The explosive growth of ChatGPT has triggered unprecedented demand for artificial intelligence (AI) computing power, leading to industry-wide supply constraints. While Nvidia maintains its stronghold as the premier AI GPU provider,

Finding an RTX 5090 FE at MSRP would be lucky, but does anyone really need this power-hungry monster with its heightened temperatures?

A $2,000 video card for consumers shouldn't exist. The GeForce RTX 5090, like the $1,599 RTX 4090 before it, is more a flex by NVIDIA than anything truly meaningful for most gamers. NVIDIA CEO Jensen Huang said as much when he revealed the GPU at CES 2025,

Qdrant, the developer of a high-performance open-source vector database, today introduced its graphics processing unit accelerated vector indexing capability that will make scaling up artificial intelligence applications easier.

The Biden export limits, enacted during his last days in office, may drive data center construction to US allies while forcing China and Russia to develop their own AI chips.

So, how can Nvidia's stock soar 67% in 2025? Simple. It does what it's expected to and gives a solid outlook for next year. Right now, Nvidia trades for 52 times trailing earnings, which is near the cheapest level it has traded at over the past two years.

This chip cojoins existing AMD CPU and GPU architectures, along with a high speed memory interface, in an unprecedented way, compared to traditional X86 chip designs.

The technical evaluation of the bids was done on January 13, sources said, adding that New Delhi-based E2E Networks and Bengaluru-based NxtGen Datacenter and Cloud Technologies are among the shortlisted firms.

We ran the Nvidia RTX 5090 through its paces. Here are our full benchmark results and impressions on the new desktop GPU.

Nvidia has purportedly disabled overclocking and multi-GPU support on the RTX 5090D to ensure its performance does not exceed U.S. export regulations.

Qdrant’s hardware-agnostic approach to GPU acceleration enables speed index-building with support for most modern GPUs to give users the flexibility to efficiently process massive datasets while adopting and using the most suitable infrastructure for their real-time AI applications based on technical, cost and other considerations.

The growing demand for advanced AI has led to a massive surge in computing power needs, prompting the rise of GPU-as-a-Service (GPUaaS) businesses. According to IEEE Spectrum, as artificial ...