The future of artificial intelligence requires a paradigm transformation. Centralized designs are reaching their boundaries, challenged by latency and bandwidth issues. This emphasizes the growing need to distribute intelligence, pushing processing power to the edge. Edge devices offer a attractive solution by bringing computation closer to sources

The landscape of artificial intelligence (AI) is rapidly adapting, with a surge in adoption for edge computing solutions. This paradigm shift facilitates real-time analysis by executing AI models directly on systems at the network's boundary. Leveraging the power of edge computing offers a myriad of opportunities, including faster response tim