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The key to operational AI: Modern data architecture

CIO

For example, there should be a clear, consistent procedure for monitoring and retraining models once they are running (this connects with the People element mentioned above). To succeed, Operational AI requires a modern data architecture.

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Agentic AI design: An architectural case study

CIO

They tested the prompts, modified them to give better examples, changed the wording of what was being asked from the LLM and kept testing. Eight different prompts were created that were tailored to the specific output data each agent was charged with generating.

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Linking Modular Architecture to Development Teams

Martin Fowler

Matthew Foster describes an example of this from his work with clients, and how using Domain-Driven Design and Team Topologies helped create a modular architecture that substantially reduced the time needed to deliver new features.

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Are enterprises ready to adopt AI at scale?

CIO

To overcome those challenges and successfully scale AI enterprise-wide, organizations must create a modern data architecture leveraging a mix of technologies, capabilities, and approaches including data lakehouses, data fabric, and data mesh. Another challenge here stems from the existing architecture within these organizations.

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Partner Webinar: A Framework for Building Data Mesh Architecture

Speaker: Jeremiah Morrow, Nicolò Bidotti, and Achille Barbieri

In this webinar, learn how Enel Group worked with Agile Lab to implement Dremio as a data mesh solution for providing broad access to a unified view of their data, and how they use that architecture to enable a multitude of use cases.

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Making Zero Trust Architecture Achievable

Tenable

4, NIST released the draft Guidance for Implementing Zero Trust Architecture for public comment. Tenable has been proud to work alongside the NIST National Cybersecurity Center of Excellence (NCCoE) to launch the Zero Trust Architecture Demonstration Project.

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CIOs contend with gen AI growing pains

CIO

Unfortunately, despite hard-earned lessons around what works and what doesn’t, pressure-tested reference architectures for gen AI — what IT executives want most — remain few and far between, she said. I cannot say I have abundant examples like this.” “What’s Next for GenAI in Business” panel at last week’s Big.AI@MIT

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