On-Device AI Processing Load Distribution for Speed and Accuracy
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Solution Overview
Problem
On-device AI processing faces limitations in processing speed and accuracy, particularly in noisy environments or with long texts, compared to server or cloud-based processing.
Innovation Solution
An on-device AI processing system that distributes AI processing load to external or internal devices when the terminal's capacity is exceeded, combining local and distributed processing results to enhance performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If on-device AI processing is used, then processing speed is improved, but processing accuracy deteriorates
Solution Approach 1:
The patent segments AI processing into two parts: simple tasks are processed locally on the terminal device for speed, while complex tasks are processed externally for accuracy. This segmentation allows the system to optimize for both speed and accuracy depending on the task requirements.
Solution Approach 2:
The patent introduces an intermediary mechanism that determines whether to process AI tasks locally or externally based on task complexity. This intermediary selection process enables the system to achieve both fast processing for simple tasks and high accuracy for complex tasks.
2Productivity
If on-device AI processing is used, then processing capability is improved, but power consumption increases
Solution Approach 1:
The patent segments processing tasks based on their computational requirements, assigning simple tasks to local processing and complex tasks to external processing. This segmentation enables the terminal to maintain processing capability while avoiding excessive power consumption for tasks that don't require full local processing power.
Solution Approach 2:
The patent applies partial processing locally and external processing for the remainder, rather than always using full local processing capability. This partial action approach maintains necessary processing capability while reducing overall power consumption by avoiding excessive local computation.
3Loss of time
If on-device AI processing is used, then response time is improved, but processing completeness deteriorates
Solution Approach 1:
The patent segments processing based on task complexity, handling simple tasks locally for fast response and complex tasks externally for complete processing. This segmentation ensures that response time is optimized for simple tasks while processing completeness is maintained for complex tasks.
Solution Approach 2:
The patent introduces an intermediary selection mechanism that determines whether to process tasks locally or externally based on complexity assessment. This intermediary process ensures that simple tasks get fast local response while complex tasks receive complete external processing.
Data Source
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AI summary
An on-device artificial intelligence (AI) processing distributed processing device and method capable of distributing AI processing load of a terminal through internal or external other devices are provided. The on-device AI processing distributed processing device can, measure an amount of AI processing for performing the user command, select an AI processing distributed processing target when the measured amount of AI processing exceeds a self-processing capacity, request distributed process for AI processing to the selected AI processing distributed processing target, and when a first AI processing result value is received from the AI processing distributed processing target, provide a final result value based on the first AI processing result value and a self-processed second AI processing result value.