Users of OpenAI’s GPT-4 are complaining that the AI model is performing worse lately. Industry insiders say a redesign of GPT-4 could be to blame.
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But the only thing it’s actually good at is generating languages, if they try and pretend to know stuff in fields, they’re quickly exposed as frauds.
I cant express my diappointment with chatgpt, they let loose a bot that makes content farms shreek in joy but messes up basic things if their is no well treaded answer, wont give you non mainstream answers (you likely already know and watched what it tells you is “really obscure anime”) And jenuinely has no tolerance for error, from you or itself
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Its consistant tho! Most older ones would fluxuate down to the level of chatgpt somtimes
A lot of people in the media are routinely confused about the different between AI and ordinary software. They are started to call all software “AI” now.
Can you quantify the difference? Far as I can tell, there’s just an imaginary line where software becomes AI just because the logic filtering it depends on to operate is sufficiently complex. The term doesn’t really seem to be a useful categorization either, e.g. the fundamentally different approaches of diffusion models and transformer models.
yeah this makes more sense. companys arent just going to buy a licence to GPT-6 and replace 80% of their staff from an off the shelf solution, rather I expect AI’s will be trained specifically within certain industries and tasks and drive efficiencies
Its head is pretty empty, there gonna fill it with jargen and other BS
Not the first time OpenAI has done this. DALLE2 used to be the best AI art program in the world. Then OpenAI decided that they didn’t want to get sued by celebrities, so they made it so that if a face came out that resembled a celebrity, it would be distorted. But every face kind of looks like someone famous. Ta da! Now DALLE2 can’t do faces.
Want a crane shot areal image of a teen couple in a corvette driving off into the sunset? Well, you are now banned for life from the DALLE2 service, because DALLE2 produced an image of a ‘shot teen’ and that violates it’s terms of service.
Dalle2 was always kind of shit tbh.
Dalle2 was great when it was free and stable diffusion didn’t exist. I don’t see the logic of: “Someone made a free version. Lets make the program worse and charge money for it!”
The only way in mind this dumbing down happens is by fumbling with the model. So that’s the one thing we can be sure: the AI is most definitely changed while publicly staying “ChatGPT 4”. I assume they are either using clipping or token limitations to split the server load but fucking up the result, or they are purposely dumbing it down to capitalise on it later by introducing other pay models like ppl already mentioned.
Either way they are shooting themselves in the foot because a bunch of ppl will unsubscribe either out of spite for the change or because it’s just not worth it anymore for them.
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I remember one time a guy was trying to add SDL (a programming library) to Visual Studio (code editor and IDE), and said that it wouldn’t link to a project no matter what he’s done. You can google how to do this in five minutes, with video tutorials and everything, it’s like a basic thing every programmer does in that IDE. Like 5 question threads later, turns out he was “following all ChatGPT steps” and they were all complete nonsense, just random functions of Visual Studio done with the filenames of SDL.
lmfao. Why haven’t most people figured out yet that chatgpt lies more often than not?
No, because their sales team and ceo are spending millions so that people don’t find that out.
Its not even suppost to tell the truith, we warped it into doing so. Why AI lies
Might be right but in my experience a lack of skill in conversing with AI is a much greater factor in determining it’s usefulness. It’s almost always going to defer to the user. It’s like when someone is dealing with tech support and they tell them to try turning it off and on again. If that really is the solution, and the user insists that it is not, CGPT is going to make something up just to appease the user’s request.
Users have to know that CGPT isn’t magic. How they behave affects how it behaves. Kind of like talking to actual people, which is what it’s essentially trying to simulate.
Some people have been saying that since the beginning while some haven’t noticed this “decline”. It seems very subjective.
Honestly as a daily user I think it’s a combination of it getting worse at understanding vague prompts and people bumbing up against edge cases more. I would suspect the former is due to things like prompt hardening but can only speculate, while the latter isn’t hard to imagine just from frequent use.
AI taking a running leap at enshittification.
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lmao I was write back then :D
You mean "I was right* or “i wrote*”?
No no, he used to work as a wright. Built ships and shit.
Also the title of the attached post is lols: “Yes, ChatGPT became dumber and I 2 days ago I cancelled my subscription”
It could even tell me what 1312 means, after I told it it was a number substitution cypher
Are we sure they aren’t just becoming lazier and dumber by using it?
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The model has become inbred because it’s now impossible to scrape the web without AI content getting ingested, which is full of “hallucinations” and other weird artifacts. The last opportunity to get “uncontaminated” training data was sometime in mid 2022.
Not to say that it’s causing this particular problem, but this issue will emerge eventually. Garbage in = garbage out. Eventually GPT-19 will grow a mighty Habsburg chin.
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Maybe not yet, but…
- Spez will turn Reddit into a bot farm and sell this as training data
- Musk turns Twitter into a bigoted cesspool and will sell this as training data, which will subsequently be flagged for low quality (also: a botfarm)
- Threads is a corporate ad dashboard (and we already know how easy it is to GPT copy) and Zuck will sell this as training data
- Facebook is either dead or only good for boomers and Poles
- blogs are dead
- Fediverse is out there waiting to be scraped but possibly too small to sustain a big model
We’te getting there, hopefully.
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