Unless the original standard agrees and implements it, then you've just created a new standard.
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.
“The Copilot is like the Start button,” Nadella explains. “It becomes the orchestrator of all your app experiences. So for example, I just go there and express my intent and it either navigates me to an application or it brings the application to the Copilot, so it helps me learn, query and create — and completely changes, I think, the user habits.”
I like to put down M$ when I can, but I don't think replacing the start button is the exact plan here. I think he's just using it as a comparison.
I use adnauseum on my computer so it blocks the ads, but also sends a request simulating a click to the ad network. Based on average CPM, I've cost advertisers like $300 so far.
Hopefully development studios can hold strong and continue their boycott anyway. Backing down now basically means Unity got away with it, in a sense. Plus, companies are learning from each other's shitty tactics lately ala Twitter, Reddit, and Recently Facebook coming out with payment schemes on things that used to be free.
So if Unity does this, other software companies will probably try some similar stuff.
It's possible that she looked up information about cutting down on drinking, and because you're connected in the ad network system, you also got ads from it. They like to learn who is connected to who and target ads that way. Facebook is, as you might predict, one of the most notorious.
That's correct, you can insult someone accidentally while complimenting them in a similar way. The particles は (as in wa) and が (ga) have different connotations that can simply different things.
So saying メリーさんの顔はきれい (Mary-san no kao wa kirei, "Mary has a beautiful face") causes an implication that Mary has a beautiful face, (... But nothing else about her is beautiful). Changing the は for が makes the statement come across as intended.
Without going into detail on the whole wa vs ga thing, wa is more like "as for x..." which can imply a "but..." at the end, whether stated or not, which causes this effect.
Probably about as many as ever, I think. They might have more instant feedback than previously on how popular their works are, but there are plenty of pre-internet creatives who pursued their art and had nothing to show for it even into their deaths. Many of the same self-justifications they used then can still apply now, even with the Internet around giving them feedback.
Anyone who walked into an IHOP and ate 3.26 pounds of pancakes would be an absolute legend at that IHOP. I can barely eat 4 or 5 before I'm done.
Because all of our food is stuffed with sugar and our teeth rot rapidly as a result.
Jamie
joined 1 year ago
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.