New NVIDIA Research Creates Interactive Worlds with AI
04 December 2018 - 12:00AM
Conference on Neural Information Processing
Systems --
NVIDIA today introduced
groundbreaking AI research that enables developers for the first
time to render entirely synthetic, interactive 3D environments
using a model trained on real-world videos.
Company researchers used a neural network to render synthetic 3D
environments in real time. Currently, every object in a virtual
world needs to be modeled individually, which is expensive and time
consuming. In contrast, the NVIDIA research uses models
automatically learned from real video to render objects such as
buildings, trees and vehicles.
The technology offers the potential to quickly create virtual
worlds for gaming, automotive, architecture, robotics or virtual
reality. The network can, for example, generate interactive scenes
based on real-world locations or show consumers dancing like their
favorite pop stars.
“NVIDIA has been inventing new ways to generate interactive
graphics for 25 years, and this is the first time we can do so with
a neural network,” said Bryan Catanzaro, vice president of Applied
Deep Learning Research at NVIDIA, who led the team developing this
work. “Neural networks — specifically generative models — will
change how graphics are created. This will enable developers to
create new scenes at a fraction of the traditional cost.”
The result of the research is a simple driving game that allows
participants to navigate an urban scene. All content is rendered
interactively using a neural network that transforms sketches of a
3D world produced by a traditional graphics engine into video. This
interactive demo will be shown at the NeurIPS 2018 conference in
Montreal.
The generative neural network learned to model the appearance of
the world, including lighting, materials and their dynamics. Since
the scene is fully synthetically generated, it can be easily edited
to remove, modify or add objects.
“The capability to model and recreate the dynamics of our visual
world is essential to building intelligent agents,” the researchers
wrote in their paper. “Apart from purely scientific interests,
learning to synthesize continuous visual experiences has a wide
range of applications in computer vision, robotics, and computer
graphics,” the researchers explained.
For more information, read NVIDIA’s Developer News Center post.
About NVIDIANVIDIA’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:Ken
BrownDirector, Corporate
CommunicationsNVIDIA+1-510-290-2603kebrown@nvidia.com
Certain statements in this press release including, but not
limited to, statements as to: new NVIDIA research creating
interactive virtual worlds with AI; the potential impact of
NVIDIA’s AI research quickly creating virtual worlds for gaming,
automotive robotics and VR; NVIDIA research enabling developers for
the first time to render 3D environments using a model trained on
real-world videos; the abilities, benefits, performance and impact
of NVIDIA’s research technology, including its ability to generate
interactive scenes based on real-world locations or consumers
dancing like their favorite pop stars, its ability to model the
appearance of the world and how it can be edited; NVIDIA creating
new ways to generate interactive graphics with neural networks;
neural networks changing how graphics are created and it enabling
developers to create scenes at a fraction of the traditional cost;
NVIDIA’s research being shown at the NeurIPS conference and its
results in a simple driving game; the capability to model and
recreate dynamics of our visual world being essential to building
intelligent agents; and the wide range of applications learning to
synthesize continuous visual experiences has 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 integrated into
systems; as well as other factors detailed from time to time in the
most recent reports NVIDIA files with the 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 company's website and
are available from NVIDIA without charge. These forward-looking
statements are not guarantees of future performance and speak only
as of the date hereof, and, except as required by law, NVIDIA
disclaims any obligation to update these forward-looking statements
to reflect future events or circumstances.
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