From Raw Robot Logs to a Trained Detector

This talk will explore practical workflows for building, evaluating, and improving modern computer vision systems. We'll dive into real-world approaches to dataset curation, model analysis, multimodal AI workflows, and production-ready vision pipelines using open-source technologies. The session is designed for engineers, researchers, and AI practitioners looking to better understand how teams are developing and scaling computer vision applications today. Expect practical demos, technical insights, and discussions around the evolving AI tooling ecosystem. Daniel Gural leads technical partnerships at Voxel51, where he's building the Physical AI Workbench, a platform that connects real-world sensor data with realistic simulation to help engineers better understand, validate, and improve their perception systems. With a background in developer relations and computer vision engineering, Daniel focuses on making complex workflows approachable and practical, helping teams move seamlessly between real and synthetic data to accelerate their work on the next generation of autonomous systems. * Voxel51 - https://voxel51.com * Connect with Dan on LinkedIn - https://www.linkedin.com/in/daniel-gural/ #FiftyOne #Voxel51 #ComputerVision