Earlier quoted context omitted.
> I think it's sad that Apple doesn't even give attribution to any of the authors. Pretty much like Stable Diffusion and the grifters using it in general and they will never credit the artists and images that they stole to generate these images.
This is sort of like if you learned English from reading a book and the author said they owned all your English sentences after that. Of course you can see the original images ( https://rom1504.github.io/clip-retrieval/ ), it was legal to collect them (they used robots.txt for consent just like Google Image Search) and it was legal to do this with them (but not using US legal principles since it's made in Germany). "…
Stable Diffusion with Core ML on Apple Silicon
161–170 of 184 posts
Re: Stable Diffusion with Core ML on Apple Silicon
#162Earlier quoted context omitted.
That laptop feels like liquid power. It's uncanny. Macbook Airs (way back when) felt sluggish. The MBA M1 changed that, it was "fine". These M2s are unexpectedly responsive on an ongoing basis. The MacBook Pro M1 Max is great (would be fantastic except they lost a Thunderbolt port in favor of legacy HDMI and memory card jacks), but you expect that machine to be responsive, so it's less surprising. The Studio Ultra, t…
I dont like lack of open source drivers, but honestly for work DisplayLink works just fine on MacOS. E.g I used 4 monitors on M1 Air using DisplayLink: * Air built-in display * 2K display connected via USB-C -> DisplayPort adapter * Two more 2K displays of same model via DisplayLink connected via USB hub For all practical means it's almost impossible to see any DisplayLink compression artifacts even in most of games.…
Been nervous to dip into it, given the architecture change and last year's challenges with display link docks.
// UPDATE: Oops, looking at the product, I see I should have specified: 4K screens or higher. About half our desks are 2 x 4K, about half 2 x 5K, except the Air M1 folks who are 1 x 5K.
Re: Stable Diffusion with Core ML on Apple Silicon
#163Earlier quoted context omitted.
It doesn't. MPS largely is on GPU. PyTorch's MPS implementation is incomplete a few weeks ago as well. This is about 3x faster.
Is it? I just ran it on my M1 MacBook Air and am getting 3 it/sec, same as I was using Stable Diffusion for M1. Maybe I'm doing something wrong?
Re: Stable Diffusion with Core ML on Apple Silicon
#164Earlier quoted context omitted.
4) If computers get good enough at 1) or 2), then there'd be much bigger problems, and essentially all humans will become the starving artists. Also, I'm not so sure that language models like SD, Imagen, GPT-3, PaLM are purely copycats. And I'm not so sure that most human artists are not mostly copycats either. My suspicion is that there's much more overlap between how these models work and what artists do (and how h…
If we manage to create life capable of doing 1) and 2) but also capable of self-improvement and self-design of their intelligence I think what we've just done is created the next step in the universe understanding itself, which is a good thing. Bacteria didn't panic when multi-cellular life evolved. Bacteria is still around, it's just a thriving part of a more complex system. At some point biological humans will eith…
A vast number of species are no longer around, and we are relatively unusual in being a species that can even contemplate its own demise, so it's entirely reasonable that we would think about and be potentially concerned about our own technological creations supplanting us, possibly maliciously.
Re: Stable Diffusion with Core ML on Apple Silicon
#165Earlier quoted context omitted.
I think humans do in fact create things out of 'thin air' - but only in very, very small pieces. What we consider to be an absolute genius is typically a person who has made one small original thought and applied it to what already exists to make something different.
Creating something novel is not even remotely the same as creating something out of thin air. Even the genius with an original thought only could come by that thought by being informed through their life experiences. Not unlike an AI training set allowing an AI to create something novel.
Re: Stable Diffusion with Core ML on Apple Silicon
#166Earlier quoted context omitted.
This is sort of like if you learned English from reading a book and the author said they owned all your English sentences after that. Of course you can see the original images ( https://rom1504.github.io/clip-retrieval/ ), it was legal to collect them (they used robots.txt for consent just like Google Image Search) and it was legal to do this with them (but not using US legal principles since it's made in Germany). "…
> future artists having their jobs taken by AIs that's simply not going to happen. as in every technological development so far, this is just another tool. 1) artists create the styles out of thin air 2) artists create the images out of thin air 3) computers are just collectors of this data and do not actually originate anything new. they are just very clever copycats. you're looking at an artist tool more than anyth…
It will indeed happen, though not to all artists.
> as in every technological development so far, this is just another tool.
Just like every other tool, it changes things, and not everyone wants to change. Those who embrace the new tech are more likely to thrive. Those who don't, less likely.
> 1) artists create the styles out of thin air > 2) artists create the images out of thin air
I understand what you're saying, but as an artist, I can't agree. No artist lives in total isolation. No artist creates images out of thin air. Those who claim to are lying, or just don't realize how they're influenced.
How artists are influenced varies, obviously, but for me I think that however I've been influenced, that influence impacts my output similarly to how the latest generation of AI driven image generation works.
I'm influenced by the collective creative output of every artist who's stuff I've seen. An AI tool is influenced by its model. I don't see a lot differences there, conceptually speaking. There are obvious differences about human experience, model training, bias, etc, but that's a much larger conversation. Those differences do matter, but I don't think they matter enough to change my stance conceptually they work the same in terms of leveraging "influence" to create something unique.
> 3) computers are just collectors of this data and do not actually originate anything new. they are just very clever copycats.
Stable Diffusion does a pretty damn good job of mixing artistic styles to the point where I have no problem disagreeing with you here. It comes as close to originating something new as humans do. You could argue about how it does it disqualifies its output as "origination", but those same arguments would be just as effective at disqualifying humans for the same reasons.
That all said, I agree with you that the tech is a disruptive tool. It's a threat the same way that cameras were a threat to portrait artists, or Autocad for architects, or CNC machines for machinists might be a threat. The idea that new tech doesn't take jobs is naive - it always does. But it doesn't always completely eliminate those jobs. Those who adapt and leverage and take advantage of the new tools can still survive and thrive. Those who reject the new tech might not. Some might find a niche in using "old" techniques (which in away still leverages the new tech - as a marketing/differentiation strategy).
For me, I've been using Stable Diffusion a lot lately as a tool for creating my own art. It's an incredibly useful tool for sketching out ideas, playing with color, lighting, and composition.
Re: Stable Diffusion with Core ML on Apple Silicon
#167Earlier quoted context omitted.
> Oh gosh that's an intimidating installation process I'm not seeing any installation instructions on either link - what am I missing?
All I had to do was: - create a virtual environment (Python 3.8.15 worked best) - upgrade pip - pip install wheel - pip install -r requirements.txt - and then, python setup.py install - Had to update my XCode to use the generated mlpackage files :/ - Expand drawer with instructions and follow them to download model and convert it to Core ML format - Run their CLI command as mentioned
I keep running into this, message is
RuntimeError: Error compiling model: "Error reading protobuf spec. validator error: The model supplied is of version 7, intended for a newer version of Xcode. This version of Xcode supports model version 6 or earlier.".
I upgraded XCode, tried re-installing the command line tools with various invocations of `sudo rm -rf /Library/Developer/CommandLineTools ; xcode-select --install` etc but still get the above message(thanks in advance, in case you see this and reply)
edit: I see from https://github.com/apple/ml-stable-diffusion/issues/7 that somebody upgraded to macos 13.0.1 and that fixed the issue for them. I've put off upgrading to Ventura so far and don't want to upgrade just to mess around with stable diffusion on m1, if it can be avoided.
Re: Stable Diffusion with Core ML on Apple Silicon
#168Earlier quoted context omitted.
It is still kind of toxicity: “cool, you did it, but you could do it better - I could do it better, just out of time”. Don't be toxic to don’t get that hostility.
That’s not at all what I’m saying, in fact you keep trying to infer the opposite of what I’m saying, and now you’re just doubling down. If anything you’re the one being toxic because you’re unable to have a reasonable conversation about a misunderstanding, and are instead trying to put words in my virtual mouth to conform to your outrage.
Re: Stable Diffusion with Core ML on Apple Silicon
#169Earlier quoted context omitted.
All hail Grand Perspective back in the day, not sure who is carrying the "what's wasting my disk space" torch for free these days. Edit: still alive! https://grandperspectiv.sourceforge.net/
ncdu is the best in my book. TUI, supports deletion of files and folders, and very simple to understand. GUI apps for this task like GP and the like are more visually complex than they need to be.
Re: Stable Diffusion with Core ML on Apple Silicon
#170Earlier quoted context omitted.
I dont like lack of open source drivers, but honestly for work DisplayLink works just fine on MacOS. E.g I used 4 monitors on M1 Air using DisplayLink: * Air built-in display * 2K display connected via USB-C -> DisplayPort adapter * Two more 2K displays of same model via DisplayLink connected via USB hub For all practical means it's almost impossible to see any DisplayLink compression artifacts even in most of games.…
Appreciate this reply, TY for sharing the exact product that's working for you! Been nervous to dip into it, given the architecture change and last year's challenges with display link docks. // UPDATE: Oops, looking at the product, I see I should have specified: 4K screens or higher. About half our desks are 2 x 4K, about half 2 x 5K, except the Air M1 folks who are 1 x 5K.
For higher resolution some other solution is required.