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Awesome! A thought: now that neural compression is becoming widespread, it could be a good idea to put some kind of indicator or watermark stating the compress

Awesome! A thought: now that neural compression is becoming widespread, it could be a good idea to put some kind of indicator or watermark stating the compression is neural (learned/function approximation in general). I think this would avoid liabilities and criticism around the fact that some weird things may appear (incorrect detail generation), maybe giving a wrong semantic idea. It may also be a good idea to put a mean squared error term in your objective function to help preserve general meaning.

danuker 4y ago
> incorrect detail generation Absolutely. Reminds me of Xerox number mangling: https://www.dkriesel.com/en/blog/2013/0802_xerox-workcentres_are_switching_written_numbers_when_scanning https://www.dkriesel.com/en/blog/2013/0802_xerox-workcentres...
- gnramires 4y ago
  Interesting, and it may also indicate a way to address this issue with learning. For example, you could train a network to give semantic image descriptions of significant features in the image, and maybe also transcribe text. Then you can include semantic preservation in the objective, or some kind of graceful degradation when semantic preservation isn't achieved.
- sitkack 4y ago
  Or when AI resolution enhancement inserts Ryan Goslings face. https://petapixel.com/2020/08/17/gigapixel-ai-accidentally-added-ryan-goslings-face-to-this-photo/ https://petapixel.com/2020/08/17/gigapixel-ai-accidentally-a...
  - monkeybutton 4y ago
    Also white Obama! https://www.theverge.com/21298762/face-depixelizer-ai-machine-learning-tool-pulse-stylegan-obama-bias https://www.theverge.com/21298762/face-depixelizer-ai-machin...
newaccount74 4y ago
> put some kind of indicator or watermark stating the compression is neural That ship has sailed. Smartphone cameras and laptop webcams already use machine learning algos to improve low light performance and noise. The result is that the images already contain details that are generated. And it's impossible to turn off.

danuker 4y ago

> incorrect detail generation Absolutely. Reminds me of Xerox number mangling: https://www.dkriesel.com/en/blog/2013/0802_xerox-workcentres_are_switching_written_numbers_when_scanning https://www.dkriesel.com/en/blog/2013/0802_xerox-workcentres...

gnramires 4y ago
Interesting, and it may also indicate a way to address this issue with learning. For example, you could train a network to give semantic image descriptions of significant features in the image, and maybe also transcribe text. Then you can include semantic preservation in the objective, or some kind of graceful degradation when semantic preservation isn't achieved.
sitkack 4y ago
Or when AI resolution enhancement inserts Ryan Goslings face. https://petapixel.com/2020/08/17/gigapixel-ai-accidentally-added-ryan-goslings-face-to-this-photo/ https://petapixel.com/2020/08/17/gigapixel-ai-accidentally-a...
- monkeybutton 4y ago
  Also white Obama! https://www.theverge.com/21298762/face-depixelizer-ai-machine-learning-tool-pulse-stylegan-obama-bias https://www.theverge.com/21298762/face-depixelizer-ai-machin...

newaccount74 4y ago

> put some kind of indicator or watermark stating the compression is neural That ship has sailed. Smartphone cameras and laptop webcams already use machine learning algos to improve low light performance and noise. The result is that the images already contain details that are generated. And it's impossible to turn off.