IncognitoErgoSum

joined 1 year ago

Any vegan with half a brain knows that you need more than just fruit to be healthy. Assuming her death by infection is a result of her diet (which is possible, but we don't know that), she died of being an idiot, not a vegan.

I said it was a neural network.

You said it wasn't.

I asked you for a link.

You told me to do your homework for you.

I did your homework. Your homework says it's a neural network. I suggest you read it, since I took the time to find it for you.

Anyone who knows the first thing about neural networks knows that, yes, artificial neurons are simulated with matrix multiplications, why is why people use GPUs to do them. The simulations are not down to the molecule becuase they don't need to be. The individual neurons are relatively simple math, but when you get into billions of something, you don't need extreme complexity for new properties to emerge (in fact, the whole idea of emergent properties is that they arise from collections of simple things, like the rules of the Game of Life, for instance, which are far simpler than simulated neurons). Nothing about this makes me wrong about what I'm talking about for the purposes of copyright. Neural networks store concepts. They don't archive copies of data.

[–] IncognitoErgoSum@kbin.social 1 points 1 year ago (2 children)

LOL, I love kbin's public downvote records. I quoted a bunch of different sources demonstrating that you're wrong, and rather than own up to it and apologize for preaching from atop Mt. Dunning-Kruger, you downvoted me and ran off.

I advise you to step out of whatever echo chamber you've holed yourself up in and learn a bit about AI before opining on it further.

Unfortunately, you pretty much have to specify a specific time and place for it to be actionable. These guys are very familiar with how those laws work and know exactly how to avoid getting caught by them.

[–] IncognitoErgoSum@kbin.social 1 points 1 year ago* (last edited 1 year ago)

I'm not sure why you're asking that. You literally just asked me if I'm refusing to admit that AI could cause trouble for people's livelihoods. I don't know where you even got that idea. I never asked you anything about whether you admit it could help with things, because that's irrelevant (and also it would be a pretty silly blanket assumption to make).

Are you sure you're not projecting here? In this entire thread, have you budged an inch based on all the people arguing against your original post?

Who am I supposed to be budging for? Of the three people here who are actually arguing with me, you're the only one who isn't saying they're going to slash my car tires and likening personal AI use to eating steak in terms of power usage (it's not even in the same ballpark), or claiming that Stable Diffusion doesn't use a neural network. I only replied to the other guy's most recent comment because I don't want to be swiftboated -- people will believe other people who confidently state something that they find validating, even if they're dead wrong.

We just seem to mostly have a difference of opinion. I don't get the sense that you're making up your own facts. And fundamentally, I'm not convinced of the idea that only a small group of people deserve laws protecting their jobs from automation, particularly not at the expense of the rest of us. If we want to grant people relief from having their jobs automated away, we need to be doing that for everybody, and the answer to that isn't copyright law.

And as far as AI being used to automate dangerous jobs, copyright isn't going to stop that at all. Tesla's dangerous auto-pilot function (honestly, I have no idea if that's a neural network or just a regular computer program) uses data that Tesla gathers themselves. Any pharmaceutical company that develops an AI for making medicines will train it on their own trade secrets. Same with AI surgeons, AI-operated heavy machinery, and so on. None of that is going to be affected by copyright, and public concerns about safety aren't going to get in the way of stockholders and their profits anymore than it has in the past. If you want to talk about the dangers of overreliance on AI doing dangerous work, then by all means talk about that. This copyright fight, for those large companies, is a beneficial distraction.

You need to do your own homework. I'm not doing it for you. What I will do is lay this to rest:

https://en.wikipedia.org/wiki/Stable_Diffusion

Stable Diffusion is a latent diffusion model, a kind of deep generative artificial neural network. Its code and model weights have been released publicly [...]

https://jalammar.github.io/illustrated-stable-diffusion/

The image information creator works completely in the image information space (or latent space). We’ll talk more about what that means later in the post. This property makes it faster than previous diffusion models that worked in pixel space. In technical terms, this component is made up of a UNet neural network and a scheduling algorithm.

[...]

With this we come to see the three main components (each with its own neural network) that make up Stable Diffusion:

  • [...]

https://stable-diffusion-art.com/how-stable-diffusion-work/

The idea of reverse diffusion is undoubtedly clever and elegant. But the million-dollar question is, “How can it be done?”

To reverse the diffusion, we need to know how much noise is added to an image. The answer is teaching a neural network model to predict the noise added. It is called the noise predictor in Stable Diffusion. It is a U-Net model. The training goes as follows.

[...]

It is done using a technique called the variational autoencoder. Yes, that’s precisely what the VAE files are, but I will make it crystal clear later.

The Variational Autoencoder (VAE) neural network has two parts: (1) an encoder and (2) a decoder. The encoder compresses an image to a lower dimensional representation in the latent space. The decoder restores the image from the latent space.

https://www.pcguide.com/apps/how-does-stable-diffusion-work/

Stable Diffusion is a generative model that uses deep learning to create images from text. The model is based on a neural network architecture that can learn to map text descriptions to image features. This means it can create an image matching the input text description.

https://www.vegaitglobal.com/media-center/knowledge-base/what-is-stable-diffusion-and-how-does-it-work

Forward diffusion process is the process where more and more noise is added to the picture. Therefore, the image is taken and the noise is added in t different temporal steps where in the point T, the whole image is just the noise. Backward diffusion is a reversed process when compared to forward diffusion process where the noise from the temporal step t is iteratively removed in temporal step t-1. This process is repeated until the entire noise has been removed from the image using U-Net convolutional neural network which is, besides all of its applications in machine and deep learning, also trained to estimate the amount of noise on the image.

So, I'll have to give you that you're trivially right that Stable Diffusion does use a Markov Chain, but as it turns out, I had the same misconception as you did, that that was some sort of mathematical equation. A markov chain is actually just a process where each step depends only on the step immediately before it, and it most certainly doesn't mean that you're right about Stable Diffusion not using a neural network. Stable Diffusion works by feeding the prompt and partly denoised image into the neural network over some given number of steps (it can do it in a single step, although the results are usually pretty messy). That in and of itself is a Markov chain. However, the piece that's actually doing the real work (that essentially does a Rorschach test over and over) is a neural network.

[–] IncognitoErgoSum@kbin.social 1 points 1 year ago (2 children)

When did I refuse to admit automation causes problems for people?

[–] IncognitoErgoSum@kbin.social 1 points 1 year ago (4 children)

So most of my opinions about what AI can do aren't about hype at all, but what I've personally experienced with it firsthand. The news, frankly, is just as bad a source about AI is marketing departments of AI companies, because the news is primarily written by people who feel threatened by its existence and are rationalizing reasons that it's bad, as well as amplifying bad things that they hear and, in the best case, reporting on it without really understanding what it actually does. The news is partly why you're connecting what's happening with that WGA/SAG-AFTRA contract; nothing I've said here supports people losing their existing rights to their own likenesses, and the reason they're trying to slip it into the contracts is because even under existing copyright law, AI isn't a get out of jail free card to produce copyrighted works despite the fact that you can train it on them.

At any rate, here are a few of my personal experiences with using AI:

  • I've used AI art generation to create background art for a video game that I made with my kids over winter break, and because of that, it looks really good. It would have otherwise looked pretty bad.
  • For my online tabletop roleplaying campaign, I generate images of original locations and NPCs.
  • I subscribe to ChatGPT and because of that I have access to the GPT-4 version, which is leaps and bounds smarter than GPT-3 (although it's still like talking to some kind of savant who knows a whole lot of information but has trouble with certain types of reasoning). While ChatGPT isn't something you should use to write your legal briefs (I could have told you that before that dumbass lawyer even tried it), it's an amazing replacement for google, which nowadays involves a lot of fiddling and putting quotations marks around things just so you can get a result that's actually addressing what you want to know as opposed to "here's a bunch of vaguely related shit that has almost nothing to do with what you asked." That alone has improved my life.\
  • It's also great at helping you figure out what something is called. "I'm looking for a thing that does X and Y, but I don't know what it's called." Google is absolutely terrible at that.
  • I've used ChatGPT to generate custom one-shot adventure ideas for my online roleplaying game. Rather than having to adapt an existing adventure module to what I'm doing, if I give it information about my campaign, it'll come up with something that utilizes my existing locations, NPCs, and setting. (Indicentally, when people say that AI "can't be creative", they're essentially using a tautological definition of creativity that amount so "AI isn't creative because only humans can be creative, therefore AI can't be creative." AI, in my experience, is very creative.) Compare this to the common advice that people give to game masters who can't come up with an idea: take someone else's story, change a few things, and drop it into your campaign. ChatGPT is also amazing at worldbuilding.

This kind of thing is why I'm excited about AI -- it's improving my life in a big way right now. None of what I've done with it is "hype". I don't care that Elon Musk's dumb ass is starting his own AI company, or what tech company marketing divisions have to say about it, or what some MBA CEO's wild guess about what we'll be using it for in 5 years is.

[–] IncognitoErgoSum@kbin.social 1 points 1 year ago* (last edited 1 year ago) (6 children)

So what does that mean? Do you not believe that AIs like ChatGPT and Stable Diffusion have neural networks that are made up of simulated neurons? Or are you saying that we haven't simulated an actual human brain? Because the former is factually incorrect, and I never claimed the latter. Please explain exactly what "hype" you believe I'm buying into? Because I don't think you have any clue what it is you think I'm wrong about. You just really don't want me to be right.

Ok.

Again, though, why make the ridiculous comparison of AI to steak? If you eat a steak or hamburger once a week (which I don't, because believe it or not I actually know the environmental impact of it), you use orders of magnitude more energy than using chatgpt or stable diffusion.

[–] IncognitoErgoSum@kbin.social 3 points 1 year ago (8 children)

What, specifically, do you think I'm wrong about?

If it's the future potential of AI, that's just a guess. AGI could be 100 years away (or financially impossible) as easily as it could be 5 years. AGI is in the future still, and nobody is really qualified to guess when it'll come to fruition.

If you think I'm wrong about the present potential of AI, I've already seen individuals with no budget use it to express themselves in ways that would have required an entire team and lots of money, and that's where I believe its real potential right now lies. That is, opening up the possibility for regular period to express themselves in ways that were impossible for them before. If Disney starts replacing animators with AI, I'll be right there with you boycotting them. AI should be for everyone, not for large corporations that can already afford to express themselves however they want.

If you think I'm wrong that AIs like ChatGPT and Stable Diffusion do their computing with simulated neurons, let me know and I'll try to find some literature about it from the source. I've had a lot of AI haters confidently tell me that it doesn't (including in this thread), and I don't know if you're in that camp or not.

[–] IncognitoErgoSum@kbin.social 2 points 1 year ago (2 children)

That word has been around since at least the 1980s.

 

I know a lot of people want to interpret copyright law so that allowing a machine to learn concepts from a copyrighted work is copyright infringement, but I think what people will need to consider is that all that's going to do is keep AI out of the hands of regular people and place it specifically in the hands of people and organizations who are wealthy and powerful enough to train it for their own use.

If this isn't actually what you want, then what's your game plan for placing copyright restrictions on AI training that will actually work? Have you considered how it's likely to play out? Are you going to be able to stop Elon Musk, Mark Zuckerberg, and the NSA from training an AI on whatever they want and using it to push propaganda on the public? As far as I can tell, all that copyright restrictions will accomplish to to concentrate the power of AI (which we're only beginning to explore) in the hands of the sorts of people who are the least likely to want to do anything good with it.

I know I'm posting this in a hostile space, and I'm sure a lot of people here disagree with my opinion on how copyright should (and should not) apply to AI training, and that's fine (the jury is literally still out on that). What I'm interested in is what your end game is. How do you expect things to actually work out if you get the laws that you want? I would personally argue that an outcome where Mark Zuckerberg gets AI and the rest of us don't is the absolute worst possibility.

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