3D Scene Interaction Using Intent-Based Personal Knowledge Selection
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Solution Overview
Problem
Existing computer systems lack the ability to provide personalized and efficient assistance to users in three-dimensional environments by accurately interpreting user intent and generating relevant actions based on user-specific knowledge, leading to inefficient user interactions and increased power consumption.
Innovation Solution
A computer system that utilizes image sensors to detect data representing a scene, determines user intent, and selects a relevant portion of a personalized knowledge base to generate actions that account for both the user's personal information and the three-dimensional environment, thereby improving interaction efficiency and reducing power usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the computer system uses a personalized knowledge base to generate actions, then action accuracy and user interaction efficiency are improved, but device complexity increases
Solution Approach 1:
The knowledge base is segmented into a personalized portion specific to each user and a general portion. The system selectively queries only the relevant personalized portion when generating actions, rather than processing the entire knowledge base. This segmentation allows the system to maintain high action accuracy using user-specific information while reducing the computational complexity of knowledge base processing.
Solution Approach 2:
The system performs preliminary actions by pre-processing and storing user-specific information in the personalized knowledge base during user interactions. This pre-processed information is then quickly retrieved and used to generate accurate actions without requiring complex real-time analysis, thereby improving action accuracy while managing system complexity.
2Reliability
If the computer system processes all available personal information, then action completeness is improved, but processing time and power consumption increase
Solution Approach 1:
The system extracts only the relevant portion of personal information from the complete knowledge base that is necessary for generating the current action. Instead of processing all available personal information, the system selectively retrieves and processes only what is needed based on the current scene and user intent, thereby maintaining action completeness while significantly reducing processing time and power consumption.
Solution Approach 2:
The system applies partial action by processing only a subset of the available personal information - specifically, the personalized knowledge base portion that is relevant to the current task. This partial processing approach ensures that sufficient information is used to generate complete and accurate actions without the overhead of processing the entire knowledge base, thus reducing processing time and energy consumption.
3Ease of operation
If the computer system reduces the number of user inputs, then ease of operation is improved, but information accuracy may deteriorate
Solution Approach 1:
The system performs self-service by automatically inferring user intent and generating actions using the personalized knowledge base without requiring explicit user inputs for each action. The system self-corrects and self-adjusts by learning from past user interactions stored in the knowledge base, thereby improving ease of operation while maintaining information accuracy through automated intent recognition and action selection.
Solution Approach 2:
The system implements feedback mechanisms where user responses to generated actions are stored in the personalized knowledge base. This feedback loop allows the system to continuously improve its intent inference accuracy by learning from actual user behavior patterns, ensuring that reduced user inputs do not compromise information accuracy - instead, accuracy improves over time through accumulated feedback.
Data Source
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AI summary
An example process includes: detecting, via at least the one or more image sensors, first data that represents a first scene; and in response to detecting, via at least the one or more image sensors, the first data that represents the first scene and after an inference about a user intent with respect to the first scene is determined based on the first data that represents the first scene: in accordance with a determination that a portion of a knowledge base is selected based on the inference about the user intent with respect to the first scene, wherein the knowledge base is personal to a user of the computer system, and in accordance with a determination that a first action satisfies a set of action criteria, performing the first action, wherein the first action is generated based on the selected portion of the knowledge base.