Smart Assistant Command Caching for Low-Latency Device Control
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Solution Overview
Problem
Existing techniques for controlling smart devices through automated assistants often result in high latency and excessive resource usage due to the need for remote processing and data transmission.
Innovation Solution
Implementing a caching system on assistant client devices that stores mappings of text to semantic representations, allowing for local processing and reduced reliance on remote systems for common commands.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If remote automated assistant servers process user input data to generate control requests, then comprehensive processing capability is achieved, but latency increases and network resources are excessively consumed
Solution Approach 1:
The system segments processing tasks between client devices and remote servers. Common commands are processed locally on client devices using cached semantic representations, while unusual or complex commands are forwarded to remote servers for processing. This segmentation reduces latency for frequent operations while maintaining comprehensive processing capability for all command types.
Solution Approach 2:
The system performs preliminary action by caching semantic representations of common commands on client devices before they are needed. When a user issues a common command, the client device can immediately match it against cached representations and execute locally without waiting for remote server processing, thereby reducing latency while maintaining accurate semantic understanding.
2Measurement precision
If remote automated assistant servers process all user inputs, then processing accuracy is maintained, but server resources are excessively consumed
Solution Approach 1:
The system applies partial action by processing only the necessary subset of commands through the remote server. Common, frequently-issued commands are handled locally using cached semantic representations, consuming minimal server resources. Only unusual, complex, or first-time commands are forwarded to the server for full processing, thereby maintaining processing accuracy for all commands while significantly reducing overall server resource consumption.
3Reliability
If frequent data transmission to remote servers occurs, then up-to-date processing is achieved, but network bandwidth is excessively consumed
Solution Approach 1:
The system extracts and caches frequently-used semantic representations on client devices, removing the need to repeatedly transmit these common commands to remote servers. This extraction of commonly-needed data to the edge (client device) maintains processing timeliness for frequent operations while dramatically reducing network bandwidth consumption, as only unusual or updated commands require server communication.
Data Source
AI summary
Various implementations relate to techniques, for controlling smart devices, that are low latency and/or that provide computational efficiencies (client and/or server) and/or network efficiencies. Those implementations relate to generating and/or utilizing cache entries, of a cache that is stored locally at an assistant client device, in control of various smart devices (e.g., smart lights, smart thermostats, smart plugs, smart appliances, smart routers, etc.). Each of the cache entries includes a mapping of text to one or more corresponding semantic representations.