Cloud Message Processing via Language Model Routing
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Solution Overview
Problem
Current cloud computing systems lack an efficient method to process messages from client devices, determine the appropriate language, and execute corresponding functions provided by applications, especially when messages contain characters and graphical symbols, leading to difficulties in identifying intended functions and providing accurate responses.
Innovation Solution
A system that receives messages from client devices, determines the language, identifies a corresponding language model, and sends requests to perform associated functions, utilizing natural language processing when necessary, to execute functions and send responses back to the client devices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If cloud computing systems use traditional message processing methods, then system simplicity is maintained, but the ability to accurately process multilingual messages with characters and graphical symbols deteriorates
Solution Approach 1:
The patent introduces a language model as an intermediary component between the message processing system and the application functions. The language model receives messages, determines their language, and translates them into executable commands, enabling the system to handle multilingual messages with characters and graphical symbols without requiring complex native language processing capabilities in each application.
Solution Approach 2:
The patent implements a universal language model that can process multiple languages and message types through a single system component. This language model serves multiple functions including language detection, message interpretation, and command generation, allowing diverse messages (text, characters, graphical symbols) to be processed through a unified interface.
2Measurement precision
If the system processes messages by determining language and executing corresponding functions, then message processing accuracy is improved, but processing time increases
Solution Approach 1:
The patent pre-establishes language models for multiple languages before runtime, with each model containing predefined mappings between message patterns and application functions. When a message arrives, the system quickly matches it against these pre-compiled models rather than performing complex analysis from scratch, significantly reducing processing time while maintaining high accuracy.
3Adaptability or versatility
If the system supports multiple languages and functions, then user accessibility is improved, but system complexity increases
Solution Approach 1:
The patent divides the multilingual processing system into separate language models, each dedicated to a specific language. Each language model contains only the mappings and rules relevant to its language, allowing independent development, maintenance, and optimization of each model without affecting others. This segmentation reduces the complexity of managing any single language model while supporting multiple languages overall.
Data Source
AI summary
Some embodiments provide a non-transitory machine-readable medium that stores a program. The program receives a message from a client device. The program further determines a language from a plurality of languages associated with the message. The program also determines a model from a plurality of models that corresponds to the determined language. Based on the determined model, the program further determines a function from a plurality of functions provided by a computing device that is associated with the message. The program also sends the computing device a request to perform the function.