

I would say of the services to give money to, Discord is on the lesser evil side.
Sure, they lock a bunch of stuff behind Nitro, but they’re at least only giving people ads for their own stuff and not scams or dong pills. Because if nobody paid for anything, that money would have to come from somewhere.
The only thing more eco-friendly than buying an eco-friendly printer, is to not buy a new printer at all.
Both of my local libraries offer printing at $0.25 a page. For photos, I just go to the photo lab at the store and print them there.
Both are cheaper than owning a printer unless you’re doing a ton of it, and in the former case, I get to support a library just a little bit.
Speaking for LLMs, given that they operate on a next-token basis, there will be some statistical likelihood of spitting out original training data that can’t be avoided. The normal counter-argument being that in theory, the odds of a particular piece of training data coming back out intact for more than a handful of words should be extremely low.
Of course, in this case, Google’s researchers took advantage of the repeat discouragement mechanism to make that unlikelihood occur reliably, showing that there are indeed flaws to make it happen.
I’m not an expert, but I would say that it is going to be less likely for a diffusion model to spit out training data in a completely intact way. The way that LLMs versus diffusion models work are very different.
LLMs work by predicting the next statistically likely token, they take all of the previous text, then predict what the next token will be based on that. So, if you can trick it into a state where the next subsequent tokens are something verbatim from training data, then that’s what you get.
Diffusion models work by taking a randomly generated latent, combining it with the CLIP interpretation of the user’s prompt, then trying to turn the randomly generated information into a new latent which the VAE will then decode into something a human can see, because the latents the model is dealing with are meaningless numbers to humans.
In other words, there’s a lot more randomness to deal with in a diffusion model. You could probably get a specific source image back if you specially crafted a latent and a prompt, which one guy did do by basically running img2img on a specific image that was in the training set and giving it a prompt to spit the same image out again. But that required having the original image in the first place, so it’s not really a weakness in the same way this was for GPT.
I mean, I like mounting an SFTP server on my system and playing stuff with MPV just fine, but I host this stuff for my friends, too. Having something like Plex where they can use an interface that’s familiar and easily watch what they want is worth it to me.
But then, none of us are watching porn on it, either.
It’s not a terribly complicated idea, really. You can train it to output formatted calculations when presented with a problem, then something in the middle watches for those and inserts the solution for it behind the scenes. You might even trigger another generation to let it appear more smooth when presented to the user.
I’m glad this comment section seems to agree that some fault lies on the game companies, too. I get it that parents gotta also parent, but when games are hiring behavior/psychology experts to design their games to become addictive and suck in people’s money as effectively as possible… adults struggle enough with resisting gaming addiction, let alone kids.
I know a guy that spent all of his free time, and on average $2,000 a month, on Genshin Impact.
Hot take: I think there’s not a great deal to fear even for most common people. Technological innovation has always stolen away jobs from somewhere, but the large majority of people are still finding work despite the human population exploding drastically over the last century as that happened.
Because realistically, if only a few people are working and earning money, then there’s no one consuming to feed the shareholders’ desire for unsustainable infinite growth every quarter. It would hurt the economy as much as it does the people in it, and that’s the one thing that regulators actually care about.
Fortunately, they at least aren’t deleting accounts with YouTube videos “at this time”
I still backed up the videos from a deceased friend’s channel just in case- but I’m glad his content will still be there.
They’re probably referring to quantum entanglement, which affects the entangled particles instantly.