Definition
AI Training is the process of teaching an artificial intelligence model by using large datasets and computational resources to learn patterns, relationships, and behaviors.
During training, AI models adjust internal parameters through repeated calculations to improve their ability to perform specific tasks.
Why It Matters
AI training requires significant computing resources, especially for modern large-scale models.
Large AI training workloads require:
- Powerful GPUs or AI accelerators
- High-speed networking
- Large-scale storage
- Advanced cooling systems
- Reliable power infrastructure
Key Technologies
GPU Computing
AI training commonly relies on GPU clusters to accelerate complex mathematical operations.
Distributed Computing
Large models are trained across multiple computing nodes working together.
High-Speed Networking
Fast communication between computing nodes improves training efficiency.
Applications
AI training supports:
- Large language models
- Generative AI systems
- Machine learning models
- Computer vision applications
- Research computing
Related Terms
Related ATTOM Solutions
ATTOM provides infrastructure solutions designed to support AI training environments requiring high-density computing, advanced cooling, and scalable deployment.
