AI Capability Intent Orchestration for Update-Resilient Productivity Tools
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing AI productivity tools require frequent updates and high overhead due to changes in hardware configurations and software versions, leading to inefficient management of API calls for executing user queries.
Innovation Solution
An OTB AI productivity tool employs machine learning models to identify pre-registered capabilities using NLP, allowing it to instruct AI productivity tool enableable software applications to perform actions without direct API calls, dynamically adjusting capabilities based on current hardware configurations and policies.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional AI productivity tools use direct API calls to execute user queries, then they can perform actions accurately, but they require frequent updates and have high overhead when hardware configurations and software versions change
Solution Approach 1:
The patent introduces NLP-based capability intent values as an intermediary layer between user queries and API calls. Instead of directly mapping queries to specific APIs, the system translates queries into semantic capability intents that can be executed by enableable software applications. This mediator layer decouples the query execution mechanism from specific API implementations, allowing the system to adapt to configuration changes without requiring frequent updates to the core AI tool.
Solution Approach 2:
The system changes the parameter representation from rigid API call signatures to flexible NLP-based capability intent values. By transforming the execution parameter from a fixed API interface to a semantic representation that can be dynamically interpreted, the system gains adaptability to hardware and software configuration changes while maintaining reliable action execution through the enableable software applications that implement these capabilities.
2Adaptability or versatility
If AI productivity tools frequently update to adapt to hardware and software changes, then they maintain compatibility, but they increase management overhead and reduce operational efficiency
Solution Approach 1:
The patent creates a universal capability intent layer that can interface with multiple different hardware configurations and software versions through enableable software applications. The NLP-based capability intents serve as a universal interface that can be implemented across various applications and configurations without requiring the AI productivity tool itself to be updated for each specific hardware or software change, thus maintaining compatibility while preserving operational efficiency.
Solution Approach 2:
The system performs preliminary translation of user queries into capability intent values before execution, creating a standardized intermediate representation that can be handled by various enableable software applications. This preliminary action of semantic translation occurs once during query processing, eliminating the need for continuous updates and reconfiguration when underlying hardware or software changes, thereby maintaining adaptability without sacrificing productivity.
3Ease of operation
If AI productivity tools use a standardized interface for all software applications, then they simplify integration, but they cannot leverage application-specific capabilities and features
Solution Approach 1:
The patent segments the system into three distinct layers: (1) a standardized NLP-based capability intent interface that simplifies integration, (2) enableable software applications that implement specific capabilities, and (3) application-specific API calls that leverage unique features. This segmentation allows the standardized interface to handle general integration while enabling applications to opt-in and expose their specific capabilities through the same interface, thus achieving both integration simplicity and capability versatility.
Solution Approach 2:
The system implements a dynamic capability registration mechanism where enableable software applications can dynamically register their specific capabilities with the AI productivity tool through the standardized interface. The capability intent values are not fixed but can be dynamically added, removed, or modified based on which applications are enabled and their current capabilities, allowing the system to maintain a simple standardized interface while adapting to leverage application-specific features as they become available.
Data Source
AI summary
An information handling system operating an On the Box (OTB) Artificial Intelligence (AI) productivity tool may comprise a hardware processor to execute machine readable code instructions of an AI productivity tool enableable software application to register with the OTB AI productivity tool a dynamically updated capability for an AI productivity tool enableable software application having a natural language description. The hardware processor may execute machine readable code instructions of the OTB AI productivity tool to generate a vectorized capability intent value from the updated capability natural language description, to receive a user query input requesting performance of an action, to determine that a vectorized query input intent value for the user query input correlates to the vectorized capability intent value, indicating that the user query input is requesting performance of the updated capability, and to instruct the AI productivity tool enableable software application to perform the updated capability.