Nvidia corporation (20240095460). DIALOGUE SYSTEMS USING KNOWLEDGE BASES AND LANGUAGE MODELS FOR AUTOMOTIVE SYSTEMS AND APPLICATIONS simplified abstract
Contents
- 1 DIALOGUE SYSTEMS USING KNOWLEDGE BASES AND LANGUAGE MODELS FOR AUTOMOTIVE SYSTEMS AND APPLICATIONS
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 DIALOGUE SYSTEMS USING KNOWLEDGE BASES AND LANGUAGE MODELS FOR AUTOMOTIVE SYSTEMS AND APPLICATIONS - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Potential Applications
- 1.6 Problems Solved
- 1.7 Benefits
- 1.8 Potential Commercial Applications
- 1.9 Possible Prior Art
- 1.10 Unanswered Questions
- 1.11 Original Abstract Submitted
DIALOGUE SYSTEMS USING KNOWLEDGE BASES AND LANGUAGE MODELS FOR AUTOMOTIVE SYSTEMS AND APPLICATIONS
Organization Name
Inventor(s)
Peng Xu of Redwood City CA (US)
Mostofa Patwary of Fremont CA (US)
Rajath Shetty of Sunnyvale CA (US)
Niral Lalit Pathak of San Jose CA (US)
Ratin Kumar of Cupertino CA (US)
Bryan Catanzaro of Los Altos Hills CA (US)
Mohammad Shoeybi of Foster City CA (US)
DIALOGUE SYSTEMS USING KNOWLEDGE BASES AND LANGUAGE MODELS FOR AUTOMOTIVE SYSTEMS AND APPLICATIONS - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240095460 titled 'DIALOGUE SYSTEMS USING KNOWLEDGE BASES AND LANGUAGE MODELS FOR AUTOMOTIVE SYSTEMS AND APPLICATIONS
Simplified Explanation
The abstract describes systems and methods that use dialogue systems associated with various machine systems and applications to retrieve question/answer pairs and generate prompts based on contextual information.
- Dialogue systems associated with machine systems and applications
- Retrieval of question/answer pairs and contextual information
- Generation of prompts using text data
- Determination of output based on prompts and language models
Potential Applications
This technology could be applied in customer service chatbots, virtual assistants, and automated help desks for various industries.
Problems Solved
This technology helps in efficiently retrieving relevant information and providing accurate answers to user queries in real-time.
Benefits
The benefits of this technology include improved customer service, increased efficiency in handling user queries, and enhanced user experience.
Potential Commercial Applications
Potential commercial applications of this technology include customer support services, e-commerce platforms, and online education platforms.
Possible Prior Art
One possible prior art could be the use of natural language processing in chatbots and virtual assistants to provide automated responses to user queries.
Unanswered Questions
How does this technology handle complex and ambiguous queries from users?
The article does not provide details on how the system processes and responds to complex or ambiguous queries from users.
What measures are in place to ensure the accuracy and reliability of the information provided by the system?
The article does not mention any specific measures or mechanisms to ensure the accuracy and reliability of the information generated by the system.
Original Abstract Submitted
in various examples, systems and methods that use dialogue systems associated with various machine systems and applications are described. for instance, the systems and methods may receive text data representing speech, such as a question associated with a vehicle or other machine type. the systems and methods then use a retrieval system(s) to retrieve a question/answer pair(s) associated with the text data and/or contextual information associated with the text data. in some examples, the contextual information is associated with a knowledge base associated with or corresponding to the vehicle. the systems and methods then generate a prompt using the text data, the question/answer pair(s), and/or the contextual information. additionally, the systems and methods determine, using a language model(s) and based at least on the prompt, an output associated with the text data. for instance, the output may include information that answers the question associated with the vehicle.
