Over 2017, Nvidia is looking to boost the number of developers using its Deep Learning Institute (DLI) throughout the year to hit its target of 100,000, a tenfold jump from its 2016 numbers.
Speaking at the GPU Technology Conference in San Jose, Greg Estes, Nvidia vice president of developer programs, told journalists the beginning courses would be free, and the more advanced courses would cost $30. Courses range form online self-teaching, all the way to a five-day onsite course for autonomous vehicles.
To boost its training numbers, the chip manufacturer is porting DLI to Microsoft Azure and IBM Cloud, as well as training instructors from Hewlett Packard Enterprise and Microsoft.
"They are going to help us expand our reach, and if you think about it, it makes a lot of sense. Because these companies are much bigger than we are, and they have a lot of worldwide reach," Estes said.
"If we take our knowledge and expertise, and we work with these other companies, they can help bring that out into the community — it's a win for everybody."
Estes said Nvidia is on its way to formal competence certification.
"Today when you go through and you take these learning courses, we give you a certificate that you have attended the course, but we don't have the testing at the end to certify competence — that is on our roadmap and we plan to do that this year," he said.
The DLI subject matter covers frameworks including Caffe2, Microsoft CNTK, MXNet, Tensorflow, and PyTorch.
Estes told TechRepublic that the content is a mix of collaborating with framework makers, and Nvidia's own content.
Earlier on Monday, Nvidia unveiled Metropolis, a video analytics platform for monitoring smart cities. Backed by Jetson TX2 as the edge device, and Tesla GPUs in the datacentre, Nvidia is betting on predictions there will be over a billion cameras throughout cities by 2020.
"Nvidia's end-to-end Metropolis platform can be applied to video streams to create smarter and safer applications for a variety of industries — from transportation to commercial," said Shiliang Pu, president at Hikvision Research Institute, one of 50 partners Nvidia worked with.
"The benefit of GPU deep learning is that data can be analysed quickly and accurately to drive deeper insights."
- Understanding the differences between AI, machine learning, and deep learning (TechRepublic)
- Your life in AI's hands: The battle to understand deep learning (TechRepublic)
- Caffe2: Deep learning with flexibility and scalability (ZDNet)
- IBM, NVIDIA partner for 'fastest deep learning enterprise solution' in the world (TechRepublic)
Disclosure: Chris Duckett attended GTC as a guest of Nvidia
Some would say that it is a long way from software engineering to journalism, others would correctly argue that it is a mere 10 metres according to the floor plan.During his first five years with CBS Interactive, Chris started his journalistic adventure in 2006 as the Editor of Builder AU after originally joining the company as a programmer.Leaving CBS Interactive in 2010 to follow his deep desire to study the snowdrifts and culinary delights of Canada, Chris based himself in Vancouver and paid for his new snowboarding and poutine cravings as a programmer for a lifestyle gaming startup.Chris returns to CBS in 2011 as the Editor of TechRepublic Australia determined to meld together his programming and journalistic tendencies once and for all.In his free time, Chris is often seen yelling at different operating systems for their own unique failures, avoiding the dreaded tech support calls from relatives, and conducting extensive studies of internets — he claims he once read an entire one.