Apple just admitted something interesting at WWDC26: its own data centers aren’t enough. The company announced that its Private Cloud Compute service, originally built to run exclusively on Apple ...

Most infrastructure decisions look fine on paper until real AI workloads begin running at scale. Then performance issues appear quickly. GPUs remain underutilized, storage pipelines slow training, ...

CME Group and Silicon Data are launching a futures exchange for computing capacity. Contracts will be based on daily GPU benchmarks for on-demand rental rates. Memory prices soared in the first ...

Abstract: GPU-accelerated services accelerate computation-intensive tasks by leveraging the parallel processing power of GPUs but incur high costs. Existing researches lack consideration for GPU’s ...

For quantum computing to reach the point where it is fault-tolerant, scalable, and commercially viable, it’s going to be with the help of key components of advanced computing today, namely AI, open ...

Government-funded academic research on parallel computing, stream processing, real-time shading languages, and programmable graphics processing units (GPUs) directly led to the development of GPU ...

The VACC has a heterogeneous GPU environment, and not all GPUs are created equal. The cluster contains a mix of GPU architectures spanning multiple generations, each with different strengths in ...

Nvidia said quantum computing will complement rather than replace GPUs, even as Taiwan accelerates investment in quantum technology. Speaking at an industry event, the company said it does not expect ...

NodeAI is transforming the future of GPU computing with a decentralized infrastructure that’s fair, transparent, and community-driven. By leveraging the $GPU token ...

Shkreli’s Substack essay, titled “Photonic Computing: The Final AI Hardware Frontier,” lays out a simple thesis: GPUs from Nvidia Corp. (NASDAQ: NVDA) spend roughly 99% of their time doing one thing, ...