Building Enterprise Large Language Model Applications

This workshop provides a comprehensive introduction to building AI applications with large language models. Attendees will learn the foundations of models like GPT-3.5/GPT4 and LLaMa2, including how they work, how to access them, and best practices for fine-tuning and prompting. A key part of the day will involve hands-on work with custom datasets to train models on specific tasks and document types. We'll cover gathering quality data, cleaning and labeling, choosing model architectures, prompting techniques, and evaluating performance. The workshop wraps up with deployment strategies, including hosting models locally, leveraging APIs, monitoring, and maintaining production systems. Participants of all backgrounds are welcome. The material will cater to beginners while still diving deep on topics critical to real-world language model adoption.

Some key recent topics to cover could include chain-of-thought prompting, an approach to conversational AI; reinforcement learning from human feedback for improved answers over time; and cross-domain transfer learning to leverage models trained in one domain for new domains with limited data.

See weblink for additional information and to register