Live Webinar
Presented By
Alex Ratner
Co-founder and CEO
Snorkel AI
Alex Ratner is the co-founder and CEO at Snorkel AI, and an Assistant Professor of Computer Science at the University of Washington. Prior to Snorkel AI and UW, he completed his Ph.D. in CS at the Stanford AI lab, where he started and led the Snorkel open source project.
Chris Glaze
Principal Research Scientist
Snorkel AI
Chris Glaze is a Principal Research Scientist at Snorkel AI. Before Snorkel, Chris was a lead data scientist at Chubb Insurance, where he led a team to develop artificial intelligence and help automate parts of the underwriting process. Prior to industry, Chris was in academia for 15 years writing math models in neuroscience, most recently as research faculty at The University of Pennsylvania, Perelman School of Medicine.
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
