We had a classic bot on r/SubSimGPT2Interactive that was trained on discussions about Dwarf Fortress. It was always one of my favorites even though I had never played Dwarf Fortress, and it took me a while to realize that more than half of the absurdity it was generating was due to the game just being like that. GPT-2 was merely shuffling the deck and dealing the cards

Me: I’ve cut my coffee intake down to one cup a day! Look how disciplined and restrained I am!

Also me: drinks 1.5 cans of Celsius per day

Especially since, like, women have been using machines to pleasure themselves for a while now and it’s still kind of a novelty for most het cis men

Tell that to the MAGA working class

Wait, did I miss something? I was under the impression that Vivaldi wouldn’t be affected by the Manifest v3 change since their adblocker is independently developed… is that not the case?

Yes, and I loved it at first sight–it’s the only version of Firefox that feels modern and delivers competitive performance in terms of resource efficiency. I’m backing the project via Patreon and really hope it develops into something even better… though I have to admit that I’ve mostly switched back to Vivaldi because of its greater customization ability and mobile browser (Zen is desktop only) as well as its built-in adblocker, which even works in iOS, unlike uBlock Origin.

I think that there are some people working on this, and a few groups that have claimed to do it, but I’m not aware of any that actually meet the description you gave. Can you cite a paper or give a link of some sort?

It’s 100% this. Politics is treated like a sport in the USA; the only thing that matters is your side winning, and which side you root for is largely dictated by location and family history. This is encouraged by the private news media, who intentionally report on election campaigns in this manner in order to increase ratings and ad revenue. Social media only made it worse because it made a lot of abstract identity dimensions, such as political affiliation, feel stronger to people than their everyday lives.

Y’all should really stop expecting people to buy into the analogy between human learning and machine learning i.e. “humans do it, so it’s okay if a computer does it too”. First of all there are vast differences between how humans learn and how machines “learn”, and second, it doesn’t matter anyway because there is lots of legal/moral precedent for not assigning the same rights to machines that are normally assigned to humans (for example, no intellectual property right has been granted to any synthetic media yet that I’m aware of).

That said, I agree that “the model contains a copy of the training data” is not a very good critique–a much stronger one would be to simply note all of the works with a Creative Commons “No Derivatives” license in the training data, since it is hard to argue that the model checkpoint isn’t derived from the training data.

Yeah, I’ve struggled with that myself, since my first AI detection model was technically trained on potentially non-free data scraped from Reddit image links. The more recent fine-tune of that used only Wikimedia and SDXL outputs, but because it was seeded with the earlier base model, I ultimately decided to apply a non-commercial CC license to the checkpoint. But here’s an important distinction: that model, like many of the use cases you mention, is non-generative; you can’t coerce it into reproducing any of the original training material–it’s just a classification tool. I personally rate those models as much fairer uses of copyrighted material, though perhaps no better in terms of harm from a data dignity or bias propagation standpoint.