GTC 2017: Nvidia aims to spread knowledge of Deep Learning

  • 10 times training increase from previous year to meet surging demand for AI expertise
  • Collaborates with institutes of higher learning and companies to train more experts

 

GTC 2017: Nvidia aims to spread knowledge of Deep Learning

 

ARTIFICIAL intelligence (AI) is capable of helping humans in many ways. From being able to identify potentially dangerous objects left in public spaces and policing company networks from cyber-attacks to analysing videos to prevent objectionable content from being uploaded.

According to analyst firm IDC, 80% of all applications will have an AI component by 2020.

The reality is that there is a surging demand for expertise in the field of AI developers and experts trained in the field of deep learning. But at present, there are just not enough experts in the field to fill this demand.

Recognising that there is a gap in talent, Nvidia announced plans to train 100,000 developers this year which is a tenfold increase over last year, through its Deep Learning Institute (DLI) which provides developers, data scientists and researchers with practical training on the use of the latest AI tools and technology.

“It is not just about learning the theory but it is getting in and working with the latest GPU technology, manipulating neural networks to be used in areas like automotive and healthcare,” explained Nvidia’s vice president for developer programmes Greg Estes (pic, above).

For the uninitiated, Deep Learning is the fastest-growing field in Machine Learning and uses many-layered Deep Neural Networks (DNNs) to make sense of data such as images, sound and text.

Being at the forefront in the field of AI and Deep Learning puts Nvidia in a good position to spread this knowledge to developers.

 

GTC 2017: Nvidia aims to spread knowledge of Deep Learning

 

Nvidia said its institute has trained developers from around the world at sold-out public events and onsite training at companies such as Adobe, Alibaba, SAP; government research institutions like the US National Institute of Health and at institutes of higher learning such as Temasek Polytechnic, Singapore and India Institute of Technology, Bombay.

“AI is the defining the technology of our generation,” Estes stressed.

“We are dramatically expanding the breadth and depth of our offerings so developers worldwide can learn how to leverage on this transformative technology.”

Nvidia said it is broadening DLI’s curriculum to include the applied use of Deep Learning for self-driving cars, healthcare, web services, robotics and video analytics.

Coursework is delivered online using Nvidia’s GPUs in the cloud through Amazon Web Services and Google’s Qwiklabs, as well as through instructor-led seminars and workshops.

Expert instructors from Nvidia, partner companies and universities teach the hands-on labs, covering the fundamental tenets of Deep Learning such as using AI for object detection or image classification, applying AI to determine the best approach to cancer treatment or using Nvidia Drive PX2 and DriveWorks to develop autonomous vehicles.

He adds that the introductory courses will be offered for free and those seeking to take advanced courses will have to pay US$30.

“We believe there is real value in our content. While we don’t believe in giving away that knowledge for free, at the same time we are not out to make a profit from this. We want to make it inexpensive and accessible for anyone who wants to learn about DL,” said Estes.

At Nvidia’s eighth annual GTC in San Jose, Deep Learning Institute will offer 14 different labs and train more than 2,000 developers on the applied use of AI.

In the coming days, DNA will cover the latest announcements from Nvidia at the conference including the keynote address by the company’s chief executive officer and founder Jensen Huang on the third day of the conference.

Chong Jinn Xiung reports from GTC 2017 in San Jose, at the invitation of Nvidia. All editorials are independent.

 

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