Generative AI patterns on AWS: Exploring modern applications with generative AI

Generative AI offers the potential to transform the way we interact, as you can create new content that are both realistic and creative by learning from large datasets of text, images, and code. It opens up the possibility of developing a wide range of applications for a variety of use cases. This session covers the guidelines on when to apply RAG, vs. fine-tuning vs. prompt engineering, to improve generative AI performance. We explore some of the solutions that use generative AI models in conjunction with AWS building blocks such as Amazon SageMaker and Amazon SageMaker JumpStart to solve common use cases including question and answer, summarization, simplification, and tone augmentation. We explain when and how to use advanced prompt engineering, fine-tuning, and RLHF options to improve the results and demonstrate one of the patterns. Download slides », Download demo »

Speaker: Arun Balaji, Principal Prototyping Engineer, AWS India