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The Future Of … AI

Mobile Chip Leader’s AI Starts in Mobile and Grows to the Cloud Cloud

Company acquires assets of Twenty Billion Neurons GmbH to strengthen its AI team.

Qualcomm Technologies (QTI) is hosting a series of webinars titled “The Future of…”, and the most recent edition is about AI. In this lively session, I hosted a conversation with Ziad Asghar, QTI VP of Product Management, Alex Katouzian, QTI SVP and GM Mobile Compute and Infrastructure, and Clément Delangue, co-founder and CEO of open source AI model company Hugging Face, Inc. I also wrote a short research paper on the company’s AI strategy, which can be found here at Cambrian-AI, where we outline some impressive AI use cases.

Qualcomm Technologies increases AI capabilities.

Qualcomm believes AI is evolving exponentially thanks to billions of smart mobile devices connected by 5G to the cloud, fueled by a vibrant ecosystem of application developers armed with open-source AI models. Other semiconductor companies might say something similar, but in Qualcomm’s case, it starts uniquely with mobile. The latest Snapdragon 888 has a sixth-generation AI engine powerful enough to handle key AI models on the phone, enabling applications such as on-device speech processing and even real-time spoken language translation. Qualcomm complements the edge devices with cloud processing using the Cloud AI100, which recently demonstrated industry-leading performance efficiency on the MLPerf V1.0 benchmarks. Qualcomm calls this approach Distributed Intelligence.

Qualcomm provides a tightly coupled network of AI processors in the cloud, edge cloud and… [+] endpoints on the device.


To add more talent and IP to Qualcomm’s AI research lab, the company announced today that it has acquired a team from Twenty Billion Neurons GmbH (TwentyBN), including their high-quality video dataset widely used by the AI ​​research community. The founding CEO is Roland Memisevic, who co-directed the world-renowned MILA AI Institute with Yoshua Bengio of the Université de Montréal.

Mobile AI is here today

While few smartphone users realize they use AI every time they take a photo, even fewer understand that AI helps them stay connected. QTI integrates AI into both applications, such as computational photography and precise voice interaction, as well as the operation of the mobile handset itself, optimizing 5G to increase the range of the network, and power management to extend battery life. Here are a few excerpts from the “The Future Of…” session.

Alex Katouzian comments: “What we’re doing strategically is using our largest channel, which is mobile, to create inventions that spiral and are reused in adjacent markets with the same mobile properties. For example, PCs and XR or car. And then also in some of the infrastructure-based designs, because AI can be used in edge cloud, in some private network environments.”

Ziad Asghar notes, “We took our family tree, which is amazing energy efficiency, and applied it to AI processing. We took that from mobile, took our lessons and applied it to the cloud. If you look at what some of the Seeing major platforms these days, there’s a huge power consumption problem where power consumption basically doubles every year on the cloud side, so what we did was we used our AI expertise, developed a new architecture and came up with a product that specifically is designed for inference, which has given us the ability to deliver a level of performance that no one else can.”

Clément Delangue of Hugging Face believes Transfer Learning will be the next big thing in AI. “I think in five years most of the machine learning models out there will be transfer learning models. And that’s super exciting because they have new capabilities, but also new capabilities for them to be smaller, more compressed, to to be trained on smaller data sets, thanks to the unique features and capabilities of transfer learning.”


Qualcomm is one of the few, if not only, semiconductor companies to offer AI engines in both mobile edge processing SoCs and cloud servers. With over a decade of experience in mobile and now data center AI, the company is in a unique position to build for the future:

Powerful AI engines that transparently support ubiquitous AI-powered functions on consumer mobile platforms. An ecosystem of development software and partners that leverage the AI ​​engines to create valuable new applications using AI models. An energy-efficient server platform that leverages the mobile technology and application stack to provide high-performance cloud services. A technology roadmap driving ever-increasing AI performance on the device and in the cloud.

We believe this comprehensive strategy, combined with leadership performance and energy efficiency, will position Qualcomm well for significant growth in AI.

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