NVIDIA looks to train 100,000 developers to meet demand for AI expertise

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In a move to address surging demand for expertise in the field of Artificial Intelligence (AI), NVIDIA has announced that it plans to train 100,000 developers IN 2017, a tenfold increase over 2016, through the NVIDIA Deep Learning Institute.

According to market research from the analyst firm IDC, around 80 percent of all applications will have an AI component by 2020.

The NVIDIA Deep Learning Institute looks to provide developers, data scientists and researchers with practical training on the use of the latest AI tools and technology and has trained developers around the world at numeorus public events and provided onsite training at companies such as Adobe, Alibaba and SAP as well as at government research institutions and at institutes of higher learning such as the Temasek Polytechnic in Singapore and the India Institute of Technology.

“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.”

As well as instructor-led workshops, NVIDIA provides on-demand access to training on the latest deep learning technology, using the company’s 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.

NVIDIA is also looking to broaden 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.

The Deep Learning Institute uses 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.

NVIDIA is also working with Microsoft Azure, IBM Power and IBM Cloud teams to port lab content to their cloud solutions.