Definition
AI infrastructure encompasses the foundational technology stack necessary for artificial intelligence operations. This includes high-performance computing hardware like GPUs and TPUs, cloud storage solutions, data pipelines, and orchestration tools such as Kubernetes. It also involves the software frameworks and libraries that facilitate model development and deployment. Robust infrastructure ensures scalability, reliability, and efficiency, enabling organizations to handle massive datasets and complex computational workloads required for modern AI applications.
Summary
The hardware, software, and network resources required to develop, train, and deploy artificial intelligence models at scale.
Key Concepts
- GPU/TPU clusters
- Cloud computing
- Data pipelines
- Model deployment
Use Cases
- Planning large-scale model training environments
- Optimizing cloud costs for AI workloads
- Building MLOps pipelines for production systems