Many companies are adopting a modern data stack centered around cloud data warehouses as the basis for operationalizing analytic use cases at scale. Despite its success, there remains a gap around AI tooling, which prevents companies from getting the most value out of their data.
In this replay Jordan describes the modern data stack, why traditional ML platforms fail to meet design and user experience requirements of the modern data stack, and how a new generation of ML platforms based on a data-first, declarative design can make AI on the modern data stack a reality.