If you were looking for your own personal AI supercomputer, Nvidia has you covered.
The chipmaker announced at CES It is launching a personal AI supercomputer called Project Digits in May. The heart of Project Digits is the new GB10 Grace Blackwell Superchip, which fits on a desk and runs from a standard power outlet, as well as packing enough processing power to run sophisticated AI models (a lot for that kind of processing power). require larger, more power-hungry systems). This desktop-sized system can handle AI models with 200 billion parameters, and has a starting price of $3,000. The product itself is visible Much like the Mac Mini.
“AI will be mainstream in every application for every industry. With Project Digits, the Grace Blackwell Superchip reaches millions of developers,” said NVIDIA CEO Jensen Huang in a press release. “Having an AI supercomputer on the desk of every data scientist, AI researcher and student empowers them to connect and shape the age of AI.”
Each Project Digit system comes equipped with 128GB of unified, coherent memory (by comparison, a good laptop might have 16GB or 32GB of RAM) and up to 4TB of NVMe storage. For even more demanding applications, the two project number systems have 405 billion parameters (META’s best model, LAMA 3.1, There are 405 billion parameters).
The GB10 chip delivers up to 1 petaflop of AI performance at FP4 accuracy (which means it can perform 1 quadrillion AI calculations per second) (which helps speed up calculations by approximation), and the system uses Nvidia’s latest Contains next-generation CUDA cores and features. The fifth-generation Tensor cores are joined by a Grace CPU from NVLink-C2C that has 20 power-efficient ARM-based cores. MediaTek, known for its ARM-based chip designs, collaborated in the development of the GB10 to optimize its power efficiency and performance.
Users will also have access to Nvidia’s AI software library, including development kits, orchestration tools, and pre-trained models available through the Nvidia NGC catalog. The system runs on Linux-based Nvidia DGX OS and supports popular frameworks like PyTorch, Python, and Jupyter notebooks. Developers can optimize models using the Nvidia NeMo framework and accelerate data science workflows with Nvidia RAPIDS libraries.
Users can develop and test their AI models locally on Project Points, then deploy them to cloud services or data center infrastructure using the same Grace Blackwell architecture and Nvidia AI enterprise software platform.
Nvidia offers a range of similar devices Accessibility Style — In December, it announced a $249 version of its Jetson computer for AI applications aimed at hobbyists and startups, called the Jetson Orion Nano Super (it handles models Up to 8 billion parameters).
