Edge Devices and LLMs: What's Ahead for AI
OnTrack: The PCB Design Podcast
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Edge Computing, AI, and Software Development
The chapter delves into the integration of edge computing, AI, and software development, emphasizing the importance of running AI and machine learning models locally on edge devices. It discusses various hardware options such as microcontrollers, GPUs, Jetson Nano, FPGAs, and specialized silicon for AI at the edge, focusing on power efficiency and cost-effectiveness. The conversation also explores future scenarios for AI integration, including customizing AI per model, integrating AI into EDA tooling, and the challenges of running large language models on GPUs due to RAM constraints.
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