AI Infrastructure
AI Infrastructure refers to the integrated hardware, software, and networking systems designed to support the development, training, deployment, and scaling of artificial intelligence and machine learning models. It encompasses specialized compute resources (like GPUs/TPUs), data storage solutions, orchestration tools, and frameworks that enable efficient AI workflows. This infrastructure is essential for handling the massive computational and data requirements of modern AI applications.
Developers should learn AI Infrastructure when building or deploying large-scale AI systems, as it provides the necessary foundation for model training, inference, and management. It is critical for use cases such as natural language processing, computer vision, and recommendation systems, where performance, scalability, and cost-efficiency are paramount. Understanding AI Infrastructure helps optimize resource utilization and accelerate AI development cycles.