Goto

Collaborating Authors

Nvidia reveals 'supercomputer' for self-driving cars

ZDNet

Nvidia has unveiled Xavier, a new "supercomputer" system-on-a-chip (SoC) which will act as the control center for future autonomous vehicles. On Wednesday at the GPU Technology Conference Europe in Amsterdam, Nvidia CEO Jen-Hsun Huang revealed the SoC, branding the chip the "greatest SoC endeavor I have ever known." Dubbed Xavier, the SoC integrates a new GPU architecture called Volta, a new 8-core CPU architecture and a new computer vision accelerator. The US chip maker says the processor can deliver up to 20 trillion operations per second in performance, while only consuming 20 watts of power -- an important aspect for vehicles. In addition, as the chip has been developed with the vehicle industry in mind, Xavier will be compliant with automotive standards, such as the ISO 26262 safety specification.


Nvidia reveals new AI platforms for smart assistants and AR in the car

#artificialintelligence

Nvidia revealed a lot of news about its Xavier autonomous machine intelligence processors at this year's CES show in Las Vegas. The first production samples of the Xavier are now shipping out to customers, after being unveiled last year, and Nvidia also announced three new variants of its DRIVE AI platform, which are based around Xavier SoCs.


NVIDIA Shatters Inference Benchmarks

#artificialintelligence

The key to these cutting-edge vehicles is inference -- the process of running AI models in real time to extract insights from enormous amounts of data. And when it comes to in-vehicle inference, NVIDIA Xavier has been proven the best -- and the only -- platform capable of real-world AI processing, yet again. NVIDIA GPUs smashed performance records across AI inference in data center and edge computing systems in the latest round of MLPerf benchmarks, the only consortium-based and peer-reviewed inference performance tests. NVIDIA Xavier extended its performance leadership demonstrated in the first AI inference tests, held last year, while supporting all new use cases added for energy-efficient, edge compute SoC. Inferencing for intelligent vehicles is a full-stack problem.


Understanding the Myths and Realities of Autonomous Vehicles

#artificialintelligence

The topic of autonomous vehicles, also known as self-driving cars, has been at the forefront of technology news for the better part of this decade. I get the appeal, as the vision of vehicles that drive, or fly around on their own, has historically been the stuff of science fiction. Autonomous vehicles are fascinating as they use almost every kind of technology imaginable, including network connectivity, messaging, cloud services, graphics processing units (GPUs), artificial intelligence (AI), video analytics, and more. Over the past year, I've noticed the self-driving topic has become more widespread. Last month at Microsoft Ignite, we heard how the autonomous vehicle is one of the core components of Goodyear's strategy, as outlined in a previous No Jitter post.


Nvidia is partnering with Uber, Volkswagen and Baidu on driverless cars

#artificialintelligence

Nvidia has partnered with Uber, Volkswagen and China's Baidu in driverless cars, as the chipmaker looks to expand its presence in the autonomous driving space.