Deploy Fast and Accurate YOLOv8 Object Detection Models on CPUs

Discover how to deploy fast and accurate YOLOv8 object detection models on CPUs in this 48-minute webinar recording from Neural Magic. Learn about state-of-the-art sparsification techniques, including pruning and quantization, that result in 10x smaller and 8x faster models with minimal accuracy loss. Explore topics such as GPU performance, baseline results, DeepSparse Engine, sparsity quantization, and sparse transfer learning. Gain insights into performance comparisons, open-source repositories, and upcoming features. Get practical guidance on implementing these optimizations for computer vision use cases to achieve best-in-class inference performance on existing CPUs. Understand the benefits of sparse ML and how to get started with free resources available on the Neural Magic website.