
Covers cost management for AI/ML and generative AI workloads: GPU and accelerator costs and utilisation, training versus inference spend, token-based pricing and cost per inference unit economics. Explains model selection and right-sizing, caching and batching, provisioned throughput versus on-demand capacity, and how to allocate shared AI costs to teams.