It seems you misunderstand the goal of goverment.
This is your opinion of what you want governments to be, not what they actually are.
What is the point of not researching and having bigger budget, if it can’t buy thing that did not get created?
What a lot of negatives and hypotheticals. All solved by getting a return on investment and having that money to do more things with, including research.
And then on goverment level there is no such thing as copyright or patent.
I’d like to introduce you to the World Intellectual Property Organisation (WIPO) which is an intergovernmental organisation that does precisely what you say doesn’t exist.
They STILL need to put in money to create their own product.
Sure, but the cost to duplicate the product is tiny compared to researching, developing then creating a production run for it. And this fake normally severely impacts the profits for the inventor.
But now we’re just repeating the same arguments.
I’m guessing that exactly the same LLM model is used (somehow) on both sides - using different models or different weights would not work at all.
An LLM is (at core) an algorithm that takes a bunch of text as input and produces an output of a list of word/probabilities such that the sum of all probabilities adds to 1.0. You could place a wrapper on this that creates a list of words by probability. A specific word can be identified by the index in the list, i.e. first word, tenth word etc.
(Technically the system uses ‘tokens’ which represent either whole words or parts of words, but that’s not important here).
A document can be compressed by feeding in each word in turn, creating the list in the LLM, and searching for the new word in the list. If the LLM is good, the output will be a stream of small integers. If the LLM is a perfect predictor, the next word will always be the top of the list, i.e. a 1. A bad prediction will be a relatively large number in the thousands or millions.
Streams of small numbers are very well (even optimally) compressed using extant technology.