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3D News

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 www.geforce.com/drivers 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

What if you could cut your commute from Silicon Valley to San Francisco to just 20 minutes from the 90 minutes it might have taken you this morning? Absurd, perhaps, but this could soon become reality, thanks to the work of Arne Stoschek and A³ Airbus.

Stoschek, head of autonomous systems at the San Jose, Calif.-based Airbus unit, joined this week’s AI Podcast to talk about how he plans to make pilotless flights our new mode of transportation.

“The problem that we want to address is … congestion and commute,” said Stoschek in a conversation with AI Podcast host Michael Copeland. “Particularly in the U.S., people spend more than an hour per day commuting. And though that’s a lot of time people spend, it’s also very painful.”

His team developed an airborne, self-navigating vehicle that can reach a speed of 240 km/hr (150 mph). Roughly the size of two parking spots, it can comfortably fit two passengers plus luggage. It also has the ability to conduct vertical take-offs.

How is developing self-flying vehicles different from developing self-driving cars? Everything goes faster, for one, Stoschek said. Not only does the vehicle move faster, but obstacles appear quickly, so you have to identify “roadblocks” well in advance.

“We believe we cannot simply afford any longer to not utilize the certain amount of space that we have on top of the ground infrastructure,” he said.

AI Podcast: Deep Learning is Changing Our Hands-Free, Voice Experiences

If you’re interest in AI that is more down to earth, check out last week’s podcast. We spoke with Kitt.ai founder Xuchen Yao about how we may one day see a smart-home device that is more conversational and natural.

How to Tune in to the AI Podcast

Our AI Podcast is available through iTunes, Google Play Music, DoggCatcher, Overcast, Podbay, Pocket Casts, PodCruncher, PodKicker, Stitcher and Soundcloud. If your favorite isn’t listed here, leave a comment below.

 

The post AI Podcast: AI to Take Our Vehicles Up, Up and Away appeared first on The Official NVIDIA Blog.

Eat healthy. Sleep enough. Exercise regularly. And ask your doctor about AI.

AI could soon help you stay healthy longer. Thanks to GPUs and deep learning, physicians can predict the onset of diseases far earlier than is now possible, simply by analyzing patient electronic health records (EHRs).

“We’re moving from treatment to prevention,” said Narges Razavian, a professor at New York University’s Langone School of Medicine. “We want to know, is this person at risk for something and can we predict it?”

AI to Predict Disease

In a talk at this month’s GPU Technology Conference, Razavian explained how her NYU team predicted 200 ailments three months faster than traditional methods by analyzing EHRs such as lab tests, doctors’ notes and X-rays.

Razavian’s deep learning software accurately predicted heart failure, severe kidney disease, liver problems, diabetes and hormone-related conditions based on just 18 common lab measurements captured over three years.

“Lots of diseases are preventable, but they happen so slowly that people get worse without realizing it,” Razavian said. “If we can use deep learning as a powerful tool to give patients a wake-up call, we’d be able to prevent diseases when there’s still time.”

The NYU team predicted severe kidney disease with its deep learning software. Detecting kidney disease early could keep patients off dialysis. Researchers Find Hidden Links to Disease

The NYU researchers aren’t the first to realize the potential of EHRs to keep people healthier longer. (For examples, see “Doctor, Doctor, Give Me the News” and “How AI Can Predict Heart Failure Before It’s Diagnosed.”)

What’s different is the team’s ability to combine many different types of records over time to find previously unknown relationships, Razavian said.

For example, researchers predicted Type 2 diabetes by drawing connections among 900 measurements such as the patient’s weight, blood pressure, glucose levels, liver function and cholesterol levels. In the process, they found that some factors not typically associated with diabetes – a history of sleep apnea or acute bronchitis, hypothyroidism and anemia – may also predict the disease.

“This gets us closer to the biological mechanisms of diseases,” Razavian said.

How Deep Learning Aids Prevention

To predict disease, the researchers trained two neural networks on lab measurements and diagnosis information for 200,000 people selected from among 4.1 million insurance subscribers. The data was “raw,” meaning it had not been labeled or processed.

The team put its research to the test to improve an NYU medical center initiative that provides nurses’ visits and phone calls for 250,000 high-risk patients. By using deep learning to predict which patients were likely to suffer certain conditions, they helped the hospital determine who might be helped by an intensive lifestyle-management program aimed at preventing disease.

The work also helped automate scheduling for high-risk patients’ nurse visits and screening tests.

Razavian and other researchers hope to use EHRs and deep learning to advance precision medicine, an approach to disease prevention and treatment that’s customized for each patient.

“The applications for this work are enormous, and we’re just limited by personnel and time,” she said.

The post Prevention by Prediction: How AI Spots Early Warnings of Disease appeared first on The Official NVIDIA Blog.