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

The company says its new architecture marks a shift from training-focused infrastructure to systems optimized for continuous, low-latency enterprise AI workloads.

Nvidia CEO Jensen Huang unveils a high-speed AI inference system using Groq technology, targeting growing demand.

The message from Nvidia is that AI is no longer about models or chips, but about monetizing inference at scale – where tokens become the core unit of value.

Roman Chernin is the CBO and cofounder of AI infrastructure company Nebius. His career spans over 20 years in the tech industry. Every major advance in AI begins with model training, but the ...

Nvidia is preparing to launch a new chip designed to speed up AI responses, breaking with its long-running habit of flogging the same processor for every job. Nvidia chief executive Jensen Huang is ...

Google expects an explosion in demand for AI inference computing capacity. The company's new Ironwood TPUs are designed to be fast and efficient for AI inference workloads. With a decade of AI chip ...

Broadcom looks poised to become a big inference winner in 2026.

Artificial intelligence startup Runware Ltd. wants to make high-performance inference accessible to every company and application developer after raising $50 million in Series A funding. It’s backed ...

While the tech world obsesses over headlines about the $100 million price tag to train GPT-4, the real economic story is happening in inference: the ongoing cost of actually running AI models in ...

0G’s Sealed Inference takes a fundamentally different approach: privacy by code. The architecture makes unauthorized data ...