Uber partners with NVIDIA to enhance autonomous vehicle technology. NVIDIA's Cosmos and DGX Cloud platforms will power Autonomous Vehicle development. The collaboration will leverage NVIDIA’s ...

The collaboration will leverage NVIDIA’s platforms, including Cosmos and DGX Cloud, to accelerate the development of autonomous driving solutions. NVIDIA Cosmos is a state-of-the-art platform ...

And, by the way, it will be running Nvidia's DGX OS, a customized Ubuntu Linux 22.04 distro. As you might guess, DGX OS is a Linux distro designed with system-specific optimizations and ...

The other two are Nvidia DGX for training AI models and software stacks, and the Nvidia Omniverse platform to test AV software and generate synthetic data in simulation. Toyota has been a customer ...

Joint initiative will leverage NVIDIA’s new Cosmos platform and DGX Cloud to boost autonomous development Uber Technologies, Inc. (NYSE: UBER) and NVIDIA announced they are collaborating on new ...

Uber will use Nvidia’s new generative world model simulation tool, Cosmos, and cloud-based AI supercomputing platform, DGX Cloud, to support the development of autonomous vehicle technology ...

In terms of computing power, it should be in no way inferior to previous DGX systems, which have to be plugged into server cabinets in data centers: Nvidia promises that AI models with 200 billion ...

Capable of running 200B-parameter models, Nvidia Project Digits packs the new Nvidia GB10 Grace Blackwell chip to allow ...

Look Ma! No server! With DIGITS, researchers can prototype, fine-tune and test models on a local workstation running Linux-based NVIDIA DGX OS, and then deploy them on NVIDIA DGX Cloud ...

With the Grace Blackwell architecture, enterprises and researchers can prototype, fine-tune and test models on local Project Digits systems running Linux-based Nvidia DGX OS, and then deploy them ...

The AI computing giant said customers using Nvidia HGX and DGX systems as well as DGX Cloud will “[have] access to Run:ai’s capabilities for their AI workloads.” At the same time ...