I'm not a data scientist, but I assume that having more information about the subject would yield better results. In particular, upscaling faces doesn't produce convincing outcomes; the results tend to look eerie and uncanny.
Instead of training on vast amounts of arbitrary data that may lead to hallucinations, wouldn't it be better to train on high-resolution images of the specific subject we want to upscale? For example, using high-resolution modern photos of a building to enhance an old photo of the same building, or using a family album of a person to upscale an old image of that person. Does such an approach exist?
I've been there, and it was a pain. All my backups were corrupted due to a faulty RAM module. Initially, I blamed the hard drives because they seemed to be failing right before my eyes. I was copying a large file; sometimes it copied okay, but occasionally it would become corrupted. Since then, I've been paying a premium for ECC.
The demoscene has always been about real-time graphics. It never sought to compete with video animations. Many demosceners were, at heart, game developers who valued and appreciated real-time code, often considering animations to be "lame".
Silent data corruption is silent. ECC should be mandatory just for the error reporting. The system should inform the user that a DIMM has gone bad and needs replacement.