Our third regional GPU Technology Conference in as many weeks reached another packed house today, as NVIDIA co-founder and CEO Jen-Hsun Huang unveiled technology that will accelerate the deep learning revolution.
“GPU computing is at the beginning of something very, very important, a brand new revolution, what people call the AI revolution, the beginning of the fourth industrial revolution,” Huang told a crowd of 1,600 scientists, engineers, entrepreneurs and press, gathered at Amsterdam’s gleaming waterfront music hall. “However you describe it, we think something really big is around the corner.”
In the latest stop in a tour that will bring GTC to eight cities around the world, Huang unveiled Xavier, our next-generation system-on-a-chip for powering self-driving cars; announced an agreement with TomTom, the Dutch mapping and navigation group, to use AI to create a cloud-to-car mapping system for self-driving cars; detailed our DriveWorks Alpha 1 release, and highlighted the work we’re doing with some of Europe’s most innovative startups and research labs.
In the previous two weeks, Huang spoke at regional GTCs in Beijing and Taiwan that each drew crowds of more than 2,000. He described how GPUs are transforming AI in just five years from an ambitious university research project into a $500 billion industry that touches broad aspects of everyday life.
The biggest news: Xavier, an all-new SoC based on our next-gen Volta GPU, which will be the processor in future self-driving cars. Xavier features unprecedented performance and energy efficiency, while supporting deep-learning features important to the automotive market. A single Xavier-based AI car supercomputer will be able to replace today’s fully configured DRIVE PX 2 with two Parker SoCs and two Pascal GPUs.
“This is the greatest SoC endeavor I have ever known, and we have been building chips for a very long time,” Huang said. “Just imagine what an autonomous vehicle can do in the near future with Xavier.”
Huang also detailed the Alpha 1 release of our DriveWorks software, which incorporates a number of new modules, including support for free space detection — which helps self-driving cars determine where it’s safe for cars to drive; distance detection; lane detection; and 3D bounding boxes, which determine the size and shape of objects around the car.
Huang showed how a new neural network, PilotNet, will enable the handling of more challenging situations, such as construction sites, night driving and foul weather. Another neural network, OpenRoadNet, will enable free space computation and enable the creation of the occupancy grid to help cars determine where they can safely drive.
“Together we will work as an industry to move autonomous driving forward, this is going to be an area of research and development for years to come,” Huang said. DriveWorks Alpha 1 will be released to early partners in October.
Mapping the Road Ahead
Huang also announced global navigation powerhouse TomTom will port and run localization and mapping software on DRIVE PX 2 AutoCruise. In addition, our NVIDIA DriveWorks software will integrate support for TomTom’s HD mapping environment.
TomTom is working to create high-definition maps of the world’s driveable roads, and it’s an incredible challenge. “You want to localize your car with a centimeter of accuracy, because you don’t want to miss by 20 centimeters when you have a self driving car,” explained Alain De Taeye, of TomTom’s management board.
“People used to believe creating navigable maps was unaffordable, now people believe HD maps, which are very detailed, very accurate is unaffordable — it’s not: you need to be clever about it and use AI and AI platforms to automatically create and maintain them,” De Taeye said.
From Research Labs to Startups
AI computing is also sweeping through Europe’s world-leading research centers, technology companies and thriving startup scene. Huang announced two of Europe’s top AI research centers will collaborate with NVIDIA to ramp up their efforts in the fast-growing field.
The German Research Center for Artificial Intelligence and Switzerland’s Dalle Molle Institute for Artificial Intelligence will both be early users of the new NVIDIA DGX-1 AI supercomputer.
Huang also announced that software powerhouse SAP is now using DGX-1 AI supercomputers at its operations in Potsdam, Germany, and in Israel, where teams are building machine learning solutions for enterprises.
“Now with the partnership of SAP we will soon have applications running on these servers to serve the world’s largest enterprises,” Huang said.
Over the last two months, DGX-1 has been adopted by AI labs around the world, including those based at UC Berkeley, Stanford University and OpenAI.
DGX-1 packs some 170 teraflops of computing power, equal to 250 conventional servers, into a single box. It uses eight NVIDIA Pascal powered Tesla P100 accelerators, interconnected with high-speed NVIDIA NVLink technology, and includes a range of deep learning frameworks (see “Blood, Sweat, and 120 Billion Transistors: How NVIDIA Built DGX-1”).
Huang also called out four European startups — among the more than 1,500 worldwide — that are using GPU-powered AI.
BenevolentAI, our first DGX-1 customer in Europe, is using AI to help medical professionals understand the vast amounts of medical research published every year.
Smilart is using GPU-powered AI to analyze faces, even if their appearance has changed, or if an image is captured in low light or from a challenging angle.
Intelligent Voice uses AI to not only recognize speech, but distinguish between speakers and even detect a speaker’s emotions.
Sadako Technologies uses AI to train robots to sort trash. So far it has saved more than 60,000 tons of plastic from going to landfills.