Yeah, you can stop pretending that the neutering is the right thing to do, clearly it's something you somehow are forced to do, due to some serious threat your received.

I don't see how NSFW photos can easily be stopped from being generated, with the model being open source. Maybe the model could be heavily pre-filtered to remove any photos that could possibly be used for NSFW images.

I tend to thinking they are co-joined, but clarity helps.

I think the social harms side, they need to be careful to under-promise and over-deliver. The likelihood of preventing social harms is frankly close to zero, what they can do is make it more complicated.

Think like this: use stable diffusion to make one "actor" dance a lambada in the left field and save it. in a new state, make a different "actor" dance a lambada in the "right" field. Now using alpha masks combine the two actors. Can this represent sexy dancing? you bet your sweet bippy.

Promising not to release "two person sexy dancing" in this situation would be over-promising. Sure, it was done outside of the AI by masks. Will the law makers care?

(for actor and lambada and sexy dance, substitute whatever contextually means "harm" in a two-actor situation, semantically)

Who are these regulators?

With hardware prices going down and new GPUs and better algorithms coming to light, it’s only a matter of few years until anybody will be able to train custom versions as powerful as today’s AI, without protections, probably biased, etc.

Sure, they will be 5-10 years behind big corps, but it won’t matter once poorman AI will be good enough to matter.

Their new handlers can do anything to the contrary and are incentivized to curb release as well. The market is saying their new handlers are going to do that.

So we enjoy you proving us wrong!

https://salsa.debian.org/deeplearning-team/ml-policy

That has to be a dig at OpenAI

Open source or not they are funded. And that funding needs to generate profit one way or the other.

This first release gave them the popular attention which they needed. It was successful.

Before this gets flagged to oblivion, this is obvious. You just have to recognise that the "regulators" and industry insiders Emad is trying to "shield" you from are enemies and ask yourself, how do I hurt them?

And reasonably technical people have zero issues, as it should be.

Media piracy has been abundant my entire life. It's never slowed down or become inaccessable.

What I would value much more is the writing, directing, editing, and acting... and you can't yet get very good quality of any of that through AI yet.

Maybe someday, but not today.

True, but that might not matter to the general public, legislators, or judges.

I just read a new article on the BBC related to this: "Deepfaked: 'They put my face on a porn video'"[1]

The person in question was not physically abused. Only a fake porn video with her face on it was released. But she was still emotionally distraught over it, and said: "You start thinking about your family," she says, holding back tears. "How would they feel if they saw this content?"

This is a real concern to a lot of people, and I doubt they'll be swayed by people pointing out that they weren't physically abused.

So, yeah, there'll likely be a massive backlash against some AI-generated content and the software that generates it, and laws will likely be made against it in some countries.

But in other countries and on the dark web it'll still exist. There's ultimately no way of stopping it, and eventually people will come to terms with its existence and widespread availability, no matter what the law of some countries says.

[1] - https://www.bbc.co.uk/news/uk-62821117

https://youtu.be/0_BBRNYInx8?t=85 This video (released yesterday) talks about how SD takes an image, converts it to latents.

You'd need to decode those latents back to an image representation and scan. (possibly other ways but that's the most straightforward I can come up with although time intensive).

Many products benefit pedophiles in one way or another. Mobile phones, computers, video editing software, cars (vans?).

"But that's ridiculous, of course we can't prohibit cars just because they can be used by criminals."

Exactly.

More specifically, researchers and hobbyists would be made criminals in this hypothetical. Why would I stop playing with ML just because someone passed a useless and poorly thought out law?

Have you monitored its temperature while using it? Did your warranty cover it?

But sure, let's talk about outputs as well. From the second source we can see this from Tyler Ochoa:

"If there's only one good way to do it, OK, then that's probably not eligible for copyright. But chances are that there's just a lot of code in [the training data] that has used the same open source solution, and that the output is going to look very similar to that. And that's just copying."

I have seen some probable copyright violations from the output of Copilot, such as comments and some certain structural similarities that might be protected, although it is hard to say. But focus on the first part of what Mr. Ochoa is saying here, which is also laid out in this quote:

“In computer programs, concerns for efficiency may limit the possible ways to achieve a particular function, making a particular expression necessary to achieving the idea. In this case, the expression is not protected by copyright."

https://en.wikipedia.org/wiki/Abstraction-Filtration-Compari...

This allows for verbatim copies if they are utilitarian in nature!

As for why we should allow verbatim copies of utilitarian features... First, let's preface this with the substantial similarity of the structure, sequence and organization as established in Whelan v. Jaslow which amongst other things says that you cannot merely change the variable names if the expressive structure of the code remains the same. Now let's imagine 10,000 software developers who all implement Dijkstra's algorithm in C and then run it through clang-format. Aside from variable names, isn't it safe to assume that many of the implementations are going to be exactly the same?

As for why it was carefully selected... more often than not when I bring these things up people who feel upset about Copilot go off to cherry-pick some random quote out of context in order to support their upset feelings. Therefore I'm highlighting the important parts as to help people look beyond their upset feelings.

This is a complicated and nuanced matter. Attempting to channel everything through the lens of "this makes me personally feel bad and must be completely wrong" does not help the discourse. It may make you popular to a certain crowd but it might be unpopular to the public at large and it might also be incoherent from a legal standpoint, akin to bashing your head against a wall at a weekly meetup of the local heads-bashing-against-walls club.

There is plenty of room for discussion on what constitutes not only the legal interpretation of fair use and the idea/expression dichotomy but also the bigger picture. The knife always cuts both ways. Would it be acceptable to the open-source community if Microsoft could stop anyone from publishing Dijkstra's algorithm in C# because they wrote it first?

The law moves slow. Even were that to happen eventually, the laws will very likely be challenged in courts, and those will take a while to be resolved.

Finally, even if the US outlaws this, there'll be plenty of other countries where it'll be legal. There's plenty of infringement of US copyright in China, for instance. The same is likely to happen in regards to AI that's illegal in the US but legal elsewhere.

By the time the law catches up, model creation may become so easy to create by individuals instead of just by deep-pocketed corporations, it may be practically impossible to stop.

Long live clopen source!

Definitions are not what matters in the end. Why doesn't the viral and restrictive element of GNU's GPL license make the license "non-open"?

Then Amazon comes in and sets up their own even easier hosting while providing none of the profits or development effort back to the original project. The AGPL is no problem because Amazon is fine to publish any changes they make, thats not an issue because the real product is the hosting and not the code.

The AGPL is easy to comply with in a way that still earns a company profit while the software authors get nothing.

Agreed that non-commercial public source or just closed source is what these people should be doing.

Funny way to admit that your original statement was flat-out wrong.

There is no separate "civil law jurisprudence" and "common law jurisprudence". Common law by itself is by definition not jurisprudence. Civil law combines aspects of statutory and common law (as one form of precedent) into a single system. Some aspects of common law even make their way into criminal law. Instead of just Googling for buzzwords, learn what they mean before you try to bluster your way through an argument with them.

Oh, you mean the very first thing I had to explain to you at the beginning of this exchange because you seemed to be ignoring it? Very little of these discussions has been about the models. Most of the discussion is about the outputs, and there the fair-use case is - as Lemley/Casey and Ochoa both concede - much weaker.

But by all means keep going on about feelings. We can all tell it's not others' feelings that are being hurt by mere disagreement.

The entire art tradition is based on copying for study, and then using our brains to convince ourselves that we've "transformed it enough" or "my reference is obscure enough that no one will know."

Now we've simplified that process, and more people are exposed to the risk. I hope that the law takes a minute to evaluate the pace of change instead of saying "ITS TOO DANGEROUS, we must BAN IT", but my hopes are low.

The iPod would not have had the impact it had without piracy.

AI thrives and depends on large amounts of clean, well labeled data.

Large corporations understand this and have hoarded data for a long time now. Some of them have also managed to label this data by millions of people through things like Recaptcha, or just by hiring lots of people to do it.

Open datasets tend to be much smaller and dirtier than small, open projects have access to.

I suppose it would be possible to, over time, collect lots of data and crowd-source some project to clean it up and label it well enough to be useful, then crowd-source the AI model training itself, but it would probably take a long time and by then corporate-owned AI models will already dominate (as they do now with MidJourney, for example, being way better in my experience than Stable Diffusion, but with time the difference will only get starker).

I'd also be concerned with such ostensibly open projects eventually going closed and commercial as IMDB did after getting lots of work by volunteers freely giving their time to writing reviews.

A fair compromise is any marketplace for clusters with good interconnect but a lot cheaper than the cloud. Tuning distributed training and network transport layer for settings not as homogeneous as the cloud will also help on top of generally good interconnect. Security is a concern.

Building on points raised by pmoriarty, being able to scrape data makes up for lacking labeled data in the era of self-supervised training. IP-hawks are now putting a damper on that option, which is why I worry this might backfire from a freedom perspective.

I even think there will be multiple initiatives like this, and there will be at least 1 big repository that accepts inputs and retrains periodically for anyone who wants the model.

This should be next on my list since my current project depends on SD model and having data backed up gives me confidence that I can get rid of all their stuff if needed.

This is part of the motivation for “foundation models”.

There’s another paradigm called student/teacher models where a randomly initialized model updates it’s weights according to another pretrained model. This could (maybe?) be used to achieve the desired effect of a model that learned in a “clean room”.

No one will go to jail, except maybe some people who get caught creating, distributing or collecting those images.

Detection becomes easier - is it pornography with a child in it?

Generation starts to become trivial - this video, but this person has the features of an X year old.

At least in the latter case no-one's actually getting raped.

Then there are narratives. They are weaved so that the suggested actions and solutions will somehow fit the interests of the participants. The narrative can be CSAM, it can be copyright of artists and owners of the training set, the narrative can be disinformation. The narrative doesn't care that current laws do not prohibit anything and that it's all legal. The narrative justifies actions the participants wanted to do because of their interests.

And finally there are actions. They can push legislations, but that's not the only tool (and yes it's slow). Companies can always comply and cooperate, especially when their interests align. Google itself is a participant, with Imagen. They can create a restrictive policy and kick things off their search engine, because that is in their interests too, not because of a narrative or legislation. Just like they profited in YouTube for every piracy site suppressed.

The interests of every single company is stacked against individuals running this at home for free. There are enough narratives to be weaved to justify actions which would stop that.

For decades, and in many countries even today, just getting paid to drive someone in your car is illegal, and you need a "taxi license". It doesn't need to make sense. We could end up with required license to use generative AI in 10 years and nobody would bat an eye after decades of propaganda and narratives.

I mean this isn't even speculative anymore after what happened with - hilariously named - OpenAI

> that many companies will, ironically, use "ethical" as a pretext to not be open.

Yes, weaponized ethics as sleight of hand for control is a common historical pattern.

In fact, generally DL is quite tolerant to label noise, especially using modern training methods such as SSL pretraining.

https://arxiv.org/pdf/1705.10694.pdf https://proceedings.neurips.cc/paper/2018/file/a19744e268754... https://proceedings.mlr.press/v97/hendrycks19a.html

Or multiple IPFS CIDs. I think you can have a "directory" (CID) that contains multiple CIDs, and only need the content hashes to build it.

You can also publish multiple CIDs and ask people to seed random ones; that's how Libgen does it (and is similar to the multiple torrents concept).

The same file can be used to seed both torrents and IPFS.

Same with CP. You have to be sick to enjoy it. Very sick.

One example of a bad thing - you could easily imagine an instagram bot that looks for pictures of people with their kids, then uses a Stable Diffusion like model to produce pictures of the people having sex with their kids, or horrible things happening to the kids, and reply to the target account. The bot might threaten to post the pictures and accuse the person of being a pedophile unless the person pays X in bitcoin (or whatever). Or, the bot could just post such pictures for fun.

I think we don't know if fake CSAM will have a good or bad effect on pedophiles and, sadly, there is no real way to reliably test that (so far as I know). Fake CSAM might placate pedophiles, or it might whet their appetite. It's hard to know what to do.

I think we will eventually get to the point where very good unrestricted image generation models are available to the general public. When that happens there will be chaos - you will live to see man-made horrors beyond your comprehension.

I’m referring to legally, sorry I should have specified.

There are way too many factors at play to simply point at porn, which is probably harder to obtain now in all honesty. I found many random porn magazines/pages as a child. Never did I ever go looking for it, but finding it was always a thrill.

People buy less magazines now (based on convenience store shelves increasingly excluding them.)

This is the right conclusion, but the logic is entirely wrong.

The reason why video games do not cause violence is that play violence is not anywhere close to the real thing, not that people firewall off fiction from reality. There's plenty of cases in which a piece of fiction has changed people's views! Crime shows are notorious for skewing how actual juries rule on cases. Perry Mason[0] taught them to expect dramatic confessions and CSI[1] taught them to weigh whiz-bang forensics over other kinds of evidence.

In the specific case of porn, there isn't really a difference between "play sex" and "real sex": they poke the same regions of your brain. And the people who are responsible for keeping actual pedophiles from reoffending are pretty much unanimous that the worst thing you can do is give them a bunch of, uh... let's call it "material". So if you're already a pedophile, giving you access to simulated CSAM won't substitute for the real thing. It'll just desensitize you to reoffending.

[0] https://en.wikipedia.org/wiki/Perry_Mason_syndrome

[1] https://en.wikipedia.org/wiki/CSI_effect

I've favoured the MIT licence for what little OSS I've published thus far. But, I'm becoming increasingly concerned that ruthless profit-above-all-else driven companies can include my (benign) work in systems that causes real harm.