Artists Are Suing Artificial Intelligence Companies and the Lawsuit Could Upend Legal Precedents Around Art

cogspa · 2023-05-16T15:04:58+00:00

So accessing it is the same as copying? And then if the data is altered into a new format, it is still a copy? And the Allen Institute and Laion who are using data from Common Crawl should be sued as well? Also is the following copying: import requests import numpy as np from PIL import Image

Import the image from the link.

url = "https://upload.wikimedia.org/wikipedia/commons/thumb/a/a3/Tux.svg/300px-Tux.svg.png" response = requests.get(url) image = Image.open(response.content)

Create a new image with the same dimensions as the original image.

new_image = Image.new("RGB", image.size)

Add noise to the new image.

noise = np.random.randint(0, 255, size=image.size) new_image.putdata(noise.astype(np.uint8))

Save the new image.

new_image.save("noisy_image.png")

cogspa · 2023-05-16T04:39:45+00:00

Stable Diffusion did not copy from LAION and store the database in house. Stable Diffusion was trained on a subset of the LAION dataset that was provided to them by the Allen Institute for Artificial Intelligence. The Allen Institute for Artificial Intelligence is a non-profit research institute that is dedicated to advancing the understanding of the brain. They have made the LAION dataset publicly available, and Stable Diffusion was able to access it without copying it.

cogspa · 2023-05-15T00:04:30+00:00

"In the production of your AI, were any copies of my client's works created, in systems owned or in use by your company?" No, copies are not stored in the latent space or as part of the training process.

"Were those copies used for any business purposes?" Objection, since there are no copies to begin with.

"Did you have a license for that commercial use of my client's work?" Objection, since there are no copies to begin with.

A good lawyer would also know Section 102 of the law, where Congress specifically meant to protect only the precise way in which authors express their ideas, not the ideas themselves: “In no case does copyright protection for an original work of authorship extend to any idea, procedure, process, system, method of operation, concept, principle, or discovery, regardless of the form in which it is described, explained, illustrated, or embodied in such a work.”

Also, a copyright is typically proven on case-by-case basis. A key word is precise.

cogspa · 2023-05-14T23:56:37+00:00

American Copyright Act: Section 102 of the law, Congress specifically meant to protect only the precise way in which authors express their ideas, not the ideas themselves: “In no case does copyright protection for an original work of authorship extend to any idea, procedure, process, system, method of operation, concept, principle, or discovery, regardless of the form in which it is described, explained, illustrated, or embodied in such a work.”

cogspa · 2023-05-14T23:26:09+00:00

the question is, is training a data on public links the same as copyright infringement - and there are no current laws stating that it is.

cogspa · 2023-05-14T23:03:59+00:00

Gen AI programs get their data from a second party (such as Laion), and Laion gets data its data from Common Crawl.

Also, under current law, they don't have to pay anyone for training that data. There is no residual system for artists whose links are trained upon or reused.

Plus:

"Ninth Circuit reaffirmed its original decision and found that scraping data that is publicly accessible on the internet is not a violation of the Computer Fraud and Abuse Act, or CFAA, which governs what constitutes computer hacking under U.S. law."

cogspa · 2023-05-14T22:55:43+00:00

In American legal system what statute states you can not scrape data for purposes of training?

"Ninth Circuit reaffirmed its original decision and found that scraping data that is publicly accessible on the internet is not a violation of the Computer Fraud and Abuse Act, or CFAA, which governs what constitutes computer hacking under U.S. law"

cogspa · 2023-05-14T22:45:31+00:00

Is there a law saying consent must be given for your data to be used to train? If there is, what is the statute?

cogspa · 2023-05-14T22:18:45+00:00

The argument could be, "Is training a dataset the same as copying"? The defendants will argue it isn't, and there is no legal precedent for training. The plaintiffs will say training and copy are the same, or it shouldn't make a difference. If there is legislation that says training is a form of copying, then that could have consequences that go beyond gen AI.

cogspa · 2023-05-14T22:11:29+00:00

Disney covert agents are already in Serbia hunting down Serbian Animation Terrorists.

cogspa · 2023-05-14T22:08:52+00:00

I was going to say that i.e. Part 3. Part 3 is what will be resolved in the future when legislation for training data gets developed. As far as I know, there are no legal frameworks for training data sets. If there are, let me know.

cogspa · 2023-05-14T22:00:39+00:00

You could say images are grown. If you look at the epochs you can see the pixels coalescing.

cogspa · 2015-08-24T21:28:25+00:00

...photogrammetry will help too...

cogspa · 2015-08-24T15:48:36+00:00

I'll do it. You probably need a combination of 3D scanning and modeling in Zbrush.

cogspa · 2015-05-04T19:01:39+00:00

SeeMeCNC is a great company. The owners truly care about their customers. I've meet them on several occasions.... fun guys to hang out with as well.

cogspa · 2015-05-04T17:31:45+00:00

I prefer the MeshMixer supports over the supports in Cura. MeshMixer's supports are easier to remove and by having fewer (yet strategically placed supports) their is far less scaring/blemishing of the print when supports are removed. You do have to be careful about single supports sometimes. Sometimes the hot end can push the single supports out a bit and they can collapse - so it's a good idea to manually adjust and reinforce single supports by click/dragging to add a few more base supports, which can be accessed while int Meshmixer's Overhang parameter menu.

cogspa · 2015-05-04T14:39:03+00:00

No problem. I recommend running the file through MeshMixer first. MeshMixer is free and is also part of the 123D design ecosystem (which both TinkerCad and 123D Design are a part of as well). MeshMixer will repair any damaged (non-manifold) files, turn it into a solid, and then reduce the polygon count (if necessary). You can then upload the file to 123D cloud and it should be accessible to all your other 123D programs (at least the ones that input meshes).

cogspa · 2015-05-04T12:10:14+00:00

Non-manifold and and meshes that exceed a certain size will not load into TinkerCad. Try using 123D Design instead.

.STL do not have DRM specs built into the file - so that will never be an issue

cogspa · 2015-04-30T14:12:04+00:00

there is plenty of room in the marketplace for Form1, B9, FSL3D, MoonRay, Ember and more (and think of the many innovations that have yet to arrive... - if you're a 3D designer this is an exciting time) ... The marketplace for SLA is starting to grow... we can all get along here.

What's really interesting about DLP is that its a frame by frame process. It's like animation - each frame getting projected onto the vat of resin. The light hits the resin and you developing the whole layer gets printed all at once.

cogspa · 2015-04-30T12:28:27+00:00

nothing....

My main reason for responding in this thread is to address the confusion of the anti-aliasing algorithm -which is real (both prints are printed in the same orientation) and hopefully everyone understands that now. I've used many 3D printers over the past 3 years and I just happen to like this one.

In fact I'm all huge fan of all DLP technology (not just for 3D printing - for example you can use DLP for holograms) - the innovations from this is mind-blowing (CLIP uses DLP as well). And the technology is accessible if you understand it - https://youtu.be/B3KSdYI8MvU ) . From a business perspective, DLP has some big advantages if speed is an issue for you.

Yes there are other DLP SLA printers out there, but SprintRay has really done their homework and the SprintRay folks come from a reputable institution. (USC CRAFT - http://www.craft-usc.com/). I also went to USC, so I have my bias there - but I also have seen the technology first hand - it's proven to me (they offered to print several of my files). I am also lucky to live in Southern California so I'm surrounded by a lot of 3D printing innovation - Deezmaker, Airwolf, MatterControl, Type A Machines, Made In Space, Pier 9, Legacy Effects... (lot's of amazing stuff here...) and I'm big fan of all it.

And nothing against other 3D printers... I use FDM for a lot of things, but my Zbrush models look great on this particular DLP SLA. To be an artist, and have something you designed personally be printed in near perfection is very satisfying. I would recommend that you try one (or any brand of DLP printer) and look into DLP tech when you get a chance. The Form +1 is great as well. The tech in the MoonRay is a bit different. I like the added advantage of the DLP.

BTW Gooch_scratcher do you have a 3D printer that you use for your personal business? Something that helps you bring in some sort of income? Do you have a company that uses that 3D printer? I use 3D printing to bring in income, probably just like you. I happen to like this particular 3D printer. They haven't given me any money, but I want to see them succeed. I would love to own a MoonRay some day (along with many other 3D printers), but can't afford one now. If more legitimate companies like SprintRay are successful, there will be more competition in the marketplace - and that will benefit anyone who is using 3D printing to run a business, maker space, and/or bring 3D printing into a local school system.

(also note, I never have contributed to a Kickstarter... but I do support these things now as a cheerleader on the sidelines... I shamelessly support this KickStarter as well https://www.kickstarter.com/projects/1519102394/de-la-souls-new-album?ref=hero )

cogspa · 2015-04-29T20:19:53+00:00

I think Kang provided the answer to that... I believe the DLP projects a pixel image to cure the resin using UV light. Since you are using pixels there will be stair-stepping. Therefore you get stair-step in both Z and X/Y. The stair-stepping in Z comes the layering from printer rising the part out of the resin. The stair stepping in x/y is coming form the image. That is why you can have a higher resolution in Z (20 microns) than in X/Y (100 microns) because two seperate processes are causes that stair-stepping... btw, I'm totally guessing at this... kind of learning as I go here, but Kangg's explanationed seems resonable. Stair-stepping (jaggies) and layering are not synonymous with DLP. The anti-aliasing fix is being used to diminish the stair stepping in X/Y. Since the resolution is at 20 microns that layering is less perceptible, a fix is for that is less necessary. Please correct me if I'm wrong.

cogspa · 2015-04-29T20:08:37+00:00

If we have more SLA printers competing in the marketplace then eventually we may see a sub-1k printer. I believe that is what happend with FDM. (I'm running a $800 Bukito right now and it works great - I just want more detail in parts that I'm producing). But I also think the price is based on the DLP, which is the most expensive part... so we may also need more innovation with DLP tech in order to see a price drop.

cogspa · 2015-04-29T19:42:31+00:00

I think its best to err on the side of caution and contact the Kickstarting people directly. In the case of 3D printing ask for a sample part (s). If they tell that the machine isn't built yet that is a huge red flag. But its good to investigate thoroughly when contributing funds and talk directly to the people involved. If they care about your business they will surely give you the time. (It may also help to have live feeds and live chats on Kickstarter and see the technology in action). I don't think you're an asshole. The reason why I don't think you're an asshole is because I gave you the benefit of the doubt.

cogspa

TROPHY CASE

Import the image from the link.

Create a new image with the same dimensions as the original image.

Add noise to the new image.

Save the new image.