The focus of artificial-intelligence spending has gone from training models to using them. Here’s how to understand the difference—and the implications.

Nvidia is pushing its artificial-intelligence hardware beyond Earth, unveiling a computing module designed for space missions and potential orbital data centers. The California-based company said March 16 at its annual GTC conference in San Jose that it is developing the Space-1 Vera Rubin Module,

Dhruv Roongta is the Co-Founder & CTO of Slashy, a startup building general AI agents.

Making chips for training AI models made it the world’s biggest company, but demand for inference is growing far faster.

Silicon-based artificial intelligence has come a very long way in a very short space of time, driving massive advances in the large language models that sit at the heart of today’s generative AI chatbots, image creation tools and autonomous agents.

Nvidia’s GTC 2026 unveiled AI factories, token-based economics, and agentic systems—signaling a new era where energy converts into intelligent economic value.

Bell CEO Mirko Bibic discusses a $1.7B AI data centre investment in Saskatchewan and how the project fits into the company’s AI growth strategy.

For much of the last three decades, investors have had a game-changing technology or hyped trend to capture their attention and capital. Some of these popular trends include the advent and proliferation of the internet, genome decoding, nanotechnology, 3D ...

Amazon and Microsoft are two huge players in the AI realm that don't get enough credit.