Blogs

As AI demand surges, performance-per-watt and rack-level density can prevent runaway infrastructure expansion and ease pressure on water and energy resources

ShapeBlue and Ampere recently announced the availability of a mutually developed reference architecture for Infrastructure as a Service (IaaS) on Arm.

Modern AI Compute workloads have pushed legacy processor architectures to their limits. The need for higher performance, greater scalability...

Global spending on public cloud services is projected to exceed $725 billion this year, reflecting a dramatic rise in demand for scalable, cloud-native solutions.

Artificial Intelligence (AI) workloads are growing at an unprecedented rate with the resulting data center electricity consumption expected to exceed 1,000 terawatt-hours globally by 2026.

Large Language Models (LLMs) are revolutionizing our interactions with technology. However, their size typically makes them resource-intensive, driving up costs and energy consumption.

The digital world is evolving rapidly, constantly adapting to new user behaviors. Streaming services have long established...

On Feb 26, 2024, the White house office of the National Cyber Director released a report asking the technical community to proactively reduce the attack surface in cyberspace.

The Chimera, an iconic hybrid in Greek mythology, combines a lion, a goat, and a serpent. It features a lion's head, a goat's body with another goat's head on its back, and a serpent's tail, and it breathes fire.

Drastic efficiency improvements are waiting for you. Kick x86 to the curb and bring in AmpereOne. By repurposing freed-up rackspace, you can invest in the future and modernize your infrastructure.

For years, AI enthusiasts believed that powerful and costly GPUs are essential for training and running complex large language models (LLMs) like ChatGPT and Llama 2. But the landscape is changing

An innovation in CPU architecture—Cloud Native Processors—is providing a viable alternative to the high cost and power consumption of x86 for AI inferencing.