Microsoft technology licensing, llc (20240202584). MACHINE LEARNING INSTANCING simplified abstract

MACHINE LEARNING INSTANCING

Organization Name

microsoft technology licensing, llc

Inventor(s)

Samuel Edward Schillace of Portola Valley CA (US)

Umesh Madan of Bellevue WA (US)

Brian Krabach of Snohomish WA (US)

MACHINE LEARNING INSTANCING - A simplified explanation of the abstract

This abstract first appeared for US patent application 20240202584 titled 'MACHINE LEARNING INSTANCING

The present disclosure pertains to machine learning instancing, where an instance of an agent is encapsulated as an agent object, allowing for portability and various processing capabilities.

• An agent object stores an instance of an agent, such as processing user input through a machine learning model to generate model output.
• The agent object can be stored as a file, document, or in a database, enabling easy access and manipulation.
• It includes a persona definition and/or an object embedding memory, defining different aspects of the agent.
• This portability allows the agent to be transferred between users, contexts, and for various processing purposes.

Potential Applications: - Personalized recommendation systems - Chatbots and virtual assistants - Adaptive learning platforms

Problems Solved: - Enhancing user experience through personalized interactions - Improving efficiency in processing user input - Facilitating seamless transfer of agents between different systems

Benefits: - Increased user engagement and satisfaction - Enhanced performance of machine learning models - Simplified management and deployment of agents

Commercial Applications: Title: "Enhancing User Experience Through Machine Learning Instancing" This technology can be utilized in customer service applications, e-commerce platforms, and educational tools to provide personalized and efficient interactions with users.

Questions about Machine Learning Instancing: 1. How does machine learning instancing improve the performance of virtual assistants? Machine learning instancing allows virtual assistants to adapt to individual user preferences and provide more accurate and relevant responses, enhancing the overall user experience.

2. What are the key factors to consider when implementing machine learning instancing in a new system? When implementing machine learning instancing, factors such as data privacy, model training, and integration with existing systems need to be carefully considered to ensure successful deployment and operation.

Original Abstract Submitted

aspects of the present disclosure relate to machine learning instancing, where an instance of an agent (e.g., including processing of user input by a machine learning model to generate model output) is encapsulated as an agent object. in examples, an agent object is stored as a file, as a document, and/or in a database, among other examples. an agent object includes a persona definition and/or an object embedding memory, thereby defining various aspects of the agent. thus, an agent object permits portability the agent, for example between users, across contexts, and/or for a variety of subsequent processing, among other examples.