…Tom's Hardware Premium Roadmaps High-Bandwidth Memory (HBM) Roadmap Nvidia Enterprise GPU and CPU Roadmap AI accelerator Roadmap Desktop GPU Roadmap 3D NAND Roadmap TSMC began volume production on its N2…
…This is important as modern rack-scale AI solutions like Nvidia’s VR200 NVL72 are rumored to cost around $8 million, so their protection is crucial. Also, reducing downtime in AI data…
…Premium Premium In this roadmap, we analyze what the future of Quantum Computing might look like over the next decade, including the future of qubit scaling, trapped ions, and superconducting chips. Premium…
…The original Maia 100, built on TSMC 5nm, was reportedly designed more for image processing than generative AI and never powered production AI services at scale. Maia 200 was delayed roughly six…
…custom hardware. Since LiquidJet is designed to remove 400W – 600W of thermal energy per square centimeter, it can cool down very hot components. Furthermore, since these components tend to scale horizontally, it…
Most all you hear about "running an AI model" involves a GPU of some sort, but not every AI task is suited to that hardware. Smaller models or single-user latency-sensitive…
…4's accelerated FP8 hardware, but an FSR 4 source code leak in August 2025 revealed that the company had also created an INT8 version of the AI upscaling model that was…
…momentum as inferencing and agentic AI drive increasing demand for high-performance CPUs and accelerators. Looking ahead, we expect server growth to accelerate meaningfully as we scale supply to meet demand." Article…
…That said, MSI's implementation likely uses a hardware scaler where 1440p is being spatially interpolated at the silicon level. The true RGB stripe subpixel layout also helps here. But that's…
…Hyperscalers tend to deploy custom silicon, own AI accelerators, or hardware from competitors, which limits Nvidia's growth in this segment. By contrast, there are thousands of participants in the broad ACIE…