One of the most promising applications of large language models is giving non-experts the ability to easily query their own data. A potential positive side effect is reducing ad-hoc data analysis requests that often strain data teams.
Sarah Nagy is the Co-founder and CEO at Seek which is using natural language processing to change how teams work with data. She joins the podcast to talk about the platform and providing a natural language interface to databases.
Sean’s been an academic, startup founder, and Googler. He has published works covering a wide range of topics from information visualization to quantum computing. Currently, Sean is Head of Marketing and Developer Relations at Skyflow and host of the podcast Partially Redacted, a podcast about privacy and security engineering. You can connect with Sean on Twitter @seanfalconer . The post LLMs for Data Queries with Sarah Nagy appeared first on Software Engineering Daily.
