AI Modality Entry Points for Streamlined Interaction Processing
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Solution Overview
Problem
Existing human-machine interaction systems require multiple steps and are limited in their ability to quickly apply artificial intelligence (AI) and respond to user needs, lacking efficient integration of AI with electronic devices and sensors, which hinders personalized and efficient interactions.
Innovation Solution
An interaction processing method that invokes AI application modality entry points through trigger instructions, acquires and processes interaction information via modality entry points, and outputs results through associated modality types, reducing operation steps and enhancing efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional human-machine interaction systems are used, then system stability is maintained, but the number of operation steps increases and interaction efficiency deteriorates
Solution Approach 1:
The patent merges multiple interaction modalities (voice, text, image, video) into a unified AI processing framework. The modality entry point integrates various input types and the large language model processes them collectively, reducing the need for separate processing paths for each modality and thereby reducing operation steps while maintaining system stability.
Solution Approach 2:
The AI application is designed with universal processing capability across multiple modalities. The same large language model handles different input types (voice, text, image, video) through a unified interface, eliminating the need for modality-specific processing chains and reducing the overall number of interaction steps required.
2Productivity
If AI application is directly invoked through trigger instruction, then interaction efficiency is improved, but system complexity increases
Solution Approach 1:
The modality entry point acts as an intermediary component between the trigger instruction and the large language model. It receives various types of input data, standardizes them into a unified format, and passes them to the AI processing system. This intermediary layer simplifies the overall system architecture by providing a single entry point for multiple modalities rather than requiring separate processing paths.
Solution Approach 2:
The system is segmented into distinct functional modules: the trigger instruction detector, the modality entry point, the large language model processor, and the output generator. This modular segmentation allows each component to be optimized independently while maintaining overall system simplicity and enabling direct invocation through the trigger instruction mechanism.
3Adaptability or versatility
If multiple modalities are integrated into one AI processing system, then interaction versatility is improved, but processing complexity increases
Solution Approach 1:
The large language model is configured to universally process multiple input modalities (voice, text, image, video) through a single processing framework. This universal processing capability allows the system to handle diverse interaction types without requiring separate processing architectures for each modality, thereby maintaining processing simplicity while achieving high versatility.
Solution Approach 2:
The system handles different modalities by transforming them into a unified parameter format that the large language model can process. Each modality (voice, text, image, video) is converted into standardized input parameters, allowing the same processing logic to handle all modalities uniformly and reducing the complexity of managing multiple processing paths.
Data Source
AI summary
An interaction processing method and related products are provided. In the method, at least one modality entry point of an artificial intelligence (AI) application is invoked in response to a trigger instruction detected; interaction information to-be-processed is acquired, and the interaction information to-be-processed is input to the AI application through the modality entry point; and according to an input modality type of the interaction information to-be-processed, a processing result corresponding to the interaction information to-be-processed is output by the AI application through an output modality type associated with the input modality type.