ABSTRACTOur guest this episode is Glenn Jocher, CEO and founder of Ultralytics, the company that brought you YOLO v5 and v8. Gil and Glenn discuss how to build an open-source community on Github, the history of YOLO and even particle physics. They also talk about the progress of AI, diffusion and transformer models and the importance of simulated synthetic data today. The first episode of season 2 is full of stimulating conversation to understand the applications of YOLO and the impact of open source on the AI community. TOPICS & TIMESTAMPS 0:00 Introduction2:03 First Steps in Machine Learning9:40 Neutrino Particles and Simulating Neutrino Detectors14:18 Ultralytics17:36 Github21:09 History of YOLO25:28 YOLO for Keypoints29:00 Applications of YOLO30:48 Transformer and Diffusion Models for Detection35:00 Speed Bottleneck37:23 Simulated Synthetic Data Today42:08 Sentience of AGI and Progress of AI46:42 ChatGPT, CLIP and LLaMA Open Source Models50:04 Advice for Next Generation CV Engineers LINKS & RESOURCES Linkedin Twitter Google scholar  Ultralytics Github National Geospatial Intelligence Agency Neutrino Antineutrino Joseph Redmon Ali Farhadi Enrico Fermi Kashmir World Foundation R-CNN Fast R-CNN LLaMA model MS COCO GUEST BIO Glenn Jocher is currently the founder and CEO of Ultralytics, a company focused on enabling developers to create practical, real-time computer vision capabilities with a mission to make AI easy to develop. He has built one of the largest developer communities on GitHub in the machine learning space with over 50,000 stars for his YOLO v5 and YOLO v8 releases. This is one of the leading packages used for the development of edge device computer vision with a focus on object classification, detection, and segmentation at real-time speeds with limited compute resources. Glenn previously worked at the United States National Geospatial Intelligence Agency and published the first ever Global Antineutrino map.  ABOUT THE HOST: I’m Gil Elbaz, co-founder and CTO of Datagen. In this podcast, I speak with interesting computer vision thinkers and practitioners. I ask the big questions that touch on the issues and challenges that ML and CV engineers deal with every day. On the way, I hope you uncover a new subject or gain a different perspective, as well as enjoying engaging conversation. It’s about much more than the technical processes – it’s about people, journeys, and ideas. Turn up the volume, insights inside.