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 productivityFollow the hosts:Follow BenFollow AndrewFollow today's guest(s):Learn more about Contextual AI: Contextual.ai WebsiteFollow Contextual AI on Social Media: LinkedIn | X (formerly Twitter)Connect with Elizabeth: LinkedInReferenced 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 cursedOFFERS Start Free Trial: Get started with LinearB's AI productivity platform for free. Book a Demo: Learn how you can ship faster, improve DevEx, and lead with confidence in the AI era. LEARN ABOUT LINEARB AI Code Reviews: Automate reviews to catch bugs, security risks, and performance issues before they hit production. AI & Productivity Insights: Go beyond DORA with AI-powered recommendations and dashboards to measure and improve performance. AI-Powered Workflow Automations: Use AI-generated PR descriptions, smart routing, and other automations to reduce developer toil. MCP Server: Interact with your engineering data using natural language to build custom reports and get answers on the fly.

There are no comments yet.

Please log in to write the first comment.