Virtual Assistant Task Caching for Faster Low-Battery Response
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Solution Overview
Problem
Existing methods for executing tasks with virtual assistants, whether client-side or server-side, suffer from inefficiencies that lead to slow task execution speeds and increased cognitive burden on users, particularly in battery-operated devices, due to chronic or intermittent limitations in client-server connections.
Innovation Solution
Implementing a distributed personal assistant system with a client-side and server-side component architecture that optimizes task execution by reducing redundant user inputs and conserving processor and battery power, utilizing a non-transitory computer-readable storage medium to execute instructions for faster and more efficient task completion.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If tasks are executed locally on the electronic device, then response time and user experience are improved, but device battery life and processing capabilities are reduced
Solution Approach 1:
The system segments tasks into different categories based on their performance characteristics. Frequently executed tasks are identified and separated from other tasks, allowing them to be cached locally for fast execution while other tasks can be processed remotely or on-demand, thus balancing local processing speed with energy conservation.
Solution Approach 2:
The system performs preliminary actions by identifying frequently executed tasks in advance and caching their executable code locally on the device. This preliminary caching operation enables these tasks to be executed quickly when needed without consuming battery power during actual execution, as the code is already prepared and stored.
2Speed
If tasks are executed locally on the electronic device, then response time is improved, but device complexity increases
Solution Approach 1:
The system applies partial action by caching only the most frequently executed tasks locally rather than all possible tasks. This selective approach provides the speed benefits of local execution for critical tasks while avoiding the complexity and resource requirements of maintaining all task code locally, thus achieving a balanced solution.
3Use of energy by moving object
If tasks are executed remotely, then device battery life is extended, but response time and user experience deteriorate
Solution Approach 1:
The system applies local quality by providing different execution locations for different tasks based on their specific characteristics. Frequently executed tasks are cached and executed locally on the device for fast response, while less frequent tasks can be executed remotely. This differentiated approach optimizes both battery life and response time for different task types.
Data Source
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AI summary
An exemplary method for using a virtual assistant may include, at an electronic device configured to transmit and receive data, receiving a user request for a service from a virtual assistant; determining at least one task to perform in response to the user request; estimating at least one performance characteristic for completion of the at least one task with the electronic device, based on at least one heuristic; based on the estimating, determining whether to execute the at least one task at the electronic device; in accordance with a determination to execute the at least one task at the electronic device, causing the execution of the at least one task at the electronic device; in accordance with a determination to execute the at least one task outside the electronic device: generating executable code for carrying out the least one task; and transmitting the executable code from the electronic device.