.
It could be argued that the adoption of the automobile was a bad move. You and I debating either its efficacy or social good though is irrelevant if it marches on regardless.
I didn't explain my point there, let me try with the automobile example. There's a key difference in the how the impact of the automobile happened - consumers got to choose to buy them and the impact was driven in large part by market demand. The fact that LLMs are going to have a big impact seems obvious because a comparatively few number of people are making a huge deal out of them, both with attention and money. L…
"The LLMs have no ground truth" claim (around chapter 2) that's core to the "bullshit machines" argument is itself wrong. Of course LLMs have ground truth. What do the authors think here, that the text in training corpus is random ? Hint: it isn't. Real conversations are anything but random. There's a lot of information hidden in "statistical ordering of the words", because the distribution is not arbitrary . Statist…
Statistical truths based on observation of reality is the basis for science. Statistical truth based on the text on the internet is the basis for something else, and I would personally not like to call whatever that is science, or any truths established this way "ground truths".
There's few things in our lives any of us actually learned first-hand, empirically. Everything else we learned the same way LLMs did - as what is expected to be the right completion to a question or inquiry.
The objective truth as we experience is things that, were we to make a prediction conditioned on them, our prediction would turn out correct. That doesn't mean we actually make such predictions often, or that we ever made such predictions learning it.