AI Infrastructure is the combination of computing hardware, storage, networking, software, and cloud or on-premises resources that support the development and operation of artificial intelligence systems. It provides the processing capacity needed to train models, store and move large datasets, run inference workloads, and monitor AI applications in production.
Typical AI infrastructure includes GPUs or other accelerators, high-speed networking, data storage, orchestration platforms, and model-serving systems. It is essential for scaling demanding workloads such as generative AI, computer vision, large language models, and enterprise machine learning applications.
