Amazon SageMaker AI: build, train, deploy, and manage GenAI and ML models at scale

About this session

In this session, we will explore Amazon SageMaker AI and how its features support the full lifecycle of a Machine Learning and Generative AI project. We will begin with the exploration and creation phase, where services like SageMaker Unified Studio and SageMaker Jumpstart allow users to explore various Generative AI models. We will then move on to the training phase, where features like SageMaker Training and SageMaker Hyperpod help optimize the customization of Foundation Models for specific business tasks and use cases. Finally, we will dive into deployment and automation, where SageMaker Inference and MLOps solutions enable the automated and optimized deployment of these models across different types of applications.

Speakers

Bruno Pistone

Senior World Wide Generative AI/ML Specialist Solutions Architect, AWS Italy, AWS Italy