US 12,292,907 B2
Method and system for multi-level artificial intelligence supercomputer design
Vijay Madisetti, Alpharetta, GA (US); and Arshdeep Bahga, Chandidgarh (IN)
Assigned to Vijay Madisetti, Alpharetta, GA (US)
Filed by Vijay Madisetti, Alpharetta, GA (US)
Filed on Nov. 1, 2024, as Appl. No. 18/934,384.
Application 18/934,384 is a continuation of application No. 18/921,923, filed on Oct. 21, 2024.
Application 18/921,923 is a continuation of application No. 18/391,165, filed on Dec. 20, 2023, granted, now 12,153,612.
Application 18/391,165 is a continuation of application No. 18/348,692, filed on Jul. 7, 2023, granted, now 12,001,462.
Claims priority of provisional application 63/463,913, filed on May 4, 2023.
Claims priority of provisional application 63/469,571, filed on May 30, 2023.
Prior Publication US 2025/0061138 A1, Feb. 20, 2025
Int. Cl. G06F 16/332 (2019.01); G06F 16/3329 (2025.01); G06F 40/284 (2020.01)
CPC G06F 16/3329 (2019.01) [G06F 40/284 (2020.01)] 28 Claims
OG exemplary drawing
 
1. A system for answering queries using one or more families of large language models (h-LLMs) comprising:
a processor;
a non-transitory computer-readable storage medium positioned in communication with processor and having stored thereon software that, when executed by the processor, is operable to:
provide a user interface to receive a user prompt;
operate an input broker operable to generate a plurality of derived prompts from the user prompt;
generate a plurality of prompt embeddings from the plurality of derived prompts by applying a plurality of embedding models;
transmit the plurality of prompt embeddings to a vector database, the vector database comprising a database of knowledge documents, each knowledge document comprised by the database of knowledge documents having one or more embeddings associated therewith;
receive one or more knowledge documents that are determined to be relevant to the plurality of prompt embeddings at the input broker;
generate a plurality of context-aware prompts by the input broker responsive to the user prompt, the plurality of derived prompts, and the one or more knowledge documents;
transmit the plurality of context-aware prompts to the one or more h-LLMs;
operate an output broker operable to receive a plurality of h-LLM results, the h-LLM results being generated responsive to the one or more h-LLMs receiving at least one context-aware prompt and generating a response thereto;
process the plurality of h-LLM results by the output broker to produce processed h-LLM results, each processed h-LLM result having a score;
identify one or more preferred results responsive to the scores; and
transmit the one or more preferred results to a user via the user interface; and
a communication device operable to facilitate the transmitting and receiving functions of the software.