Anuj Sinha
Anuj is a graduate student specializing in Data Science at the University of Washington, Seattle. Currently, he is working as a Research Graduate Scholar at the Scientific Software Engineer Center at eScience Institute, UW. Before joining UW, he worked as a Software Developer at Goldman Sachs, India for 4 years.
Sessions
Generative AI systems built upon large language models (LLMs) have shown great promise as tools that enable people to access information through natural conversation. Scientists can benefit from the breakthroughs these systems enable to create advanced tools that will help accelerate their research outcomes. This tutorial will cover: (1) the basics of language models, (2) setting up the environment for using open source LLMs without the use of expensive compute resources needed for training or fine-tuning, (3) learning a technique like Retrieval-Augmented Generation (RAG) to optimize output of LLM, and (4) build a “production-ready” app to demonstrate how researchers could turn disparate knowledge bases into special purpose AI-powered tools. The right audience for our tutorial is scientists and research engineers who want to use LLMs for their work.