20230085061. SYSTEMS AND METHODS FOR CONTINUAL UPDATING OF RESPONSE GENERATION BY AN ARTIFICIAL INTELLIGENCE CHATBOT simplified abstract (Cambia Health Solutions, Inc.)
SYSTEMS AND METHODS FOR CONTINUAL UPDATING OF RESPONSE GENERATION BY AN ARTIFICIAL INTELLIGENCE CHATBOT
Organization Name
Inventor(s)
Weicheng Ma of Brooklyn NY (US)
SYSTEMS AND METHODS FOR CONTINUAL UPDATING OF RESPONSE GENERATION BY AN ARTIFICIAL INTELLIGENCE CHATBOT - A simplified explanation of the abstract
This abstract first appeared for US patent application 20230085061 titled 'SYSTEMS AND METHODS FOR CONTINUAL UPDATING OF RESPONSE GENERATION BY AN ARTIFICIAL INTELLIGENCE CHATBOT
Simplified Explanation
The abstract describes a patent application for a natural language processing system with a chatbot that generates responses to user queries. The system combines a variational autoencoder (VAE) and a generative adversarial network (GAN) to improve the quality of the chatbot's responses. Here are the key points:
- The system includes a chatbot that generates natural responses to user queries.
- It uses a combination of a variational autoencoder (VAE) and a generative adversarial network (GAN).
- The VAE converts queries into vector embeddings, which are then used by the GAN.
- The GAN continuously updates and improves the responses provided by the chatbot.
- The goal is to enhance the chatbot's ability to generate more natural and contextually relevant responses.
Potential applications of this technology:
- Customer service chatbots that provide more accurate and helpful responses to user queries.
- Virtual assistants that can engage in more natural and meaningful conversations with users.
- Language learning tools that can generate realistic dialogues for practice and learning purposes.
Problems solved by this technology:
- Improves the quality of responses generated by chatbots, making them more human-like and contextually relevant.
- Addresses the challenge of generating natural language responses in a conversational setting.
- Enhances the overall user experience by providing more accurate and engaging interactions.
Benefits of this technology:
- Provides more accurate and helpful responses to user queries, improving customer satisfaction.
- Enables chatbots to have more meaningful and natural conversations with users.
- Enhances language learning experiences by generating realistic dialogues for practice.
- Reduces the need for human intervention in customer service or support scenarios.
Original Abstract Submitted
methods and systems are provided for a natural language processing system comprising a chatbot adapted for dialog generation. in one example, the system may include a combination of a variational autoencoder (vae) and a generative adversarial network (gan) for generating natural responses to input queries. the vae may convert queries into vector embeddings that may then be used by the gan to continuously update and improve responses provided by the chatbot.
