DataBloomAn A-list of female AI researchers and industry executives will take the stage at next month’s GPU Technology Conference to share the latest breakthroughs in every industry imaginable. Recognized in Forbes as a top conference for women to attend to further their careers in AI, GTC runs online, April 12-16, and is set to draw Read article >
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With GeForce NOW, over 5 million gamers are playing their favorite games in the cloud on PC, Mac, Chromebook, NVIDIA SHIELD TV, Android and iOS devices. With over 800 instantly available games and 80+ free-to-play games, there’s something for everyone. And there are multiple ways to build your library. We’ll review how to sync your Read article >
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This April, learn about the future of AI-powered transportation from those who are building it. The NVIDIA GPU Technology Conference returns to the virtual stage April 12-16, featuring autonomous vehicle leaders in a range of talks, panels and virtual networking events. Attendees will also have access to hands-on training for self-driving development and other deep Read article >
The post From Audi to Zoox: Autonomous Vehicle Innovators to Showcase Latest Breakthroughs at GTC 2021 appeared first on The Official NVIDIA Blog.
The autonomous trucking industry is about to get a major new addition. Self-driving truck company Plus announced that its upcoming autonomous vehicle platform will be built on NVIDIA DRIVE Orin. This software-defined system will continuously improve upon the safety and efficiency of the delivery and logistics industry with high-performance compute and AI algorithms that can Read article >
The post A Plus for Autonomous Trucking: Startup to Build Next-Gen Self-Driving Platform with NVIDIA DRIVE Orin appeared first on The Official NVIDIA Blog.
Runs on VMware vSphere; Optimized, Certified and Supported by NVIDIA; Hundreds of Thousands of Customers in World’s Largest Industries Can Now Adopt NVIDIA AI Enterprise at Scale SANTA CLARA, …
As enterprises modernize their data centers to power AI-driven applications and data science, NVIDIA and VMware are making it easier than ever to develop and deploy a multitude of different AI workloads in the modern hybrid cloud. The companies have teamed up to optimize the just-announced update to vSphere — VMware vSphere 7 Update 2 Read article >
The post How Suite It Is: NVIDIA and VMware Deliver AI-Ready Enterprise Platform appeared first on The Official NVIDIA Blog.
Artists, this is your chance to push past creative limits — and win great prizes — while exploring NVIDIA Omniverse through a new design contest. Called “Create with Marbles,” the contest is set in Omniverse, the groundbreaking platform for virtual collaboration, creation and simulation, and based on the Marbles RTX demo that first previewed at Read article >
The post Artists: Unleash Your Marble Arts in NVIDIA Omniverse Design Challenge appeared first on The Official NVIDIA Blog.
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Open Neural Network Exchange (ONNX) is a powerful and open format built to represent machine learning models. The final outcome of training any machine learning or deep learning algorithm is a model file that represents the mapping of input data to output predictions in an efficient manner.
Read more: https://analyticsindiamag.com/converting-a-model-from-pytorch-to-tensorflow-guide-to-onnx/
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Driver assistance technology is an incredibly active research domain – from supervised assistance functions all the way to fully autonomous driving. The best way to showcase the capabilities of novel AV approaches is to demonstrate them in a real car, but there are significant challenges to this type of deployment. Getting to the point where a new approach for multi-agent prediction, camera-based localization […]
Driver assistance technology is an incredibly active research domain – from supervised assistance functions all the way to fully autonomous driving. The best way to showcase the capabilities of novel AV approaches is to demonstrate them in a real car, but there are significant challenges to this type of deployment.
Getting to the point where a new approach for multi-agent prediction, camera-based localization or night-time obstacle detection runs in a car requires efforts on multiple levels:
The NVIDIA DRIVE AGX autonomous vehicle compute platform is designed to substantially simplify these efforts, enabling researchers to focus on what’s most important.
Research in Motion
Prof. Daniel Watzenig and the Autonomous Racing Graz team (a collaboration between Graz University of Technology and Virtual Vehicle Research) are pushing autonomous driving to the limit with driverless racing. Powered by NVIDIA DRIVE AGX, the team’s vehicle managed to secure the third place in the 2020 Roborace Season Alpha and was the highest-finishing academic team.
“Autonomous racing comes with very high requirements against software and hardware but also against weight and space. As researchers, we need to focus on trying out new approaches and iterate quickly – the NVIDIA DRIVE AGX platform is a perfect fit to these needs and has proven to be a key factor of our team’s success.” Watzenig said.
The team has published their research in papers such as Smooth Reference Line Generation for a Racetrack with Gates based on Defined Borders and Increased Accuracy For Fast Moving LiDARS: Correction of Distorted Point Clouds with more publications coming. They’ll also race in the new Indy Autonomous Challenge, competing against 30 other university teams.
Why DRIVE AGX?
The NVIDIA DRIVE AGX Developer Kit provides the hardware, software and sample applications needed for the development of autonomous vehicles. The platform is built on production auto-grade silicon, features an open software framework, and has a large ecosystem of supported auto grade sensors to choose from. The developer kit comes with unrivaled compute performance in a compact form factor, reaching up to 320 TOPs (INT8).
An ADAS and AV development platform must offer a software environment that supports established research tools. The DRIVE AGX Developer Kit supports a tailored Linux-derivate that provides a familiar environment to researchers. The possibility of running numerous popular Linux libraries makes it easy to migrate existing code.
The comprehensive NVIDIA DRIVE Software gives researchers a head start with a rich software suite that provides low-level hardware interfacing and middleware out-of-the-box.
DRIVE OS provides Hypervisor, CUDA, deep learning inference with TensorRT and camera interfacing. DriveWorks comprises tools for calibration, sensor and vehicle interfacing and recording and many additional tools and APIs. Finally, samples showcase typical AV modules that can be used as a reference.
Another important research requirement is that the development platform should be compact and durable. While it is possible to install desktop computers and additional hardware in cars to develop ADAS and AV functions, these setups typically require a large amount of space and add additional points of failure, especially since these components will likely not be auto-grade.
Getting Started with DRIVE AGX
The DRIVE AGX Developer Kit is available through the NVIDIA DRIVE Developer Program for DRIVE AGX. Please contact your NVIDIA representative (or contact us) to ensure necessary agreements have been signed before requesting to join the program. Users may only join with a corporate or university email address.
The DRIVE AGX Developer Kit comes with plenty resources to jump-start development:
* only accessible post NVIDIA DRIVE Developer Program for DRIVE AGX registration.
