NVIDIA Provides Transportation Industry Access to Its Deep Neural Networks for Autonomous Vehicles
December 17 2019 - 11:01PM
GTC China -- NVIDIA today
announced that it will provide the transportation industry with
access to its NVIDIA DRIVE™ deep neural networks (DNNs) for
autonomous vehicle development on the NVIDIA GPU Cloud (NGC)
container registry.
NVIDIA DRIVE has become a de facto standard for AV development,
used broadly by automakers, truck manufacturers, robotaxi
companies, software companies and universities. Now, NVIDIA is
providing access of its pre-trained AI models and training code to
AV developers. Using a suite of NVIDIA AI tools, the ecosystem can
freely extend and customize the models to increase the robustness
and capabilities of their self-driving systems.
“The AI autonomous vehicle is a software-defined vehicle
required to operate around the world on a wide variety of
datasets,” said Jensen Huang, founder and CEO of NVIDIA. “By
providing AV developers access to our DNNs and the advanced
learning tools to optimize them for multiple datasets, we’re
enabling shared learning across companies and countries, while
maintaining data ownership and privacy. Ultimately, we are
accelerating the reality of global autonomous vehicles.”
AI is central to the development of safe, self-driving cars —
allowing them to perceive and react in real time to their
surroundings for intelligent operation. At its core are dozens of
DNNs that tackle redundant and diverse tasks, ensuring accurate
perception, localization and path planning.
“NVIDIA leads the world in developing the deepest and broadest
suite of DNNs and AI tools for the transportation industry,” said
Luca De Ambroggi, senior research director of Artificial
Intelligence at IHS Markit. “Making these algorithms available to
others, along with the tools and workflow infrastructure to
customize them, will help enable the deployment of safe autonomous
transportation.”
NVIDIA has spent years developing and training DNNs that run on
the NVIDIA DRIVE AGX™ platform, turning raw sensor data into a deep
understanding of the world. These DNNs cover such tasks as
traffic-light and sign detection, object detection (for vehicles,
pedestrians, bicycles) and path perception, as well as gaze
detection and gesture recognition inside the vehicle.
Advanced Learning Tools for AI Development:In
addition to providing access to the DNNs, NVIDIA announced the
availability of a suite of advanced tools so developers can
customize and enhance NVIDIA’s DNNs using their own datasets and
target feature set. These tools allow the training of DNNs using
active learning, federated learning and transfer learning:
- Active learning improves model accuracy and reduces data
collection costs by automating data selection using AI, rather than
manual curation.
- Federated learning enables companies to utilize datasets across
countries and with other companies while maintaining data privacy
and protecting their intellectual property.
- Transfer learning gives DRIVE customers the ability to speed
development of their perception software by leveraging NVIDIA’s
significant investment in AV development, then further developing
these networks for their own applications and target
capability.
By providing access to its AI models on NGC and introducing
advanced training tools, NVIDIA strengthens its end-to-end platform
for AV development and deployment.
About NVIDIA NVIDIA’s (NASDAQ: NVDA) invention
of the GPU in 1999 sparked the growth of the PC gaming market,
redefined modern computer graphics and revolutionized parallel
computing. More recently, GPU deep learning ignited modern AI — the
next era of computing — with the GPU acting as the brain of
computers, robots and self-driving cars that can perceive and
understand the world. More information at
http://nvidianews.nvidia.com/.
For further information, contact:Marie LabriePR
Manager, AutomotiveNVIDIA Corporation
+1-408-921-6987mlabrie@nvidia.com
Certain statements in this press release including, but not
limited to, statements as to: NVIDIA providing the transportation
industry with full source access to NVIDIA DRIVE deep neural
networks for autonomous vehicle development on the NVIDIA GPU Cloud
(NGC) container registry; the benefits and impact of NVIDIA DRIVE,
providing partners source access of NVIDIA’s deep neural networks,
and NVIDIA’s advanced learning tools for AI development; NVIDIA
accelerating the reality of global autonomous vehicles; AI as
central to the development of safe, self-driving cars; NVIDIA
leading the world in developing the deepest and broadest suite of
DNNs and AI tools for the transportation industry are
forward-looking statements that are subject to risks and
uncertainties that could cause results to be materially different
than expectations. Important factors that could cause actual
results to differ materially include: global economic conditions;
our reliance on third parties to manufacture, assemble, package and
test our products; the impact of technological development and
competition; development of new products and technologies or
enhancements to our existing product and technologies; market
acceptance of our products or our partners’ products; design,
manufacturing or software defects; changes in consumer preferences
or demands; changes in industry standards and interfaces;
unexpected loss of performance of our products or technologies when
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Securities and Exchange Commission, or SEC, including, but not
limited to, its annual report on Form 10-K and quarterly reports on
Form 10-Q. Copies of reports filed with the SEC are posted on the
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© 2019 NVIDIA Corporation. All rights reserved. NVIDIA, the
NVIDIA logo, NVIDIA AGX and NVIDIA DRIVE are trademarks and/or
registered trademarks of NVIDIA Corporation in the U.S. and other
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