NVIDIA CUDA

Earlier this week at GTC Taipei, NVIDIA unveiled the NVIDIA RTX Spark product family, including small form factor desktops and laptops built for the age of personal assistants. These desktops and laptops deliver 1 petaflop of AI power, up to 128 GB of memory, and CUDA-accelerated AI frameworks for running large models alongside everyday work.  Microsoft is creating an RTX Spark special developer edition—the Microsoft Surface NVIDIA RTX Spark Dev Box—preloaded with a modified Windows configured for developers and the top developer tools you need to get started. To learn more, see Building the n

NVIDIA NemoClaw for building autonomous AI agents now supports all NVIDIA client systems—GeForce RTX, NVIDIA RTX PRO, NVIDIA DGX Spark, and NVIDIA DGX Station for Windows—through Linux and Windows Subsystem for Linux (WSL). This enables you to easily set up and sandbox an agent, with optimized local models handpicked for your hardware. The update also includes enhancements to the installer to make it easier and more seamless. NemoClaw also now supports running Hermes Agent as an option.  This week, Hermes Agent also released native Windows support, including both a command-line interface, alon

With agents running 24 hours a day, seven days a week on increasingly complex tasks, efficient local compute matters even more. NVIDIA has collaborated with the open source community to enhance the top inference backends for agents, llama.cpp and vLLM. llama.cpp now delivers 2x performance on Qwen 3.5 and 3.6 27B dense models, and 1.6x performance on Qwen 3.5 and 3.6 35B mixture-of-expert (MoE) models. The following two techniques make this possible: Multi-Token Prediction (MTP): An advanced speculative decoding technique, where a smaller draft model proposes several tokens ahead that the targ

With JetPack 7.2, Jetson is NemoClaw-ready out of the box. JetPack 7.2 comes preconfigured with the required dependencies and software stack, so you can deploy and run NemoClaw-based workflows on Jetson without manual environment setup. This enables you to easily build agentic physical AI applications across robotics, industrial automation, vision agents, and edge AI systems. To install NemoClaw on a Jetson device running JetPack 7.2, run the following single command:  curl -fsSL nvidia.com/nemoclaw.sh | bash