Manufacturing and design firms continue to stumble upon novel use cases for artificial intelligence. Today we learn more about how 3D imaging data is reducing supply chain complexity for manufacturing parts. Startups also have an interesting challenge in acquiring the data necessary to train machine learning models. In this episode with Paul Powers, Founder and CEO of Physna, we dive into what it takes to build an AI startup. We also discuss his early career in the legal field…in Germany. Timestamps: 1:39 Launching a career in law in Germany 3:13 Where the idea for Physna originated 7:04 Funding Physna before raising venture capital 8:44 The evolution of Physna | Pivoting to a higher value use case in engineering productivity 16:32 How artificial intelligence is used to understand relationships in 3D images 19:45 Leveraging unique data sets to deliver customized, more accurate predictions 23:53 Acquiring the initial data a startup needs to train AI algorithms 28:25 Establishing data partnerships with the enterprise and public organizations 37:28 How much do customers care that AI is driving your product? 39:00 Perspectives on fundraising 45:00 Thangs.com – See what Physna can do…for free

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