Join us for an insightful webinar on the transformative impact of AI on networking. This session will delve into the various use cases of AI, the nature of traffic for different workloads, and the network impact of these workloads. We will explore the multiple networking challenges posed by AI and how Ethernet is evolving to meet these demands. Special focus will be given to congestion issues during model training, the role of Ultra Ethernet Consortium (UEC), and the specific requirements related to training large language models (LLMs) and other use cases. Learning Objectives: - Understand the different types of Network Topologies typically used with AI workloads. - Identify the nature of traffic for various AI workloads and their impact on networks. - Learn about the challenges Ethernet faces with AI workloads and the solutions being implemented. - Explore a specific use case to see how Ethernet addresses bandwidth and congestion issues. Don’t miss this opportunity to stay ahead in the rapidly evolving field of AI and networking. Register now to secure your spot and gain valuable insights from industry experts!
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