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Qualcomm is no stranger to the world of artificial intelligence (AI) on its silicon. But for the most part, Qualcomm’s AI efforts have been somewhat bespoke and specific for certain parts of its technology stack.

That situation is changing today, with the announcement of the Qualcomm AI Stack. The new offering is intended to be a unified platform that brings together Qualcomm’s various AI software tools into a single stack that spans its portfolio. The goal of the Qualcomm AI Stack is to continue to meet the specific needs of the various industry verticals that Qualcomm serves, while making it easier for developers to benefit from a single stack.

In a briefing with press and analysts, Ziad Asghar the vice president of product management at Qualcomm Technologies, explained that some organizations want to use AI across multiple product lines. With the Qualcomm AI Stack, Asghar said an organization can take an AI model built for one vertical — a mobile use case, for example — and then use the same model for another deployment, such as an edge network or even an automotive deployment. In the past, that might have been a challenge, as the different use cases rely on different Qualcomm hardware, which didn’t all previously support the same AI stack.

“We think with the Qualcomm AI stack, we are enabling developers and OEMs [Original Equipment Manufacturers] to be able to do so much more with the AI capability that we’re baking into our devices,” Asghar said.

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One AI stack for many Qualcomm products

Recently, Qualcomm has been releasing a steady stream of hardware and software designed to accelerate AI.

Qualcomm’s mobile chip is the Snapdragon, which integrates hardware acceleration capabilities for AI. The Qualcomm XR platform, on the other hand, is intended for virtual and augmented reality applications that also benefit from AI. The company has also taken aim at edge AI and robotics as well. 

“We have now made this leap, where essentially the same offering is able to cover each and every business line that we have today,” Asghar said.

The overall market for AI-optimized silicon is large and growing. According to Verified Market Research, the AI chip market is forecast to generate up to $202 billion in revenue by 2030, growing significantly from the $10 billion in revenue generated in 2021.

Qualcomm AI engine direct

The Qualcomm AI Stack provides support for multiple AI frameworks, including the open-source TensorFlow PyTorch and ONNX. The step below the common AI frameworks is where the Qualcomm AI Engine Direct technology now comes into play across Qualcomm’s portfolio.

Asghar explained that the Qualcomm AI Engine Direct is for developers that want to more directly benefit from the silicon capabilities that Qualcomm hardware enables. AI Engine Direct will directly run software compilers, programming languages and math libraries, as well as profilers and debuggers. AI Engine Direct also supports multiple operating systems including Android, Windows, Linux and even QNX for automotive.

The ability to support the various capabilities that developers might need to enable an AI application is important, but there is more that is required to successfully deploy and run AI. One of the tools in the Qualcomm AI Stack is the AI model efficiency toolkit, which has several components. One is the ability to compress a model down from something that might have been trained in the cloud onto something that can run in an embedded device in a kitchen.

Ashghar also highlighted Qualcomm’s Neural Architecture Search capabilities that have been developed with Google. He explained that Neural Architecture Search enables more accuracy and lower latency to run models, even on lower power devices.

“I think hardware is of course critical, but increasingly AI software is absolutely critical,” Ashghar said. “We’ve made very large investments to be able to make this AI stack, the best in class, AI stack for the intelligent edge.”

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