I Don't Want to Interact with Stochastic Parrots
ploum.net
ploum.net
I still don't understand given the advancement in those models (both closed and open source) one could have such a reductionist view on them. And my only guess is that they derive the feeling of importance through the act of rebellion. Almost like a teenage rebelling against others.
But it doesn't take much to see this tech is here to stay.
Hating AI is the norm right now..all those college students, almost everyone in my circle hates AI..the real courage is to speak the truth and try to be objective..
This is unfair to drug users and perverts
How is this post breaking any guidelines? How does a reasoned essay about LLM use not belong on HN?
Something is rotten in the state of Denmark.
I could find 10 anti-AI posts on HN and they all will contain points from a very narrow pool of anti-AI takes. I mean, how many more times do you need to repeat them?
> stochastic algorithms trained to produce tons of "average," non-human content
As we can see, humans are also quite capable of producing "average" content. And by "average" I don't mean "average quality", I mean "average opinion of a certain group".
Exactly! It's not as if humans are special (though LLM's certainly are). Humans, they've been the same for thousands of years, same old stories (there's like only 7 archetypal stories they've ever come up with). Same old poems, love this, romance that blah blah blah!
We certainly don't need yet another anti-AI article, same as all the others. Though as it's written entirely by a human who must have thought about every word, certainly poles apart from an LLM generated article one, I'll give him credit for making the effort.
It was also deeply uneconomic, and didn't change the world, or materially advance our understanding. Mostly it's demoralised the mathematicians already working to solve those problems. They're not going to say 'That's great, I can now devote my energies to another problem', they're more likely to look at 10 years of poorly paid intellectually rigorous work and go home and kick the dog. For a headline.
I think here it's meant to imply that LLMs will be forced on the population at large as a form of social control.
If it makes the author happier they can ask dang what is the prompt used for automated HN processing.
This is HN's newest guideline / rule, seems the opposite to me. Does it still happen, yes, is it as bad as 6 months ago, no.
I still don't see it as data point we can differentiate human-ness on.
This is, ironically, similar to my mom's anti-mental-healthcare argument that the system producing a good outcome is not evidence that the process is correct.
It's everyone's choice what stances they take, and if being utterly opposed to any kind of AI interaction is their's, that's their choice, but just own that choice without resorting to absurdity to attempt to lend it a false sense of credibility.
LLMs don't produce working code through mere hallucinatory chance, they do it by mathematical approximation, which is no more or less valid than pasting together programs from stack overflow answers.
Idgaf if the person who coded a program had intention when writing a line of code I never see because it's a compiled binary blob, I care that the program works. And frankly, pretending otherwise is pretentious BS.
And in any case, if the code you had experience with (and produced?) before AIs was stack overflow answers pasted together, it's not surprising that you don't see any worsening.
Btw, if your idea of LLMs is of something doing "mathematical approximation", you have some reading to do; and I won't say what I consider pretentious BS.
I believe that 2 programs that execute the same are of equal value, no matter the intentions of the person writing the code (or lack thereof). If you read the article, you'd probably know what I was referring to:
> But at least we know that each line, as bad as it can be, was added by a human for a reason.
That's what immediately preceded the bit I quoted, and the entire point of my critique is that this author is treating human intention in coding as intrinsically valuable.
And rather than snark, I'd love if you actually explained why me calling LLMs "mathematical approximations" of their training data is inaccurate? They're literally weighted vector graphs of their training data.
[1] In IBM there's a religion in software that says you have to count K-LOCs, and a K-LOC is a thousand line of code. How big a project is it? Oh, it's sort of a 10K-LOC project. This is a 20K-LOCer. And this is 5OK-LOCs. And IBM wanted to sort of make it the religion about how we got paid. How much money we made off OS 2, how much they did. How many K-LOCs did you do? And we kept trying to convince them - hey, if we have - a developer's got a good idea and he can get something done in 4K-LOCs instead of 20K-LOCs, should we make less money? Because he's made something smaller and faster, less KLOC. K-LOCs, K-LOCs, that's the methodology. Ugh anyway, that always makes my back just crinkle up at the thought of the whole thing.
FWIIW, I don't think I was anthropomorphizing. Stretching an analogy, yes. Optimization pressure is producing something with at least characteristics of intelligence. Obviously in a very different way than evolution produced the human brain, but the similarities are there.
So, examples of "Look, it did this!" mean nothing to me. What matters is their internal systems.
So it absolutely has experiential knowledge of words but not of the actual things.
(You can absolutely train models on other inputs. I have no objections to those not being stochastic parrots)
But if your claim is at least that you are fine with thinking AI's that also include physical training are not stochastic parrots, then thats good enough for me.
And never mind that the whole premise of this article is simply wrong. Look at the things GenAI systems are doing today and it's clear that they are more than just "parrots" stochastic or otherwise. Not even looking at the Navier-Stokes thing, but there are Youtube videos out there of PhD candidates in math who have tried out various models from a "can this help me with research level mathematics?" perspective multiple times, and quite often the answer is at least a qualified "yes". Does it really make sense to say that a stochastic approximation of "very average" content can be helpful in doing research level mathematics? I'm thinking "no".
My own anecdotal experience also suggests that whatever LLM's do, it amounts to more than being a mere parrot. ChatGPT was incredibly helpful to me over the weekend, for example, getting started on some neuromorphic computing stuff I wanted to do. It was amazingly helpful at debugging circuit problems, helping me setup some LXI/SCPI automation of my test equipment, doing literature reviews, yadda, yadda, yadda. Even better, unlike most human interlocutors I might want to interact with, it is fine with my weird "night owl" hours, happily debugging circuits at 2:00am, 3:00am, and on into the early morning hours. It never gets tired, never belittles me, tolerates my repeated questions, etc.
I get that some people are "anti-AI" for their own reasons, but I hope some of those people will at least stop and try to understand why some of us think modern GenAI systems are about the best thing since sliced bread. shrug
[1] https://news.ycombinator.com/newsguidelines.html
[2] https://news.ycombinator.com/item?id=49605192 (currently at -1 but went as as low as -7)
You go on other sites like Reddit and posit a question. Someone will inevitably reply "So I asked $insert_AI_bot and it said"
It's like second hand smoke. Those of us who don't want to smoke are still subjected to the externalities of the people who want to smoke in public
I understand the qualities of LLM's but I do fear that we might lose much which once lost may be gone forever. That gives me pause for thought.
I have a SKILL that emulates how my supervisor prefers his answers and papers, he used to get triggered by generated stuff, but now it just writes in a style he likes which I got from a bunch of his papers and everything goes smoother. If you are bottlenecking someone they will just do the same to you.
Here's an AI-generated pull request I made, but you wouldn't know because there's no slop:
https://github.com/numtide/devshell/commit/a67c0f87b63bcbdbd...
It got merged by someone who is too busy to respond to personal emails.
"Don't waste my precious attention" is only getting more real.
So your direct superior asked you not to do something and you still worked your way around his preference while feeling cool about of it? Just to save the time of typing?
The only result is that we both have more time. If he didn't like slop, he would catch the new writing as well and I would have to make an effort there, but clearly he is just molded by bias.
Its like people who claim branded stuff is better when it's the same, or that expensive wine/coffee is better when it's about how you serve it. Cognitive bias and stubbornness.