Does anyone else have the feeling that with the current trajectory, something exactly like this, but with perhaps a million times the amount of feedback and data, thought will just emerge ? Yes, this is all 2D and abstract/selective training sets etc, but what if AI is the ultimate fake-it-until-you-make-it?
Image-to-Image Translation with Conditional Adversarial Nets
21–30 of 61 posts
Re: Image-to-Image Translation with Conditional Adversarial Nets
#22Re: Image-to-Image Translation with Conditional Adversarial Nets
#23The "sketches to handbags" example, which is buried toward the bottom, is really cool. It's basically an extension of the "edges to handbags," but with hand-drawn sketches. Even though the sketches are fairly crude, with no shading and a low level of detail, many of the generated images look like they could, in fact, be real handbags. They still have the mark of a generated image (e.g. weird mottling) but they're tot…
This is be a popular shopping website. Sketch your perfect handbag. See an image of the product. Click to buy.
Re: Image-to-Image Translation with Conditional Adversarial Nets
#24Earlier quoted context omitted.
> real creativity What is real creativity? Creativity is just random noise converted into patterns. Is the computer variety of creativity not real enough?
Why are some people better at it than others then if it's purely noise and patterns?
Re: Image-to-Image Translation with Conditional Adversarial Nets
#25I'm interested in having a play. As an out and out ML newbie, is there such a thing as an AWS image I could run on a GPU instance and then just git clone and go?
Re: Image-to-Image Translation with Conditional Adversarial Nets
#26I feel this can potentially revolutionize creative processes, for example in the clothing industry. You just draw up a purse or a shoe, let the machines generate dozens of variants (with pictures), and then you only have to filter and rank them. You can pipe these product sketches directly into focus groups who tell you which product is most likely to sell. You don't need massive staff to come up with product variant…
Re: Image-to-Image Translation with Conditional Adversarial Nets
#27Does anyone else have the feeling that with the current trajectory, something exactly like this, but with perhaps a million times the amount of feedback and data, thought will just emerge ? Yes, this is all 2D and abstract/selective training sets etc, but what if AI is the ultimate fake-it-until-you-make-it?
From that, the AI could generate books, movies, and do a lot of things.
Re: Image-to-Image Translation with Conditional Adversarial Nets
#28The "sketches to handbags" example, which is buried toward the bottom, is really cool. It's basically an extension of the "edges to handbags," but with hand-drawn sketches. Even though the sketches are fairly crude, with no shading and a low level of detail, many of the generated images look like they could, in fact, be real handbags. They still have the mark of a generated image (e.g. weird mottling) but they're tot…
This is be a popular shopping website. Sketch your perfect handbag. See an image of the product. Click to buy.
Re: Image-to-Image Translation with Conditional Adversarial Nets
#29I feel this can potentially revolutionize creative processes, for example in the clothing industry. You just draw up a purse or a shoe, let the machines generate dozens of variants (with pictures), and then you only have to filter and rank them. You can pipe these product sketches directly into focus groups who tell you which product is most likely to sell. You don't need massive staff to come up with product variant…
I feel like we would end up here: http://www.gianlucagimini.it/prototypes/velocipedia.html
Re: Image-to-Image Translation with Conditional Adversarial Nets
#30Earlier quoted context omitted.
This is be a popular shopping website. Sketch your perfect handbag. See an image of the product. Click to buy.
"Sketch your perfect handbag" may be a bit much to ask of most people.