Automated Assistant Self-Training for Procedure Detection
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Solution Overview
Problem
Existing automated assistants require explicit user instructions and manual training to perform procedures, leading to inefficient use of computational resources and increased power consumption.
Innovation Solution
An automated assistant that can detect and learn procedures without explicit user identification, by analyzing user actions and differentiating relevant from irrelevant computational actions, allowing for self-recognition and self-training of procedures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If automated assistants require explicit user instructions and manual training to perform procedures, then the assistant can accurately learn user-specific procedures, but computational resources are inefficiently consumed and power usage increases
Solution Approach 1:
The automated assistant performs self-training by automatically detecting procedures from user actions without requiring explicit user instructions. The system autonomously identifies procedural patterns, learns from them, and improves its capabilities independently, thereby reducing the computational overhead associated with manual training while maintaining accurate procedure detection
Solution Approach 2:
The system performs preliminary procedure detection and learning during periods when the assistant is not actively engaged in other tasks. By proactively identifying and learning procedures in advance, the system prepares training data and models during low-utilization periods, reducing real-time computational resource consumption while ensuring accurate procedure recognition when needed
2Adaptability or versatility
If users directly correspond with each other to complete tasks, then communication flexibility is maintained, but computing devices must be continuously initialized consuming additional power
Solution Approach 1:
The automated assistant serves as an intermediary that learns user communication patterns and procedures. Instead of users directly corresponding with each other, the assistant mediates interactions by automatically performing learned procedures, reducing the need for users to continuously initialize their devices while maintaining the flexibility of direct communication through the assistant's autonomous actions
3Productivity
If automated assistants perform procedures autonomously without user involvement, then efficiency improves and power consumption decreases, but the system requires sophisticated procedure detection and learning capabilities
Solution Approach 1:
The automated assistant autonomously detects procedures from user actions and performs self-training to learn these procedures. The system automatically identifies procedural patterns, generates training data, and improves its capabilities without external intervention, enabling efficient autonomous procedure execution while managing system complexity through self-organizing learning mechanisms
Data Source
AI summary
Implementations relate to an automated assistant that can automate repeatedly performed procedures. The automation can involve communicating with different users, organizations, and/or other automated assistants. The automated assistant, with prior permission from respective user(s), can detect repeated performance of a particular series of manually initiated computational actions. Based on this determination, the automated assistant can determine automated assistant computational action(s) that can be performed by the automated assistant in order to reduce latency in performing a procedure, reduce quantity and/or size of transmissions in performing the procedure, and/or reduce an amount of client device resources required for performing the procedure. Such actions can include communicating with an additional automated assistant that may be associated with another user and/or organization. In these and other manners, manually initiated computational actions that include electronic communications amongst users can be converted to backend operations amongst instances of automated assistants to achieve technical benefits.