Overview
AI is everywhere. But in test systems, performance must be measured, verified, and traceable.
As AI tools accelerate development, they also introduce new challenges around validation, repeatability, and real-world behavior. For test engineers working close to hardware, these concerns directly impact measurement integrity and system performance.
In this interview-style webinar, we’ll explore how disciplined, verification-first approaches combined with FPGA-based platforms can turn AI from a black-box generator into a practical, trustworthy, and rigorously engineered tool. We’ll discuss how AI-assisted design workflows can be incorporated into established engineering processes: defining requirements, generating configurations, and validating results against measurable criteria.
We’ll also examine how reconfigurable hardware enables real-time execution closer to signals, sensors, and systems without the latency and unpredictability of traditional software-only approaches.
Attendees will gain a practical perspective on where AI fits into modern test workflows, how to evaluate it using familiar engineering principles, and how to apply it without compromising rigor.
Attendees will learn to:
- Understand where AI fits in test engineering workflows: Identify practical use cases where AI can accelerate development without compromising measurement integrity or system performance.
- Apply verification-first principles to AI-assisted design: Learn how to incorporate requirements, validation criteria, and measurable thresholds into AI-driven workflows.
- Evaluate AI-generated outputs using engineering metrics: Develop strategies for assessing repeatability, accuracy, and reliability in AI-assisted test configurations.
- Explain the role of FPGA-based systems in deterministic test environments: Understand how reconfigurable hardware enables real-time execution closer to signals and reduces latency, jitter, and OS-related variability.
- Integrate AI into existing test workflows without sacrificing control: Explore how AI can support engineers in moving from high-level intent to validated, deployable test systems within established engineering processes.
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Date: June 4, 2026
Speaker: Brian Neff Ph. D.
Aerospace and Defense Application Engineer,
Liquid Instruments