One little correction, digital zoom is not something that belongs on that list. It’s essentially just cropping the image. That said, “enhanced” digital zoom I agree should be on that list.

Are you saying CSI lied to me?

Even CSI: Miami?

Digital zoom is just cropping and enlarging. You're not actually changing any of the data. There may be enhancement applied to the enlarged image afterwards but that's a separate process.

Hold up. Digital zoom is, in all the cases I'm currently aware of, just cropping the available data. That's not reconstruction, it's just losing data.

Otherwise, yep, I'm with you there.

A term created in order to vacuum up VC funding for spurious use cases.

It's the new "4k". Just buzzwords to get clicks.

Optical Character Recognition used to be firmly in the realm of AI until it became so common that even the post office uses it. Nowadays, OCR is so common that instead of being proper AI, it’s just another mundane application of a neural network. I guess, eventually Large Language Models will be outside there scope of AI.

Dehance! [Click click click.]

It will wild out for the foreseeable future until the masses stop falling for it in gimmicks then it will be reserved for the actual use cases where it's beneficial once the bullshit ai stops making money.

AI-based video codecs are on the way. This isn't necessarily a bad thing because it could be designed to be lossless or at least less lossy than modern codecs. But compression artifacts will likely be harder to identify as such. That's a good thing for film and TV, but a bad thing for, say, security cameras.

The devil's in the details and "AI" is way too broad a term. There are a lot of ways this could be implemented.

Not all of those are the same thing. AI upscaling for compression in online video may not be any worse than "dumb" compression in terms of loss of data or detail, but you don't want to treat a simple upscale of an image as a photographic image for evidence in a trial. Sport replays and hawkeye technology doesn't really rely on upscaling, we have ways to track things in an enclosed volume very accurately now that are demonstrably more precise than a human ref looking at them. Whether that's better or worse for the game's pace and excitement is a different question.

The thing is, ML tech isn't a single thing. The tech itself can be used very rigorously. Pretty much every scientific study you get these days uses ML to compile or process images or data. That's not a problem if done correctly. The issue is everybody is both assuming "generative AI" chatbots, upscalers and image processers are what ML is and people keep trying to apply those things directly in the dumbest possible way thinking it is basically magic.

I'm not particularly afraid of "AI tech", but I sure am increasingly annoyed at the stupidity and greed of some of the people peddling it, criticising it and using it.

Unfortunately it does need pointing out. Back when I was in college, professors would need to repeatedly tell their students that the real world forensics don't work like they do on NCIS. I'm not sure as to how much thing may or may not have changed since then, but based on American literacy levels being what they are, I do not suppose things have changed that much.

Yes. When people were in full conspiracy mode on Twitter over Kate Middleton, someone took that grainy pic of her in a car and used AI to “enhance it,” to declare it wasn’t her because her mole was gone. It got so much traction people thought the ai fixed up pic WAS her.

I met a student at university last week at lunch who told me he is stressed out about some homework assignment. He told me that he needs to write a report with a minimum number of words so he pasted the text into chatGPT and asked it about the number of words in the text.

I told him that every common text editor has a word count built in and that chatGPT is probably not good at counting words (even though it pretends to be good at it)

Turns out that his report was already waaaaay above the minimum word count and even needed to be shortened.

So much about the understanding of AI in the general population.

I'm studying at a technical university.

The layman is very stupid. They hear all the fantastical shit AI can do and they start to assume its almighty. Thats how you wind up with those lawyers that tried using chat GPT to write up a legal brief that was full of bullshit and didnt even bother to verify if it was accurate.

They dont understand it, they only know that the results look good.

There's people who still believe in astrology. So, yes.

Of course, not everyone is technology literate enough to understand how it works.

That should be the default assumption, that something should be explained so that others understand it and can make better, informed, decisions. .

It's incredibly obvious when you call the current generation of AI by its full name, generative AI. It's creating data, that's what it's generating.

Every photo you take with your phone is post processed.

Years ago, I remember looking at satellite photos of some city, and there was a rainbow colored airplane trail on one of the photos. It was explained that for a lot of satellites, they just use a black and white imaging sensor, and take 3 photos while rotating a red/green/blue filter over that sensor, then combining the images digitally into RGB data for a color image. For most things, the process worked pretty seamlessly. But for rapidly moving objects, like white airplanes, the delay between the capture of red/green/blue channel created artifacts in the image that weren't present in the actual truth of the reality being recorded. Is that specific satellite method all that different from how modern camera sensors process color, through tiny physical RGB filters over specific subpixels?

Even with conventional photography, even analog film, there's image artifacts that derive from how the photo is taken, rather than what is true of the subject of the photograph. Bokeh/depth of field, motion blur, rolling shutter, and physical filters change the resulting image in a way that is caused by the camera, not the appearance of the subject. Sometimes it makes for interesting artistic effects. But it isn't truth in itself, but rather evidence of some truth, that needs to be filtered through an understanding of how the image was captured.

Like the Mitch Hedberg joke:

I think Bigfoot is blurry, that's the problem. It's not the photographer's fault. Bigfoot is blurry, and that's extra scary to me.

So yeah, at a certain point, for evidentiary proof in court, someone will need to prove some kind of chain of custody that the image being shown in court is derived from some reliable and truthful method of capturing what actually happened in a particular time and place. For the most part, it's simple today: i took a picture with a normal camera, and I can testify that it came out of the camera like this, without any further editing. As the chain of image creation starts to include more processing between photons on the sensor and digital file being displayed on a screen or printed onto paper, we'll need to remain mindful of the areas where that can be tripped up.