Introduction to On-Device AI

Complete this Guided Project in under 2 hours. As AI moves beyond the cloud, on-device inference is rapidly expanding to smartphones, IoT devices, robots, ...

• Learn to deploy AI models on edge devices like smartphones, using their local compute power for faster and more secure inference.
• Explore converting PyTorch/TensorFlow models for device compatibility and quantize them for better performance and reduced model size.
• Learn about device integration, including runtime dependencies, and how GPU, NPU, and CPU compute unit utilization affect performance.