Measurement Application Control With AI Knowledge Retrieval

The patent introduces an AI-based assistant as an intermediary between the user and the complex measurement application device. The assistant receives natural language queries from users, processes them through a multi-component system including embedding models, similarity search, and language models, and returns simplified guidance or automated configurations. This mediator translates user intent into actionable device commands without requiring users to navigate complex parameter interfaces directly.

The system enables self-service through automated configuration capabilities where the AI assistant can independently determine and apply optimal measurement settings based on user descriptions of measurement goals. The device performs self-configuration by processing user queries through the knowledge base and generating appropriate parameter settings, reducing the need for manual user configuration of numerous parameters.

The patent segments the AI assistant architecture into distinct functional modules: an embedding model component for converting queries to vectors, a similarity search component for matching queries with the knowledge base, a language model component for generating responses, and multiple database interfaces for different knowledge sources. This segmentation allows each component to specialize in a specific task, improving overall system efficiency and maintainability despite the increased complexity.

The system employs universal components that serve multiple functions. The embedding model, for example, serves both as a query understanding mechanism and as a basis for similarity comparison. The knowledge base serves both as a reference for generating recommendations and as a source for automated configuration parameters. This multi-functionality reduces redundancy and manages complexity by having components serve multiple purposes.