Method and System for Multi-Level Artificial Intelligence Supercomputer Design

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.