Intel bets on AI, partners Preferred Networks for open source deep learning

Intel and Japan-based Preferred Networks have announced a collaboration that will focus on the development of Chainer, an open source Python-based deep learning framework developed by the Preferred Networks.

The partnership, announced at Intel’s Tokyo AI Day, aims to boost the performance of deep learning applications on Intel’s products and forms part of Intel’s strategy for gaining ground in the artificial intelligence (AI) space. The collaboration will also focus on easing AI development and affordability, with results of the collaboration published on Intel’s GitHub repository.

Chainer was made open-source in June 2015 and the framework has since been adopted for the development of deep learning in both research and real-world applications. The framework will utilize Intel’s open source library – Intel Math Kernel Library and Intel Math Kernel Library Deep Neural Network as a fundamental building block.

“We believe in an open, standards-based ecosystem,” shared Intel’s senior director for AI products Nidhi Chappell (pictured), who added that HPC use cases in the academic community have contributed significantly to the development of AI.

Intel is investing heavily in AI across several verticals, including financial services, healthcare, retail and manufacturing.  The chipmaker recently formed a new AI business unit and its AI portfolio currently includes its Xeon and Xeon Phi processors, Arria 10 FPGAs and deep learning technology Nervana, which the chipmaker acquired last year.

The chipmaker maintains a bullish outlook on AI, betting that the technology will eventually account for one of the largest workloads in corporate data centers. “The nature of AI requires that training be done both at the edge and in the data center,” said Chapelle. “Many of our customers do not wish to share their data on the public cloud, so deep learning will still be kept on premise.”

An October 2016 report from research firm IDC estimates that the widespread adoption of cognitive systems and AI across various industries will drive revenues from nearly $8 billion in 2016 to more than $47 billion in 2020. IDC expects cognitive/AI solutions is expected to experience a compound annual growth rate of 55.1% between 2016 – 2020.