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3D News

NVIDIA is pleased to announce the first Photo Champion for 3D Vision Live, Nick Saglimbeni. Regular visitors to the site should be well familiar with Nick's images. His Warehouse Wonderland image won the site's first monthly Photo Contest, and he was also the first repeat winner of the Contest two months later with Kim Kardashian's Wild West - one of the site's first 3D celebrity images. Nick is receiving the 2012 3D Vision Live Photo Champion Award as our formal...
Sorry folks for the delay in announcing the winner for May's Photo Contest - we had an issue with the search function and needed to make sure all entries were considered. Without further ado, on to the results! Alex Savin has been submitting some excellent images from his European adventures for some time now, and his "Fontana di Trevi" is a wonderful example of stereo photography that just plain works. The composition is top notch and the image is sharp throughout, which...
James Cameron continues to pioneer 3D technology. With the first Avatar he showed what 3D could add to the film experience. After criticizing the fast conversions from 2D to 3D that many Hollywood studios have released since Avatar, Cameron oversaw a team that turned Titanic into a 3D blockbuster. That film has been a commercial and critical success, showing what a year of meticulous conversion and $18 million can add to a 15-year-old movie. The director talks about Avatar,...
Marvel Entertainment was one of the first major Hollywood companies to commit to 3D movies. Beginning last summer, every movie based on a Marvel comic property was to be either filmed in 3D or converted to 3D for theatrical and home entertainment releases. When this mandate came down, Ari Arad (Iron Man), producer of Ghost Rider: Spirit of Vengeance, turned to NVIDIA to help with the production of the Sony Pictures sequel, which is now out on Blu-ray 3D, Blu-ray and DVD....
People are flocking to the theater to take in Pixar’s latest animated film, Brave, which we recommend seeing in 3D, of course. After seeing the movie you can relive the adventure by picking up the gorgeous Brave: The Video Game for PC. The third-person action/adventure game lets you play the role of Princess Merida—Pixar’s first female lead character—as you follow her adventures in a family-friendly storyline based on the film. Engage in bow-and-arrow and sword combat and...

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.