YOLOv9: Computer vision is alive and well (Practical AI #259)
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Navigating the Complexities of AI Model Selection and Deployment Strategies
The chapter explores the challenges in selecting content amidst technological advancements, focusing on parameter efficient models like Qualcomm AI models, one bit LMS, and YOLO. It discusses the evolution of computer vision software and models, emphasizing the need to balance edge and cloud deployment. The integration of MLOps into software architecture, nuances of AI APIs from companies like open AI, and the impact of product layers on model outputs are also discussed.
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