Edge AI for Smart Manufacturing with Trista Chen

800 800 The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)

Today we’re joined by Trista Chen, chief scientist of machine learning at Inventec.

At GTC, Trista spoke on “Edge AI in Smart Manufacturing: Defect Detection and Beyond.” In our conversation, we discuss a few of the challenges that Industry 4.0 initiatives aim to address and dig into a few of the various use cases she’s worked on, such as the deployment of machine learning in an industrial setting to perform defect detection, safety improvement, demand forecasting, and more. We also dig into the role of edge, cloud, and what she calls hybrid AI, which is inference happening both in the cloud and on the edge concurrently. Finally, we discuss the challenges associated with estimating the ROI of industrial AI projects and the need that often arises to redefine the problem to understand the ultimate impact of the solution.

Thanks to our Sponsor!

This week’s shows are drawn from some of the great conversations I had at the recent NVIDIA GPU Technology Conference, and they’re brought to you by Dell.

If you caught my tweets from GTC, you may already know that one of the announcements this year was a new reference architecture for Data Science Workstations, powered by high-end GPUs and accelerated software such as NVIDIA’s RAPIDS. Dell was among the key partners showcased during the launch, and offers a line of workstations designed for modern ML and AI workloads.

To learn more about Dell Precision workstations, and some of the ways they’re being used by customers in industries like Media and Entertainment, Engineering and Manufacturing, Healthcare and Life Sciences, Oil and Gas, and Financial services, visit Dellemc.com/Precision.

About Trista

Mentioned in the Interview

“More On That Later” by Lee Rosevere licensed under CC By 4.0

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