427
submitted 1 day ago by [email protected] to c/[email protected]
top 50 comments
sorted by: hot top controversial new old
[-] [email protected] 4 points 29 minutes ago

Anyone who has made copies of videotapes knows what happens to the quality of each successive copy. You're not making a "treasure trove." You're making trash.

[-] [email protected] 6 points 1 hour ago

Having now flooded the internet with bad AI content not surprisingly its now eating itself. Numerous projects that aren't AI are suffering too as the quality of text reduces.

[-] [email protected] 2 points 53 minutes ago

If we can work out which data conduits are patrolled more often by AI than by humans, we could intentionally flood those channels with AI content, and push Model Collapse along further. Get AI authors to not only vet for "true human content", but also pay licensing fees for the use of that content. And then, hopefully, give the fuck up on their whole endeavor.

[-] [email protected] 1 points 46 minutes ago

I couldn't care less.

[-] [email protected] 21 points 3 hours ago

Uh, good.

As an engineer who cares a LOT about engineering ethics, it is absolutely fucking infuriating watching the absolute firehose of shit that comes out of LLMs and public-consumption ML audio, image, and video ML systems, juxtaposed with the outright refusal of companies and engineers who work there to accept ANY accountability or culpability for the systems THEY FUCKING MADE.

I understand the nuances of NNs. I understand that they’re much more stochastic than deterministic. So, you know, maybe it wasn’t a great idea to just tell the general public (which runs a WIDE gamut of intelligence and comprehension ability - not to mention, morality) “have at it”. The fact that ML usage and deployment in terms of information generating/kinda-sorta-but-not-really-aggregating “AI oracles” isn’t regulated on the same level as what you’d see in biotech or aerospace is insane to me. It’s a refusal to admit that these systems fundamentally change the entire premise of how “free speech” is generated, and that bad actors (either unrepentantly profit driven, or outright malicious) can and are taking disproportionate advantage of these systems.

I get it - I am a staunch opponent of censorship, and as a software engineer. But the flippant deployment of literally society-altering technology alongside the outright refusal to accept any responsibility, accountability, or culpability for what that technology does to our society is unconscionable and infuriating to me. I am aware of the potential that ML has - it’s absolutely enormous, and could absolutely change a HUGE number of fields for the better in incredible ways. But that’s not what it’s being used for, and it’s because the field is essentially unregulated right now.

[-] [email protected] 2 points 1 hour ago

Well duh. I think a lot of us here learned that lesson from watching the movie Multiplicity.

[-] [email protected] 1 points 1 hour ago

Would you recommend it?

[-] [email protected] 1 points 2 hours ago
[-] [email protected] 24 points 9 hours ago

So AI:

  1. Scraped the entire internet without consent
  2. Trained on it
  3. Polluted it with AI generated rubbish
  4. Trained on that rubbish without consent
  5. Are now in need of lobotomy
[-] [email protected] 16 points 14 hours ago
[-] [email protected] 15 points 17 hours ago

have we tried feeding them actual human beings yet ?

[-] [email protected] 7 points 14 hours ago

Billionaires are the smartest, give them the most knowledge first!

[-] [email protected] 5 points 14 hours ago

It's like a human centipede where only the first person is a human and everyone else is an AI. It's all shit, but it gets a bit worse every step.

[-] [email protected] 53 points 1 day ago

Every single one of us, as kids, learned the concept of "garbage in, garbage out"; most likely in terms of diet and food intake.

And yet every AI cultist makes the shocked pikachu face when they figure out that trying to improve your LLM by feeding it on data generated by literally the inferior LLM you're trying to improve, is an exercise in diminishing returns and generational degradation in quality.

Why has the world gotten both "more intelligent" and yet fundamentally more stupid at the same time? Serious question.

[-] [email protected] 18 points 15 hours ago

Why has the world gotten both "more intelligent" and yet fundamentally more stupid at the same time? Serious question.

Because it's not actually always true that garbage in = garbage out. DeepMind's Alpha Zero trained itself from a very bad chess player to significantly better than any human has ever been, by simply playing chess games against itself and updating its parameters for evaluating which chess positions were better than which. All the system needed was a rule set for chess, a way to define winners and losers and draws, and then a training procedure that optimized for winning rather than drawing, and drawing rather than losing if a win was no longer available.

Face swaps and deep fakes in general relied on adversarial training as well, where they learned how to trick themselves, then how to detect those tricks, then improve on both ends.

Some tech guys thought they could bring that adversarial dynamic for improving models to generative AI, where they could train on inputs and improve over those inputs. But the problem is that there isn't a good definition of "good" or "bad" inputs, and so the feedback loop in this case poisons itself when it starts optimizing on criteria different from what humans would consider good or bad.

So it's less like other AI type technologies that came before, and more like how Netflix poisoned its own recommendation engine by producing its own content informed by that recommendation engine. When you can passively observe trends and connections you might be able to model those trends. But once you start actually feeding back into the data by producing shows and movies that you predict will do well, the feedback loop gets unpredictable and doesn't actually work that well when you're over-fitting the training data with new stuff your model thinks might be "good."

[-] [email protected] 3 points 6 hours ago

Another great example (from DeepMind) is AlphaFold. Because there's relatively little amounts of data on protein structures (only 175k in the PDB), you can't really build a model that requires millions or billions of structures. Coupled with the fact that getting the structure of a new protein in the lab is really hard, and that most proteins are highly synonymous (you share about 60% of your genes with a banana).

So the researchers generated a bunch of "plausible yet never seen in nature" protein structures (that their model thought were high quality) and used them for training.

Granted, even though AlphaFold has made incredible progress, it still hasn't been able to show any biological breakthroughs (e.g. 80% accuracy is much better than the 60% accuracy we were at 10 years ago, but still not nearly where we really need to be).

Image models, on the other hand, are quite sophisticated, and many of them can "beat" humans or look "more natural" than an actual photograph. Trying to eek the final 0.01% out of a 99.9% accurate model is when the model collapse happens--the model starts to learn from the "nearly accurate to the human eye but containing unseen flaws" images.

[-] [email protected] 4 points 15 hours ago

good commentary, covered a lot of ground - appreciate the effort to write it up :)

[-] [email protected] 28 points 23 hours ago

Because the people with power funding this shit have pretty much zero overlap with the people making this tech. The investors saw a talking robot that aced school exams, could make images and videos and just assumed it meant we have artificial humans in the near future and like always, ruined another field by flooding it with money and corruption. These people only know the word "opportunity", but don't have the resources or willpower to research that "opportunity".

[-] [email protected] 5 points 17 hours ago* (last edited 17 hours ago)

Remember Trump every time he's weighed in on something, like suggesting injecting people with bleach, or putting powerful UV lights inside people, or fighting Covid with a "solid flu vaccine" or preventing wildfires by sweeping the forests, or suggesting using nuclear weapons to disrupt hurricane formation, or asking about sharks and electric boat batteries? Remember these? These are the types of people who are in charge of businesses, they only care about money, they are not particularly smart, they have massive gaps in knowledge and experience but believe that they are profoundly brilliant and insightful because they've gotten lucky and either are good at a few things or just had an insane amount of help from generational wealth. They have never had anyone, or very few people genuinely able to tell them no and if people don't take what they say seriously they get fired and replaced with people who will.

[-] [email protected] 3 points 15 hours ago

Because the dumdums have access to the whole world at the tip of the fingertip without having to put any efforts in.

In a time without that, they would be ridiculed for their stupid ideas and told to pipe down.

Now they can find like minded people and amplify their stupidity, and be loud about it.

So every dumdum becomes an AI prompt engineer (whatever the fuck that means) and know how to game the LLM, but do not understand how it works. So they are basically just snake oil salesmen that want to get on the gravy train.

[-] [email protected] 9 points 23 hours ago

Oh no. Anyways...

[-] [email protected] 25 points 1 day ago* (last edited 1 day ago)

oh no are we gonna have to appreciate the art of human beings? ew. what if they want compensation‽

[-] [email protected] 1 points 17 hours ago

Two outcasts among their peers, Gary Wallace and Wyatt Donnelly spent a good deal of their youth as pioneers and early adopters of AI.

[-] [email protected] 9 points 1 day ago
[-] [email protected] 10 points 1 day ago
[-] [email protected] 7 points 1 day ago* (last edited 1 day ago)

If mainstream blogs are writing about it, what would make someone think that AI companies haven't thoroughly dissected the problem and are already working on filtering out AI fingerprints from the training data set? If they can make a sophisticated LLM, chances are they can find methods to XOR out generated content.

[-] [email protected] 9 points 23 hours ago

What would make me think that they haven't "thoroughly dissected" it yet is that I'm a skeptic, and since I'm a skeptic I don't immediately and without evidence believe that every industry is capable of identifying, dissecting, and solving every problem with its products.

[-] [email protected] 2 points 18 hours ago

Ironically given their skillset, training an ML model on known and properly tagged AI generated and non-AI-generated stuff might actually work.

[-] [email protected] 110 points 1 day ago

It is their own fault for poisoning the internet with their slop.

[-] [email protected] 5 points 13 hours ago

DUDE ITS SO FUCKING ANNOYING TRYNNA USE GOOGLE IMAGES ANYMORE--

ALL IT GIVES ME IS AI ART. IM SO FUCKING SICK AND TIRED OF IT.

load more comments (7 replies)
[-] [email protected] 179 points 1 day ago

Let's go, already!

How you can help: If you run a website and can filter traffic by user agent, get a list of the known AI scrapers agent strings and selectively redirect their requests to pre-generated AI slop. Regular visitors will see the content and the LLM scraper bots will scrape their own slop and, hopefully, train on it.

[-] [email protected] 3 points 3 hours ago

It’s kinda interesting in how it actually roughly parallels the dawn of the nuclear age in some specific ways. Namely, that there’s a clear “purity” line established by the advent of the technology - and I mean that literally, not figuratively. Content on the internet is going to have a very similar dividing line. But it’s also going to be way harder to definitively source data from before that line, unless someone clairvoyant happened to offline and archive a huge storage array with a complete internet snapshot right before ML made its public debut. And I know exactly what the scale of that storage commitment would be, and how much it would cost. So I’m certain nobody has done that.

[-] [email protected] 1 points 11 hours ago

Are there any good lists of known AI user agents? Ideally in a dependency repo so my server can get the latest values when the list is updated.

[-] [email protected] 1 points 13 hours ago

Okay but I like using perchance cus they dont profit off anything 👉👈

a large chunk of that site is some dudes lil hobby project and its kinda neat interacting with the community and seein how the code works. Its the only bot I'll ever use cus they arent profiting off of other people shit. the only money they get is from ads and thats it.

Dont kill me with downvotes, I like making up cool OC concepts or poses n stuff and then drawing em.

load more comments (11 replies)
[-] [email protected] 13 points 1 day ago

Fake news, just like that one time Nightshade "killed" stable diffusion (literally had no effect) Flux came out not long ago and it's better than ever

load more comments (2 replies)
load more comments
view more: next ›
this post was submitted on 18 Sep 2024
427 points (94.2% liked)

Technology

58150 readers
4781 users here now

This is a most excellent place for technology news and articles.


Our Rules


  1. Follow the lemmy.world rules.
  2. Only tech related content.
  3. Be excellent to each another!
  4. Mod approved content bots can post up to 10 articles per day.
  5. Threads asking for personal tech support may be deleted.
  6. Politics threads may be removed.
  7. No memes allowed as posts, OK to post as comments.
  8. Only approved bots from the list below, to ask if your bot can be added please contact us.
  9. Check for duplicates before posting, duplicates may be removed

Approved Bots


founded 1 year ago
MODERATORS