At Nissan’s powertrain plant in Decherd, Tennessee, a 3.8-liter V6 sits bolted to a dynamometer, screaming at redline while ...

Here is how you know that GenAI training and GenAI inference are very different computing and networking beasts, and ...

Learn prompt engineering with this practical cheat sheet covering frameworks, techniques, and tips to get more accurate and ...

Cybercriminals are tricking AI into leaking your data, executing code, and sending you to malicious sites. Here's how.

For years, GPUs have been the default answer for AI workloads. That made sense. They were already widely available, they were ...

Inference platform FriendliAI is partnering with Samsung’s IT division to offer Nvidia GPU-based frontier AI services. FriendliAI's core Friendli Inference will be deployed by Samsung SDS on its ...

Ahead of Nvidia Corp.’s GTC 2026 this week, we reiterate our thesis that the center of gravity in artificial intelligence is shifting from “How fast can you train?” to “How well can you serve?” ...

Builds on ZEDEDA’s proven edge orchestration foundation, which already manages tens of thousands of application instances in the world's most demanding field environments Enables customers to build, ...

Amazon Web Services plans to deploy processors designed by Cerebras inside its data centers, the latest vote of confidence in the startup, which specializes in chips that power artificial-intelligence ...

Every GPU cluster has dead time. Training jobs finish, workloads shift and hardware sits dark while power and cooling costs keep running. For neocloud operators, those empty cycles are lost margin.

Adding big blocks of SRAM to collections of AI tensor engines, or better still, a waferscale collection of such engines, turbocharges AI inference, as has been shown time and again by AI upstarts ...