131–140 of 171 posts
Earlier quoted context omitted.
In some use cases, like OCR, the accuracy of these guesses can be established in a scientific way. And it tends to be very good.
Unless they’re not: https://www.dkriesel.com/en/blog/2013/0802_xerox-workcentres...
...I guess the enhance jokes were just rendered void! https://www.youtube.com/watch?v=Vxq9yj2pVWk
Absolutely not. If there's not enough information available, there's not enough information, full stop. Plausible (i.e. "good looking" or "believable") results are not the same as actual data, which is why enhance wouldn't work on vehicle licence plates or faces for example. Sure, the result might be a plausible looking face or text, but it's still not a valid representation of what was originally captured. That's th…
I hope some day there will be an episode of a crime show where by chance two teams of detectives will independently work on the same case without noticing each other and by using standard police methods they will come to completely different incompatible conclusions and detain two different suspects who of course both confess after going through standard police interrogation. Screenwriters, use your powers for good!
(Actually Czech writer Karel Čapek (the same who invented the word robot) did practically the same thing in one of the short stories in Stories from Another Pocket, everybody should read it together with Stories from a Pocket)
Earlier quoted context omitted.
Unless they’re not: https://www.dkriesel.com/en/blog/2013/0802_xerox-workcentres...
Did you read that article? That wasn't an OCR issue it was an image compression issue.
But the issue manifests as characters being incorrectly identified because of an algo t
...I guess the enhance jokes were just rendered void! https://www.youtube.com/watch?v=Vxq9yj2pVWk
Hm. So I took the example image, upscaled by 200%, applied a sharpen filter (all in Paint.NET) and compared the result to the AI upscaled image. TBH, I couldn't see a difference. 2x upscaling isn't all that impressive to begin with (e.g. produce 4 pixels from 1) and can be done in fairly high quality using traditional non-learning algorithms. I'm much more impressed by 4x and 8x super-resolution. I'm really not sure…
Does the ML algorithm with the millions of images training set get run locally or as a remote service? When I use ML these days is it all hardcore data crunching by remote servers or is some of it running on my phone/laptop?
The model is trained on Adobe servers and run locally on your device. The training of the model is much more processor intensive than actually utilizing the trained model, usually by multiple orders of magnitude.
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What worries me is that COTS photo equipment increasingly comes with these algorithmic retouches that "over-represent" the data - or, put another way, bake its own interpretation into image, in a way that cannot be distinguished from source data. It's nice for a casual Instagrammer, but then a lot of science and engineering also gets done using COTS equipment. I worry that at some point, a lot of money will be burned…
I did a web search for "cots" and learned that a cot is... > a small usually collapsible bed often of fabric stretched on a frame But in this case, COTS is apparently... > commercial, off-the-shelf In other words "photo equipment" or "consumer/retail photo equipment." Upon further reading[0] it seems odd to use the term here, but maybe I'm misunderstanding something. It's often used for software and has a key phrase.…
Is that Ryan Gosling? There's definitely something going on there. https://petapixel.com/2020/08/17/gigapixel-ai-accidentally-a...