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What happens when the information runs out

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Re: What happens when the information runs out

#21

Post by calf »

lordnacho wrote: post #4

But this is exactly what you expect when you ask intelligence (machine or human) to fill in missing information. It picks some plausible, middle-of-the-road filler. If you were a restoration artist with an airbrush (or photoshop) with just the instruction to make the picture nicer, that's what you'd do. If you got told the right colour, you use it, and if not, you guess.

A restoration artist would not invent eyebrows because they would have worked under a theory of the sort "human faces are especially sensitized to human interpretation so if the noise image does not strongly support a feature then it is better to leave it vague and noisy than to try and pick one out of a large space of eyebrows belonging to other human faces". This is an entirely reasonable, intuitive theory.

I bet that ChatGPT actually would regurgitate exactly this notion but cannot effectuate it.

Re: What happens when the information runs out

#23

Post by graypegg »

I think ChatGPT will just be calling out to a diffusion workflow to generate the new image, so this is using a general tool for a precise problem. It's not going to be great output.

I think, given you know some details about the film you're scanning and how it reacts to certain hues/brightnesses, you can remap colours from greyscale to a few possible colours right? Obviously it's not a 1:1 mapping since there's some data lost. (A dark blue is going to be a similar grey to a brown or something) but I'm almost certain there's old ML technology that essentially takes the most likely colour based on the context of the entire scene/some convolution matrix chunk of the scene, trained for specific film formulations.

Re: What happens when the information runs out

#24

Post by Terr_ »

sixdimensional wrote: post #3

This reminds me of an old problem I used to run into with duplicate data. Duplicates are not always what they seem - duplicates have a relative quantity of how duplicate they are, for example - 100% duplicate identical is what it sounds like, but then what is a 50% duplicate? Well.. that could be a duplicate where semantic meaning that only a human is aware of (missing information) could be used to determine that the…

Occasionally I've advocated to product-owners that their design needs a business/domain-concept for uncertainty or data-quality, rather than treating it as an implementation detail.

This is especially true when you've got data where even a human specialist would throw up their hands and say: "It could be this, or that, I can't tell."

Re: What happens when the information runs out

#25

Post by TacticalCoder »

CM30 wrote: post #6

This reminds me of how a lot of older TV shows and movies had an 'enhance' button that could somehow magically take a tiny, blurred image and blow it up to a level of detail where even the most minor things could be seen again. Like a suspect's eyes in the reflection of a window that looked like it was maybe 4 pixels in size in the original image. The AI examples and reasoning in the article are exactly why this can'…

> This reminds me of how a lot of older TV shows and movies had an 'enhance' button that could somehow magically take a tiny, blurred image and blow it up to a level of detail where even the most minor things could be seen again.

Mandatory BladeRunner scene:

https://youtu.be/8-Rw-XAsBhM

Re: What happens when the information runs out

#26

Post by m463 »

CM30 wrote: post #6

This reminds me of how a lot of older TV shows and movies had an 'enhance' button that could somehow magically take a tiny, blurred image and blow it up to a level of detail where even the most minor things could be seen again. Like a suspect's eyes in the reflection of a window that looked like it was maybe 4 pixels in size in the original image. The AI examples and reasoning in the article are exactly why this can'…

or samsung and it's "space zoom" AI feature that helps you take pictures of the moon:

https://www.androidauthority.com/samsung-fake-space-zoom-moo...

now that astronauts can take their phones into space, wonder what a shot of the earth would look like on a "space zoom" phone?

Re: What happens when the information runs out

#27

Post by SoftTalker »

The human brain does the same thing. It fills in details that aren't really there. The eye can only resolve detail in a fairly small spot at the center of vision. But we normally don't perceive that. Our entire field of view seems equally sharp. The brain is filling in the detail.

Re: What happens when the information runs out

#28

Post by NL807 »

milesvp wrote: post #16
CM30 wrote: post #6

This reminds me of how a lot of older TV shows and movies had an 'enhance' button that could somehow magically take a tiny, blurred image and blow it up to a level of detail where even the most minor things could be seen again. Like a suspect's eyes in the reflection of a window that looked like it was maybe 4 pixels in size in the original image. The AI examples and reasoning in the article are exactly why this can'…

> is just going to be making up the missing data. This is generally true. What I find fascinating is the application of information that is not present in the data but that can be confirmed by the data. I’m thinking specifically of deblurring algorithms people use to recover text. If you can guess what font is being used in a screengrab with, say, someone’s bank account blurred out, you can take the i formation conta…

>What I find fascinating is the application of information that is not present in the data but that can be confirmed by the data. I’m thinking specifically of deblurring algorithms people use to recover text.

I would argue that high frequency information is not missing in a blurred image, rather it's spread out spatially. Every sample in the blurred image is a convolution of multiple samples (i.e. high frequency data) from the originating source. Theoretically, it should be invertible, provided the exact function is known that does the convolution, but there are practical limitations, such as knowing how to apply the inverse operations at the edges and dealing with the extreme sensitivity to errors.

Re: What happens when the information runs out

#29

Post by bob1029 »

CM30 wrote: post #6

This reminds me of how a lot of older TV shows and movies had an 'enhance' button that could somehow magically take a tiny, blurred image and blow it up to a level of detail where even the most minor things could be seen again. Like a suspect's eyes in the reflection of a window that looked like it was maybe 4 pixels in size in the original image. The AI examples and reasoning in the article are exactly why this can'…

https://youtu.be/FVOydVwOO4M

Re: What happens when the information runs out

#30

Post by vitally3643 »

NL807 wrote: post #28
milesvp wrote: post #16

Earlier quoted context omitted.

> is just going to be making up the missing data. This is generally true. What I find fascinating is the application of information that is not present in the data but that can be confirmed by the data. I’m thinking specifically of deblurring algorithms people use to recover text. If you can guess what font is being used in a screengrab with, say, someone’s bank account blurred out, you can take the i formation conta…

>What I find fascinating is the application of information that is not present in the data but that can be confirmed by the data. I’m thinking specifically of deblurring algorithms people use to recover text. I would argue that high frequency information is not missing in a blurred image, rather it's spread out spatially. Every sample in the blurred image is a convolution of multiple samples (i.e. high frequency data…

It's a visual hash. It isn't reversible, but it is uniquely confirmable.
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