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For the last few years we’ve worked with the National Stereoscopic Association to support the 3D Digital Showcase photo competition featured at the NSA’s annual conventions. The images from this past year’s showcase are now live for everyone to view. We really enjoy the diversity of images submitted by 3D artists and enthusiasts to this event, and this gallery is certainly no different. You’ll see everything from close ups of insects to people juggling fire. Simply put,...
In driver 334.89 NVIDIA introduced a new proprietary rendering mode for 3D Vision that enables us to improve the 3D experience for many key DirectX 10 and 11 games. This mode is now called “3D Compatibility Mode”. We have continued to iterate on this feature in driver 344.11, increasing game support and adding some new interface elements. You can get the new driver at or via the update option in Geforce Experience. With the release of 344.11, new 3D...
We’re fortunate enough to have another fine 3D video from New Media Film Festival to share with you here on 3DVisionLive—a pop music video from Italy called “The Way,” which you can view here. Even better, New Media Film Festival has provided an interview with one of the co-directors of the video, Edoardo Ballanti, which provides insights on how the video was created and the vision behind it. Enjoy! (Alice Corsi also co-directed the video.) What was the Inspiration behind “...
The Fall Photo Contest received nearly 100 images – thanks to all that entered! The contest called for your best “nature” shots with the only other requirement being that they had to be true stereo images. Submissions ranged from shots of spiders in gardens to artistic approaches to tasteful nudes. As before, members were invited to vote for the winner by tagging images in the contest gallery as favorites. Without further ado, the winner is: Autumn Goodbye to Summer This...
In driver 334.89 NVIDIA introduced a new proprietary rendering mode for 3D Vision that enables us to improve the 3D experience for many key DirectX 10 and 11 games. This mode is now called “3D Compatibility Mode”. We have continued to iterate on this feature in beta driver 337, increasing game support and adding a toggle key to enable/disable the mode. Games with 3D Compatibility Mode will launch in this mode by default. To change the render mode back to standard 3D Vision...

Recent Blog Entries

As the AI revolution gains momentum, NVIDIA founder and CEO Jensen Huang took the stage Tuesday in Beijing to show the latest technology for accelerating its mass adoption.

His talk — to more than 3,500 scientists, engineers and press gathered for the three-day event — kicks off a GTC world tour where in the months ahead we’ll bring our story to an expected live audience of some 22,000 in Munich, Tel Aviv, Taipei, Washington and Tokyo.

“At no time in the history of computing have such exciting developments been happening, and such incredible forces in computing been affecting our future,” said Huang, clad in his trademark leather jacket, after striding onto the stage at the gleaming Beijing International Hotel Convention Center.

Demand is surging for technology that can accelerate the delivery of AI services of all kinds. And NVIDIA’s deep learning platform — which the company updated Tuesday with new inferencing software — promises to be the fastest, most efficient way to deliver these services.

In a nearly two-hour keynote, Huang explained how the neural networks that power AI applications are growing exponentially more complex, even as far more consumers use them. As a result, we’re in an entirely new era of computing, with new kinds of demands, Huang said.

“What technology increases in complexity by a factor of 350 in five years? We don’t know any, What algorithm increases in complexity by a factor of 10? We don’t know any,” Huang said. “We are moving faster than Moore’s law.”

TensorRT 3: Recognizing 5,200 Images a Second

To meet that demand, NVIDIA unveiled TensorRT 3 AI inferencing software, which runs a trained neural network in a production environment (see “What’s the Difference Between Deep Learning Training and Inferencing?”). The new software will boost the performance and slash the cost of inferencing from the cloud to edge devices, including self-driving cars and robots.

The combination of TensorRT 3 with NVIDIA GPUs delivers the world’s fastest inferencing on the widely used TensorFlow framework for AI-enabled services — such as image and speech recognition, natural language processing, visual search and personalized recommendations. Coupled with our Tesla V100 GPU accelerators, TensorRT can process as many as 5,700 images a second, versus just 140 using today’s CPUs, Huang said.

The speed and efficiency TensorRT 3 offers when paired with NVIDIA GPUs translates into incredible savings, Huang explained. It takes 160 dual CPU servers — costing $600,000 to $700,000, including networking and power delivery — that consume 65 kilowatts of power, to crank through 45,000 images per second.

By contrast, the same work can be done with a single NVDIA HGX server equipped with eight Tesla V100 GPUs that consume just 3 kilowatts of power.

That means “less carbon footprint, less space. And this is the part I love best,” Huang said with a grin. “Save money.”

In addition to TensorRT 3, Huang announced software to accelerate AI, including the DeepStream SDK — which provides real-time, low-latency video analytics at scale — and CUDA 9, the latest version of our accelerated computing software to speed up HPC and deep learning applications.

China Cloud Service Providers, OEMs Adopt Tesla V100

And there are now more options than ever for those looking to put this technology to work.

Huang announced that Alibaba, Baidu and Tencent are all deploying Tesla V100 GPU accelerators in their cloud services. Plus, China’s top OEMs — Huawei, Inspur and Lenovo — have all adopted our HGX server architecture to build a new generation of accelerated data centers with Tesla V100 GPUs.

In addition, Jensen announced all five of the leading Internet and AI companies in Chinas – Alibaba, Tencent, Baidu,, and iFlyTech have adopted NVIDIA’s GPU inferencing platform.

“Every single Internet transaction, every piece of traffic that goes through the datacenter will in the future touch a neural network, or many neural networks,” Huang said.

New Metropolis Partners

And with the addition of Alibaba and Huawei as new partners — and the general availability of the NVIDIA DeepStream SDK — we’ve added more building blocks to our smart city foundation at GTC China this week.

DeepStream simplifies the development of scalable intelligent video analytics powered by deep learning for AI cities and hyperscale data centers.

Alibaba and Huawei join more than 50 of the world’s leading companies already using NVIDIA Metropolis. Together, we’re taking advantage of the more than 1 billion video cameras that will be in our cities by the year 2020 to solve such problems as traffic congestion, emergency notifications and locating lost persons.

“Artificial Intelligence is going to revolutionize how cities are built in the future,” Huang said. “We call it AI City.”

NVIDIA Drive Adopted by Autonomous Vehicle Efforts Around China

One of the greatest impacts of AI will be autonomous vehicles – the self-driving car, Huang explained.

To meet this challenge, NVIDIA has created a platform for autonomous vehicles called DRIVE. It addresses every aspect of autonomous vehicles, and partners can utilize all — or some — of this platform.

To power autonomous efforts such as these — machines that can perceive the surroundings, understand the situation and reason about what to do, control itself to interact — NVIDIA created “Xavier,” the world’s first processor for autonomous machines. Xavier is the most complex SOC ever created.

It will be available in Q1 to early access partners; general availability in Q4‘18.

Pillars in Place to Invent Next AI Era

Huang finished his talk by by recapping the five big innovations shown on his last slide – NVIDIA AI computing platform TensorRT 3, AI Cities platform, NVIDIA DRIVE PX, and Xavier.

“Our vision is to enable every researcher everywhere to enable AI for the goodness of mankind,” Huang said.  “We believe we now have the fundamental pillars in place to invent the next era of artificial intelligence, the era of autonomous machines.”

The post NVIDIA CEO Kicks Off Global GTC Tour, Unveiling AI Tools and Partnerships in China appeared first on The Official NVIDIA Blog.

NVIDIA GPU Ventures has joined a group of investors led by Chinese venture capitalist firm, Qiming Venture, in investing $52 million in Chinese startup JingChi.

Founded last spring by Tony Han and Jing Wang, former leaders of the autonomous driving unit at Baidu, JingChi uses NVIDIA GPUs and NVIDIA DRIVE PX 2 to develop its autonomous cars.

In June, it successfully completed its first autonomous mode testing on public roads. The company plans to put 50 self-driving cars on the streets of Anging City, China, by the end of this year, and to launch an Uber-like ride-hailing service there in 2018.

JingChi said the investment will allow it quickly scale up its research and development teams in Beijing and Sunnyvale, Calif., and ramp up deployment of a fully Level 4 autonomous driving test fleet in China by the end of the year.

The NVIDIA DRIVE PX AI platform is crucial to developing and deploying deep learning capabilities for JingChi and many other autonomous vehicle projects around the world.\

“NVIDIA offers significant computational benefits that will boost in-vehicle computation abilities, making JingChi’s autonomous vehicles safer and more reliable,” said Han. “JingChi is eager to work with NVIDIA to maximize the benefits of DRIVE PX to realize its vision of bringing autonomous ride-hailing to China.”

“AI is reshaping the transportation industry, and startups in China and around the world are playing a big part in that,” said Jeff Herbst, NVIDIA’s vice president of Business Development. “JingChi is making impressive progress on its vision for harnessing deep learning for autonomous driving and we’re dedicated to supporting their important work.”

NVIDIA continues to expand its portfolio of startup investments, adding more than 10 companies in five countries over the past year. Among the new investments are:

  • ABEJA – Tokyo startup focused on AI-powered retail analytics systems
  • Datalogue – New York AI data-mining platform developed out of Cornell University
  • Deep Instinct – Israeli startup focused on cybersecurity
  • Element AI – Montreal startup helps companies quickly integrate AI capabilities
  • – California startup offering streaming analytics software
  • Optimus Ride – MIT spinoff developing fully autonomous vehicles
  • SoundHound – Silicon Valley startup building voice-enabled AI solutions
  • TempoQuest – Colorado startup doing GPU-accelerated weather forecasting
  • TuSimple – Chinese autonomous truck startup
  • Zebra Medical – Israeli startup using AI to read medical images

The post NVIDIA Invests in Chinese Self-Driving Car Startup, JingChi appeared first on The Official NVIDIA Blog.