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Now you're chasing your own tail. You've gone from "I can losslessly compress everything" to "I can losslessly compress exactly one thing only".
by ebg13 7y ago
Now you're chasing your own tail. You've gone from "I can losslessly compress everything" to "I can losslessly compress exactly one thing only".
- yters 7y agoI'm arguing it's the same as this image compression technique. They rely on a huge neural network which must exist wherever the image is to be decompressed. If I'm allowed to bring along an unlimited amount of background data, then I can compress everything down to zero bits. In contrast, an algorithm like LZ78 can expressed in a 5 line python script and perform decently on a wide variety of data types.
- ebg13 7y ago> If I'm allowed to bring along an unlimited amount of background data, then I can compress everything down to zero bits. If by "background data" you mean the decompressor, this is patently false. No matter how much information is contained in the decompressor (The Algorithm + stable weights that don't change), you can only compress one thing down to any given new representation ( low resolution image + differential from rescale using stable weights ). If by "background data" you mean new data that the decompressor doesn't already have, then you're ignoring the definition of compression. Your compressed data is all bits sent on the fly that aren't already possessed by the side doing the decompression regardless of obtuse naming scheme. > I'm arguing it's the same as this image compression technique. That's wrong, because this scheme doesn't claim to send a custom image generator instead of each image, which is what you're proposing.
- mypalmike 7y agoThe neutral network is not an unlimited amount of data. It is fixed size, and not transferred. Further, if you're not familiar with the pigeonhole principle, it might be worth a read on Wikipedia.