Yotta Data Services, which controls up to 70% of India’s GPU capacity, said surging demand from local AI startups and global ...

A growing wave of artificial intelligence applications is driving unprecedented demand for GPU compute power, opening th ...

Below are the top five decentralized GPU platforms that AI developers should not ignore in 2026. Akash is a reverse auction ...

AMD is announcing its first three Ryzen AI chips for desktops using its AM5 CPU socket. These Ryzen AI 400-series CPUs are ...

Against this backdrop, SoftBank has been developing Orchestrator, which manages computing resources and optimally allocates AI applications, with the aim of realizing a next-generation AI ...

A remarkably efficient way to handle two very different workloads ...

Vembu sees this technology as a turning point that moves AI from massive cloud GPU clusters to compact, low-power “AI appliances” that can run locally in devices.

LM Studio turns a Mac Studio into a local LLM server with Ethernet access; load measured near 150W in sustained runs.

AI users and developers can now measure the amount of electricity various AI models consume to complete tasks with an ...

GPU memory (VRAM) is the critical limiting factor that determines which AI models you can run, not GPU performance. Total VRAM requirements are typically 1.2-1.5x the model size due to weights, KV ...

The Mobile World Congress in Barcelona has heard the same pitch for years that AI will “run the network.” This time, Mobile ...