NATICK, Mass., July 15, 2020 -- MathWorks announced that a comprehensive "Deep Learning with MATLAB" course is now available, developed in …

Nvidia sales executive Kevin Connors says channel partners play an important role in the chipmaker's strategy for selling and supporting GPU-accelerated solutions for artificial intelligence -- a market that is still in its early stages and can provide the channel major growth opportunities as a result. "People are wanting higher performance computing at supercomputing levels, so that they can solve the world's problems, whether it's discovery of the next genome or better analysis and other such workloads," Connors, Nvidia's vice president of sales, global partners, said in an interview with CRN. The Santa Clara, Calif.-based company's GPUs have become increasingly important in high-performance computing and artificial intelligence workloads, thanks to the parallel computing capabilities offered by their large number of cores and the substantial software ecosystem Nvidia has built around its CUDA platform, also known as Compute Unified Device Architecture, which debuted in 2007. "As a company, we've always been focused on solving tough problems, problems that no one else could solve, and we invested in that. And so when we came out with CUDA -- which allowed application developers to port their high-performance computing apps, their scientific apps, engineering apps to our GPU platform -- that really began the process of developing a very rich ecosystem for high-performance computing," said Connors, who has been with Nvidia since 2006.

Kicking off the Washington edition of our GPU Technology Conference, Buck, NVIDIA's VP for accelerated computing, detailed a new generation of technologies that will help companies put modern AI to work. Buck also announced that the United States Postal Service -- the world's largest delivery service, with 146 billion pieces of mail processed and delivered annually -- is adopting end-to-end AI technology from NVIDIA. "The challenge is how do we take AI from innovation to actually applying AI," Buck told an audience of more than 3,500 developers, CIOs and federal employees at the three-day GTC DC. "Our challenge, NVIDIA's challenge, and my challenge is'How can I bring AI to industries and activate it.'" Over the course of his hour-long talk, Buck explained how modern AI is trained and deployed, and described how NVIDIA is adapting AI for the automotive, healthcare, robotics, and 5G industries, among others. The U.S. Postal Service offers a glimpse at what's possible. Buck said the U.S. Postal Service will roll out a deep learning solution based on NVIDIA EGX to 200 processing facilities that should be operational in 2020.

In the past DIY (do-it-yourself) was usually a scissors and glue or hammer and nails affair. Today, as artificial intelligence (AI) continues to transform how we work, learn, and live, AI is becoming increasingly accessible to non-experts and even beginning to transform our hobbies. Cait Etherington – When most of us think about AI, we don't think about DIY. Can you first tell us a bit about Jetson Nano? What is it and how does it make AI a DIY affair?

Millions of people are using modern AI every day, even if they don't know it. It's saving lives with semi-autonomous drones that help first responders locate survivors of natural disasters. These and many other AI-powered capabilities would've seemed like magic just a few years ago. But with the rapid pace of innovation, how does one "get smart" on where AI is headed next? The GPU Technology Conference is known as the world's premier AI conference for a reason: Over the course of a few days it offers everything described below: research and news, businesses and startups, networking and coursework.

That was the message one young officer gave Lt. General John "Jack" Shanahan -- the Pentagon's director for defense for warfighter support -- who is hustling to put artificial intelligence and machine learning to work for the U.S. Defense Department. Highlighting the growing role AI is playing in security, intelligence and defense, Shanahan spoke Wednesday during a keynote address about his team's use of GPU-driven deep learning at our GPU Technology Conference in Washington. Shanahan leads Project Maven, an effort launched in April to put machine learning and AI to work, starting with efforts to turn the countless hours of aerial video surveillance collected by the U.S. military into actionable intelligence. "We have analysts looking at full-motion video, staring at screens 6, 7, 8, 9, 10, 11 hours at a time. They're doing the same thing photographic interpreters were doing in World War II," Shanahan said.

December 21, 2017: Business Wire India NVIDIA brought together the best minds in research, academia and industry across Hyderabad, Chennai, Mumbai, Pune, Delhi and Bangalore 42 speaker sessions from leading experts in fields such as computer vision, sensor fusion, software development, regulation and HD mapping provide expertise NVIDIA today completed its first edition of Developer Connect 2017 in Bangalore. The six-city developer roadshow witnessed over 5,000 attendees who experienced some of the highest quality workshops and demonstrations of AI and deep learning tools, designed to meet the challenges big data presents. Attendees got a closer look at NVIDIA's DGX systems, as well as the opportunity to learn more about its new Volta architecture. Both the DGX-1 and DGX Station were on display to demonstrate the full power of these AI supercomputers. The concluding segment witnessed prominent speakers from organizations such as Ola, Cognitive Computing, Microsoft, Hewlett Packard Enterprise Labs, Shell India, Sony India and Aditya Imaging Information Technologies provide their views.

Roundup It's been an interesting fortnight, sorry, two weeks in AI. In addition to what we've already reported, we have news about HPE developing what looks like a neural network accelerator chip, TensorFlow updates, Google's effort to teach software to make software, and other bits and pieces. The next biz in line claiming to be working on developing a fast custom-designed chip supposedly for neural networks is HPE. It was first reported on our sister site, The Next Platform, this week, although there are scant details on how the hardware works, its specs or even if it can deal with stuff like deep learning. That's mainly because our colleagues got wind of the secret R&D effort before it was due to be made public, and the enterprise IT giant is keeping schtum for now. The mysterious chip's "dot product engine" (DPE) architecture is apparently geared toward carrying out matrix operations at speed, which is useful for executing AI algorithms quickly.

NVIDIA (NVDA) is moving fast in its mission to make AI (artificial intelligence) affordable. The company is expanding its efforts to create more AI researchers and developers through its DLI (Deep Learning Institute). Don't miss the next report. You are now receiving e-mail alerts for new research. A temporary password for your new Market Realist account has been sent to your e-mail address.

Pentagon official: AI and machine learning to revolutionize the US intelligence community 2. How AI could spot lung cancer sooner – and save lives 3. AI researchers can now access optimized deep learning framework containers in the cloud 4. AI4ALL improves student access to AI resources through NVIDIA partnership 5. READ BLOG 6. HOW AI COULD SPOT LUNG CANCER SOONER – AND SAVE LIVES Lung cancer is the most common cancer worldwide. More than 80 percent of people with lung cancer die within five years of being diagnosed, and half die within a year. H. Michael Park, co- founder of startup Innovation DX, is working to improve those odds. In December, his St. Louis-based medical analytics company plans to release its first product -- a GPU-accelerated AI system that detects lung cancer in its early stages from a simple chest X-ray. "Lung cancer is so deadly today because it's diagnosed so late. READ BLOG 7. AI RESEARCHERS CAN NOW INNOVATE IN MINUTES, NOT WEEKS, WITH NVIDIA GPU CLOUD NVIDIA announced the NVIDIA GPU Cloud (NGC), a cloud-based platform that gives developers convenient access – deskside or the cloud -- to a comprehensive software suite for harnessing the transformative powers of AI. Jim McHugh, vice president and general manager of DGX Systems at NVIDIA, shared: "We're designing a cloud platform that will unleash AI developers, so they can build a smarter world.