Show Notes
In this episode of the Targeting AI podcast from Informa TechTarget, Ben Flast, of NoSQL database vendor MongoDB, discusses the company's rapid integration of generative AI technologies, including vector search and real-time updates through Atlas Stream Processing. He emphasizes the importance of community engagement and the role of agentic AI in enhancing developer productivity. The conversation also explores the differences between open source and proprietary models, the impact of model sizes on performance, and MongoDB's approach to AI governance. Flast shares customer applications that highlight the transformative potential of AI in various industries and concludes with insights into future innovations at MongoDB. Featuring: Ben Flast, director of product management at MongoDB In today's episode, we cover these topics:
Vector search enhances the capabilities of GenAI applications. Agentic AI represents a new application pattern for AI capabilities. Model size affects performance and cost for developers.
To learn more about AI and the importance of GenAI in database platforms, check out SearchEnterprise AI and SearchDataManagement. To watch video clips from our podcast, subscribe to our YouTube channel, @EyeonTech. References:
Atlas Stream Processing MongoDB vector search Model Context Protocol GenAI standard
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