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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...
Okay, we've gone over all the submissions for our first Winter Photo Contest and debated at length over our favorites. And, we've finally come to a consensus, which will introduce our second, second-time contest winner: ZZ3D.   First Prize: Snow Fight   ZZ3D's a long-time contributor to 3DVisionLive and has shared some amazing work with us. Snow Fight is certainly no exception! We felt this image captured the essence of the contest's Winter theme very well, and...
The votes have all been cast and we can now, finally, bring you the results of our First Annual Summer Photo Contest. Dozen's of excellent images were submitted and it was a challenge to whittle all the entries down and select the prize winners. Without further ado we get to the results - drumroll please!   First Prize: "Soap Bubble" Zoran Zelic (ZZ3D)'s "Soap Bubble 1" takes the top prize. We like the spontaneity the image implies along with the overall composition...
Sometimes it’s just great “when a plan comes together.” An avid warbird photographer, I’d been familiar with Christian Kieffer’s outstanding pinup photography for years – his company produces some truly amazing nostalgic calendars featuring vintage WWII aircraft and models done up to mimic the pinups from the same era that helped to keep many an airman’s spirits high. Thinking the subject matter would lend itself well to 3D, I approached Christian a few months ago about...

Recent Blog Entries

This April 22 put a little AI in your Earth Day.

Whether you’re cleaning up a beach, planting a tree or starting a garden, iNaturalist makes it easy to get in touch with nature.

iNaturalist is a crowd-sourced species identification app powered by AI. For the casual nature observer, the app allows people to snap photos of such easy targets as backyard plants and bugs and upload images for its AI to provide a match or for members of the community to identify.

The app is also a social network for nature enthusiasts to record information on species, meet others with similar interests and learn. It’s available on Android and iOS , where it’s already been downloaded nearly a million times.

It began as a website, iNaturalist.org, founded in 2008 by students at the University of California, Berkeley. Now it’s a joint program of the California Academy of Sciences and the National Geographic Society.

Previously it took 18 days on average for species to be identified by the website’s community. But that all changed after iNaturalist worked with researchers from Caltech and Cornell to build a computer vision AI into the app.

Now species can be identified in a matter of milliseconds, and much more accurately, with the use of AI, said Scott Loarie, co-director of iNaturalist.

“Our goal is to get millions of people outside exploring and connecting to nature and engage them to become lifelong stewards of the natural world,” Loarie said.

People mostly put up observations of plants to iNaturalist, but posts of birds, insects and other organisms can be found as well.

The app harnesses NVIDIA GPUs and the CUDA deep neural network library along with the TensorFlow deep learning framework, allowing training of the neural networks on a database of images that have been labeled by the site’s community of experts.

Today iNaturalist boasts 8.6 million observations uploaded and more than 155,000 species observed.

The post iNaturalist: An AI-Powered App to Crow About on Earth Day appeared first on The Official NVIDIA Blog.

Assessing risk is a concern in most industries, although perhaps never more so than following a merger or acquisition. It turns out AI may be just the tool to help.

GPU Technology Conference attendees last month got a high-level education in how AI can bring speed and precision to this process from Congruity360, a Massachusetts-based data management consultancy.

Mitigating Risk in M&A

Two people deciding to live together can see all of their belongings and make quick decisions about what to do with them. But a company that’s joined another is almost always saddled with data that’s not so easy to categorize.

While AI may not be well suited to analyzing text-based documents, Congruity360 has developed a method for parsing text data with GPU-powered machine learning.

“GPUs are not going to operate on text,” said Chris Ryan, vice president of sales engineering at Congruity360. “We need to come up with a mathematical representation of text documents.”

Doing so has allowed Congruity360 to classify unstructured documents based on whether they look the same or contain some of the same keywords. At its essence, the company’s work involves taking data it knows nothing about — “dark data,” as Ryan called it — and assigning high-level headers so it can separate the data into buckets related to topics such as invoices, taxes, intellectual property or even code.

The result is a visual representation that groups data in topical clusters, some of which stand on their own and some of which overlap. Companies can use this method to zero in on clusters of riskier documents, such as those that have regulatory implications.

Turning Data into Useful Information

Congruity360’s approach starts with the assumption that as much as 80 percent of all corporate data is unstructured, and seeks to answer the question, how can GPUs help machine learning turn raw text into information?

Most obviously, GPUs bring speed to the equation.

“If you’re a data scientist and you want to do this, you don’t want to wait weeks and weeks for models to run,” said Jonathan Bailey, vice president of analytics at Congruity360.

Speeding up the process translates to identifying — and mitigating — risks sooner. M&A activity involves working with legal teams, which are typically most concerned with ensuring that data is defensible. Congruity360 uses GPUs to perform comparisons of documents and compute their defensibility. It’s a process took four weeks using CPUs, and now unfolds in just 20 seconds on GPUs.

“We’re just trying to give users a tool to learn about data,” said Bailey. “We want to see if there’s any risky data in there.”

The post Risky Business: Tapping AI to Assess and Limit Risk in M&A appeared first on The Official NVIDIA Blog.