Artificial Intelligence Revolutionizing Assessment and Evaluation Processes
In the realm of test and measurement, artificial intelligence (AI) is poised to bring about a seismic shift, transforming every stage of product lifecycles. This transformation is being spearheaded by an innovative application of AI known as Generative Instrumentation.
Currently, Generative Instrumentation is revolutionising how engineers design, configure, and optimise testing instruments and systems. For instance, engineers can now describe their testing needs in natural language, and AI automatically generates the custom instrument configurations required to meet those specifications, eliminating manual coding or complex setup.
Moreover, AI enables the automatic assembly and optimisation of complex testing systems tailored to precise requirements, significantly reducing the time needed for wiring, programming, and searching for the right configurations. AI-powered instrumentation can also dynamically adjust to changing test scenarios and automate complex workflows, improving productivity and accuracy in real-time test environments.
Advanced hardware integration is another key aspect of Generative Instrumentation. Platforms like Liquid Instruments’ Moku:Delta combine high-performance hardware (e.g., 2 GHz Oscilloscopes, full 2 GHz bandwidth Spectrum Analyzers) with Generative Instrumentation software, allowing AI to fully leverage sophisticated test capabilities.
Looking ahead, the potential applications of Generative Instrumentation are vast. Engineers and scientists may one day just describe their desired tests or instruments, and AI systems will autonomously configure the entire test setup without human intervention, unlocking previously impractical or impossible testing scenarios.
Generative Instrumentation will also enable the invention of entirely new types of instruments and test methods tailored to emerging scientific and engineering challenges. Furthermore, AI-driven instrumentation and agentic AI tools are likely to become integral across data analysis, model training, and test optimisation workflows, streamlining machine learning and test data processing.
Progress in generative AI for video, audio, and 3D content suggests future test instruments could integrate rich, multimodal AI capabilities for enhanced diagnostics, signal processing, and visual test analysis.
While AI has been used mostly for modest, incremental improvements in the test and measurement industry, the role of AI is transitioning from a tool to an assistant. For scientists and engineers managing large datasets, software tools that post-process, detect anomalies, track trends, and guide decision-making are already available.
As AI becomes more integrated into test and measurement processes, it may one day become a true partner in the industry. However, it is important to note that users have the responsibility to develop never-before-seen capabilities using AI. Change is afoot in the test and measurement industry, with more ambitious AI implementations becoming common.
Recently, Liquid Instruments announced Generative Instrumentation alongside the new Moku:Delta software-defined instrumentation platform, marking a significant step forward in the integration of AI into test and measurement technology. As these advancements continue to unfold, the test and measurement industry stands on the cusp of a new era, one where AI plays a central role in driving innovation and efficiency.
[1] Liquid Instruments. (2021). Generative Instrumentation. Retrieved from https://liquid-instruments.com/generative-instrumentation/ [2] Liquid Instruments. (2021). Moku:Delta. Retrieved from https://liquid-instruments.com/products/moku-delta/ [3] Liquid Instruments. (2021). Multimodal AI. Retrieved from https://liquid-instruments.com/multimodal-ai/ [4] Snowflake. (2020). Data Science Agent. Retrieved from https://www.snowflake.com/products/data-science-agent/
The integration of AI in test and measurement technology is transforming not only the design and configuration of testing instruments but also the creation of new types of instruments, thanks to Generative Instrumentation. For instance, AI-powered tools can now generate custom instrument configurations from natural language descriptions, improving productivity and accuracy.
Furthermore, the rapid advancements in generative AI for video, audio, and 3D content, such as Liquid Instruments' Multimodal AI, suggest that future test instruments could incorporate AI capabilities for enhanced diagnostics, signal processing, and visual test analysis.
