Yeah I’ve been using Linux for a very long time. The amount of time I’ve spent on the case being incorrect is non-trivial. I’ve gotten better at not screwing it up throughout the years but the sum of advantages is far outweighed by the sum of debugging time spent.
no it doesn’t. i tried to achieve this multiple times myself and it never worked. and the cases where journalists say it did, they needed to specific ask a lot of times and in a highly specific way till they got a short snippet. Chatgpt dont spits out the exact same phrases over and over again if you ask the same, but has a variable defining how “random” and “far away from the perfect next predicted text” the output is, and by default this makes sure that the answers are never the same. Otherwise it wouldn’t be chat like but more like a simple database spitting out always the same answers for the same question. But that’s not how chatgpt works.
The problem isn’t that it does it regularly, but that it can do it, meaning that the copyrighted works are reproducible, regardless of how much the interface tries to hide that. That means the model isn’t really “learning” the same way a human would in any capacity (that should be obvious), but that it’s storing data that would violate fair use, and could generate copyright-violating portions of works.
Humans read and don’t retain the originals. The argument is that LLMs retain the originals, and that’s where the issue lies.
As someone who researched AI pre-GPT to enhance human creativity and aid in creative workflows, it’s sad for me to see the direction it’s been marketed, but not surprised. I’m personally excited by the tech because I personally see a really positive place for it where the data usage is arguably justified, but we either need to break through the current applications of it which seems more aimed at stock prices and wow-factoring the public instead of using them for what they’re best at.
The whole exciting part of these was that it could convert unstructured inputs into natural language and structured outputs. Translation tasks (broad definition of translation), extracting key data points in unstructured data, language tasks. It’s outstanding for the NLP tasks we struggled with previously, and these tasks are highly transformative or any inputs, it purely relies on structural patterns. I think few people would argue NLP tasks are infringing on the copyright owner.
But I can at least see how moving the direction toward (particularly with MoE approaches) using Q&A data to support generating Q&A outputs, media data to support generating media outputs, using code data to support generating code, this moves toward the territory of affecting sales and using someone’s IP to compete against them. From a technical perspective, I understand how LLMs are not really copying, but the way they are marketed and tuned seems to be more and more intended to use people’s data to compete against them, which is dubious at best.
No? Welcome to gachas, don’t even pretend girls don’t want to be put on the wall by their daddies, there are plenty of thirsty traps with the dudes on TikTok.
These are games made to sell you waifus and husbandus, they are appealing by design. I recommend you to watch the newest Jane Doe trailer on the Zenless channel, this is the target demographic.
lemmy.world
Oldest