This is cool and fixes a very big need I have. I often use Comfy as a shortcut to generating content in a larger pipeline and the JSONified API is OK, but not the easiest to use. Node graphs are just complicated and difficult to edit in the JSON form. Love this! Now if someone would point me toward a way to better pass binary data to/from comfy I'll be a happy camper.
We don't train any models, we're just bringing existing AI models to the VFX workflow. The choice of models and technologies is up to the individual artists .
We're working on demo videos and will be releasing regular content updates at our Youtube channel https://www.youtube.com/@deepmakeai soon. Bear with us as we get everything up and running.
You can still try it with Llama, and no it wasn't the full text of the page, or even very accurate. Even the "popular" quotes were VERY likely to be paraphrased and missing any poetry or cadence of the original.
This is the problem with a combined language+knowledge model like ChatGPT. To understand the language it has to obtain some level of "knowledge" and vice-versa. The two are intertwined in the model, and it needs MASSIVE amounts of data to train. Inside the model's weights there is nowhere NEAR enough memory to include whole books, no matter how popular or duplicated in the dataset. Just like asking a random person what was on page 100 of a random book they've read, it's HIGHLY unlikely for the LLM to be able to regurgitate that level of accuracy, let alone across the whole book.
"Cliff Note" style content sometimes outsells the content they're summarizing. LLMs aren't a new problem, the internet did that already. In fact, they're really LESS likely to provide a large amount of the original content.
I do agree on the fact that the current laws aren't going to work for this context, especially bad is trying to fit the new challenges to copyright laws.
In fact, it's the same legal team basically making the same argument again. They're just repeating the same play hoping to get more chances at the huge nest-egg that OpenAI has.
You know what else stores nearly verbatim copies of texts and then regurgitates those to the public often including direct quotes from the text? Cliff Notes.
Those aren't copyright violations. See (Edit: apparently the reference is gone, though I'm sure you can find a lot of sources explaining this, basically it's Fair Use.) for a great in depth analysis of the legality.
Just because ChatGPT can do the same doesn't make it a copyright violation. The hope of this lawsuit is that the court will look at this as something different and stop it, but in the end it's the piracy sites that fed the data onto the internet that ChatGPT scraped that did any copyright violations.
These lawsuits seem to be missing the point. Copyright protects their right to copies and the piracy sites are OBVIOUSLY at fault here, but there is a good argument that OpenAI's work in transformative and that they're not liable for copyright violations.
One argument this law firm has made is that ChatGPT can summarize the books, so it must have read them. This is spurious and meaningless as many sources summarize books and some like cliff notes actively sell summaries and analysis of books!
In the end, I think we need to follow Japan and say that AI training is transformative and not a copyright issue.
One clarification: That is training an AI where the training data isn't returned directly, but instead it works off of it.
These lawsuits seem to be missing the point. Copyright protects their right to copies and the piracy sites are OBVIOUSLY at fault here, but there is a good argument that OpenAI's work in transformative and that they're not liable for copyright violations.
One argument this law firm has made is that ChatGPT can summarize the books, so it must have read them. This is spurious and meaningless as many sources summarize books and some like cliff notes actively sell summaries and analysis of books!
In the end, I think we need to follow Japan and say that AI training is transformative and not a copyright issue.
One clarification: That is training an AI where the training data isn't returned directly, but instead it works off of it.
UX is always a major question with Open Source. Strangely, according to the examples posted, FOSS seems to be the ones working hardest on making UX better, but always seems to fall behind.
What are the secrets of UX that we seem to be missing? There has to be something we can do to make FOSS software "easy" like commercial tools have the reputation for.
Is the ease of use just familiarity with the software that you've used? How can FOSS overcome that challenge then since those users will never move beyond the first tool they get used to?
Llama is a very cool language model, it being used for coding was all but inevitable. I especially love it being released open for everyone.
I do wonder about how much use it'll get, seeing as running a heavy language model on local hardware is kinda unlikely for most developers. Not everyone is runnning a system powerful enough to equip big AIs like this. I also doubt that companies are going to set up large AIs for their devs. It's just a weird positioning.
I came here thinking they were removing the PGP package from PyPi, but they're just removing a barely-used signature system? I don't know why they have to remove it though. I doubt it requires much maintenance now that it's already in place.
Even if only 37% of keys are verifiable, that's infinitely more than will be verifiable if they remove the PGP support.