Microsoft technology licensing, llc (20240346256). RESPONSE GENERATION USING A RETRIEVAL AUGMENTED AI MODEL simplified abstract
Contents
RESPONSE GENERATION USING A RETRIEVAL AUGMENTED AI MODEL
Organization Name
microsoft technology licensing, llc
Inventor(s)
Yinghua Qin of Redmond WA (US)
RESPONSE GENERATION USING A RETRIEVAL AUGMENTED AI MODEL - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240346256 titled 'RESPONSE GENERATION USING A RETRIEVAL AUGMENTED AI MODEL
The patent application describes a system that uses retrieval augmented artificial intelligence to generate a response to a query.
- A first feature vector is generated based on the query.
- The first feature vector is compared to a plurality of second feature vectors to determine a subset that meets a predetermined condition.
- Augmentation information corresponding to the determined subset of second feature vectors is retrieved.
- An augmented prompt is generated based on the query and the retrieved augmentation information and provided to a large language model.
- The response generated by the large language model is received.
Potential Applications: - Natural language processing - Information retrieval systems - Chatbots and virtual assistants
Problems Solved: - Enhancing the accuracy and relevance of responses to user queries - Improving the efficiency of information retrieval processes
Benefits: - Faster and more accurate responses to user queries - Enhanced user experience with AI-powered systems
Commercial Applications: - Customer service chatbots - Search engines - Knowledge management systems
Questions about the technology: 1. How does the system determine which subset of second feature vectors to retrieve augmentation information from? 2. What are the potential limitations of using retrieval augmented artificial intelligence in generating responses to queries?
Original Abstract Submitted
systems, methods, apparatuses, and computer program products are disclosed for using retrieval augmented artificial intelligence to generate a response to a query. a first feature vector is generated based at least on the query. the first feature vector is compared to a plurality of second feature vectors to determine a subset of the second feature vectors that satisfy a predetermined condition. augmentation information corresponding to the determined subset of second feature vectors are retrieved. an augmented prompt, generated based on the query and the retrieved augmentation information, is provided to a large language model. a response generated by the large language model is received.
