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Comment by dagmx | Hacker News Reader

Hmm this seems incorrect. There’s no AI use for compression, that’s just standard HEIC.

There is a variety of computational photography tricks to enhance the quality of sensor data. However none of it is generating data wholesale but is rather just doing combination of sensor pixels to create the image.

To the best of my knowledge, Apple has no generative post processing so wouldn’t fall afoul of this.

Samsung on the other hand do generate content that isn’t in the shot, for example if it thinks there’s a moon it’ll insert a virtual one.

Google also have various post processing technologies like picking the best of faces from multiple photos. However it does mark them as edited.

I don’t know of any smartphone doing generative upscaling. It’s still quite a costly process that doesn’t scale well to mobile SoCs yet within a user acceptable timeframe .

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Apple is using some sort of generative technology[0], though not clear if it's done in the displaying viewer or in the post processing, or if it's Diffusion based.

0: https://twitter.com/rubyondia/status/1761258088164970836

Afaik all the text enhancements aren’t baked in to the image.

If you send the image to someone or open it another app, they’re removed when I try it.

this one[0] is a lot better example of generative "enhancements". It was noticed as the result was less than flattering.

[0]: https://news.ycombinator.com/item?id=29739235

This was debunked by the original photographer as an actual leaf in the way. The comments on that post link to the authors tweet where they admit that.

Here’s the link to the “Oops, that was a mistake!” HN post:

https://news.ycombinator.com/item?id=29750660

He admits he made a mistake and posts a little video showing what happened.

^ this parent comment is an example of the common human generative failure mode called “hallucination” which introduces fictional details about the iPhone camera

That one is actually an example of how humans are perceptually bad at understanding perspective from a still.

There’s an actual leaf in front of the head but the camera flattening makes them blend together.

If they shot this as a video or a “Live Photo” it would be much more apparent what they’re looking at.

>There’s no AI use for compression, that’s just standard HEIC.

Where is the line drawn between "AI" and codec compression?

* Both are algorithms.

* Both are fed source material.

* Both can be trained to produce a better output.

* Both are prompted.

* Both are highly parallel workloads.

* Both can be accelerated using accelerators.

* Both can produce new things ("hallucinate") and reproduce the source.

xerox was already changing numbers in copier :

https://www.theverge.com/2013/8/6/4594482/xerox-copiers-rand...

Codecs don’t hallucinate new things. They have a much stricter input and output. HEIC and AV1 cannot add materially new information that wasn’t in the source data.

The rest of your points are too vague such that they could basically be applied to any number of computer algorithms.

Hallucination is the key element at play.

>The rest of your points are too vague such that they could basically be applied to any number of computer algorithms.

That is, in fact, a point I am making: "AI" as it stands today is a meaningless marketing term.

Fair. Though in the case of the primary article the issue is hallucination, and they likely mean generative AI tools that infill to get the resolution increase

I tried using AI to translate a letter from German to English. It "helpfully" inserted a number of sentences that didn't exist in the German version.

This may not be germane to your example, but in my experience of German -> English translation creating several sentences can be the smoothest way to make sense out of something German gets across in a couple of overloaded compound words.

I get that, but I know enough German to know it was adding things that were not there.

In general German is much more verbose than English. Compound words can sometimes shorten sentences, however the English dictionary has significantly more vocabulary (see comparisons between Shakespeare and Goethe for example). In German you use causal sentences. Because of that German texts are typically much longer than the English originals, e.g. IIRC the goblet of fire was 150 pages longer in english

I think it's not said often enough that LLMs hadn't solved translation problem or anything: we only got a new tool, and it is not a perfect universal everything tool.

  - classical MTs: just jarring, "every work and without slack produce blunt child lift"  
  - pre-LLM AI MT: most natural, but drops expressions that it's not sure about: "We choose to visit in this decennial and it's not easy."  
  - LLM: too US English centric, dry, and weighing flows over content too much: "Is it one obsolete-aesthetic word? So scary to say that."

All these are useful, just none are panacea to translation problem(including humans).

Samsung does use it for x100 zoom photos

The original example[0] of a lot more happening due to iPhone's processing, far beyond compression. It was hotly discussed[1] here. I was under the impression that's a well known fact now.

[0]: https://twitter.com/mitchcohen/status/1476351601862483968

[1]: https://news.ycombinator.com/item?id=29739235

There’s a comment explaining there really was a leaf in the shot.

Reply on news.ycombinator.com