- AI continues to permeate every aspect of our lives, and data centers are the engines behind AI as the demand for processing power skyrockets. AI model training requires massive parallel processing in data centers, often accomplished using hundreds or even thousands of GPUs.
- Optimizing AI training and inference requires a high-performance network that minimizes AI job completion time, thereby maximizing GPU utilization and the return on investment of these prohibitively expensive resources.
- Networking is critical to AI, but AI is also critical to networking. AIOps is increasingly necessary to manage these complex data centers efficiently.