HPE’s technical white paper guides organizations through the generative AI lifecycle—from defining a problem to deploying a production-ready application. It outlines key roles (model producers and consumers), AI types (ML, DL, GenAI), and each lifecycle stage: problem definition, data curation, model selection, training, deployment, and monitoring. It emphasizes workload-specific considerations for training, fine-tuning, and inference. The paper also explores deployment options, including AI service providers, cloud-native tools, and full-stack private cloud solutions, helping enterprises accelerate generative AI adoption while delivering tangible business value.

Join for free to read