Qualcomm reveals deep learning SDK for devices powered by Snapdragon 820 SoC

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Aware that its future in mobile SoCs and baseband silicon will always be threatened by the race to the bottom and the rise of the Chinese vendors, Qualcomm is turning its IP powerhouse’s attention to new areas – as an attempt to hedge against a future in which it is not the number one name in mobile processing.

Qualcomm has revealed a deep learning SDK for devices powered by its Snapdragon 820 SoC. Called the Snapdragon Neural Processing Engine, and unveiled at the Embedded Vision Summit, the SDK is an attempt by Qualcomm to entice automotive, industrial, and IoT developers to its Snapdragon SoC platform.

There’s huge potential in these markets for Qualcomm, and the new SDK follows its other drone and industrial hardware development kits into the market that is aiming to create new ecosystems and devices as part of the Internet of Things (IoT), and its Industrial IoT subset. With enterprise customers realizing the potential of drones and automation to increase their profit margins, the coming few years will be pivotal for Qualcomm, as it tries to transition its smartphone knowhow into a profit-making entity inside the complex devices that comprise the IoT.

Based on the neuromorphic Zeroth Machine Intelligence Platform, Qualcomm’s equivalent to IBM TrueNorth neurosynaptic chips, the kit aims to bring the hardware-specific functions of those brain chips to a more general purpose Snapdragon platform – so that mobile devices can leverage the incredible potential of silicon that acts in the same manner as a human brain.

While IBM is planning on shipping its brain chips to end-customers, who will put them to use in servers, the Qualcomm approach currently relies on software to bring those capabilities to a much more adaptable chipset – one that can be used in mobile devices.

Notably, Qualcomm has moved away from its initial plans to create this functionality in hardware. Back in May 2014, when Qualcomm first introduced the Zeroth project, the goal was to build a Neural Processing Unit that would be a hardware module for its advanced SoCs. There were rumors that it would be a standard component of the 820 chipset, but there’s no sign of it in the spec sheet.

Machine learning is central to the evolution of the IoT. There simply aren’t enough engineers to monitor and manage the billions of devices that are expected to be deployed. There aren’t enough developer resources to teach image recognition to camera systems, or collision avoidance to autonomous cars, and so the machines have to be able to evolve from a base-level intelligence installed in the factory, and adapt to the dynamic world around them.

Read the source article at Rethink Wireless