18674509. PERFORMING SUBTASK(S) FOR A PREDICTED ACTION IN RESPONSE TO A SEPARATE USER INTERACTION WITH AN AUTOMATED ASSISTANT PRIOR TO PERFORMANCE OF THE PREDICTED ACTION simplified abstract (Google LLC)

PERFORMING SUBTASK(S) FOR A PREDICTED ACTION IN RESPONSE TO A SEPARATE USER INTERACTION WITH AN AUTOMATED ASSISTANT PRIOR TO PERFORMANCE OF THE PREDICTED ACTION

Organization Name

Google LLC

Inventor(s)

Lucas Mirelmann of Zurich (CH)

Zaheed Sabur of Baar (CH)

Bohdan Vlasyuk of Zurich (CH)

Marie Patriarche Bledowski of Richterswil (CH)

Sergey Nazarov of Kilchberg ZH (CH)

Denis Burakov of Zurich (CH)

Behshad Behzadi of Freienbach (CH)

Michael Golikov of Merlischachen (CH)

Steve Cheng of Los Altos CA (US)

Daniel Cotting of Islisberg (CH)

Mario Bertschler of Zurich (CH)

PERFORMING SUBTASK(S) FOR A PREDICTED ACTION IN RESPONSE TO A SEPARATE USER INTERACTION WITH AN AUTOMATED ASSISTANT PRIOR TO PERFORMANCE OF THE PREDICTED ACTION - A simplified explanation of the abstract

This abstract first appeared for US patent application 18674509 titled 'PERFORMING SUBTASK(S) FOR A PREDICTED ACTION IN RESPONSE TO A SEPARATE USER INTERACTION WITH AN AUTOMATED ASSISTANT PRIOR TO PERFORMANCE OF THE PREDICTED ACTION

Simplified Explanation

The patent application describes a system for processing natural language input to provide information and predict actions for an automated assistant.

Key Features and Innovation

• Receiving natural language input requesting information
• Processing the input to identify requested information and predicted actions
• Rendering the information and predicted actions in response to the input
• Initializing predicted actions upon user confirmation

Potential Applications

This technology can be used in various applications such as virtual assistants, customer service chatbots, and smart home devices.

Problems Solved

This technology streamlines the process of receiving and responding to natural language requests, improving user experience and efficiency.

Benefits

• Enhanced user interaction with automated assistants
• Faster and more accurate responses to user queries
• Improved efficiency in completing tasks based on predicted actions

Commercial Applications

• Virtual assistant software development
• Customer service automation solutions
• Smart home device integration

Prior Art

Researchers can explore prior art related to natural language processing, virtual assistants, and predictive analytics to understand the evolution of this technology.

Frequently Updated Research

Stay updated on advancements in natural language processing, machine learning, and artificial intelligence to enhance the capabilities of automated assistants.

Questions about Natural Language Processing

How does natural language processing improve user interactions with automated assistants?

Natural language processing enables automated assistants to understand and respond to user queries more effectively, enhancing the overall user experience.

What are the key challenges in implementing predictive actions based on natural language input?

Implementing predictive actions requires advanced algorithms and data processing to accurately anticipate user needs and preferences.

Original Abstract Submitted

Implementations relate to receiving natural language input that requests an automated assistant to provide information and processing the natural language input to identify the requested information and to identify one or more predicted actions. Those implementations further cause a computing device, at which the natural language input is received, to render the requested information and the one or more predicted actions in response to the natural language input. Yet further, those implementations, in response to the user confirming a rendered predicted action, cause the automated assistant to initialize the predicted action.