18062691. SYNTHESIS OF PERSONALIZED CONVERSATIONAL AUTOMATION AGENTS simplified abstract (International Business Machines Corporation)
Contents
SYNTHESIS OF PERSONALIZED CONVERSATIONAL AUTOMATION AGENTS
Organization Name
International Business Machines Corporation
Inventor(s)
Praveen Venkateswaran of Cambridge MA (US)
Nigel Steven Fernandez of Sunderland MA (US)
Yara Rizk of Cambridge MA (US)
Vatche Isahagian of Belmont MA (US)
Vinod Muthusamy of Austin TX (US)
SYNTHESIS OF PERSONALIZED CONVERSATIONAL AUTOMATION AGENTS - A simplified explanation of the abstract
This abstract first appeared for US patent application 18062691 titled 'SYNTHESIS OF PERSONALIZED CONVERSATIONAL AUTOMATION AGENTS
Simplified Explanation: This patent application describes a method, computer system, and computer program product for synthesizing software agents based on natural language inputs from users.
Key Features and Innovation:
- Generating training examples from historical data and software agents
- Training a language model to synthesize software agents based on natural language inputs
- Monitoring for natural language user inputs using input devices
- Synthesizing software agents based on user inputs and executing them to carry out tasks
Potential Applications: This technology could be applied in customer service chatbots, virtual assistants, automated help desks, and other systems that require understanding and responding to natural language inputs.
Problems Solved: This technology addresses the challenge of efficiently creating and deploying software agents that can understand and act upon natural language inputs from users.
Benefits:
- Improved user experience with more intuitive interactions
- Increased efficiency in handling user requests
- Scalability in deploying software agents across various applications
Commercial Applications: The technology could be used in customer service industries, healthcare for patient interactions, and various other sectors where automated responses to user queries are needed.
Prior Art: Prior research in natural language processing, machine learning, and artificial intelligence may provide insights into similar approaches to synthesizing software agents based on user inputs.
Frequently Updated Research: Stay updated on advancements in natural language processing, machine learning, and software agent synthesis to enhance the capabilities and efficiency of this technology.
Questions about Software Agent Synthesis: 1. What are the key challenges in training language models to synthesize software agents based on natural language inputs? 2. How does this technology compare to existing methods for creating and deploying software agents in response to user inputs?
Original Abstract Submitted
According to one embodiment, a method, computer system, and computer program product for software agent synthesis is provided. The present invention may include generating one or more training examples from historical data and software agents; training, using the on the one or more training examples, a language model to synthesize a software agent based on a natural language input from a user; monitoring, using one or more input devices, for one or more natural language user inputs; responsive to identifying one or more natural language user inputs, synthesizing, using the trained language model, one or more software agents based on the one or more natural language user inputs; execute the one or more new software agents to carry out one or more tasks invoked by the one or more natural language user inputs.
