Sunday, 30 April 2017

Qualcomm, Facebook take aim at mobile machine learning

By Nick Wood, Total Telecom
Thursday 20 April 17

Companies collaborate to reduce reliance on cloud-based data-processing.

Qualcomm was confirmed this week as working with Facebook to equip devices with machine learning capabilities. The world's biggest social network announced at its F8 conference on Wednesday that it is open sourcing Caffe2, its deep learning toolkit…

Qualcomm was confirmed this week as working with Facebook to equip devices with machine learning capabilities.

The world's biggest social network announced at its F8 conference on Wednesday that it is open sourcing Caffe2, its deep learning toolkit, giving developers and the like a software development kit (SDK) for building apps and devices that use AI.

"Most of the attention around machine learning technology has involved super-fast data processing applications, server farms, and supercomputers. However, far-flung servers don't help when you're looking to magically perfect a photo on your smartphone, or to translate a Chinese menu on the fly," Qualcomm said on Thursday. "Making machine learning mobile — putting it on the device itself — can help unlock everyday use cases for most people."

With that in mind, Qualcomm is collaborating with Facebook to optimise Caffe2 for its Snapdragon neural processing engine (NPE) framework.

"The NPE is designed to do the heavy lifting needed to run neural networks efficiently on Snapdragon, leaving developers with more time and resources to focus on creating their innovative user experiences," Qualcomm said.

The mobile chip maker plans to launch an SDk for its neural processing engine later this summer.

"We don't yet know the full range of applications for the technology, but we can't wait to see how it's used by innovative developers around the world," the company said.

Qualcomm also on Thursday published its financial results for the three months to 31 March.

Fiscal second quarter revenue was down 10% year-on-year to $5 billion (€4.65 billion), while operating income fell 48% to $700 million. Net income fell to $700 million from $1.2 billion a year earlier.

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