If someone wants to read one of those papers, I can recommend Extracting Training Data from Diffusion Models. It shouldn't be too hard for someone with little experience in the field to be able to follow along.
Mirodir
Understanding the math behind it doesn't immediately mean understanding the decision progress during forward propagation. Of course you can mathematically follow it, but you're quickly gonna lose the overview with that many weights. There's a reason XAI is an entire subfield in Machine Learning.
I think it's much more likely whatever scraping they used to get the training data snatched a screenshot of the movie some random internet user posted somewhere. (To confirm, I typed "joaquin phoenix joker" into Google and this very image was very high up in the image results) And of course not only this one but many many more too.
Now I'm not saying scraping copyrighted material is morally right either, but I'd doubt they'd just feed an entire movie frame by frame (or randomly spaced screenshots from throughout a movie), especially because it would make generating good labels for each frame very difficult.
I haven't personally used it but from what I can find: if you're using torrents with Stremio (e.g. the ones found with torrentio) you are totally uploading parts of what you're watching to others.
Or "watch". That way they don't have to make it obvious that their customers won't own it but still don't straight up lie.
It usually happens a lot faster in video games than 3 sessions in. If it happens later in a video game, it's usually a very short, very temporary scene of depowerment.
I had a whole paragraph typed out on my phone but didn't like most of it. By now many other players said most of what was in there already before I had the chance to proofread and reword it. The gist of it was though: Don't alter player characters or take their power away without at least one of those three being true:
- The player agrees beforehand and is aware it will happen.
- The player character has done something so horrendously stupid that it could've easily been their death so e.g. them losing a limb and now having a pegleg is them being lucky.
- It is very temporary, I'd say max 1 in-game day/1session and the player (not necessarily the character) is aware of that.
You might argue that picking that fight that would get them sent to hell would qualify as #2. But with you planning it out ahead of time it's less them doing something dumb and more the DM guiding them to do something dumb.
Giving you the benefit of the doubt of only 3 hour sessions and ignoring the time they planned out their characters, you let them play with their characters for around 6 hours by now and it'll probably be another hour or two until they "die". This might sound harsh but even with you backtracking on this, seriously entertaining this idea in the first place worries me about what else you might have in store.
Regarding the "OP staff of fire" one of your players has: Did you talk to that player about it in private? I find that usually players respond well to the DM being open about something being so overpowered it warps the entire campaign to the point where you have to design every encounter around it. I'd recommend approaching them about it in private, and not at the (virtual?) table when everyone's eager to play already.
Maybe you could just get the player on board to trade the item in for something less disruptively powerful. Essentially nullifying their magic item by being in hell where every enemy is fire-immune while everyone else still has some useful, fun magic toy feels uncool too after all.
Edit: and a player who wouldn't agree to "Hey, your item is so strong I have to design everything around it so you don't just steamroll everything. Can we, for example, have you meet a merchant where your character trades it for something else?" would react HORRIBLY to having it and all levels taken by force to the point where they'll just quit.
no where near Reddit yet on niche subjects
I'm always saddened by how not-active some of those subjects are. For example: Even many large games struggle to have dedicated, active communities on Lemmy (assuming I'm not terrible at finding them, which is sadly also possible). Even some of the largest games have only completely dead communities here. A huge draw of Reddit for me was to be able to talk about the games I play with other people who do too. And mostly, the games I'd love to talk about aren't in the top 10 most played games list.
Now I could try to (re)vitalize those communities I would love to see around, and I have done so shortly after the exodus (on my previous account that died with the instance it was on). However, there's only so much talking into the void I can do until it gets boring.
I also feel like that might be a big issue for people coming over. After I manage to explain to my friends how federation works, they ask me to help them find the [topic of their interest] community, and all I can show them is a community with 10 threads, all over 3 months old and with 0 comments. Sadly it shouldn't surprise anyone they're not sticking around after that.
I was curious too and checked the article but skimming it, instead of a total, I found this:
A new analysis from MUSO, a U.K.-based anti-piracy analyst [...]
With the study being done by a clearly biased person/group and that large omission, I think it's fair to assume that the % of total web traffic going to pirates might not have gone up all that much, maybe it even went down.
I'm guessing they just generate a bunch of pictures, pick the closest and fix the rest in photoshop.
Not like real models aren't already often photoshopped to (near) unrecognizability.
Merriam Webster says either is okay.
I interpreted it more as a "I'm willing to sacrifice all Ameircan's right for anonymous free speech, which I do value, to take away that of foreigners too." which is a typical braindead racist take.
It's not as accurate as you'd like it to be. Some issues are:
Also it's not all that novel. People have been doing this with (variational) autoencoders (another class of generative model). This also doesn't have the flaw that you have no easy way to compress new images since an autoencoder is a trained encoder/decoder pair. It's also quite a bit faster than diffusion models when it comes to decoding, but often with a greater decrease in quality.
Most widespread diffusion models even use an autoencoder adjacent architecture to "compress" the input. The actual diffusion model then works in that "compressed data space" called latent space. The generated images are then decompressed before shown to users. Last time I checked, iirc, that compression rate was at around 1/4 to 1/8, but it's been a while, so don't quote me on this number.
edit: fixed some ambiguous wordings.