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Patent drawing for Collaborative augmented language models for capturing and utilizing domain expertise
US 20,240,428,045 A1
Machine learning US 20,240,428,045 A1 Under examination

Collaborative augmented language models for capturing and utilizing domain expertise

This invention describes a system that creates specialized AI assistants, called digital subject matter experts (dSMEs), by capturing knowledge from human experts through conversations and then organizing it. When a user asks a question in natural language, a chatbot routes the request to the most relevant dSME by comparing the request to descriptions of the available dSMEs using vector similarity. The selected dSME then attempts to answer the question or guide the user, potentially using external tools if its own knowledge is insufficient.

Why it matters: The claims describe a system for routing natural language requests to domain-specific AI models using vector similarity. While this was technically feasible in 2024, rapid advancements in LLM reasoning, knowledge extraction, and agentic capabilities by 2026 make the system's core functions of capturing expert knowledge conversationally and providing nuanced guidance significantly more effective and automated.

Status
Under examinationA pending application. It has not been granted, and it has not been abandoned.
How hard to build
SpecializedHeavy software system, AI models, vector databases, chatbot

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