Qualcomm unveils ‘AI Stack’ portfolio to unify mobile, automotive, IoT and other devices

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Mobile and IoT chip giant Qualcomm announced Wednesday an extension of its AI developer runtime offering, called the Qualcomm AI Stack portfolio, which the company says will address the “unique AI needs for each industry sector” that Qualcomm’s chips serve, including mobile phones, connected infrastructure in Internet of Things facilities and connected vehicles.

The software integrates existing tools, such as the company’s Neural Processing SDK, while allowing developers to “leverage that same work on every product.”

“We are extending a technology roadmap across all of our different lines of business,” Qualcomm vice president of product management Ziad Asghar said during a press briefing. “The stage function here is being able to take your work and transfer it to these different business areas.”

The software stack emphasizes energy efficiency, such as how to quantify workloads and code portability across the many hardware targets of Qualcomm and its customers.

On the efficiency side, “the performance per watt we’re showing is just outstanding in terms of the amount of work we can do for a given amount of energy,” Asghar said. “Even for the same hardware, as we optimize the software, we’re able to get 30% to 40% better performance in some cases.”

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Asghar said the ability to handle many contexts is the main virtue.

“Some of the environments are very focused on their end markets – on automotive or cloud,” Asghar noted.

“It’s the best in class experience for what you can get from our hardware, that’s the unique advantage,” he said.

“It will allow you to get the most optimized and best experience from an efficiency and accuracy perspective, so we think that’s a huge differentiation for us and our partners.”

One of the goals of the technology is for customers to be able to tune machine learning performance based on different criteria, Asghar said.

“For this application, latency is very critical, you need to have the ability to optimize for that, whereas for this application, latency is more important, or accuracy – you can make those trade-offs with the stack we offer , then leverage that work everywhere.”

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