On-demand webinar
Speakers

Alex Ratner
Co-founder & CEO
Snorkel AI
Alex Ratner is the co-founder and CEO at Snorkel AI, and an affiliate assistant professor of computer science at the University of Washington. Prior to Snorkel AI and UW, he completed his Ph.D. in computer science advised by Christopher Ré at Stanford, where he started and led the Snorkel open source project. His research focused on data-centric AI, applying data management and statistical learning techniques to AI data development and curation.

Chris Glaze
Principal Research Scientist
Snorkel AI
Experienced PhD with a demonstrated history of developing novel machine learning tools and mathematical models in academia and industry. Accomplishments span data mining, experimental research, and application to digital technologies.

Marty Moesta
Lead Product Manager, Generative AI
Snorkel AI
Marty Moesta is the lead product manager for Snorkel’s Generative AI products and services, before that, Marty was part of the founding go to market team here at Snorkel, focusing on success management and field engineering with fortune 100 strategic customers across financial services, insurance and health care. Prior to Snorkel, Marty was a Director of Technical Product Management at Tanium.
Improving RAG outcomes with your unique enterprise data
RAG (retrieval-augmented generation) is the de facto standard for grounding LLM-powered AI applications. However, prompt engineering and supplemental context are not enough to perform domain-specific tasks with precision.
Enterprise use cases that depend on subject matter expertise and demand high accuracy require a fine-tuned RAG architecture – from chunking and embedding to reranking and context-window optimization.
In this on-demand webinar, Snorkel AI co-founder and CEO Alex Ratner shares his insights into emerging AI practices and the future of enterprise adoption. He is joined by principal research scientist Chris Glaze and Generative AI product lead Marty Moesta, who discuss the latest research in RAG tuning and demonstrate how to apply it via AI data development techniques.
Watch this webinar to learn how to:
- Optimize RAG components to increase accuracy and precision
- Apply AI data development techniques to improve model accuracy
- Accelerate the delivery of production RAG implementations