Semantic Cache Mapping for Low-Latency Smart Device Control
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing automated assistant systems face high latency and resource inefficiencies when controlling smart devices due to the need for remote processing of user inputs, which can be exacerbated by hardware constraints on client devices and geographical distance between servers.
Innovation Solution
Implementing a caching mechanism on client devices that stores semantic representations of user inputs, allowing local interpretation and control of smart devices, reducing the need for constant remote processing and data transmission.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If user inputs are transmitted to remote automated assistant servers for processing, then the system can leverage robust cloud resources for natural language understanding and control request generation, but this results in high latency and excessive network resource usage
Solution Approach 1:
The patent implements a caching mechanism that stores semantic representations of frequently used user inputs and corresponding control requests locally on client devices. When a user input is received, the system first checks the local cache for a matching semantic representation. If found, the cached control request is used immediately without transmitting the input to remote servers, thereby eliminating network latency for repeated commands while maintaining reliable processing capability through pre-computed cached entries.
2Adaptability or versatility
If all user inputs are processed by remote servers, then comprehensive natural language understanding can be achieved, but this causes excessive usage of server and network resources
Solution Approach 1:
The patent implements a hybrid processing architecture where the client device maintains local cache storage for semantic representations and control requests, while remote servers provide comprehensive natural language understanding capabilities. The system selectively processes inputs locally using cached semantic representations when available, and only transmits to remote servers when cache misses occur or new semantic representations need to be generated. This local-quality approach reduces network resource usage for repeated commands while maintaining versatile natural language understanding through cloud-based processing when needed.
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.