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Training AI Together—Without Sharing Private Data 92 SMT007 MAGAZINE I MAY 2025 Feature Interview by Nolan Johnson IPC Artificial intelligence models work bet- ter with more data. While individual EMS companies can certainly create plenty of data over time, the broader the data set, the more insightful the AI results can be. Ben Rachinger, a research assistant at Friedrich- Alexander-Universität Erlangen-Nürnberg, received the NextGen Best Paper at IPC APEX EXPO 2025. His research asks: What if a model could be created that allowed indus- try-wide data in the model, while still pro- tecting proprietary information? Nolan Johnson: Ben, tell me about the award you received for your paper at IPC APEX EXPO. Ben Rachinger: I received the NextGen Best Paper Award for my paper that focuses on verifying whether a collaborative machine learning approach called federated learn- ing can be effectively applied for improving THD image classification. By using data from multiple companies and training a machine learning model, we can build an image clas- sification model based on a broader knowl-