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Extreme compression will be when you put in a movie and get a SORA prompt back that regenerates something close enough to the movie.
The compression competitions include the decompression program size in the size of the output. Must be a large series of movies compressed to win, then.
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Many older/commercial video codecs optimized for PSNR, which results in the output being blurry and textureless because that's the best way to minimize rate for the same PSNR. Even with that, showing H.265 having lower PSNR than H.264 is odd --- it's the former which has often looked blurrier to me.
at equal bitrate?
Ahhh, Sloot's digital coding system [1] is finally here ;). [1] https://en.m.wikipedia.org/wiki/Sloot_Digital_Coding_System
In the [Sloot Digital Coding System], it is claimed that no movies are stored, only basic building blocks of movies, such as colours and sounds. So, when a number is presented to the SDCS, it uses the number to fetch colours and sounds, and constructs a movie out of them. Any movie. No two different movies can have the same number, otherwise they would be the same movie. Every possible movie gets its own unique numbe…
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How big is the SORA model itself?
You only need one copy of it - even if it is 100GB. If it's baked into every OS... and storage / RAM keeps getting cheaper... just might work.
At best we might consider it a new type of lossy (or... replacey?) compression. Of course if storage / RAM / bandwidth keeps increasing, this is quite likely the least energy efficient technique available.
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Where’s that quote? Something like “AI is just compression, and compression is indistinguishable from AI”
> AI is just compression, and compression is indistinguishable from AI Almost. Compression and AI both revolve around information processing, but their core objectives diverge. Compression is focused on efficient representation, while AI is built for flexibility and the ability to navigate the unpredictable aspects of real-world data. Compression learns a representation from the same data it encodes, like "testing on…
compression is most of the times about finding the minimal grammar that unfolds to the same original material.
interestingly Fabrice Bellard somehow found a way to use transformers for compression without loss, and beats xz by significant margin. https://bellard.org/nncp/nncp_v2.1.pdf. it uses "deterministic mode of PyTorch" to make sure both directions work alike which I guess means - it saves the random toss throughout compression, for the decompression to use. note: this paper is still on my to-read list.
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You only need one copy of it - even if it is 100GB. If it's baked into every OS... and storage / RAM keeps getting cheaper... just might work.
Meh, AI doesn't break information theory. The relationship between the prompt size to the "similarity" of the result will be such that it doesn't beat traditional compression techniques. At best we might consider it a new type of lossy (or... replacey?) compression. Of course if storage / RAM / bandwidth keeps increasing, this is quite likely the least energy efficient technique available.
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“Alexa show me Star Wars but with Dustin Hoffman as Luke”.
I actually would really like this flexibility. "Star Wars, but in Korean with k-pop stars cast", etc.
Extreme compression will be when you put in a movie and get a SORA prompt back that regenerates something close enough to the movie.
Where’s that quote? Something like “AI is just compression, and compression is indistinguishable from AI”
Earlier quoted context omitted.
“Alexa show me Star Wars but with Dustin Hoffman as Luke”.
I actually would really like this flexibility. "Star Wars, but in Korean with k-pop stars cast", etc.
Gonna be able to skip holodeck episodes in real life soon
Earlier quoted context omitted.
Where’s that quote? Something like “AI is just compression, and compression is indistinguishable from AI”
How does that make sense? Compression is deterministic (for same prompt, same output is algorithmically guaranteed). AI is only deterministic in corner cases.