Is there any effort made to compress text (and maybe other media) using prediction of next word and thus sending only the order number of the word/token which will be predicted on the client-side
i.e
SERVER TEXT: This is an example of a long text example, custom word flerfom inserted to confuse, that may appear on somewhere
COMPRESSED TEXT TRANSMITTED: This [choice no 3] [choice no 4] [choice no 1] [choice no 6] [choice no 1] [choice no 3] [choice no 1], custom word flerfom inserted [choice no 4] confuse [choice no 5] [choice no 4] [choice no 6] [choice no 5] on somewhere
(Note: of course [choice no 3] will be shortened to [3] to save bytes and also maybe we can do much better in some cases by sending the first letter of the word)
of course it means that the client side neural network has to be static or only updated in a predictable fasion, so the server knows for sure that the client neural network's predictions will follow the given choice orders. I tried example with https://demo.allennlp.org/next-token-lm, but the prediction is not that good. maybe gpt-3 can do better . but its too heavy for use in a normal pc / mobile device