And honestly you can be better at writing prompts and be proud of that too, but given that AI is built entirely on using other people’s work, you’re not allowed to be upset about people using it. Don’t post them publicly if you really care.
Back before enshitification, when could use extra criteria to reliably filter and refine the search, and could go dozens of pages deep into search results. Back before it got nerfed and censored.
Now have to wrestle a dozen different websearch engines.
There used to be a strategy to it. Simply googling several specific and relevant keywords would get you incredibly good results. Nowadays, you're honestly better off typing out a whole question and hoping the bullshit Ai answer has good sources you can click on.
I have had in person conversations with multiple people who swear they have fixed the AI hallucination problem the same way. "I always include the words 'make sure all of the response is correct and factual without hallucinating'"
These people think they are geniuses thanks to just telling the AI not to mess up.
Thanks to being in person with a rather significant running context, I know they are being dead serious, and no one will dissuade them from thinking their "one weird trick" works.
All the funnier when, inevitably, they get screwed up response one day and feel all betrayed because they explicitly told it not to screw up...
But yes, people take "prompt engineering" very seriously. I have seen people proudly display their massively verbose prompt that often looked like way more work than to just do the things themselves without LLM. They really think it's a very sophisticated and hard to acquire skill...
"Do not hallucinate", lol... The best way to get a model to not hallucinate is to include the factual data in the prompt. But for that, you have to know the data in question...
It's incredible by now how many LLM users don't know that it merely predicts the next most probable words. It doesn't know anything. It doesn't know that it's hallucinating, or even what it is saying at all.
One things that is enlightening is why the seahorse LLM confusion happens.
The model has one thing to predict, can it produce a spexified emoji, yes or no? Well some reddit thread swore there was a seahorse emoji (along others) so it decided "yes", and then easily predicted the next words to be "here it is:" At that point and not an instant before, it actually tries to generate the indicated emoji, and here, and only here it falls to find something of sufficient confidence, but the preceding words demand an emoji so it generates the wrong emoji. Then knowing the previous token wasn't a match, it generates a sequence of words to try again and again...
It has no idea what it is building to, it is building results the very next token at a time. Which is wild how well that works, but lands frequently in territory where previously generated tokens back itself into a corner and the best fit for subsequent tokens is garbage.
I didn’t think prompt engineering was a skill until I read some of the absolute garbage some of my ostensibly degree-qualified colleagues were writing.
Reminds me of the very early days of the web, where you had people with the title "webmaster". When you looked deeper into the supposed skillset, it was people that knew a bare minimum of HTML and the ability to manage a tree of files?
I'll never forget being at an ATM and overhearing a conversation between two women in their 30s behind me - the one woman tells the other - "I've been thinking about what I want to do and I think I want to be a webmaster". It just sounded like a very casual choice and one about making money, and not much deeper than that.
This was in 1999 or so. I thought - man, this industry is so fucked right now - we have hiring managers, recruiters, etc...that have almost no idea of the difference in skillsets between what I do (programming, architecture, networking, database, and then trying to QA all of that and keep it running in production, etc.) and people calling themselves "webmasters".
Sure enough, not long after, the dotcom bubble popped. It was painful for everyone (even people that kept their distance from the dotcom thing to an extent) without question, whether you had skills or no. But I don't think roles like "webmaster" did very well...
No not at all, I have no other insight. It's just, the author is leaning on the idea of intellectual property so evidently, when it also happens to be the most illegitimate thing about AI. I think it's too obvious to be real.
Someone else commented the account is indeed satirical
I'm pretty sure this is real, this account is dedicated to AI slop and frequently does something called a "prompt share" where they share phraes to get what you want from AI image generators.
This instance is but the belief is absolutely real and I bet we see people think they should be able to copyright a prompt for being so creative and amazing
But I had already downloaded all existing writing that has ever been done in the Greek language, to train my own for profit LLM, thus I am a legitimate businessman, not a pirate, and it is actually Zuck who is violating my IP!
Is there something like "r/SelfAwareWolves" on Lemmy? "Creating your own prompts is actually easier than copying someone else's work!" so close yet so far from self awareness...
Based on my own in person experience with some LLM fanatics, I think this is quite probable. I've heard very sincere feedback from people that think they are amazing because they have "advanced prompt engineering" skills. They think "prompt engineer" will be a very selective job in and of itself and think they have an edge. They think they will be able to work on any field because the LLM will take care of domain specific stuff and their "rare mastery" of prompts will be the hot skill.
I hate the title creep of adding engineering to fucking every title [*] - and it's not all that new, but "prompt engineering" is really far up there in the hubris of calling that "engineering". There might not be anything overseeing the other title inflation I mention below - no real certification process or governance at all, basically - but at least in most cases, these people had to really work at what they do and learn quite a lot. I bet most people can call themselves a "prompt engineer" after sitting through a few videos on Youtube or Udemy, LOL.
[*] No one is a tester any more, oh, no, they work in "quality engineering". Not even the title QA is grandiose enough. Same for programming - people aren't just coders or programmers, oh no, they are software ENGINEERS. Same for working in operations or sysadmin, no one has that title, it's site reliability ENGINEERING.
I assure you that REAL engineers that actually have the degrees and had to take exams like EIT and then work years under a real engineer to get their PE as a real engineer get a bit salty about all this title inflation. They did all this work and are suddenly neck-deep in "engineers" that are anything but. I get why they get annoyed, believe me. Someone teaches themselves something in the latest Javascript framework and a few weeks later is calling themselves a software engineer, LOL.
LLM "creators" just really make me laugh. They aren't "creators". They're just less competent than usual art directors. Because that's what an LLM "creator" really is: an art director. A person telling someone/something else to make something to a specification.
Is one art director taking the statement "yes, just like that, but with bigger tits" and using it when instructing his own artists plagiarizing in any sense that leaves the word plagiarism with meaning? If yes, well, then, "plagiarism" has joined the term "fascist" or "commie" or any other such political epithet in meaning absolutely nothing. It has become literally as useless a word as "literally". Of no, well, then, prompt "theft" isn't a thing.
Exactly. At best you're commissioning work to a machine. You didn't provide much creativity, at best a direction and some constraints.
In the art world it's been settled ages ago that the underlying concept isn't protected, and few if any prompts go beyond just describing a vague concept.
It's worse than your typical creative claim on copyright of something like a poem - because prompts are by definition functional more than creative, and typically contain too few purely expressive elements to meet creative height. They managed to put prompts in a worse position than boilerplate code in terms of protection, lol
The literal firat thing I did with my lightweight local LLM was describe specified scenarios to it and ask it to generate a prompt for itself that would make that 'profile' of it always have that context.
Can you explain that a little more in depth. I’ve been experimenting with local LLM and am curious what type of scenarios you’re talking about and how this affected your LLM output.
Ok, for starters, I'm using Alpaca, a flatpak than acts as a kind of simplified, containerized way of managing local LLMs, it has a few basic tools you can use with LLMs, manages downloading them, and then you can make profiles based off of the model you've dl'ed, with specific context prompts, tweak a few settings for them.
So far I am most fond of the Qwen3 model, but, ymmv.
::: spoiler more explanation encapsulated herein
Uh lets see, for things like getting up to date with a particular coding language's modern syntax revisions or updates to a particular library, something like that.
Feed them some webpages of the documentation, ask them to read them, or ask them to do some of their own self directed searching to find changes, then say hey, now please generate a contextual prompt for yourself that would summarize and inform you of key points/changes.
There are a decent number of fairly powerful, fairly lightweight models, but, they tend to be some months or a year or w/e out of date in their training data, so doing this acts as a kind of 'update' for them.
You can also do this with... some set of fairly niche topics that their lightweight model just isn't that accurate about, for maybe the purpose of... maybe brainstorming worldbuilding scenarios, giving it more recent scientific/news updates, or even asking it to try to roleplay as some specific fictional or real character.
Though I've not really tried the latter scenario beyond once as basically a gimmick.
Its not like, guaranteed to make them super intelligent experts, its more like... going through a crash course and giving them a bit of a more accurate generao overview.
Any situation where they ... keep making specific, minor, fairly simple mistakes... this kind of thing can be decent at at least triaging.
I've mostly been trying to craft a coding assistant out of this, and I've had pretty decent success at getting it to 'learn' sets of syntax updates, deprecated methods that now have very close equivalent replacements.
Another thing you can do with this kind of thing is... the adversarial approach. Give two different models the same intial set of 'hey here are some things i want you to know, now generate a prompt for yourself'. Then take the generated prompt, give it in conversation to the other LLM, ask it to evaluate it and compare it to the prompt it generated, etc.
The general downside to this is that with a lightweight model, on low power hardware, the longer/more complex the intial prompt they have is, well, i guess its kind of comparable to a game having to compile shaders before a first run... you can end up in situations where you've just given them so much 'context' that it just exceeds your local HW compute power to be able to... evaluate the prompt and then generate a first actual conversstional response.
I keep it 'docked', powered up, when running an LLM on it... but yeah... anybody can do this.
Its really not that hard, you do not need a battle station.
A battle station would obviously help with more complex tasks.
But its uh ... not necessary.
I imagine the GabeCube would be even better at this.
At one point I sat down and worked out the math, and yeah, I could get a solar power station thingy, and... just actually be able to run the whole setup off of sunlight.
Its not instantaneous, it takes some time to generate complex answers/responses, but it does work.
So... yeah, I functionally could have a local LLM that is mostly kinda portable, if you carried a battery pack / dock on your person in a backpack with the Deck, or in your car, maybe along with said solar power station.
Well I recently gave it a... roughly 600 line script of GDScript from a Godot project thats roughly a yearish old... and asked it to evaluate it, and then refactor it, in line with 4.6 syntax and methods, and... in total, the actual refactoring took between 5 to 10 minutes, roughly.
Its... much faster with smaller snippets or chunks.
How fast is this compared to big players?
Well... with small snippets, an online free to use LLM of some kind is much faster.
But... they generally don't have ways that you can actually do the whole custom prompt thing that I described, not for free, infinite use. So you have to keep telling them about the same silly errors they'll make.
They're useful in generating the actual prompt for your local LLM, as they're ... you know, online, and can usually rapidly pull up relevant pages that go over API, syntax, method, feature changes, then reformulate all of them into a prompt-like format.
But... while free online LLMs may be faster... they tend to have hard limits on max tokens per day and/or on the size of input you can give them at once.
So... with that 600 line script, I would have had to feed chunks of that to it, then ask it to evaluate all of it, after first giving it the whole prompt of 'these are all the relevant syntax mistakes you are going to make if i dont tell you about them first'.
So in that kind of scenario, I'd say what I am doing with the local LLM is just actually net faster, more accurate/consistent, and requires less babying/manual input from me.
Oh and I don't have to pay anyone to keep using the premium version of my entirely local LLM.
And, other than Ecosia's LLM... the data center based big boys don't tend to be capable of running off of renewable energy, though I've no actual idea if Ecosia's actually make good on that claim.
"make your own prompts" misses by one step. Use of AI robs you of the opportunity to learn/practice/hone your skills in a certain area. why would someone use ai for any reason other than to get out of having to learn something? do you expect llms to be the best source of how to learn [blank]? which [youtuber/podcaster/old bridgetroll/televangelist/fascist/fishnet chat lightbulb] would you suggest explains [blank] better because frankly at this point i'm fucking invested.
Use of AI robs you of the opportunity to learn/practice/hone your skills in a certain area. why would someone use ai for any reason other than to get out of having to learn something?
This is not really a good argument against AI. Almost everything ever invented was invented to avoid doing something else that would take more time.
Why would anyone use animation software other than to avoid learning to draw your frames in sequence?
Why would anyone use a loom other than to avoid having to learn how to weave?
Why would anyone read a book other than to avoid learning by experience and experimentation?
Look, I don't want to be in a position of defending the plagiarism machines that are burning the world's forests whilst simultaneously somehow using all of the world's fresh water, but come on. The vast majority of people who are using AI image generation are not people who would otherwise have been involved in the creative process.
They are people who want to avoid learning Photoshop (reasonable - it takes a long time to learn, which may or may not be worth it given what you want to do, and also Adobe sucks shit) or want to avoid paying someone who knows how to use Photoshop (understandable - and would obviously be worth consideration if it weren't for all of the other problems with AI).
When you attack AI on the basis of it making people lazy - rather than any of the other things that are wrong with it - it just comes across as "Luddite". (Which is ironic, given that Luddism was originally about machinery resulting in worse working conditions for skilled workers, which is one thing AI actually will do.)
I’m a senior full-stack developer of 15 years, and more recently, a new tech lead at an AI startup. I’m definitely not attacking AI as a concept in general.
I work with AI agents every day and all day. That’s how I develop and plan our systems. It did not start that way. I was absolutely against the use of AI during development, but a few months back, I need the assistance because I developed carpal tunnel syndrome, so that’s what I automated, just the typing and the implementation of low-level logic so that my wrists can heal. But do you know what stock AI agents do to code when not given proper guidance? Ask any real developer and they’ll tell you about vibe coding. I guarantee these are not going to be success stories.
I’m not just judging people for being lazy, because lazy people like me will innovate ways to stay lazy by inventing/optimising new shit that allows them to stay lazy. That’s a survival instinct and an evolutionary selection mechanism: minimising energy investiture while doing the same thing as everyone around you is an evolutionary advantage.
No. What I’m judging them for is delegating their critical thinking capacity to an external entity, and stunting their own cognitive growth (their literal reason for existing in the first place, their continuity mechanism to stay in the gene pool, and their sole means of improving at being long-term lazy) by being short-term lazy. Makes sense?
Now to generative AI (for the multimedia substrate):
The vast majority of people you speak of are now polluting the collective “training set” with diluted slop distilled from all art historically created thus far, because the content generation equation went from: X people creating Y novel pieces of art per year, to X models creating Y million images per day, all thanks to a handful of idiots with more greed/money than common-sense. That diluted pool is ever-expanding, growing geometrically, and burying actual novelty with each new image Susan generates and shares for her new “Katz Rule” instagram profile.
The thing is: the next model will be trained on that averaged set, and the next, and the next. With each day and each generation increasing in conformity. And that set is what we’re stuck with for new inspiration (and future models) now. Because everyone is looking at screens for inspiration, and not at mountains or rivers, or even the real stars in the sky at night because we ruined that too.
All while we’re doing the things you just mentioned.
All thanks to a few assholes with more selfishness than common-sense chasing after unlimited quarterly growth in a very limited space that’s closing around us fast.
I’m a senior full-stack developer of 15 years, and more recently, a new tech lead (specifically a Systems Architect) at an AI startup. I’m definitely not attacking AI as a concept in general.
I, too, am a developer of closer to 15 years than I'd like to admit to myself, though mostly embedded and/or back-end. And while I have no problem with AI in its broad sense (obviously machine learning/spicy statistics, computer vision, and natural language processing and whatnot have potential to be enormously useful), I am generally hostile to generative AI. I thinking using copyrighted material as training data without the copyright holders' permission should be banned. And while I would have no objection to ethically-trained models in a hypothetical future where we have abundant clean energy to run the data centres and also all the new desalination plants we would need, that also remains a problem, and so I have resisted using such tools at work, too.
Now to generative AI (for the multimedia substrate)...
I agree with everything you've said after this point.
No. What I’m judging them for is delegating their critical thinking capacity to an external entity, and stunting their own cognitive growth (their literal reason for existing in the first place, their continuity mechanism to stay in the gene pool, and their sole means of improving at being long-term lazy) by being short-term lazy. Makes sense?
This is the crux of my problem. I find it to be overly judgemental. If you're self-employed and you need a website for your business or whatever, then you could pay someone to do it for you, but then you only have so much money in the budget. You could also learn how to code and/or graphic design and do it yourself, but then you only have so many hours in the day. If vibe coding produced something viable for you in the quickest, cheapest way, then that is obviously the rational and sensible thing to do. You might even spend the time learning something else instead that is more relevant to your interests.
Using generative AI to do something doesn't (necessarily) mean that you don't value the knowledge or skills required to do it the hard way, it only means that you value it less than something else that you might otherwise be doing with your time, and I don't think that is a moral failing.
As an example, I occasionally like to a bit of shitposting. Were it not for all those other things that I don't like about generative AI, I would probably be generating AI slop memes with the best of the them. As it is I mostly just stick to text-based comments with bad puns and references to song lyrics no-one will remember. I could put in the hours to learn how to use GIMP so I could do it without AI, but quite frankly I have books on the go, I've got a couple of musical instruments to learn/practise, and I spent all day at my software job, where I think critically (or so I claim), so I'd rather being doing those things instead. I don't think I have neglected my cognitive growth; I've just chosen to focus it on something different to what you might have.
Ohhh. I think we’re both defending different hills! I’m not against the use of generative AI for purposeful creation. What I’m against is the delegation of critical thinking.
It’s the difference between:
“Implement this specific feature this specific way. Never disable type checking or relax type strictness, never solve a problem using trial and error, consult documentation first, don’t make assumptions and stop and ask for guidance if you’re unsure about anything”
“Paint me a photorealistic depiction of a galaxy spinning around the wick of a candle”
(That last one is admittedly my own guilty contribution to the slop soup and favourite desktop background of at least a whole year)
Versus:
“build me an e-shop”
“draw me a cat”.
The difference is oversight and vision. The first two are asking AI to execute well-defined tasks with explicit parameters and rules, the first example in particular offers the LLM an out if it finds itself at an impasse.
The latter examples are asking a prediction engine to predict a vague concept. Don’t expect originality/innovation from something that was forcibly constrained to pick from a soup made of prior art then locked down, because that’s what gradient descent essentially does to the neural networks during training: reduce the error margin by restricting the possible solutions for any given problem to only what is possible within the training set, which is also known as plagiarism.
Edit: a slight elaboration on the last part:
Neural networks trained with gradient descent will do the absolute minimum to reach a solution. That’s the nature of the training process.
What this essentially means is that effort scales with prompt complexity! A simple/basic prompt begets you the most generic result possible. Because it allows the network to slide along the shortest path from the input token to a very predictable result.
Right, because you don't believe art has value or requires thinking. It's essentially worthless to you.
What people with a critical eye for art can tell you is that the art also has well-defined tasks with explicit perimeters and rules, and generative AI produces uncreative slop that looks amateurish if you have an eye for art. It's pretty typical for people to believe generative AI is better at tasks that they, personally, know nothing about - it's a Dunning-Kruger machine.
LLMs are a pretty good tool to summarize any subject, or present it with different words or in a different approach... They are a statistical word predictor tool after all.
So yeah, if you understand that LLMs:
don't possess intelligence;
they are just reproducing patterns from the training material used;
it's impossible for them to contain ALL "knowledge" from the training material;
the "context" provided directly influences the response
Then, I'd say that LLMs can be used as a very good facilitator to learn about almost any subject that has already been documented in any word format in almost any language.
It feels like as the models were iterated on they got worse at it over time. I wonder if it's because of all the guard-railing and internal censorship etc.
It's just a messy process, it's purely based on probability, I don't think it'll ever get good, people were just being lied to. Don't forget that they relied on "confirmatory bias" and "selection bias" from the users as well.
I have never used a LLM to write any of my comments on the internet, neither here nor in any social network I have an account.
And about the bullet points, in places that accept MarkDown similar syntax I tend to use bullet points because it's a feature that helps lay out the ideas in a good formatting for the reader when there's enumerations, lists, or similar things involved.
But yeah, you will never find comments of mine in, lets say, Instagram, with bullet points, because the editor of the app there sucks, you would have to type your comment in a external app which creates the bullet points characters already in a newline (you cannot even normally break lines in Instagram comments lol, it's really unsanitary haha), and I ain't gonna do that.
I read about that... then I saw something a few months later that said that the role was already obsolete because the "skills" prompt engineers were learning had just been incorporated into newer models.
"No one else Google things the same way as me."
I used to unironically be low-key proud of my googling skills. Before google got so crummy, at least.
And honestly you can be better at writing prompts and be proud of that too, but given that AI is built entirely on using other people’s work, you’re not allowed to be upset about people using it. Don’t post them publicly if you really care.
“You can’t add ‘site:reddit.com’, that’s MY googling trick!”
I press enter after each command I want to issue. I did it back in the 90s and now everybody does it.
Fond of google 2000-2005 (ish).
Back before enshitification, when could use extra criteria to reliably filter and refine the search, and could go dozens of pages deep into search results. Back before it got nerfed and censored.
Now have to wrestle a dozen different websearch engines.
Yeah who thought it was a good idea to remove the "-" to exclude things? I'm looking for a painters pallet not a fucking transport pallet you morons.
/Rant off 😁
There used to be a strategy to it. Simply googling several specific and relevant keywords would get you incredibly good results. Nowadays, you're honestly better off typing out a whole question and hoping the bullshit Ai answer has good sources you can click on.
I thing that's wrong
People thinking they're AI experts because of prompts is like claiming to be an aircraft engineer because you booked a ticket.
I have had in person conversations with multiple people who swear they have fixed the AI hallucination problem the same way. "I always include the words 'make sure all of the response is correct and factual without hallucinating'"
These people think they are geniuses thanks to just telling the AI not to mess up.
Thanks to being in person with a rather significant running context, I know they are being dead serious, and no one will dissuade them from thinking their "one weird trick" works.
All the funnier when, inevitably, they get screwed up response one day and feel all betrayed because they explicitly told it not to screw up...
But yes, people take "prompt engineering" very seriously. I have seen people proudly display their massively verbose prompt that often looked like way more work than to just do the things themselves without LLM. They really think it's a very sophisticated and hard to acquire skill...
"Do not hallucinate", lol... The best way to get a model to not hallucinate is to include the factual data in the prompt. But for that, you have to know the data in question...
"ChatGPT, please do not lie to me."
"I'm sorry Dave, I'm afraid I can't do that."
That's incorrect because in order to lie, one must know that they're not saying the truth.
LLMs don't lie, they bullshit.
It's incredible by now how many LLM users don't know that it merely predicts the next most probable words. It doesn't know anything. It doesn't know that it's hallucinating, or even what it is saying at all.
One things that is enlightening is why the seahorse LLM confusion happens.
The model has one thing to predict, can it produce a spexified emoji, yes or no? Well some reddit thread swore there was a seahorse emoji (along others) so it decided "yes", and then easily predicted the next words to be "here it is:" At that point and not an instant before, it actually tries to generate the indicated emoji, and here, and only here it falls to find something of sufficient confidence, but the preceding words demand an emoji so it generates the wrong emoji. Then knowing the previous token wasn't a match, it generates a sequence of words to try again and again...
It has no idea what it is building to, it is building results the very next token at a time. Which is wild how well that works, but lands frequently in territory where previously generated tokens back itself into a corner and the best fit for subsequent tokens is garbage.
Fabulating even!
Have you tried to not be depressed?
I didn’t think prompt engineering was a skill until I read some of the absolute garbage some of my ostensibly degree-qualified colleagues were writing.
Reminds me of the very early days of the web, where you had people with the title "webmaster". When you looked deeper into the supposed skillset, it was people that knew a bare minimum of HTML and the ability to manage a tree of files?
I'll never forget being at an ATM and overhearing a conversation between two women in their 30s behind me - the one woman tells the other - "I've been thinking about what I want to do and I think I want to be a webmaster". It just sounded like a very casual choice and one about making money, and not much deeper than that.
This was in 1999 or so. I thought - man, this industry is so fucked right now - we have hiring managers, recruiters, etc...that have almost no idea of the difference in skillsets between what I do (programming, architecture, networking, database, and then trying to QA all of that and keep it running in production, etc.) and people calling themselves "webmasters".
Sure enough, not long after, the dotcom bubble popped. It was painful for everyone (even people that kept their distance from the dotcom thing to an extent) without question, whether you had skills or no. But I don't think roles like "webmaster" did very well...
this is 100% satire
This does not read like satire at all to me. Is there some other indicator you're privy to?
No not at all, I have no other insight. It's just, the author is leaning on the idea of intellectual property so evidently, when it also happens to be the most illegitimate thing about AI. I think it's too obvious to be real.
Someone else commented the account is indeed satirical
Just google azed_ai and look at her accounts for yourself. 100% not satire.
Hmm, maybe just bad satire then.
I'm pretty sure this is real, this account is dedicated to AI slop and frequently does something called a "prompt share" where they share phraes to get what you want from AI image generators.
if it is real, it's a new low
Just wait until tomorrow.
I love that we're still digging !
Can you give an example of a "high" we've had in general?
1960s France ?
You do realize that during that time France still had colonies, right?
you do realize France still has colonies right now ?
Okay, so, where's the supposed "high" then?
Satire died sometime in 2016.
yes, I remember may 11th
May 28th, the day of our fallen savior.
Not according to her social media profile it isn't.
picard, his face palmed.
This instance is but the belief is absolutely real and I bet we see people think they should be able to copyright a prompt for being so creative and amazing
I've seen people in the image generation circles talk about creating "Prompt marketplaces" so yeah I'm not so sure anymore
There's people on Youtube who teach you how to take a video's transcript, use it to generate an AI video and upload it to Youtube.
And they're upset people are taking transcripts of their videos, generating AI videos and uploading them.
Just... Just take a minute to contemplate that. It's amazing.
Yep.
I saw a vid not long ago going over some of the drama involved in that, a few specific people.
We've gone past no self awareness into levels of negative self awareness that... are basically just actually breaking the fabric of semantic reality.
... Its another good day to be an absurdist.
"The only moral plagiarism is my plagiarism."
It's slop all the way down!
A human centipede of slop.
its called vibe vibing ... and if you aren't vibe vibing I don't even want to talk to you about vibe vibe vibing
Meta-vibing is the new meta for achieving the perfect vibe, while vibing out your new metas, all at the same time.
Also: Buffalo buffalo buffalo buffalo buffalo buffalo buffalo buffalo.
Uh, sir, the entire Greek language is now the intellectual property of mark zuckerberg. You owe him a trillion dollars for using that word.
Aha!
But I had already downloaded all existing writing that has ever been done in the Greek language, to train my own for profit LLM, thus I am a legitimate businessman, not a pirate, and it is actually Zuck who is violating my IP!
Tell it to the judge. (I hope you can afford more motorcoaches than mark zuckerberg).
Tell it to the judge. (I hope you can afford more motorcoaches than mark zuckerberg).
Good like catching me I'm behind 7 vibe layers
vibes all the way down
String theory has entered the chat
This is bait. She's trying to lure sloppers into checking her posts. Someone is stealing her prompts? Oh boy, they must be really good then!
Anything to get them clicks.
This has got to be satire. Please tell me it is... Pleaaaase.
My thoughts exactly, but the past few years have* really lowered my expectations of other humans
This reads like NFT bros.
Came to post exactly this.
Is there something like "r/SelfAwareWolves" on Lemmy? "Creating your own prompts is actually easier than copying someone else's work!" so close yet so far from self awareness...
![email protected] seems absolutely tiny, but it's there.
And [upon first look] there's quality stuff there on ![email protected]
Good laughs.
Comparable to ![email protected] (~ & better?)
[email protected] maybe? Not sure if that's exactly what you're looking for...
Not really, self aware wolves is like a leopard eating its own face and not realizing it
Wow ! How could you believe in yourself after writing this
this has to be satire xD
...right? right?? 😭
Everything lately seems like satire, but sadly it's the world we live in.
it's twitter, which encourage engagements. so can be assumed as rage bait
Ragebait. For my sanity it must be.
Based on my own in person experience with some LLM fanatics, I think this is quite probable. I've heard very sincere feedback from people that think they are amazing because they have "advanced prompt engineering" skills. They think "prompt engineer" will be a very selective job in and of itself and think they have an edge. They think they will be able to work on any field because the LLM will take care of domain specific stuff and their "rare mastery" of prompts will be the hot skill.
I hate the title creep of adding engineering to fucking every title [*] - and it's not all that new, but "prompt engineering" is really far up there in the hubris of calling that "engineering". There might not be anything overseeing the other title inflation I mention below - no real certification process or governance at all, basically - but at least in most cases, these people had to really work at what they do and learn quite a lot. I bet most people can call themselves a "prompt engineer" after sitting through a few videos on Youtube or Udemy, LOL.
[*] No one is a tester any more, oh, no, they work in "quality engineering". Not even the title QA is grandiose enough. Same for programming - people aren't just coders or programmers, oh no, they are software ENGINEERS. Same for working in operations or sysadmin, no one has that title, it's site reliability ENGINEERING.
I assure you that REAL engineers that actually have the degrees and had to take exams like EIT and then work years under a real engineer to get their PE as a real engineer get a bit salty about all this title inflation. They did all this work and are suddenly neck-deep in "engineers" that are anything but. I get why they get annoyed, believe me. Someone teaches themselves something in the latest Javascript framework and a few weeks later is calling themselves a software engineer, LOL.
There's no way this is real. Even they can't be that far gone right?
Do not underestimate the power of stupid.
Especially in this era of atrophying cognition by prompting LLMs to do the thinking.
What's next? Getting mad at the grocery store because other people are buying the same things you do?
Am I naive for thinking this is satire? Maybe there's some optimism left in my little heart.
Could be many things, all disingenuous. Rage bait perhaps, or even a feeble attempt at buzz marketing their shit
Oh no, someone is copying the messages I'm posting online!
This is satire, right?
“Amira” is a pretty female sounding name
Does not give you the right to assume their gender.
Didn't the first commenter assume it, and in a far more statistically wrong way?
Is this a thread of bots or something? There's a photo of her in the post.
Yes. All the bots become pretty obvious when you start paying attention.
Me choosing to mention the name and not the photo doesn't make me a clanker.
That being said, she uses the same photo on her 5 picture Instagram account, which also shows an article she wrote that contains the same photo again!
So very likely that she isn't a person, but some GenAI driven sock puppet account.
You're barking up the wrong tree.
was the assumption that I questioned with my comment. I didn't assume anything myself.
Easy solution here: just have AI write your prompts for you!
Integrity from a LLM that steals data from everywhere to build its database.
LLM "creators" just really make me laugh. They aren't "creators". They're just less competent than usual art directors. Because that's what an LLM "creator" really is: an art director. A person telling someone/something else to make something to a specification.
Is one art director taking the statement "yes, just like that, but with bigger tits" and using it when instructing his own artists plagiarizing in any sense that leaves the word plagiarism with meaning? If yes, well, then, "plagiarism" has joined the term "fascist" or "commie" or any other such political epithet in meaning absolutely nothing. It has become literally as useless a word as "literally". Of no, well, then, prompt "theft" isn't a thing.
Exactly. At best you're commissioning work to a machine. You didn't provide much creativity, at best a direction and some constraints.
In the art world it's been settled ages ago that the underlying concept isn't protected, and few if any prompts go beyond just describing a vague concept.
One additional thought and she'll realize that prompts are not work. But I doubt she is capable of doing that.
Yup.
Not capable of doing one additional thought. Not capable of realising.
Thanks to "A.I." atrophying that ability.
Must be satire. If creating something was easier than plagiarizing, there wouldn't be entire industries that revolve around detecting plagiarism.
Also, how do we then explain the amount of piracy that LLM companies do?
Isn't this a bit counterintuitive considering the nature of AI 😑
"Stop using everyone's words in the order everyone uses them; they are my words, and they are my order".
It's worse than your typical creative claim on copyright of something like a poem - because prompts are by definition functional more than creative, and typically contain too few purely expressive elements to meet creative height. They managed to put prompts in a worse position than boilerplate code in terms of protection, lol
The literal firat thing I did with my lightweight local LLM was describe specified scenarios to it and ask it to generate a prompt for itself that would make that 'profile' of it always have that context.
Can you explain that a little more in depth. I’ve been experimenting with local LLM and am curious what type of scenarios you’re talking about and how this affected your LLM output.
Ok, for starters, I'm using Alpaca, a flatpak than acts as a kind of simplified, containerized way of managing local LLMs, it has a few basic tools you can use with LLMs, manages downloading them, and then you can make profiles based off of the model you've dl'ed, with specific context prompts, tweak a few settings for them.
So far I am most fond of the Qwen3 model, but, ymmv.
::: spoiler more explanation encapsulated herein
Uh lets see, for things like getting up to date with a particular coding language's modern syntax revisions or updates to a particular library, something like that.
Feed them some webpages of the documentation, ask them to read them, or ask them to do some of their own self directed searching to find changes, then say hey, now please generate a contextual prompt for yourself that would summarize and inform you of key points/changes.
There are a decent number of fairly powerful, fairly lightweight models, but, they tend to be some months or a year or w/e out of date in their training data, so doing this acts as a kind of 'update' for them.
You can also do this with... some set of fairly niche topics that their lightweight model just isn't that accurate about, for maybe the purpose of... maybe brainstorming worldbuilding scenarios, giving it more recent scientific/news updates, or even asking it to try to roleplay as some specific fictional or real character.
Though I've not really tried the latter scenario beyond once as basically a gimmick.
Its not like, guaranteed to make them super intelligent experts, its more like... going through a crash course and giving them a bit of a more accurate generao overview.
Any situation where they ... keep making specific, minor, fairly simple mistakes... this kind of thing can be decent at at least triaging.
I've mostly been trying to craft a coding assistant out of this, and I've had pretty decent success at getting it to 'learn' sets of syntax updates, deprecated methods that now have very close equivalent replacements.
Another thing you can do with this kind of thing is... the adversarial approach. Give two different models the same intial set of 'hey here are some things i want you to know, now generate a prompt for yourself'. Then take the generated prompt, give it in conversation to the other LLM, ask it to evaluate it and compare it to the prompt it generated, etc.
The general downside to this is that with a lightweight model, on low power hardware, the longer/more complex the intial prompt they have is, well, i guess its kind of comparable to a game having to compile shaders before a first run... you can end up in situations where you've just given them so much 'context' that it just exceeds your local HW compute power to be able to... evaluate the prompt and then generate a first actual conversstional response.
:::
Hah!
I am doing this on a Steam Deck, running Bazzite.
I keep it 'docked', powered up, when running an LLM on it... but yeah... anybody can do this.
Its really not that hard, you do not need a battle station.
A battle station would obviously help with more complex tasks.
But its uh ... not necessary.
I imagine the GabeCube would be even better at this.
At one point I sat down and worked out the math, and yeah, I could get a solar power station thingy, and... just actually be able to run the whole setup off of sunlight.
Its not instantaneous, it takes some time to generate complex answers/responses, but it does work.
So... yeah, I functionally could have a local LLM that is mostly kinda portable, if you carried a battery pack / dock on your person in a backpack with the Deck, or in your car, maybe along with said solar power station.
Well I recently gave it a... roughly 600 line script of GDScript from a Godot project thats roughly a yearish old... and asked it to evaluate it, and then refactor it, in line with 4.6 syntax and methods, and... in total, the actual refactoring took between 5 to 10 minutes, roughly.
Its... much faster with smaller snippets or chunks.
How fast is this compared to big players?
Well... with small snippets, an online free to use LLM of some kind is much faster.
But... they generally don't have ways that you can actually do the whole custom prompt thing that I described, not for free, infinite use. So you have to keep telling them about the same silly errors they'll make.
They're useful in generating the actual prompt for your local LLM, as they're ... you know, online, and can usually rapidly pull up relevant pages that go over API, syntax, method, feature changes, then reformulate all of them into a prompt-like format.
But... while free online LLMs may be faster... they tend to have hard limits on max tokens per day and/or on the size of input you can give them at once.
So... with that 600 line script, I would have had to feed chunks of that to it, then ask it to evaluate all of it, after first giving it the whole prompt of 'these are all the relevant syntax mistakes you are going to make if i dont tell you about them first'.
So in that kind of scenario, I'd say what I am doing with the local LLM is just actually net faster, more accurate/consistent, and requires less babying/manual input from me.
Oh and I don't have to pay anyone to keep using the premium version of my entirely local LLM.
And, other than Ecosia's LLM... the data center based big boys don't tend to be capable of running off of renewable energy, though I've no actual idea if Ecosia's actually make good on that claim.
"make your own prompts" misses by one step. Use of AI robs you of the opportunity to learn/practice/hone your skills in a certain area. why would someone use ai for any reason other than to get out of having to learn something? do you expect llms to be the best source of how to learn [blank]? which [youtuber/podcaster/old bridgetroll/televangelist/fascist/fishnet chat lightbulb] would you suggest explains [blank] better because frankly at this point i'm fucking invested.
oh no.
rtfm being replaced by wyop.
::: spoiler wyop
write your own prompt
This is not really a good argument against AI. Almost everything ever invented was invented to avoid doing something else that would take more time.
Why would anyone use animation software other than to avoid learning to draw your frames in sequence?
Why would anyone use a loom other than to avoid having to learn how to weave?
Why would anyone read a book other than to avoid learning by experience and experimentation?
But...
If you know how to draw frames in sequence, you'll be better at using the animation software.
If you know the intricacies of weaving, you'll be more efficient with the loom.
And it follows that if you know how to code, then you would be more efficient with GitHub copilot, yes?
Look, I don't want to be in a position of defending the plagiarism machines that are burning the world's forests whilst simultaneously somehow using all of the world's fresh water, but come on. The vast majority of people who are using AI image generation are not people who would otherwise have been involved in the creative process.
They are people who want to avoid learning Photoshop (reasonable - it takes a long time to learn, which may or may not be worth it given what you want to do, and also Adobe sucks shit) or want to avoid paying someone who knows how to use Photoshop (understandable - and would obviously be worth consideration if it weren't for all of the other problems with AI).
When you attack AI on the basis of it making people lazy - rather than any of the other things that are wrong with it - it just comes across as "Luddite". (Which is ironic, given that Luddism was originally about machinery resulting in worse working conditions for skilled workers, which is one thing AI actually will do.)
I’m a senior full-stack developer of 15 years, and more recently, a new tech lead at an AI startup. I’m definitely not attacking AI as a concept in general.
I work with AI agents every day and all day. That’s how I develop and plan our systems. It did not start that way. I was absolutely against the use of AI during development, but a few months back, I need the assistance because I developed carpal tunnel syndrome, so that’s what I automated, just the typing and the implementation of low-level logic so that my wrists can heal. But do you know what stock AI agents do to code when not given proper guidance? Ask any real developer and they’ll tell you about vibe coding. I guarantee these are not going to be success stories.
I’m not just judging people for being lazy, because lazy people like me will innovate ways to stay lazy by inventing/optimising new shit that allows them to stay lazy. That’s a survival instinct and an evolutionary selection mechanism: minimising energy investiture while doing the same thing as everyone around you is an evolutionary advantage.
No. What I’m judging them for is delegating their critical thinking capacity to an external entity, and stunting their own cognitive growth (their literal reason for existing in the first place, their continuity mechanism to stay in the gene pool, and their sole means of improving at being long-term lazy) by being short-term lazy. Makes sense?
Now to generative AI (for the multimedia substrate):
The vast majority of people you speak of are now polluting the collective “training set” with diluted slop distilled from all art historically created thus far, because the content generation equation went from: X people creating Y novel pieces of art per year, to X models creating Y million images per day, all thanks to a handful of idiots with more greed/money than common-sense. That diluted pool is ever-expanding, growing geometrically, and burying actual novelty with each new image Susan generates and shares for her new “Katz Rule” instagram profile.
The thing is: the next model will be trained on that averaged set, and the next, and the next. With each day and each generation increasing in conformity. And that set is what we’re stuck with for new inspiration (and future models) now. Because everyone is looking at screens for inspiration, and not at mountains or rivers, or even the real stars in the sky at night because we ruined that too.
All while we’re doing the things you just mentioned.
All thanks to a few assholes with more selfishness than common-sense chasing after unlimited quarterly growth in a very limited space that’s closing around us fast.
I, too, am a developer of closer to 15 years than I'd like to admit to myself, though mostly embedded and/or back-end. And while I have no problem with AI in its broad sense (obviously machine learning/spicy statistics, computer vision, and natural language processing and whatnot have potential to be enormously useful), I am generally hostile to generative AI. I thinking using copyrighted material as training data without the copyright holders' permission should be banned. And while I would have no objection to ethically-trained models in a hypothetical future where we have abundant clean energy to run the data centres and also all the new desalination plants we would need, that also remains a problem, and so I have resisted using such tools at work, too.
I agree with everything you've said after this point.
This is the crux of my problem. I find it to be overly judgemental. If you're self-employed and you need a website for your business or whatever, then you could pay someone to do it for you, but then you only have so much money in the budget. You could also learn how to code and/or graphic design and do it yourself, but then you only have so many hours in the day. If vibe coding produced something viable for you in the quickest, cheapest way, then that is obviously the rational and sensible thing to do. You might even spend the time learning something else instead that is more relevant to your interests.
Using generative AI to do something doesn't (necessarily) mean that you don't value the knowledge or skills required to do it the hard way, it only means that you value it less than something else that you might otherwise be doing with your time, and I don't think that is a moral failing.
As an example, I occasionally like to a bit of shitposting. Were it not for all those other things that I don't like about generative AI, I would probably be generating AI slop memes with the best of the them. As it is I mostly just stick to text-based comments with bad puns and references to song lyrics no-one will remember. I could put in the hours to learn how to use GIMP so I could do it without AI, but quite frankly I have books on the go, I've got a couple of musical instruments to learn/practise, and I spent all day at my software job, where I think critically (or so I claim), so I'd rather being doing those things instead. I don't think I have neglected my cognitive growth; I've just chosen to focus it on something different to what you might have.
Ohhh. I think we’re both defending different hills! I’m not against the use of generative AI for purposeful creation. What I’m against is the delegation of critical thinking.
It’s the difference between:
(That last one is admittedly my own guilty contribution to the slop soup and favourite desktop background of at least a whole year)
Versus:
The difference is oversight and vision. The first two are asking AI to execute well-defined tasks with explicit parameters and rules, the first example in particular offers the LLM an out if it finds itself at an impasse.
The latter examples are asking a prediction engine to predict a vague concept. Don’t expect originality/innovation from something that was forcibly constrained to pick from a soup made of prior art then locked down, because that’s what gradient descent essentially does to the neural networks during training: reduce the error margin by restricting the possible solutions for any given problem to only what is possible within the training set, which is also known as plagiarism.
Edit: a slight elaboration on the last part:
Neural networks trained with gradient descent will do the absolute minimum to reach a solution. That’s the nature of the training process.
What this essentially means is that effort scales with prompt complexity! A simple/basic prompt begets you the most generic result possible. Because it allows the network to slide along the shortest path from the input token to a very predictable result.
Right, because you don't believe art has value or requires thinking. It's essentially worthless to you.
What people with a critical eye for art can tell you is that the art also has well-defined tasks with explicit perimeters and rules, and generative AI produces uncreative slop that looks amateurish if you have an eye for art. It's pretty typical for people to believe generative AI is better at tasks that they, personally, know nothing about - it's a Dunning-Kruger machine.
LLMs are a pretty good tool to summarize any subject, or present it with different words or in a different approach... They are a statistical word predictor tool after all.
So yeah, if you understand that LLMs:
Then, I'd say that LLMs can be used as a very good facilitator to learn about almost any subject that has already been documented in any word format in almost any language.
They're not even good at that.
It feels like as the models were iterated on they got worse at it over time. I wonder if it's because of all the guard-railing and internal censorship etc.
It's just a messy process, it's purely based on probability, I don't think it'll ever get good, people were just being lied to. Don't forget that they relied on "confirmatory bias" and "selection bias" from the users as well.
your bulleted list has me suspecting you used an llm to write this. TRAITOR
I have never used a LLM to write any of my comments on the internet, neither here nor in any social network I have an account. And about the bullet points, in places that accept MarkDown similar syntax I tend to use bullet points because it's a feature that helps lay out the ideas in a good formatting for the reader when there's enumerations, lists, or similar things involved.
But yeah, you will never find comments of mine in, lets say, Instagram, with bullet points, because the editor of the app there sucks, you would have to type your comment in a external app which creates the bullet points characters already in a newline (you cannot even normally break lines in Instagram comments lol, it's really unsanitary haha), and I ain't gonna do that.
Make your own content then you fucking bitch
::: spoiler spoiler (Apologies to my good bitches) :::
ROFL Stealing prompts, really?! That's not work or effort in the slightest, making slop isn't real work, it's just trash.
You've not tried using LLMs yet have you?
Many times, it has taken me over 30 re-writes to get a prompt that gets the LLM to do what I want.
It's very often more work and effort.
XD
First time among thieves, eh? :)
True slopmasters know that they need to ask an llm to generate a prompt, because who understands GenAI better than another GenAI /s
Is GenAI the new term for Generation Alpha?
No, it's short for Generative Artificial Intelligence. It's capital i and not the lowercase L
Word to the wise: just learn improv.
https://www.psychologytoday.com/us/blog/play-your-way-sane/202303/7-research-backed-benefits-of-improv-comedy
irony is dead, and we have killed him.
Hey ChatGPT, rewrite this prompt differently
Plot twist they're all just putting their assignments into AI and asking for a prompt that will work.
Stop searching what I search on google
Then stop sharing your prompts like idk what to tell you
The audacity of some people. Said this clueless idiot.
I felt physical pain upon reading this...
"The vibe is still the same."
Do they have their own language? What does "vibe" mean anymore?
Stolen Valor!
Prompt engineer is an emerging career btw. It’s hilarious.
I read about that... then I saw something a few months later that said that the role was already obsolete because the "skills" prompt engineers were learning had just been incorporated into newer models.
Interesting. We’ll see. It’s such trash even with improvements that it will be difficult to foresee.
A"I" "educator" is mad at people for stealing prompts. FTFY.
'Sophisticated auto-complete' user is mad at people for inputting the same tokens into it as he does.
Ironic
Lol, lmao even
There's no way this woman is real
What assholes. They can all go fuck themselves for stealing everything.
Well that's my blood boil for the day. Don't want to spill over so I'd better stop there.
Can you imagine if coders had the same mentality? Jesus f Christ, lmao.
QQ
You think it's funny to screenshot other people's prompts huh?