Technology: Toyota, GM, NVIDIA and others team up on self-driving car chips - PressFrom - US
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Technology Toyota, GM, NVIDIA and others team up on self-driving car chips

15:50  09 october  2019
15:50  09 october  2019 Source:   engadget.com

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The consortium includes ARM, Bosch, Continental, DENSO, General Motors , NVIDIA , NXP Semiconductors and Toyota (whose P4 Automated Driving Test Vehicle is pictured above), who will collaborate on overcoming some of the most significant challenges posed by autonomous vehicles

Autonomous car developers use NVIDIA DRIVE car technology to teach self - driving cars to see, think, and learn. Read more. NVIDIA uses the power of AI and deep learning to deliver a breakthrough end-to-end solution for autonomous driving—from data collection, model training, and

Autonomous vehicles pose a whole bunch of R&D challenges. With so many aspects to consider -- power consumption, safety, user interface and data management, to name just a few -- creating a common computing platform for their use is a big ask of just one company. That's why a group of automotive and tech businesses have joined forces to create the Autonomous Vehicle Computing Consortium (AVCC), in a bid to create a platform that will promote the scalable deployment of automated and autonomous vehicles.

a close up of a car

The consortium includes ARM, Bosch, Continental, DENSO, General Motors, NVIDIA, NXP Semiconductors and Toyota (whose P4 Automated Driving Test Vehicle is pictured above), who will collaborate on overcoming some of the most significant challenges posed by autonomous vehicles -- the group's first step will be developing a set of recommendations for a system architecture for the computing platform. According to Alex Harrod of Arm, "The group brings together a unique combination of expertise and a shared goal," and will be welcoming input from other interested parties and members of the automotive ecosystem.

AVCC

Nvidia and VMware team up to make GPU virtualization easier.
Nvidia today announced that it has been working with VMware to bring its virtual GPU technology (vGPU) to VMware's vSphere and VMware Cloud on AWS. The company's core vGPU technology isn't new, but it now supports server virtualization to enable enterprises to run their hardware-accelerated AI and data science workloads in environments like VMware's vSphere, using its new vComputeServer technology. Traditionally (as far as that's a thing in AI training), GPU-accelerated workloads tend to run on bare metal servers, which were typically managed separately from the rest of a company's servers.

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