D-Matrix claims Corsair chip outperforms Nvidia GPUs in AI inference

CAMPBELL, Calif., June 9, 2026 — WEKA today announced production-scale benchmarks that show how organizations can improve the economics of long-context AI inference by serving more users and tokens on […] The post WEKA Reports 10x Higher AI Inference Throughput with NeuralMesh on OCI appeared first on AIwire.

CPUs, GPUs, TPUs, and NPUs The post The Hardware That Makes AI Possible appeared first on Towards Data Science.

The agreement follows AI infrastructure deals between Corning and Nvidia and Corning and Meta.

This partnership could redefine AI's role in real-world applications, enhancing Nvidia's market reach and solidifying its tech ecosystem dominance. The post Nvidia partners with LG to build humanoid robots and next-generation data centers appeared first on Crypto Briefing.

Insider Brief Nebius has launched the Physical AI Living Lab, a six-month program aimed at helping robotics startups in the UK and Europe gain access to the computing infrastructure and software tools needed to develop physical AI systems. According to Nebius, the program will provide participating companies with access to Nvidia’s physical AI software stack, […]

Nebius' UK expansion could significantly boost AI infrastructure, impacting sectors like finance and healthcare, while enhancing investor appeal. The post Nebius commits £1.7B to build four new UK AI sites powered by Nvidia appeared first on Crypto Briefing.

The expanded Nvidia-Hyundai alliance could accelerate AI integration in robotics and mobility, potentially reshaping industrial and transport sectors. The post Nvidia and Hyundai deepen alliance to advance AI-powered robotics and autonomous mobility appeared first on Crypto Briefing.

In this tutorial, we implement a hands-on workflow for NVIDIA cuTile Python, a tile-based GPU programming interface for CUDA-style kernels in Python. We prepare a Colab-friendly environment and check GPU, driver, CUDA, and cuTile availability before running kernels. We then build tiled vector addition, matrix addition, and matrix multiplication, keeping a PyTorch fallback so the notebook stays executable. We validate correctness against PyTorch and benchmark median runtimes at every stage. The post NVIDIA cuTile Python Tutorial: Building Tiled GPU Kernels for Vector Addition, Matrix Addition, and Matrix Multiplication in Colab appeared first on MarkTechPost.