US 12,332,878 B1
Secure cross-platform orchestration and knowledge management of machine-learning models
Andrew Shimshock, San Carlos, CA (US); Peter Shimshock, Reno, NV (US); and Christopher Caen, San Francisco, CA (US)
Assigned to Mill Pond Research LLC, Reno, NV (US)
Filed by Mill Pond Research LLC, Reno, NV (US)
Filed on Mar. 11, 2025, as Appl. No. 19/076,782.
Int. Cl. G06F 16/24 (2019.01); G06F 16/242 (2019.01); G06F 16/245 (2019.01); G06F 16/2453 (2019.01)
CPC G06F 16/243 (2019.01) [G06F 16/24535 (2019.01)] 20 Claims
OG exemplary drawing
 
1. A machine-learning-based method for generating a response to a natural-language query from an entity associated with an organization, comprising:
obtaining a sub-query from the natural-language query;
determining if a cache associated with the organization stores a matching historical sub-query:
if the cache stores the matching historical sub-query, retrieving a historical sub-response associated with the historical sub-query from the cache as a sub-query response;
if the cache does not store any matching historical sub-query:
inputting the sub-query into a cache-based enhancement machine-learning model to enhance the sub-query, wherein the cache-based enhancement machine-learning model is trained based on historical query data stored in the cache associated with the organization; and
inputting the enhanced sub-query into a language model to generate the sub-query response; and
generating the response to the natural-language query based on the sub-query response.