Why enterprise AI lives or dies on applied research | Contextual AI’s Elizabeth Lingg

What does it take to transform a brilliant AI model from a research paper into a product customers can rely on? We"re joined by Elizabeth Lingg, Director of Applied Research at Contextual AI (the team behind RAG), to explore the immense challenge of bridging the gap between the lab and the real world. Drawing on her impressive career at Microsoft, Apple, and in the startup scene, Elizabeth details her journey from academic researcher to an industry leader shipping production AI.  Elizabeth shares her expert approach to measuring AI impact, emphasizing the need to correlate "inner loop" metrics like accuracy with "outer loop" metrics like customer satisfaction and the crucial "vibe check." Learn why specialized, grounded AI is essential for the enterprise and how using multiple, diverse metrics is the key to avoiding model bias and sycophancy. She provides a framework for how research and engineering teams can collaborate effectively to turn innovative ideas into robust products.  Check out:Register now: Closing the AI gap: Exceeding executive expectations for AI productivity Follow the hosts:Follow BenFollow Andrew Follow today"s guest(s):Learn more about Contextual AI: Contextual.ai WebsiteFollow Contextual AI on Social Media: LinkedIn | X (formerly Twitter)Connect with Elizabeth: LinkedIn Referenced in today"s show:Throwing AI at Developers Won’t Fix Their ProblemsWhy language models hallucinatei ran Claude in a loop for three months, and it created a genz programming language called cursed Support the show: Subscribe to our Substack Leave us a review Subscribe on YouTube Follow us on Twitter or LinkedIn Offers: Learn about Continuous Merge with gitStream Get your DORA Metrics free forever