3 Common Pitfalls for Rolling Out Industrial Edge AI

David Zhu-Grant from Teguar is here to save you time and money with his expertise in Edge AI deployments. In this video, we’ll dive into three common mistakes made when preparing for these deployments that can result in failure or added costs, and discuss how to avoid them for a successful industrial edge solution.

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DAVID: I’m David Zhu-Grant, I’m the Director of Product here at Teguar, and I’m here to talk about three common pitfalls for rolling out industrial edge AI.

The first challenge we’re talking about here is committing to a big spend on hardware before ensuring the application and model pipeline is stable and works. The key here is to prove out the concept before going too far in the hardware commitment, either in quantity of units or in the ruggedness. This is where understanding benchmarking AI compute to compare your working solution to the deployment solution is very useful for those later phases.

So the second thing here is trying to scale with consumer grade products and then watching them fail in the environment. Typical edge AI environments can be harsh with particulates in the air, wide temperature variations, shock and vibration when deployed on vehicles, or they require specific regulatory compliance or certifications such as the military standard, MIL-STD-810H. If you want more information on how to decide what hardware to choose and why, check out our other videos for more information.

So the third challenge we have here is deploying a single hardware optional solution when future needs are likely to change or shift. So it’s imperative that you have a partner like Teguar to help with a portfolio of products to allow for flexibility within edge AI solutions or for future-proofing expansions of performance. Often it’s not a one size fits all, and future needs may grow.

Obviously starting out it’s tempting to lean into purchasing a rugged, reliable system, but we find there’s real value in understanding application model needs first. Often you need to get a stable platform first, even if it’s on your desktop or a dev kit to prove your AI solution performs within your workflow. And then you can see how you deploy at the edge with the right hardware partner.

This is where leaning on Teguar’s highly reliable and trusted edge AI systems is key.

If you’re interested to learn more, don’t hesitate to reach out to Teguar. We have a great bunch of people who are prepared to talk you through what great products we have in the edge AI space.

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About the Authors:

Madelyn Brannan serves as the Digital Marketing Coordinator at Teguar, which presents an engaging opportunity to learn new things. She strives to help current and future customers by making them aware of the solutions that Teguar can provide. When Madelyn isn't researching things like you've just read about, they like to draw and play tabletop games.