"You have essentially data-powered AI platforms and AI powered data platforms. But in order for this to work in an AI era, you need to be able to have a set of data that you can get to very easily and accessibly. And that's where the interoperability story really begins because more and more you need to have a single copy of the data."
"Reducing token costs and improving AI agent performance depends on providing agents with a clear, coherent set of context, which is only possible when data is available through a unified governance layer."
"If I give you direct access to data, you need to be able to act on that data responsibly as well. By having your foundation of your data on an interoperable format and standard like Apache Iceberg, and you're using standards like Iceberg REST, you're enabling customers to then attach other engines and get multiple, we call multi reader, multi writer, access to that data."
Snowflake identifies clean and accessible data as the primary challenge in developing effective AI agents. The company is committed to open standards, particularly the Apache Iceberg format, to create an interoperable data stack. James Rowland-Jones highlights the importance of a unified governance layer for data access, which is essential for improving AI performance. However, increased data access also brings responsibilities, necessitating responsible data usage. Snowflake's approach includes using standards like Iceberg REST for secure data access and governance.
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