While AI delivers greater speed and scale, it can also produce biased or inaccurate recommendations if the underlying data, model design or oversight systems fall short.

As generative AI reshapes entire industries, frontier models are pushing data centers to their limits. The infrastructure required to train and serve these models demands extremely high bandwidth, ...

When Jeff Bezos predicted we’d be building data centers in space in twenty years while speaking at the Italian Tech Week last October, the claim made global headlines. But for the companies working ...

As the Centers for Medicare and Medicaid Services (CMS) strives to improve and expand accountable care organization (ACO) models for the future, there’s a ...

Periodic Labs wants to build AI scientists that can run experiments, learn from reality and accelerate discovery in physics ...

Buildings researchers at the Department of Energy's Pacific Northwest National Laboratory have released a new AI-driven, autonomous bot that could help speed up the energy modeling process for ...

India is moving cautiously toward an AI copyright framework, balancing innovation, creators' rights, and regulatory ...

In the AI-native enterprise, employees won't evaluate architecture diagrams. They'll judge how effortlessly their intent becomes action and how smoothly the water flows.

The decade-long assumption that everything belongs in the cloud is quietly breaking. Not because the cloud failed — but because the constraints changed.

The SpaceX CEO reveals renderings of the upcoming satellites, which feature an exceptionally long solar array, and teases a ...

AI agents fail in production for predictable reasons: fragmented data, undefined workflows, and runaway escalation. Burley Kawasaki of Creatio outlines three disciplines — data virtualization, bounded ...

The Lenovo ThinkPad P16v Gen 3 won’t be for everyone. Its performance is good, but it’s no match for consumer-aimed models ...