The post discusses a research paper that explores a novel method of compressing the weights of large language models (LLMs) into seeds for pseudo-random number generators. This approach could enable more efficient storage and loading of LLMs, making them more accessible and faster to deploy. The paper is a collaborative effort between researchers from Apple and Meta, hinting at significant advancements in model compression techniques. However, there are mixed feelings in the comments regarding the practical implementation and timely deployment of resulting technologies, especially in relation to Apple's AI initiatives.