Architecture patterns for building generative AI applications

Do you wish to have guidance on the right tools to build cost-effective and high-performance generative AI applications that are customized for your workload and traffic patterns? In this session, learn the usage patterns and techniques for key use cases such as text generation, summarization, Q&A, chatbot, and image generation to improve productivity and create organizational value. We discuss key considerations when to apply RAG, fine-tuning, or prompt engineering to improve generative AI performance. The session also covers when and how to use advanced prompt engineering, fine-tuning, and RLHF options to improve the results. Find out how to leverage generative AI models with AWS services such as Amazon SageMaker and Amazon SageMaker JumpStart in use cases such as text summarization, simplification, and tone augmentation. Download slide »
Speaker: Praveen Jayakumar, Head of AI/ML Solutions Architect, AWS India