alt Hacker News> and they create a similar product then they haven't broken the law.
That costs significantly more and involves the creation of jobs. I see this as a great outcome. There seems to be a group of people who share the opposite of my views on this matter.
> and is an error that needs correcting
It's been known for years. They don't seem interested in doing that or they simply aren't capable. I presume because most of the value in their service _is_ the copyright whitewashing.
> Memorizing specific training data means that it is not generalizing enough.
Is that like a knob they can turn or is it something much more fundamental to the technology they've staked trillions on?
> That costs significantly more and involves the creation of jobs. I see this as a great outcome.
I don't see it that way. If whatever you're doing can now be automated then it's become a bullshit job. It no longer a benefit to humanity to have a human sit on their ass, stand on their feet, or break their back to do a job that can be automated. As a software developer, it's my job to take the dumb repetitive stuff that humans do and make it so that humans never have to do that job again.
If that's a problem for society, it's because society is messed up.
> It's been known for years. They don't seem interested in doing that or they simply aren't capable.
I don't find that to be particularly big problem. Fundamentally an AI isn't just compressing all human knowledge and decompressing it on demand; it's tweaking parameters in a giant matrix. I can reproduce the lyrics of songs that I've heard but that doesn't mean there is a literal copy of that song in my brain that you could extract out with a well placed scalpel. It just means I've heard it a bunch of times and the giant matrix in my brain is tuned to be able to spit it out.
> Is that like a knob they can turn or is it something much more fundamental to the technology they've staked trillions on?
In a sense, it a knob. It's not fundamental to the technology; if it's reproducing something exactly that likely means it's over-trained on that data. It's actually bad for the models (makes them more incorrect, more rigid, and more repetitive) so that is a knob they will turn.