Trends, Challenges and Best Practices for AI at the Edge

Explore trends, challenges, and best practices for implementing AI at the edge in this 30-minute conference talk by Ekaterina Sirazitdinova. Discover how billions of sensors in enterprises collect and generate vast amounts of data, enabling AI to solve complex problems in unprecedented ways. Learn about the unique constraints of edge devices, including lower computing power, limited storage, and restricted power consumption, and how these factors impact AI inference. Examine the growing complexity of AI networks and their increasing memory requirements, which pose challenges for real-time processing on embedded systems. Gain insights into optimizing AI inference at the edge, with a focus on machine vision use cases. Understand the importance of balancing AI model complexity with the limitations of edge devices to achieve efficient and effective embedded AI solutions.