You need to make sure to remove excess whitespace from the JSON to speed up parsing. Have an AI read the JSON as plaintext and convert it to a handwriting-style image, then another one to use OCR to convert it back to text. Trailing whitespace will be removed.
Just make it a LJM (Large JSON Model) capable of predicting the next JSON token from the previous JSON tokens and you would have massive savings in file storagre and network traffic from not having to store and transmit full JSON documents all in exchange for an “acceptable” error rate.
Maybe it’s time we invent JPUs (json processing units) to equalize the playing field.
The best I can do is an ML model running on an NPU that parses JSON in subtly wrong and impossible to debug ways
You need to make sure to remove excess whitespace from the JSON to speed up parsing. Have an AI read the JSON as plaintext and convert it to a handwriting-style image, then another one to use OCR to convert it back to text. Trailing whitespace will be removed.
Did you know? By indiscriminately removing every 3rd letter, you can ethically decrease input size by up to 33%!
Just make it a LJM (Large JSON Model) capable of predicting the next JSON token from the previous JSON tokens and you would have massive savings in file storagre and network traffic from not having to store and transmit full JSON documents all in exchange for an “acceptable” error rate.
Hardware accelerated JSON Markov chain operations when?
So you’re saying it’s already feature complete with most json libraries out there?
Latest Nvidia co-processor can perform 60 million curly brace instructions a second.
Finally, something to process “databases” that ditched excel for json!
60 million CLOPS? No way!
JSON and the Argonaut RISC processors
Until then, we have simdjson https://github.com/simdjson/simdjson