Thank you for the analysis and the insights. I will surely read the full patent.

Do you think that:

“Content selection feeds through embedding distance, not keyword matching. If your content doesn’t land close to query embeddings in vector space, it won’t be selected as grounding material, regardless of how well it ranks in traditional search.”

directly correlates with the information density of an article and the amount of contextual data and facts conveyed with each sentence and that shorter more condensed pieces of content (more meaningful information, less words) will be more preffered by such systems and with time get better tolerated by the traditional search algorithms as well ?