The AI Data Paradox: High Trust in Models, Lo...

Summary In this episode Ragnor Comerford talks about OmniGraph, a lakehouse-native graph storage layer designed around the needs of agentic systems. He explores how graphs are primarily a semantic model for representing the world, rather than just a specialized engine for travers ...  Show more

Summary In this episode Prukalpa Sankar, co-founder of Atlan, talks about what it takes to build a “context flywheel” for AI agents in data-intensive organizations. She explained why model intelligence alone isn’t enough to make AI useful in production, and how real performance d ...  Show more

AI technologies are some of the most sophisticated and powerful we’ve seen in our lifetimes. With data at the center, this transformative shift brings both the potential to solve complex problems and new challenges around managing sensitive information. Join us for a deep dive in ...  Show more

As organizations implement AI in decision making and how work gets done, trustworthy data is essential to adding value every step of the way. Inadequate data governance or unclear AI ambitions leaves enterprises at risk of falling behind. In this keynote address from Gartner Data ...  Show more

Organizations are finding that data is only part of their AI strategy. In order to fully utilize their data, they need to be able to make sense of that data and effectively communicate the story their data is telling. In this episode of the AI Today podcast, hosts Kathleen Walch ...  Show more

This podcast episode provides a snippet of Cognilytica’s AI and ML education from our Cognilytica Education Subscription. Data is at the heart of AI. It should be no surprise then that proper data management is crucial for AI projects. This podcast is an excerpt from our Cognilyt ...  Show more