I think labeling things made by AI is a reasonable request. In this specific example, someone who’s buying 4K Wallace & Gromit is doing so out of a love of claymation and Aardman’s work in it. They want it in high definition specifically to see the details that went into a handcrafted set and characters. Getting a smoothed over statistical average, when you payed for it expecting the highest quality archive on an artistic work, would be more frustrating than just seeing it in lower definition.
More generally, don’t people working with these models also want AI output to be properly labeled? As I understand it, the model starts to degrade when its output is fed back into itself. With the rapid proliferation of AI posting, I’ve heard you can’t even make large language models with the same level of quality as you could before it was released to the general public.
I’m also kinda skeptical that this stuff has as many applications as are being touted. Like, I’ve seen some interesting stuff for folding proteins or doing statistical analysis of particle physics, but outside highly technical applications… kinda seems like a solution in search of a problem. It’s something investors really really like for their stock evaluations, but I just don’t see it doing much for actual workers. At most, maybe it eliminates some middle-management email jobs.
I think labeling things made by AI is a reasonable request. In this specific example, someone who’s buying 4K Wallace & Gromit is doing so out of a love of claymation and Aardman’s work in it. They want it in high definition specifically to see the details that went into a handcrafted set and characters. Getting a smoothed over statistical average, when you payed for it expecting the highest quality archive on an artistic work, would be more frustrating than just seeing it in lower definition.
More generally, don’t people working with these models also want AI output to be properly labeled? As I understand it, the model starts to degrade when its output is fed back into itself. With the rapid proliferation of AI posting, I’ve heard you can’t even make large language models with the same level of quality as you could before it was released to the general public.
I’m also kinda skeptical that this stuff has as many applications as are being touted. Like, I’ve seen some interesting stuff for folding proteins or doing statistical analysis of particle physics, but outside highly technical applications… kinda seems like a solution in search of a problem. It’s something investors really really like for their stock evaluations, but I just don’t see it doing much for actual workers. At most, maybe it eliminates some middle-management email jobs.