Father, Hacker (Information Security Professional), Open Source Software Developer, Inventor, and 3D printing enthusiast

  • 3 Posts
  • 138 Comments
Joined 3 years ago
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Cake day: June 23rd, 2023

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  • Hard disagree. You just have to describe the shape and colors of the banana and maybe give it some dimensions. Here’s an example:

    A hyper-realistic studio photograph of a single, elongated organic object resting on a wooden surface. The object is curved into a gentle crescent arc and features a smooth, waxy, vibrant yellow skin. It has distinct longitudinal ridges running its length, giving it a soft-edged pentagonal cross-section. The bottom end tapers to a small, dark, organic nub, while the top end extends into a thick, fibrous, greenish-brown stalk that appears to have been cut from a larger cluster. The yellow surface has minute brown speckles indicating ripeness.
    

    It’s a lot of description but you’ve got 4096 tokens to play with so why not?

    Remember: AI is just a method for giving instructions to a computer. If you give it enough details, it can do the thing at least some of the time (also remember that at the heart of every gen AI model is a RNG).

    A terrible image of a banana generated by AI using a prompt that did not use the word banana

    Note: That was the first try and I didn’t even use the word “banana”.



  • What that Afghanistan girl image demonstrates is simply a lack of diversity in Midjourney’s training data. They probably only had a single image categorized as “Afghanistan girl”. So the prompt ended up with an extreme bias towards that particular set of training values.

    Having said that, Midjourney’s model is entirely proprietary so I don’t know if it works the same way as other image models.

    It’s all about statistics. For example, there were so many quotes and literal copies of the first Harry Potter book in OpenAI’s training set that you could get ChatGPT to spit out something like 70% of the book with a lot of very, very specific prompts.

    At the heart of every AI is a random number generator. If you ask it to generate an image of an Afghan girl—and it was only ever trained on a single image—it’s going to output something similar to that one image every single time.

    On the other hand, if it had thousands of images of Afghan girls you’d get more varied and original results.

    For reference, finding flaws in training data like that “Afghanistan girl” is one of the methods security researchers use to break large language models.

    Flaws like this are easy to fix once they’re found. So it’s likely that over time, image models will improve and we’ll see fewer issues like this.

    The “creativity” isn’t in the AI model itself, it’s in its use.


  • Like I said initially, how do we legally define “cloning”? I don’t think it’s possible to write a law that prevents it without also creating vastly more unintended consequences (and problems).

    Let’s take a step back for a moment to think about a more fundamental question: Do people even have the right to NOT have their voice cloned? To me, that is impersonation; which is perfectly legal (in the US). As long as you don’t make claims that it’s the actual person. That is, if you impersonate someone, you can’t claim it’s actually that person. Because that would be fraud.

    In the US—as far as I know—it’s perfectly legal to clone someone’s voice and use it however TF you want. What you can’t do is claim that it’s actually that person because that would be akin to a false endorsement.

    Realistically—from what I know about human voices—this is probably fine. Voice clones aren’t that good. The most effective method is to clone a voice and use it in a voice changer, using a voice actor that can mimick the original person’s accent and inflection. But even that has flaws that a trained ear will pick up.

    Ethically speaking, there’s really nothing wrong with cloning a voice. Because—from an ethics standpoint—it is N/A: There’s no impact. It’s meaningless; just a different way of speaking or singing.

    It feels like it might be bad to sing a song using something like Taylor Swift’s voice but in reality it’ll have no impact on her or her music-related business.


  • I’ve seen original sources reproduced that show exactly what an AI copied to make images.

    Show me. I’d honestly like to see it because it means that something very, very strange is taking place within the model that could be a vulnerability (I work insecurity).

    The closest thing to that I’ve seen is false watermarks: If the model was trained on a lot of similar images with watermarks (e.g. all images of a particular kind of fungus might have come from a handful of images that were all watermarked), the output will often have a nonsense watermark that sort of resembles the original one. This usually only happens with super specific things like when you put the latin name of a plant or tree in your prompt.

    Another thing that can commonly happen is hallucinated signatures: On any given image that’s supposed to look like a painting/drawing, image models will sometimes put a signature-looking thing in the lower right corner (because that’s where most artist signatures are placed).

    The reason why this happens isn’t because the image was directly copied from someone’s work, it’s because there’s a statistical chance that the model (when trained) associated the keywords in your prompt with some images that had such signatures. The training of models is getting better at preventing this from happening though, as they apply better bounding box filtering to the images as a pretraining step. E.g. a public domain Audibon drawing of a pelican would only use the bird itself and not the entire image (which would include the artist signature somewhere).

    The reason why the signature should not be included is because the resulting image would not be drawn by that artist. That would be tantamount to fraud (bad). Instead, what image models do (except OpenAI with ChatGPT/DALL-E) is tell the public exactly what their images were trained on. For example, they’ll usually disclose that they used ImageNET (which you yourself can download here: https://www.image-net.org/download.php ).

    Note: I’m pretty sure the full ImageNET database is also on Huggingface somewhere if you don’t want to create an account with them.

    Also note: ImageNET doesn’t actually contain images! It’s just a database of image metadata that includes bounding boxes. Volunteers—for over a decade—spent a lot of time drawing bounding boxes with labels/descriptions on public images that are available for anyone to download for free (with open licenses!). This means that if you want to train a model with ImageNET, you have to walk the database and download all the image URLs it contains.

    If anything was “stolen”, it was the time of those volunteers that created the classification system/DB in order for things like OpenCV to work so that your doorbell/security camera can tell the difference between a human and a cat.



  • If someone has never seen a banana they wouldn’t be able to draw it either.

    Also, AIs aren’t stealing anything. When you steal something you have deprived the original owner of that thing. If anything, AIs are copying things but even that isn’t accurate.

    When an image AI is trained, it reads though millions upon millions of images that live on the public Internet and for any given image it will increment a floating point value by like 0.01. That’s it. That’s all they do.

    For some reason people have this idea in their heads that every AI-generated image can be traced back to some specific image that it somehow copied exactly then modified slightly and combined together for a final output. That’s not how the tech works at all.

    You can steal a car. You can’t steal an image.






  • I had to share this because no one else in my life will listen.

    I’m listening, but more importantly, I completely understand 😭

    Also, if you think this setup (with the Xbox controller) is great, wait until the Steam Frame comes out with the new Steam Controller integration (it has IR LEDs on the front of it so you can see a virtual representation of it in the menus). You also won’t need to plug it into your PC as the Steam Frame itself is basically a full PC.

    I’m so hyped about it! Finally, a real Linux OS we can customize TF out of instead of locked-down versions of Android that look like they are designed for toddlers.