Operation Mimicry System for Cross-App Task Automation
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Solution Overview
Problem
Automated virtual assistants are limited in their ability to interact with multiple applications, require precise commands, and struggle to predict user requests due to processing constraints, leading to inefficient task completion and user frustration.
Innovation Solution
An operation mimicry system that collects and stores user interactions, determines user intentions, and generates sequences of operations to execute tasks across multiple applications, allowing for natural language input and suggesting actions based on user relationships and interests.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If automated virtual assistants interact with multiple applications through specific purpose-built applications or open APIs, then the processing capabilities and task completion ability are improved, but the device complexity and integration requirements increase
Solution Approach 1:
The patent implements a universal interface layer that enables the virtual assistant to interact with multiple different applications through a standardized mechanism. This interface acts as a mediator that translates between the virtual assistant's command structure and the diverse APIs of various applications, allowing one system to perform multiple functions across different apps without requiring separate integration code for each application.
Solution Approach 2:
The patent introduces an intermediary component (the interface layer) that sits between the virtual assistant and the applications. This intermediary handles the complexity of application-specific protocols and data formats, translating them into a unified structure that the virtual assistant can process. This mediator approach resolves the contradiction by isolating the virtual assistant from application-specific complexities while maintaining broad compatibility.
2Measurement precision
If automated virtual assistants require precise commands in specific formats to complete tasks, then the processing accuracy is improved, but the ease of operation deteriorates
Solution Approach 1:
The interface layer serves as an intermediary that translates natural language user inputs into the precise structured commands required by applications. It parses and interprets user intent, converting casual language into accurate, format-compliant requests that maintain processing precision while allowing users to operate the system in natural, convenient ways.
Solution Approach 2:
The system performs automatic parsing, interpretation, and formatting of user inputs without requiring users to manually structure their commands. The interface layer autonomously handles the transformation from natural language to precise commands, making the system self-serve the formatting requirements while maintaining accuracy in task execution.
3Speed
If automated virtual assistants process user requests in real-time without collecting historical information, then the processing speed is improved, but the ability to predict user requests and provide contextual responses deteriorates
Solution Approach 1:
The system performs preliminary actions by collecting and storing user interaction data, relationship information, and contextual data in advance. This pre-collected information is then quickly retrieved and applied during user interactions, enabling fast real-time processing while incorporating predictive capabilities based on historical patterns and user preferences.
Solution Approach 2:
The system maintains continuous data collection and analysis in the background, building up user profiles and contextual understanding over time. This continuous accumulation of useful information occurs parallel to real-time request processing, allowing the system to provide predictive responses without interrupting or slowing down the immediate interaction flow.
Data Source
AI summary
Disclosed is a system for determining sequences of operations that will automatically execute one or more tasks specified by a user. In some embodiments, the sequences of operations are based on operations that have been previously performed by users and recorded by the system. The system interprets an intention of a user based on analysis of terms used by the user to indicate a request. The system generates a sequence of operations, executable by an operating system associated with a client device that will perform one or more tasks specified or implied by the request of the user.