Yep.

Yes, "you've been told" that by people who have no clue what they're talking about. Meanwhile, models just keep getting better and better. AI images have been out for years now. There's tons on the net.

First off, old datasets don't just disappear. So the *very worst case* is that you just keep developing your new models on pre-AI datasets.

Secondly, there is human selection on things that get posted. If humans don't like the look of something, they don't post it. In many regards, an AI image is replacing what would have been a much crapper alternative choice.

Third, dataset gatherers don't just blindly use a dump of the internet. If there's a place that tends to be a source of crappy images, they'll just exclude or downrate it.

Fourth, images are scored with aesthetic gradients before they're used. That is, humans train models to assess how much they like images, and then those models look at all the images in the dataset and rate them. Once again, crappy images are excluded / downrated.

Fifth, trainers do comparative training and look at image loss rates, and an automatically exclude problematic ones. For example, if you have a thousand images labeled "watermelon" but one is actually a zebra, the zebra will have an anomalous loss spike that warrants more attention (either from humans or in an automated manner). Loss rates can also be compared between data +sources+ - whole websites or even whole datasets - and whatever is working best gets used.

Sixth, trainers also do direct blind human comparisons for evaluation.

This notion that AIs are just going to get worse and worse because of training on AI images is just ignorant. And demonstrably false.

As for why I think the ruling was bad: their argument was that because the person doesn't control the exact details of the composition of the work, than the basic work (before postprocessing or selection) can't be copyrighted. But that exact same thing applies to photography, outside of studio conditions. Ansel Adams wasn't out there going, "Okay, put a 20 meter oak over there, a 50 meter spruce over there, shape that mountain ridge a bit steeper, put a cliff on that side, cover the whole thing with snow... now add a rainbow to the sky... okay, cue the geese!" He was searching the search space for something to match a general vision - or just taking advantage of happenstance findings. And sure, a photographer has many options at their hands in terms of their camera and its settings, but if you think that's a lot, try messing around with AUTOMATIC1111 with all of its plugins some time.

The winner of Nature Photographer of the year in 2022 was Dmitry Kokh, with "House of Bears". He was stranded on a remote Russian archipelago and discovered that polar bears had moved into an abandoned weather station, and took photos of them. He didn't even plan to be there then. He certainly didn't plan on having polar bears in an abandoned weather station, and he CERTAINLY wasn't telling the bears where to stand and how to pose. Yet his work is a classic example of what the copyright office thinks should be a copyrightable work.

And the very notion that people don't control the layout with AI art is itself flawed. It was an obsolete notion even when they made their ruling - we already had img2img, instructpix2pix and controlnet. The author CAN control the layout, down to whatever level of intricate detail they choose. Unlike, say, a nature photographer. And modern models give increasing levels of control even with the prompt itself - with SD3 (unlike SD1/2 or SC) - you can do things like "A red sphere on a blue cube to the left of a green cone" . We're heading to - if not there already - where you could write a veritable short story's worth of detail to describe a scene.

I find it just plain silly that Person A could grab their cell phone and spend 2 seconds snapping a photo of whatever happens to be out their window, and that's copyrightable, but a person who spends hours searching through the latent space - let alone with ControlNet guidance (controlnet inputs can be veritable works of art in their own right) - isn't given the same credit for the amount of creative effort put into the work.

I think, rather, it's very simple: the human creative effort should be judged not on the output of the work (the work is just a transformation of the inputs), but the amount of creative effort they put into said inputs. Not just on the backend side - selection, postprocessing, etc - but on the frontend side as well. If a person just writes "a fluffy dog" and takes the first pic that comes up, obviously, that's not sufficient creative endeavour. But if a person spends hours on the frontend in order to get the sort of image they want, why shouldn't that frontend work count? Seems dumb to me.

... when the original ruling itself plainly said that though the generated content itself isn't copyrightable, human creative action such as postprocessing or selection can render it copyrightable.

I still think the basic ruling was bad for a number of reasons, and it'll increasingly come under stress in the coming years. But there is zero shock to this copyright here. The copyright office basically invited people to do this.

LLMs cannot do it. Hallucination is baked-in.

LLMs alone definitely can't do it. LLMs, however, seem (to me, speaking for myself as an ML developer) to be a very likely component in an actual AI. Which, to be clear, is why I use "ML" instead of "AI", as we don't have AI yet. It's going to take other brainlike mechanisms to supervise the hugely flawed knowledge assembly that LLMs generate before we even have a chance to get there. Again, IMO.

I'd love for someone to prove me wrong. No sign of that, though. :)

I'll be impressed when one of these ML engines is sophisticated enough to be able to say "I don't know" instead of just making up nonsense by stacking probabilistic sequences; also it needs to be able tell fake news from real news. Although there's an entire swath of humans who can't do that, so it'll be a while I guess. That whole "reality has a liberal bias" truism ought to be a prime training area.

While I certainly understand that the Internet and its various social media cesspools are the most readily available training ground(s), it sure leans into the "artificial stupid" thing.

As long as other nations can purchase this, then NSA, CIA and our general intelligence community should be able to access that without a warrant.
Now, as far requiring it for DoJ/FBI/local police/etc... GREAT.

Here we go again with this.

NVidia shipped 100k AI GPUs last year, which - if run nonstop - would consume 7,4 TWh. Crypto consumes over 100 TWh per year, and the world as a whole consumes just under 25000 TWh per year.

AI consumption of power is a pittiance. To get these huge numbers, they have to assume long-term extreme exponential scaling. But you can make anything give insane numbers with an assumption like that.

I simply don't buy the assumption. Not even assuming an AI bust - even assuming that AI keeps hugely growing, and that nobody rests on their laurels but rather keeps training newer and better foundations - the simple fact is that there's far too much progress being made towards vastly more efficient architectures at every level - model structure, neuron structure, training methodologies, and hardware. . Not like "50% better", but like "orders of magnitude better". I just don't buy these notions of infinite exponential growth.

Everyone (including Slashdot) is presenting the study wrong. It's forecasting that world incomes would drop by nearly a fifth relative to what they would have otherwise been, not relative to the present.

They are NOT using AI to go after wealthy payers. They are using AI to figure out who to look which has a high probability to cheating the system. The fact that they are wealthy has NOTHING to do with it.

I find it interesting that the woke are the ones that scream about words having meaning/power, but then turn right around and screw with things like this BS.
I say go after these a55holes that are trying to hide paying their taxes.
But even better would be to re-write our taxes so that they are fair and near impossible for someone to cheat at.

First off, I said, bad title:

No Consent or ppl in that.

Secondly, adding "without consent" does not mean that it is a particular person's image, but could still require consent by someone else to create a totally fake one (which would be horrible, yet, governments do such BS).

It is images of OTTHER PEOPLE, not just images.

It's not just a question of whether it's justifiable. It's just simply nonsense to think that they can enforce this. Anyone can run Stable Diffusion on their computer. There's a virtually limitless number of models finetuned to make all kinds of porn. It's IMHO extremely annoying all the porn flooding the model sites; I think like 3/4ths of the people using these tools are guys making wank material. Even models that aren't tuned specifically for porn, rarely does anyone (except the foundation model developers, like StabilityAI) specifically try to *prevent* it.

The TL/DR is: if you think stopping pirated music was hard, well, *good luck* stopping people from generating porn on their computers. You might as well pass a law declaring it illegal to draw porn.

Light exposure, depth, degree of exposure, isolated from others or clustered... many factors can affect survivability.

That is pretty much what JPL did.