Context-Aware AI Command Translation for Test Instruments
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Solution Overview
Problem
Existing AI assistants for test and measurement devices lack the ability to understand the context of the user's environment and require complex programming to interact with test and measurement equipment, leading to inefficient and slow performance.
Innovation Solution
An AI assistant is developed that receives context-specific knowledge and instrument information, allowing for simplified interactions through a user-friendly interface, including voice control, and can perform actions without requiring detailed knowledge of the instrument's API, using a generative AI model to translate user requests into instrument commands.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If existing AI assistants are used for test and measurement devices, then basic AI functionality is provided, but they lack context understanding and require complex programming leading to inefficient performance
Solution Approach 1:
The patent introduces a context provider as an intermediary component that bridges the gap between the AI assistant and test and measurement instruments. This context provider collects instrument information, configuration settings, and environmental data, then feeds this contextual knowledge to the AI assistant, enabling it to operate efficiently without requiring complex programming from users.
Solution Approach 2:
The system performs preliminary actions by pre-collecting and storing instrument context information, configuration parameters, and environmental data before the user interacts with the AI assistant. This pre-processing of contextual information enables the AI assistant to respond more efficiently and accurately to user requests without requiring complex real-time programming.
2Reliability
If AI assistants require detailed knowledge of instrument APIs to interact with test and measurement equipment, then precise control is achieved, but user complexity increases
Solution Approach 1:
The context provider acts as an intermediary layer that translates high-level user intentions into precise instrument commands. It maintains an internal model of the instrument's capabilities and state, allowing the AI assistant to issue simple, intuitive commands while the context provider handles the complex API translation and instrument control underneath.
Solution Approach 2:
The AI assistant with context provider performs self-service by automatically understanding instrument capabilities, generating appropriate commands, and managing instrument state without requiring users to write code. The system self-adapts to different instruments by using the provided context information to autonomously determine the best way to interact with each device.
3Adaptability or versatility
If AI assistants are implemented as REPL, then interactive programming is enabled, but interaction speed and efficiency are reduced
Solution Approach 1:
The context provider serves as a mediator that enables the AI assistant to access instrument information and state directly without requiring iterative REPL cycles. By providing direct access to contextual data and instrument capabilities, the system achieves faster response times while maintaining rich interactive functionality through the AI assistant's natural language interface.
Data Source
AI summary
A test and measurement system includes one or more test and measurement instruments comprising at least one test and measurement instrument having one or more ports to connect the to a device under test (DUT), one or more memories including test and measurement knowledge, a generative artificial intelligence (AI) model connected to the one or more test and measurement instruments, and the one or more memories, one or more processors to: present a user interface having a prompt to a user, receive a request from the user, the request comprising one or more tasks to be performed by the one or more test and measurement instrument, access an application programming interface (API) of the generative AI model to translate the request to commands, send the commands to the one or more test and measurement instruments, and display an output on the user interface.