Vinay Arora

Build a fine-tuning pipeline that proves its own results. In this workshop, run the full loop, baseline eval, fine-tune, RL, re-eval, against the same bar every time.

Enterprises that own their AI lifecycle across training and inference can adapt their models as fast as their users' need change. Vanguard outgrew off the shelf models and built infrastructure that runs custom large language models (LLMs) and specialized small language models (SLMs) side by side.

Retrieval Augmented Generation (RAG) enhances generative AI inference by augmenting pretrained FMs and LLMs with current information that is contextual and relevant to the query. Learn from AWS experts about efficient RAG deployment options for use cases that optimize cloud resource usage and costs.

AWS is continuously innovating to meet customer needs and now offers more than 700 instance types for various use cases—including instances best for common workloads, like web application workloads, and those more appropriate for workloads with specific requirements, like SAP workloads.