Information technology architecture is where abstractions become real. Modern enterprises are increasingly moving toward ...

AI initiatives don’t stall because models aren’t good enough, but because data architecture lags the requirements of agentic systems.

Different teams need to make the same conclusion multiple times before a consensus is reached and the finding can be built ...

From Gen Z to Boomers, a new look at workplace retirement plans reveals wide differences in how people contribute—and how ...

The Bay Area is the runaway leader in artificial intelligence. But data centers, the physical architecture needed for AI ...

ActiveViam won Best use of cloud for enhancing Atoti with AWS Graviton optimisation, CR aC-based JVM hibernation and Atoti PaaS. Nomura saw 40% lower hardware spend and inactivity cut from 24 hours to ...

Learn how to build and self host an AI SaaS app with Next.js, Prisma, and PostgreSQL so you can launch on a low cost VPS.

Old data centers physically cannot support rows and rows of GPUs, which is one reason for the massive AI data center buildout.

1. Risk: AI Monoculture (Shared Blind Spots). This is the most critical and overlooked systemic vulnerability. Building your ...

Need a better way to plan projects? Discover mind map examples that help you visually organize tasks, ideas, and strategies ...

For advanced bonding schemes and panel operations, there is a high cost to discovering an interface issue late in the flow. Reliability improves when materials are specified as a system rather than as ...