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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...
3DVisionLive’s first-ever short-form 3D video contest received 14 entries that showed a great deal of diversity, ranging from video game captures to commercial-style clips to raw captures of pets or people doing cool things (such as bashing each other with swords). During judging we laughed, we cried (okay, maybe not), and we simply scratched our heads…. But seriously: thank-you to all that participated and we hope to see more of your content uploaded to the site for all to...
The submission period for the Fall Photo Contest is now closed, and we are happy to report we’ve received nearly 100 images from our members for consideration. And, once again, we’re opening the judging process to our community as well to help us determine the winners. The full gallery of images may be seen by clicking the link above. Between now and February 10th (11:59 PST), please view all of the images in the gallery and place your votes for the ones you’d like to win by...

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There was no escaping the automotive innovations, or the camera-toting crowds gawking at them, at CES 2018 this week in Las Vegas.

NVIDIA kicked off the show with a torrent of new partnerships and autonomous driving solutions. Uber, Volkswagen, Aurora, ZF, Baidu and Mercedes-Benz all announced new initiatives with NVIDIA. The announcements brought the total number of partners developing on the NVIDIA DRIVE platform to more than 320.

Around the North Hall, attendees at the world’s largest trade show could find our partners at almost every turn. Starting at the NVIDIA booth, Roborace drew crowds — and U.S. Secretary of Transportation Elaine Chao — with the CES debut of its low-set, sinuous Robocar. The NVIDIA-powered electric race car will take part in a future autonomous series, sanctioned by Formula E.

Nearby in the NVIDIA Holodeck, visitors took a virtual bus trip through time. After donning head-mounted displays they got to experience the transformation of the iconic 1960s era Volkswagen Type 2 microbus into the AI-infused, all-electric VW I.D. Buzz slated for 2022. Holodeck is a VR lab that lets far-flung teams come together in a realistic virtual environment to interact with photorealistic models of their designs.

For attendees interested in seeing self-driving go big in the most literal sense, TuSimple displayed an autonomous Peterbilt truck with NVIDIA DRIVE technology. The company provides a camera- and radar-based technology for autonomous driving. The startup expects to begin commercial operation of their level 4 system — supervised by test drivers — this year.

While NVIDIA has worked with both ZF and Baidu for over a year, a new initiative announced at CES brings the three companies together to realize a commercial solution for autonomous valet parking this year, with production vehicles using AI self-driving technologies expected on the roads of China starting in 2020.

Amid stunning visuals at the Mercedes-Benz booth, the automaker unveiled the NVIDIA-powered MBUX infotainment system. This revolutionary in-cabin experience can learn and adapt to driver and passenger preferences, thanks to artificial intelligence.

Dozens of other NVIDIA DRIVE partners attended the event to share their latest work with the crowds who descended on Las Vegas for the week. We spent time with many of them on the show floor, including Tertavue, Expolorer.ai, Cepton, Navya, HERE, AutonomouStuff, Deepmap, Innoviz, Cognata, Adasky and Torc. Watch our partner recap video above to hear about the latest self-driving innovations.

Take an even deeper dive into the technology at the heart of the autonomous vehicle revolution. Join us in March for the GPU Technology Conference in Silicon Valley.

The post Automotive Innovations Powered by NVIDIA DRIVE Draw Crowds at CES 2018 appeared first on The Official NVIDIA Blog.

Deep learning is performing wonders, automating everything from driving to recognizing speech to composing music. Now, it’s poised to fire up scientific discovery, thanks to new software created by scientists at the U.S. Department of Energy’s Oak Ridge National Laboratory (ORNL).

Working on the GPU-accelerated Titan supercomputer at ORNL, the team developed an algorithm that automatically generates neural networks. Modeled loosely on the connections in the human brain, these do the “learning” in deep learning.

MENNDL, short for Multi-node Evolutionary Neural Networks for Deep Learning, evaluates, tests and recommends neural networks for unique datasets like those that scientists collect. And with GPU acceleration, it’s fast, reducing what can be a months-long endeavor to a matter of weeks.

“MENNDL is about saving people time and making scientific discovery happen faster,” said Steven Young, a research scientist who’s part of ORNL’s Nature Inspired Machine Learning team.

AI for Scientists

Although the ORNL team created MENNDL for scientists, it has the potential to transform AI more broadly. By training a neural network, researchers create software to perform certain tasks. ORNL’s software creates the network itself, eliminating the trial-and-error process normally required to configure one.

Scaled across Titan’s 18,688 Tesla GPUs, the algorithm simultaneously tests and trains thousands of potential networks to predict those best suited to the job.

In many fields, researchers use existing neural networks or datasets as a launching pad for their deep learning efforts. That’s not possible for scientists, whose data comes from scientific instruments and looks a lot different from what’s used to teach computers to recognize faces or understand speech.

“At the lab we work with data that’s pulled from a neutrino detector, electron microscope or some other scientific instrument,” Young said. “It’s a far cry from pictures of cats and dogs.”

The MINERvA neutrino detector at Fermi National Accelerator Laboratory. 24-Hour Turnaround

MENNDL is already speeding research in neutrino physics. Neutrinos are subatomic particles that scientists believe could shed light on such mysteries as the origins of the universe and the nature of matter.

Because neutrinos are notoriously hard to detect, scientists at DOE’s Fermi National Accelerator Laboratory (Fermilab) use high-intensity beams to study how they react with ordinary matter. That produces mountains of data, which researchers must analyze to  identify precisely where the interaction occurred.

In the past, the Fermilab team would have spent months testing neural networks to find one that would work for their problem, Young said. MENNDL did it in just 24 hours.

“Instead of having scientists play around with deep learning frameworks for months, MENNDL gives them a network that will work with their data in just a day,” Young said.

That lets researchers conduct more experiments in less time — and advance science more quickly.

For more information, see ORNL’s paper, Optimizing Deep Learning Hyper-Parameters Through an Evolutionary Algorithm.

To learn more about the latest research at ORNL on deep learning and supercomputing, attend the GPU Technology Conference, March 26-29, in Silicon Valley. Register now.

* The main image for this story shows the inside of the MiniBooNE neutrino detector at Fermi National Accelerator Laboratory.

The post An AI for AI: New Algorithm Poised to Fuel Scientific Discovery appeared first on The Official NVIDIA Blog.