Snowflake Doubles Down on AI Strategy: Bringing Models to Enterprise Data

At Snowflake's annual Summit, Christian Kleinerman, the Executive Vice President of Product, unveiled the company's latest innovations and provided insights into Snowflake's strategic approach to artificial intelligence (AI). A recurring theme throughout the conversation was Snowflake's commitment to bringing AI models directly to enterprise data, ensuring data governance and security remain top priorities.

Addressing Regional Availability Challenges

One of the key questions addressed the availability of Snowflake's AI platform, Cortex, across different regions. Kleinerman acknowledged that currently, Cortex is available with AWS in the Sydney and Tokyo regions. However, he emphasized the importance of cross-region calling capabilities, as cloud providers often lack larger GPUs like A100 and H100 across all regions.

"Cloud providers themselves don't have the larger GPUs in every region," Kleinerman explained. "So we actually have documentation on which models, not GPUs, but whether it's a small instance or a large instance of which LLMs (large language models) are available in which region."

The Business Value Perspective on AI Costs

Kleinerman addressed concerns about the potential high costs associated with AI workloads, offering a nuanced perspective. He cited a real-world example of a small startup where an AI-powered customer support bot handled more cases than the entire human support team combined, with lower response times and higher customer satisfaction.