101–110 of 123 posts
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You are going to need to figure out how to filter out copyrighted works and images for which you don't have permission (eg, someone uploading a picture of an ex partner).
If its in public domain, there is no implicit right to privacy. It's going to be super difficult to claim derivative of copyrighted material going forward.
How much would it cost to train something like this? Is there even a good dataset for it?
I feel like the fact big porn hasn't poached talent and jumped all over this suggest at least 10s of millions. That said some for profit no-rules deepfake service for disinformation and illegal content has to be in the works.
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You are off by an order of magnitude at least. 256 TPUs-v4 (not pod), would cost you around 20k$/day. They actually used 512 TPUs (256 for base model + 128 for each of the two superresolution models). Assuming an average training time of 1 week as you said, that gives us about 280k$. It's also most likely trained for longer than a week, the base model for Dalle-2 was trained for 100-200k GPU hours, so between 2-4x lo…
Couldn't a bunch of us shell out $5000~$50,000 and do this ourselves? Create a non-profit shell corporation outside US jurisdiction, issue shares, raise funds and open source the result? The shares would simply be votes towards future training dataset endeavors as no profit would be booked here. Say you buy 5000 out of 500,000 shares, that would give you 1% voting power in what dataset to train.
> 5 on-demand Cloud TPU v3 devices, 5 on-demand Cloud TPU v2 devices, and 100 preemptible Cloud TPU v2 devices for free for 30 days
So up to 7k hours on demand and 70k pre-emptible
What is the reason Google published their research details about Imagen? Why don't they just keep their findings to themselfes and build products on top of them? Public companies can't do stuff just for the fun of it, right? So there must be some commercial reasoning behind it?
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Which is why porn is such a great dataset for crowdsource: - lots of people are stimulated by it - lots of people want DALL-E-2 for porn - and lots of people are willing to work towards that common goal The beauty of this is that people are just going to keep coming and coming to it. Like I'm trying to be mature and serious about this. What's it going to take? - Community responsible for scraping dataset, generating…
I was writing up a whole explanation for how that couldn't possibly work, but tbh you aren't really wrong with that, after all captchas these days do similar work. I guess the primary concern with a porn model would be the ethics of it, which might turn off any company from helping out on training resources (for example, Google's TPU Research Cloud requires you to follow their code of ethics on AI, which would be ver…
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Two reasons: 1) Even though it's all technically very impressive, so far there's not a huge amount of commercialization potential here. OpenAI is charging for its GPT-3 model but its revenue is probably negligible next to the hardware costs (sunk + ongoing) to train it in the first place, let alone the researcher salaries they're paying 2) Most of the stunning examples are cherry-picked. These things fail much more o…
I'm currently working fulltime on AI-powered design suite Accomplice ( https://accomplice.ai ) and if you ask me on a good day I would tell you I do think there's already huge commercial potential. On a bad day, though ;) My current approach is a "model marketplace" ( https://accomplice.ai/models ) where the most popular open source text-to-image models (VQGAN+CLIP, Disco Diffusion, DALL-E Mega coming soon…), sit alo…
What is the reason Google published their research details about Imagen? Why don't they just keep their findings to themselfes and build products on top of them? Public companies can't do stuff just for the fun of it, right? So there must be some commercial reasoning behind it?
The other reason is that the leaders at Google at the time believed that we would achieve the singularity faster if Jeff Dean periodically sent ideas back 10 years in time to Doug Cutting.
Earlier quoted context omitted.
You are off by an order of magnitude at least. 256 TPUs-v4 (not pod), would cost you around 20k$/day. They actually used 512 TPUs (256 for base model + 128 for each of the two superresolution models). Assuming an average training time of 1 week as you said, that gives us about 280k$. It's also most likely trained for longer than a week, the base model for Dalle-2 was trained for 100-200k GPU hours, so between 2-4x lo…
Couldn't a bunch of us shell out $5000~$50,000 and do this ourselves? Create a non-profit shell corporation outside US jurisdiction, issue shares, raise funds and open source the result? The shares would simply be votes towards future training dataset endeavors as no profit would be booked here. Say you buy 5000 out of 500,000 shares, that would give you 1% voting power in what dataset to train.