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naraburns  nihil supernum  1yr ago (text post)   35438 thread views

Culture War Roundup for the week of October 3, 2022

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My greatest fear for AI content generation is it being dominated by woke megacorps, with independent creators permanently locked out of contributing to culture. It looks like Google is investing heavily in that dystopia.

Novelai and stable diffusion being mostly uncensored has been a big white pill so far, but it feels like the shoe is about to drop.

Everyone rapidly generating nonsense with AI is not my ideal world

It is mine. The internet should be nonsense.

I think the day is approaching where you won’t be able to tell if anyone you’re interacting with online is even real or not, and I hope when that happens I’ll just be fed up enough to put it all aside and just stop even coming online to see what people have to say anymore.

If you can't tell if anyone you're interacting with online is real, that means that the best content online can be mass produced by AI. That would be awesome. I could spend all day watching the top-rated 0.0000001% of Youtube videos on the exact subject I want to see. I could read a thousand books that are equally as good as the best books I've ever read, in the exact genre I want to read.

If you haven't spent a few hours playing with Stable Diffusion, I highly recommend it. It's like a whole new world is opening up.

"A political drama about the Nixon administration in the style of Shakespeare," could be a click away. "A gorey superhero deconstruction like Invincible or The Boys, as written by James Joyce, as an animated film in the style of a Disney Movie, with watercolour art style," could be something you can watch just by typing that prompt into a computer. "An Isekai anime with writing by J RR Tolkien, music by Metallica, and art by Gerald Scarfe" could be yours too. In fact, if you generate it and then delete it, you could be the only human being ever to watch it.

I'd love to do stuff like that but I'm not sure we'd have the computing power before singularity.

Stable Diffusion runs decently on my 1060 6GB since I'm patient. But text is impossible for even those with a 4090TI! You need serious industrial-grade hardware for GPT-3. Fusing GPT-3 to better image-gen, turning it into a video and letting it have the memory for an entire story would require absolutely gargantuan computing power. Only big companies could afford it and you'd still have to sift through the bad prompts.

If google causes people to not take the internet seriously I think they will deserve a Nobel peace prize.

It’s a hopeful future for sure ☺️

in accelerationist Bane voice Our plan is proceeding as expected.

I don't know that your definition of "nonsense" is universal enough to apply here, but what do you think humans do right now WITHOUT AI?

Good point, we’re all already just rapidly generating nonsense 😂

My greatest fear for AI content generation is it being dominated by woke megacorps, with independent creators permanently locked out of contributing to culture.

I'm confused by this statement. How does it "lock independent creators out of contributing to culture" if only megacorps have AI tools?

Is it because you think it's impossible to produce content without using AI? That's obviously false. People have produced petabytes of content without using AI.

Is it because you think megacorps will flood the world with AI-generated content and independent creators will get drowned out and won't get noticed? That concern also doesn't really make sense. If you're worried about getting drowned out by just a few megacorps, then giving everyone access to the tools will just allow everyone to flood the world with even more content, exacerbating the problem.

EDIT: Not sure why this is getting downvoted. This isn’t supposed to be a gotcha. I really don’t understand the concern here. I mean, I assume the intuitive concern is “the megacorps have all the AI tools and I don’t and that’s not fair”, I just think that under closer examination, you can’t say that you’re “locked out of contributing to culture” in that situation.

The reasoning seems pretty simple to me. AI is an extremely powerful tool by which greatly reduces the effort involved in creating high quality art. Without it, people won't be literally "locked out," but the much higher barrier to entry and costs would mean that it would be immensely harder for independent creators to contribute high quality art at a meaningful level.

An analogy might be if only a select few megacorps had access to cameras. Independent creators could still learn to draw photorealistic drawings or perhaps hack together some sort of crude camera system, but compared to megacorps that can just have their employees snap a 20 Megapixel photo with their DSLRs, the quality and quantity of content independent creators could produce would be lower by a tremendous amount. In such a universe, the culture of photography and more generally photorealistic art would likely be dominated by megacorps.

FYI: I wasn't going to downvote your comment until I got to the EDIT part. Then I did, because any post that makes any references about its (or its author's) downvote status is one that I always downvote, regardless of the rest of the contents.

If you're worried about getting drowned out by just a few megacorps, then giving everyone access to the tools will just allow everyone to flood the world with even more content, exacerbating the problem.

Does not work that way. Content reach follows a power law in which the tail end gets nothing or little. The median is zero, the mean possibly skewed by outliers. Ranking algorithms tend to promote that which is already popular, making the problem worse.

I agree with what you said, but I don’t see how it’s relevant to the question of whether one is “locked out of contributing to culture” or not.

Agreed, but there's cause for optimism: MosaicML shows that large models can be a whole lot cheaper to train than previously believed. Half a million for a GPT-3 equivalent is... well, you know. It's not limited to GPT type systems either.

Also, the Chinese are being pretty nice as of late.

I'll admit this tweet made me nervous for a while. Mysteriously falling down stairs and quietly going off stage «to take care of personal problems and improve health» is something I 100% expect to happen to disturbers of the General Arc Of History. Emad ain't it yet, it seems.

But even if all of those failure modes are avoided, corporations still have the advantage: PR, established distribution channels, and the general problem of there being way, way too much content being produced. People will go watch the latest Marvel capeshit to keep in touch with each other, and in addition to that, they'll consoom a hundred medium-scale indie creations and fifteen thousand TikToks a year. Each one's own unique set.

Even if the total fraction of the indie content increases, it may only contribute to the relative dominance of the mainstream, astroturfed, censored culture.

Yeah I expect within two years we will see news articles cataloguing white supremacist rhetoric and imagery in ai generated art, which will necessitate handing over all access of them to the elites. And if somehow there is no white supremacist rhetoric or imagery to be found, it will be created.

handed to employer. I can see people being framed with this technology.

CP is my bet for the excuse. Which is going to come organically as soon as any of those remaining guys with big collections start training models on identifiable girls. Assuming there are any of those guys left who weren't rounded up when tor was torpedoed (... Tor-depedoed?)

Doesn't even need that. The furry AI-gen Discord I've been seeing has banned img2img starting from real people, including the poster furrifying themselves, out of (very reasonable!*) concerns about what happens if someone underage applies a model to a clothed picture of themselves. Not a can of worms they want to open, or be within a hundred miles of anyone opening.

Wait, they're letting minors into the discord for a porn generation program, or am I misunderstanding?

It's so weird how on edge people get about this stuff these days. I guess it's the one remaining taboo after normalizing anal vore ferrets or whatever. When I was a boy furries would offer me a kids' discount on the "draw you a fursona for nudes" payment plan, and the community still felt less sketchy than it does now.

No, there's a very hard "you must be 18 years old to be in here" rule, although in practice it's pretty hard to enforce. There's also a separate rule that no matter what your age is, they don't want img2img-based pictures, because someone sneaking into an adult movie theatre is bad but starring in a role is much much worse, and that's something they want to enforce at pretty high cost.

Uh, "draw you a nude fursona" or "draw you a fursona in exchange for your nudes"?

Wait, they're letting minors into the discord for a porn generation program, or am I misunderstanding?

Can't keep them out unless you want to ID check everyone, and that would be a huge hassle even if people went along with it.

The latter. Good thing I didn't have a digital camera as a kid, or I'd have been morally and legally responsible for the creation of a lot of furry art. The guilt would be crushing.

The biggest creator in podcasts is anti-woke and is employed by a company that has stood up to the woke, that being Rogan and Spotify. Same for Elon and Twitter (although twitter is woke). It does not have to lead to a dystopian end. So the anti-woke have huge audiences, assuming they can find a platform like with Rogan and Spotify. SD is just a technology, not a platform. Even if google wanted to censor it, there is nothing stopping a competing team from copying /replicating the core technology elsewhere...like Ethereum vs. Bitcoin (assuming it's open source, which Tensor Flow is).

Joe Rogan is no longer the biggest creator in podcasting. He stopped making podcasts 2 years ago.

  • -17

Uhh. A 2 hour 52 minute podcast featuring Jann Wenner came out today...

Could you link to the RSS feed?

Spotify Only

https://open.spotify.com/show/4rOoJ6Egrf8K2IrywzwOMk

Then it's not a podcast. It's some streaming service.

  • -17

Its a podcast on a platform...

I'm fairly sure you can get it elsewhere as well, its just less easy than using spotify. Is The Lion King not a movie because you only get it from Disney?

If you have a way to listen to Rogan without a Spotify account or app, I'd love to hear it.

Not an RSS feed, not a podcast. Not sure how movies are relevant.

It is telling that Google's practical use of AI (from what I've experienced) is always a downgrade compared to nothing at all. Searches now use AI to try to gauge what you really want from a search, but this makes searching for specific strings of text worse than it was a decade ago. And what they've done with YouTube is a travesty; half the time if I reply to a comment with a paragraph of text their malicious/harmful/offensive(?) text AI detector automatically deletes it because (I assume) it doesn't like some combination of words I used. I don't trust Google with employing any kind of AI.

From a profit-maximizing perspective, Google should push for an extremely regulated environment for generative models, to protect us from the fake news/deep fake revenge porn/violence/Russian bots/racism/sexism/copyright violation. Put up large barriers to entry, have the government restrict access to training data and maybe even GPUs, and then claim all the profits for themselves.

There is an easier solution to this, AIs can be trained by anyone with enough computing power and training AI isn't that expensive. AI is actually fairly democratic as everyone can make their own. Once the cat is out of the box it isn't hard for everyone to get it. Information spreads naturally. The big risk is big corporations and governments access to data to use the AI on. That can give them a tremendous advantage.

Tuning is relatively cheap, but initial training is (currently) expensive. The furry StableDiffusion tweaks probably cost 50-400 USD depending on vendor and management, but the initial StableDiffusion model they're based on reflects ~300k USD at official prices (although probably got at least some bulk discounting).

Some of that'll go down as GPU prices decrease and newer equipment becomes available, but there are some costs for bandwidth and energy that are slower to change. This might go from 'old condo' to 'new car', but it's not likely to go to 'vacation' or 'a couple weeks' savings' for a few years, maybe even the better part of a decade, without dramatic changes to the underlying code.

For data, it varies more. LAOIN's a lot of bandwidth, curation, and drive space, but it's... actually not that incredible for a single (if slightly nuts) person. Other data sources, probably less so, either due to scale (eg video), to availability (eg privacy), or to more esoteric causes (AI music is a legal clusterfuck).

but the initial StableDiffusion model they're based on reflects ~300k USD at official prices (although probably got at least some bulk discounting).

I mean... this is cheap as hell in the scheme of things. It means you only need one startup with a medium sized seed round who sees a strategic advantage in commoditizing that model, and presto, it'll be trained and released. In fact that's exactly the story behind Stable Diffusion.

The reason we don't see a lot of open source models yet is... well, actually, we do see a lot of open source models. GPT-2 is publicly available, Facebook released a large language model roughly equivalent to GPT-3, and the Eleuther crowd also trained and released a large language model. OpenAI just released an open-source speech-to-text model, they already released CLIP as open source (which powers Stable Diffusion and Craiyon among others), StyleGANs 1, 2, 2-ADA and 3 are all publicly available and open source, etc. These models are just a year or two behind the current research papers. Which is about how long it probably takes to reproduce a research paper. Some of them are even better than that, even cutting edge -- like Nvidia's StyleGANs when they were released, like OpenAI's Whisper, like Nvidia's new Get3D.

Yeah, that's fair. I do think it's meaningful if it requires a startup with a medium-sized seed round (or someone willing to risk their retirement), rather than a slightly nutty hobbyist or enthuisiast, but it's not a FAANG-only thing, at least at a lot of common levels.

Well, there are a fair number of wealthy machine learning hobbyists out there. None of them have actually funded this type of thing to date as far as I know, but I could totally imagine some centimillionaire setting up a few-million-dollar charity to just train models and release them based on research as it emerges.

AI music is a legal clusterfuck

Why, exactly, is it more of a legal clusterfuck than AI art?

Copyright's a mess in general, but the de minimis doctrine has been more heavily tested for sampling than for art collage, and while nowhere near the power it had at its height, the RIAA is far more aggressive than its visual art equivalents.

I assume this implicitly includes the infamous "Blurred Lines" case?

This might go from 'old condo' to 'new car', but it's not likely to go to 'vacation' or 'a couple weeks' savings' for a few years, maybe even the better part of a decade, without dramatic changes to the underlying code.

Completely naïve question: Would it be plausible to rig up something distributed, like the seti@home in days of yore or (shudder) crypto-farming?

To a limited extent. Several training tools (eg W&B) have built-in distributed training capabilities, although these are generally intended for local networks. There are some tradeoffs, though. Even small datasets are 100+GB (eg, the 200k images uses to tune the furry branch) and LAION is 80TB for the curated data, plus a bit more for tag info. You're not going to distribute that full set to every volunteer (might not even train on it!), but it's a scope of the bandwidth costs. Synchronization at that epoch size isn't hugely expensive, but it does slow you down and/or waste power depending on approach.

Unfortunately, the biggest problem is that models have minimum VRAM requirements to run even at a batch size of 1, and these amounts are pretty high at the cutting edge. The original CompVis version of Stable Diffusion required 20+GB of VRAM to train, and this largely limited it to 10k USD or higher specialist 'tensor core' gpus, which largely meant there'd be no @home to distribute to. There's some wiggle room here related to how you code the training, what level of precision you use, and how some averaging and back-propagation happens, and I've heard people suspect they might be able to get full training of current StableDiffusion around 8GB (right now, only textual inversion and tuning is implemented at that range, but the optimization should generalize), albeit at large CPU-RAM and small-but-significant performance costs. Which gets to some consumer-grade GPUs, but not a ton. It's possible people would come up with better optimizations than even that were there no alternative, but I'm skeptical that there'll be the demand now, between Google Colab and nVidia 3090s being available.

And that amount scales both with parameter count and training image resolution. It's suspected that at least part of the better output quality from NovelAI comes from their ability to train on uncropped data, rather than just 512px by 512px cropped or downscaled images, but this bloats run requirements out further.

Enthusiasts are unlikely to want to make huge models anyway since inference (ie, running the model) has similar-if-smaller VRAM requirements, but at least for image generation it looks like the minimum sweet spot is at least 6GB runtime inference.

Other clever stuff may run into similar problems... there's a fascinating 2d-3d analysis package at GET3D, but in addition to limits on accessing the pretrained model, probably requires all 16GB to run or train at any speed. There's probably some unexplored low-hanging fruit, but there's also probably a lot of clever-but-inaccessible stuff.

Does FSDP help at all here? My very naive understanding is that its approach allows sharding of the model parameters so that they don't have to all fit into VRAM, though I wouldn't be surprised if it couldn't scale down to arbitrarily low VRAM or scale up to arbitrary numbers of parameters. Perhaps a similar strategy could be used for wide scale distributed learning on consumer hardware.

I believe so, but I've not looked too closely at that tech to know what its limits are. From a quick glance, it seems likely that there would be some CPU-RAM, performance, and synchronization costs. But it likely could lower the floor.

Even if we assume the high-end of your range, and say that for the foreseeable future training a near-state-of-the-art deep learning model from scratch will cost around half a million dollars, that's still cheap enough to be considered fairly democratic. A lot of people and organisations have that sort of money, many of which exist outside of the Cathedral. And as you say, you can do a lot by tuning an existing model, which is feasible for hobbyists.

I think for the sort of controls you're worried about, it's not just a matter of who can afford to buy it, but also who can afford to sell it. Not just that there's a few limited companies doing this stuff, but in the sense that if you come up to the sorta companies that have and resell these resources, they demonstrably will start poking around at what you're doing, how you're paying them, and what you're doing.

((Not... uh, very effectively in an anti-fraud sense, given Amazon. But very effectively in a not-doing-things-they-don't-like, given Amazon.))

Eventually that stops being a problem as used past-generation tensor core GPUs trickle out into the used market (uh, assuming ITAR doesn't get involved), or as resellers are able to more heavily obscure stuff at larger scales, or as the relative scales decrease due to performance and efficiency gains.

But it is worth keeping in mind as a limit to the democratization of the space.

It's also possible that manufacturers could nerf GPUs for the purpose of ML except for customers with whom they have a special relationship. See e.g. the rate limiting NVIDIA did for crypto mining while still selling a higher priced card without the nerfing.

Yeah, that's another risk. It didn't work for the anti-mining stuff, but given politics and economics around ML that may have stronger incentives.

Crippling GPUs works very well in one context I've seen: FP64. Games don't use it so manufacturers don't get dinged for having lousy performance with it, and engineers/mathematicians/scientists won't flinch at paying through the nose for "professional" GPGPU cards, so with a few exceptions (Titan Black, Radeon VII, and even those were high-end) you get a pittance of FP64 support on consumer cards.

But there's a very well-delineated difference between 32-bit and 64-bit floats. What's the clear technical difference between "bad ML models, which we want to keep away from hobbyists" and "good ML models, which everybody's going to be throwing into their game engines as fast as studios can train them"? The difficulty of slowing down "bad" algorithms but not "good" ones was effectively the problem with crypto rate limiting, (which only brought the cards down to 50% speed and only worked on some crypto types and was quickly foiled via driver or BIOS changes), not any special societal support for cryptocurrency. Compare DRM, which despite massive political and economic support gets broken over and over again because from a technical standpoint the problem statement is almost a self-contradiction.

Yeah, that's plausible. So far, it's been possible to prune down to 16 or even 8-bytes-per, but it's definitely something that takes some tweaking to do right, and may not be possible for all or even most useful models.

i hate to be a doomer but the corporate overlords have all the cards in this game. The hardware requirements for training AI are already giant, but will likely grow even more as the state of the art seeks greater accuracy/breadth of expression/context retention. I imagine there will always be a market for a scrappy underdog like SD but the super-sick next gen stuff is always gonna be locked down by google or someone with similarly censorious ideology.

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