Localisation is a critical capability for autonomous vehicles, computing their three dimensional (3D) location inside of a map, including 3D position, 3D orientation, and any uncertainties in these position and orientation values.

AI technology for self-driving cars is usually trained in ideal conditions.

In this video, Nvidia is going to show you how this DNN has evolved to detect not just Lane lines, but also other important road markings and visual landmarks.

Timely and accurate diagnosis increases patient chances for successful treatment. A fusion of AI, medical imaging and edge computing is delivering real time, life saving insights at the point of care to bring scalable AI and real time imaging to the edge.

AT #MWC19, NVIDIA has announced it's collaborating with partners to fuse 5G, supercomputing, and AI for a revolutionary communications platform to power the intelligent edge revolution.

High beam lights can increase night time visibility range of standard headlights significantly; however, they can create hazardous glare to other drivers.

NVIDIA’s virtual GPU (vGPU) now supports server virtualisation for AI, deep learning and data science. Previously limited to CPU-only, AI workloads can now be easily deployed on virtualised environments like VMware vSphere with new vComputeServer software and NVIDIA NGC.

Accelerated GPU services for VMware Cloud on AWS to power modern enterprise applications, have been announced by NVIDIA and VMware. “It creates a hyper cloud for Al, machine learning and data analytics workflows” said John Fanelli, Vice President, Business Management at Nvidia.

NVIDIA was invited to attend the Global E-sports Summit and Tencent E-sports Annual Conference held in Hainan, Chinaon June 20th 2019. Tencent E-sports hopes to establish E-sports technology standards in China, including technology of E-sports network, hardware, and broadcast to improve the management of the industry. 

Get a look at how Allegorithmic's Substance Alchemist uses AI to complete time consuming tasks like delighting materials to make it easier to take materials from the real world and immediately use them for 3D designs.

Listen to influencers in radiology from the University of Chicago, the American College of Radiology, Stanford Children's Health, and OSU Wexner Medical Center deliver their insights on how AI can augment radiology workflows to improve operational efficiencies and enhance patient care.

CEO of NextLimit Maxwell, Victor Gonzalez, and Researcher and Developer Fran González, discuss how NVIDIA GPUs allowed them to maximise the speed of GPU rendering for users.

Researchers from NVIDIA have developed a first of its kind deep learning-based system that can teach a robot to complete a task by just observing the actions of a human.

Watch the video below to learn more about the new deep learning elective in Udacity​'s self-driving car, Nanodegree, co-developed with the NVIDIA Deep Learning Institute.

NVIDIA researchers developed a drone that navigates without GPS and instead relies on deep learning and computer vision.

Watch NVIDIA’s own self-driving car, called 'BB8', navigate down Lombard Street in San Francisco.

Worried about data loss? You don’t have to be.

At CES, Nvidia, a manufacturer of computer graphics cards, has detailed new moves that will move it even further into the market: partnerships with suppliers ZF and Bosch that will see it making parts for automatic cars, and an expanded deal with Audi that will see the companies bring a proper self-driving vehicle to market by 2020.

Discover how SocialEyes, a group of machine learning scientists and clinicians with expertise in eye-care, are using deep learning to create a mobile ophthalmologist-in-a-box for low-resource countries.

On August 31 in 1999, we introduced the GPU to the world! Watch its progression up to now.