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If you’ve a penchant for liking superhero-themed anything and playing games in 3D, the Batman: Arkham series has been a match made in heaven. Simply put, when it comes to 3D Vision titles it just doesn’t get much better – and it’s hard to see how it could.We’re happy to report that Batman: Arkham Origins, which releases today, continues this tradition. Out of the box, Origins is rated 3D Vision Ready, so you know it’s going to look spectacular. We’ve played it quite a bit...
Contest closed - stay tuned to 3DVisionlive.com for details about upcoming contests.     3DVisionLive.com is excited to unveil the latest in a series of photo contests aimed at giving you a platform to show off your images and potentially win some cool prizes. Like our most recent Spring Contest, this one will span three months - October, November, and December - and is themed: Your image must be something that captures or shows the essence of "nature" and what...
With sincere apologies for the delay, NVIDIA is pleased to announce the results of the Spring Photo Contest. We received more than 80 submissions from 3DVisionLive members and, for the first time, invited the membership to select the winner. The only criteria for the contest was the photos had to represent the meaning of Spring in some fashion, and be an original image created by the member that submitted it. All submitted photos were put in a gallery and ample time was...
For the third year in a row, NVIDIA worked with the National Stereoscopic Association to sponsor a 3D digital image competition called the Digital Image Showcase, which is shown at the NSA convention - held this past June in Michigan. This year, the 3D Digital Image Showcase competition consisted of 294 images, submitted by 50 different makers. Entrants spanned the range from casual snapshooters to both commercial and fine art photographers. The competition was judged by...
  VOTING IS NOW CLOSED - Thanks to all that participated. Results coming soon!   The submission period for the Spring Photo Contest is now closed, and we are happy to report we’ve received 80 images from our members for consideration. And, for the first time, we’re opening the judging process to our community as well to help us determine the winners. So, between now and the end of June (11:59 PST, June 30st), please view all of the images in the gallery and place...

Recent Blog Entries

We’ll know AI really works when we hardly notice it at all, according to Bryan Catanzaro, a key figure in the field.

“AI gets better and better until it kind of disappears into the background,” says Catanzaro — NVIDIA’s head of applied deep learning research — in conversation with host Michael Copeland on this week’s edition of the new AI Podcast. “Once you stop noticing that it’s there because it works so well — that’s when it’s really landed.”

Bryan’s been in AI since the beginning. Or, as Michael says, as “about as long as it has really worked.” It’s a journey that’s taken him from UC Berkeley, where he earned his Ph.D., to NVIDIA, to Baidu — where he worked on a team that’s made a number of deep learning breakthroughs — and back to NVIDIA.

Along the way, he’s seen deep learning make incredible advances. It’s much further along than he would have predicted five years ago, he says. Image recognition has been one major success, with sophisticated facial recognition capabilities built into photo sharing services used by hundreds of millions of people every day.

“We’re at a point now where computers are actually better at recognizing objects in images than a person is,” Bryan says.

More’s coming, he explains. Deep learning — powered by ever more powerful GPUs — only grows more useful as the amount of data in the world grows.

“There’s a great number of problems that can be framed in this way, where you have a huge number of labeled examples, and you want a system to learn what that input means,” Bryan says.

To hear the whole conversation, tune into this week’s AI Podcast.

And if you missed our podcast last week, it’s definitely worth a listen: NVIDIA’s Will Ramey, a gifted explainer of all things deep learning, provides a clear explanation of the key concepts driving the field forward.

Finally, don’t miss next week’s podcast, where we talk about how you can use deep learning to accomplish some surprising do-it-yourself projects.

The post AI Podcast: Where Is Deep Learning Going Next? appeared first on The Official NVIDIA Blog.

A team from the Massachusetts General Hospital was among the researchers talking about how they’re using AI at GTC DC earlier this year.

The Mass General researchers joined colleagues from across the healthcare industry to help tell the story of how deep-learning – which is already used by hundreds of millions of people on smartphones – can improve health care.

Mass General became the first medical institute in the world — and among the first five research institutions of any kind — to receive an NVIDIA DGX-1. We delivered the supercomputer at Mass General’s historic Ether Dome, where the first public demonstration of surgery using anesthetic took place in 1846.

Mass General’s Clinical Data Science Center joins other early DGX-1 users, including the Open AI Institute, the Stanford Artificial Intelligence Laboratory, benevolent.ai, SAP and the Berkeley Artificial Intelligence Research Lab.

The center is already using GPUs to make significant medical advances. Researchers are testing an automated bone-age analyzer they’ve created that speeds diagnosis of children’s growth problems and is nearly as accurate as human radiologists (see “Deep Learning Speeds Diagnosis of Kids’ Growth Problems”).

More is coming. The Clinical Data Science Center is using AI and deep learning to advance healthcare, beginning with radiology, pathology and genetics. The center will research, test and implement new ways to improve the detection, diagnosis, treatment and management of diseases by training a deep neural network using Mass General’s vast stores of phenotypic, genetics and imaging data. The hospital has a database containing 10 billion medical images.

We delivered the supercomputer at Mass General’s historic Ether Dome, where the first public demonstration of surgery using anesthetic took place in 1846.

“The intent is to be able to explore the integration of man and machine at this point of clinical care, taking some of the data historically and using that data to actually create information in the machine so that we can see into the future what’s happening with patients before the human has the idea that there are changes taking place,” said Dr. Keith Dreyer, vice chairman and associate professor of radiology at Mass General and Harvard Medical School and executive director of the Mass General Clinical Data Science Center.

Radiology and Medical Imaging

DGX-1 also promises to help accelerate the adoption of AI in fields where machine learning techniques have already made a difference, such as radiology and medical imaging.

“The importance of machine learning and machine learning for radiology is unquestioned,” said Dr. James Brink, head of radiology at Mass General and chair of the American College of Radiologists. “I think there’s an enormous amount of opportunity for us to improve the efficiency of our work and the accuracy of our work through automation and semi-automation.”

Work with Patients

Longer term, deep learning also promises to help deliver better care for today’s patients by letting doctors better use the flood of medical research and patient data being produced by Mass General and other medical centers.

“I see deep learning and other machine learning techniques that could help us on a day-to-day basis make the process more efficient and in essence even more accurate,” said Dr. Long Li, assistant in pathology at Mass General and an assistant professor of pathology at Harvard Medical School.

Sounds like just what the doctor ordered.

Learn more about the DGX-1. Questions? Request a call.

The post Man, Machine and Medicine: Mass General Researchers Using AI appeared first on The Official NVIDIA Blog.