lt

Of course it learned, that's the point of training.

You claimed the model can reproduce an image from that training data. That's false, and what the judge dismissed.

  “none of the Stable Diffusion output images provided in response to a 
  particular Text Prompt is likely to be a close match for any specific image in  
  the training data.”

  “I am not convinced that copyright claims based a derivative theory can 
  survive absent ‘substantial similarity’ type allegations,” the ruling stated. 

Whether using copyrighted data to train a model is fair use or not is a different discussion.

A diffusion model can't make a copy. That's the whole point. The original Picasso isn't in the model weights.

It has learned to make pixels a particular color to mimic that style, but that's it.

As I've read it, the first lead to the material was 99.

2018 They got funding to research it further,

2020 was a first attempt of publication at Nature that was retracted, further improvements were made until 22/23 were two patents were filled, then suddenly 10 days ago Kwon, one of the co-researchers jumped the gun publishing a paper with the details, on one hand fearing a leak of someone else publishing first as that was too simple to replicate, on the other hand excluding everyone else from the paper and only listing him and Lee/Kim (LK) as authors as a Nobel prize can only be shared by three people. 2.5hrs later LK published again listing other 5 authors but him.

The contents of whatever it found online is fed back in the context, plus the response it generates based on that also counts to the limit.

So 512 is really inadequate unless you just want to make search queries using natural language.

they point openai.api_base to their server that implements the same API

I see three perspectives on the whole thing:

First, Reddit's monetization is broken by design. It never made any sense to me why they would charge for reddit gold for an ad-free experience on their website and own mobile app but not on the API. Why would they let third party apps serve their own ads and let them charge to remove them? This would be simple to fix, both technically and in the API's ToS, just serve the same ads regardless of the client. People would be upset, but ultimately I feel it would be entirely fair. But no, it doesn't seem to be a solution considered.

Second, the LLM dataset issue is also attributed to the price hike. Again, I think it's fair if unpopular to charge premium for bulk data. Again, there are technical and ToS solutions for this. They could introduce exponential tiers for bulk data, restrictions on allowed usage, other things that make user-facing usage reasonable but bulk processing expensive, but then again, starting measuring api usage per client id and not per user goes against this point, just making the API extremely expensive for everyone anywhere to the point of being unusable.

Third, all points seem to lead to the fact that what they really want is to kill third party apps and hope a large part of those users move to their app, for what? More tracking, tighter grip, better engagement metrics? Not sure. Even the changes to the extremely hostile mobile site now forcing some users to download the app. Really, I'd figure they'd understand their userbase better than that and how a small fraction on content producers and a even smaller fraction of power users and moderators carry the site, and pissing them off is a really bad idea. But what do I know.

Not to mention it’s actually the users generating the content.

Recently I read Reddit has over 2000 employees. I can’t begin to imagine what they possibly do.

Can you elaborate about what you mean by pressure testing? Haven't heard this term yet.

Not sure if that was a typo or the joke, but hilarious nonetheless

It's a little confusing, but as far as a understand it, Stable Diffusion was created by a collaboration between RunwayML and Compvis (aka Machine Vision and Learning research group at Ludwig Maximilian University of Munich) with Stability.AI funding the computing power for training and LAION.AI (also funded by Stability.AI) providing the dataset.

The first few releases of model and code have been done by Compvis, and this one by RunwayML. More than permitted by the license, this seems to have been released by the actual developers.

I've seen speculation that it has been released this way to provide distance between Stability.AI from eventual future litigations, but it feels more like an internal ultimatum deadline.

How'd you compare banana.dev to inferrd and paperspace which seem more affordable at a glance?

Myself, I got down this rabbit hole when reading about Sublime history. "Caress Me Down" features the sleng teng riddim.

As far as I understood, your editorialized title is what they've been doing every two years since ever.

A possible better editorialized title would be

Creating a parallel kernel so we can continually rebase commits instead of every two years