…As we know, Matrix Multiplication is the core block of neural networks and LLMs in AI workloads. Current SIMD (Single Instruction, Multiple Data) extensions, such as AVX10, can do matrix multiplication, but…
…It's like NVIDIA taking its Grace Blackwell datacenter GPUs and optimizing a configuration that is suitable for small and more accessible form factors. The RTX Spark builds upon DGX Spark's…
…A16 will leverage an optimized Nanosheet Transistor technology, first being used by its N2 (2nm) tech, which is being deployed later this year in chips such as AMD's EPYC Venice . Intel…
…Accelerated and optimized key local agentic models, including Gemma 4, Qwen, Mistral, and NVIDIA Nemotron for NVIDIA RTX and edge devices. Announced the NVIDIA Alpamayo 1.5 open model and NVIDIA Omniverse…
…Silicon Innovation Without Memory + Networking Bottlenecks Four Blackhole ASICs work as a unified mesh inside a single desk-friendly enclosure. The system features 480 Tensix cores delivering 2,654 TFLOPS at BlockFP8…
…A 40-year Intel veteran, Johnson has held various engineering and leadership roles across the company, including in the Technology and Manufacturing Group, the Networking and Communications Group, and as general manager…
…The headline feature of DLSS 4.5 is its second-generation transformer model for Super Resolution (AKA temporal upscaling), which is a more advanced deep neural network trained on a much larger…
…Examples of it span AI and networking infrastructure, meaning that even if a prospect for Chinese memory suppliers opens up to have their modules integrated into end products sold to US customers…
…What makes PSSR distinct from simple spatial upscaling is that it uses a trained neural network rather than a purely mathematical approach . Spatial upscalers like AMD's FSR 1.0, which basically…
…Moreover, its dual radios promise to make the connection even more stable, as one radio is dedicated to streaming audio and visuals, while the other connects to the local Wi-Fi network…