Media compression and decompression using a generative artificial intelligence model that accepts partially decompressed data as input

In a computer system that implements a generative artificial intelligence (“AI”) model, a method of training the generative AI model to compress media, the method comprising:

• identifying a set of training data;
• and
• training the generative AI model in multiple training iterations using the set of training data, including, in a given training iteration of the multiple training iterations:
• receiving first input tokens that represent first input syntax elements, respectively, of compressed data for a first version of input media, the first version having a first resolution, the first version having been compressed according to a media compression format to produce the compressed data for the first version, wherein the first input tokens are encoded in an input format for the generative AI model;
• receiving second input tokens that represent second input syntax elements, respectively, of compressed data for a second version of the input media, the second version having a second resolution lower than the first resolution, the second version having been compressed according to the media compression format to produce the compressed data for the second version of the input media, wherein the second input tokens are encoded in the input format for the generative AI model;
• providing, to the generative AI model, the first input tokens and the second input tokens;
• receiving, from the generative AI model, predicted tokens that represent output syntax elements, respectively, of compressed data for output media at the first resolution;
• determining a measure of loss based at least in part on the predicted tokens;
• and
• updating one or more parameters of the generative AI model based at least in part on the measure of loss.

One or more non-transitory computer-readable media having stored thereon computer-executable instructions for causing a processor system, when programmed thereby, to perform operations to decompress media using a generative artificial intelligence (“AI”) model, the operations comprising:

• receiving input tokens that represent input syntax elements, respectively, of compressed data for a second version of input media, the second version having been compressed according to a media compression format to produce the compressed data for the second version, wherein the second version approximates a first version of the input media, the first version having a first resolution, the second version having a second resolution lower than the first resolution, and wherein the input tokens are encoded in an input format for the generative AI model;
• providing, to the generative AI model, the input tokens;
• receiving, from the generative AI model, predicted tokens that represent output syntax elements, respectively, of compressed data for output media at the first resolution;
• and
• reconstructing the output media from the predicted tokens.