GPU Technology Conference -- To meet surging demand for expertise in the field of AI, NVIDIA (
Analyst firm IDC estimates that 80 percent of all applications will have an AI component by 2020. The NVIDIA Deep Learning Institute provides developers, data scientists and researchers with practical training on the use of the latest AI tools and technology.
The institute has trained developers around the world at sold-out public events and onsite training at companies such as Adobe, Alibaba and SAP; at government research institutions like the U.S. National Institutes of Health, National Institute of Science and Technology, and the Barcelona Supercomputing Center; and at institutes of higher learning such as Temasek Polytechnic Singapore and India Institute of Technology, Bombay.
In addition to instructor-led workshops, developers have on-demand access to training on the latest deep learning technology, using NVIDIA software and high-performance Amazon Web Services (AWS) EC2 P2 GPU instances in the cloud. More than 10,000 developers have already been trained by NVIDIA using AWS on the applied use of deep learning.
"AI is the defining technology of our generation," said Greg Estes, vice president of Developer Programs at NVIDIA. "To meet overwhelming demand from enterprises, government agencies and universities, we are dramatically expanding the breadth and depth of our offerings, so developers worldwide can learn how to leverage this transformative technology."
NVIDIA is broadening the Deep Learning Institute's curriculum to include the applied use of deep learning for self-driving cars, healthcare, web services, robotics, video analytics and financial services. Coursework is being delivered online using NVIDIA GPUs in the cloud through Amazon Web Services and Google's Qwiklabs, as well as through instructor-led seminars, workshops and classes to reach developers across Asia, Europe and the Americas. NVIDIA currently partners with Udacity to offer Deep Learning Institute content for developing self-driving cars.
"There is a real demand for developers who not only understand artificial intelligence, but know how to apply it in commercial applications," said Christian Plagemann, vice president of Content at Udacity. "NVIDIA is a leader in the application of deep learning technologies and we're excited to work closely with their experts to train the next generation of artificial intelligence practitioners."
Deep Learning Institute hands-on labs are taught by certified expert instructors from NVIDIA, partner companies and universities. Each lab covers a fundamental tenet of deep learning, such as using AI for object detection or image classification; applying AI to determine the best approach to cancer treatment; or, in the most advanced courses, using technologies such as NVIDIA DRIVE™ PX 2 and DriveWorks to develop autonomous vehicles.
To meet its 2017 goal, NVIDIA is expanding the Deep Learning Institute through:
NVIDIA is also working with Microsoft Azure, IBM Power and IBM Cloud teams to port lab content to their cloud solutions.
At this week's GPU Technology Conference, in Silicon Valley, the Deep Learning Institute will offer 14 different labs and train more than 2,000 developers on the applied use of AI. View the schedule and register for a session at www.nvidia.com/dli.
Instructors can access the DLI Teaching Kits, which also cover accelerated computing and robotics, at www.developer.nvidia.com/teaching-kits.
More information on course offerings is available at NVDLI@nvidia.com.
Certain statements in this press release including, but not limited to, statements as to the expected number of developers NVIDIA plans to train in 2017; estimates regarding applications with an AI component; AI as the defining technology of our generation; the impact of NVIDIA's Deep Learning Institute; and the offerings at the GPU Technology Conference, are forward-looking statements that are subject to risks and uncertainties that could cause results to be materially different than expectations. Important factors that could cause actual results to differ materially include: global economic conditions; our reliance on third parties to manufacture, assemble, package and test our products; the impact of technological development and competition; development of new products and technologies or enhancements to our existing product and technologies; market acceptance of our products or our partners' products; design, manufacturing or software defects; changes in consumer preferences or demands; changes in industry standards and interfaces; unexpected loss of performance of our products or technologies when integrated into systems; as well as other factors detailed from time to time in the reports NVIDIA files with the Securities and Exchange Commission, or SEC, including its Form 10-K for the fiscal period ended January 29, 2017. Copies of reports filed with the SEC are posted on the company's website and are available from NVIDIA without charge. These forward-looking statements are not guarantees of future performance and speak only as of the date hereof, and, except as required by law, NVIDIA disclaims any obligation to update these forward-looking statements to reflect future events or circumstances.
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