Artificial Intelligence Research

Qualcomm AI Research

At Qualcomm AI Research, we are advancing AI to make its core capabilities – perception, reasoning, and action – ubiquitous across devices. Our mission is to make breakthroughs in fundamental AI research and scale them across industries. By bringing together some of the best minds in the field, we’re pushing the boundaries of what’s possible and shaping the future of AI.

Qualcomm AI Research Introduction

Jun 8, 2018

2:27

“Machine learning algorithms such as deep learning already use large amounts of energy. And with AI increasingly moving to power-constrained edge devices, energy efficiency will only become more important. The benchmark that matters will be how much intelligence one can squeeze out of every joule of energy. I believe that Qualcomm is uniquely positioned to address this problem and be a key player in AI.”

- Professor Dr. Max Welling
VP of Technology, Qualcomm Technologies Netherlands B.V.

Leading research and development across the entire spectrum of AI

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Our key AI research areas

Computer vision

Efficient architectures and algorithms for understanding images and videos.

Radar and RF sensing

Understanding the world through deep learning applied to RF signals.

Power efficiency

Model design, compression, quantization, neural architecture search (NAS), compiler algorithms, and efficient hardware.

Machine learning fundamentals

Foundational AI research like quantum, geometric, and Bayesian deep learning.

Speech, audio, and language processing

Keyword detection, speaker verification, speech recognition, sound detection, and contextual awareness.

Data compression and generative modeling

Learning low-dimensional representations for data such as video and speech.

Personalization and federated learning

Continuous learning, model adaptation, and privacy-preserving distributed learning.

Optimization and reinforcement learning

Learning to optimize through supervision, reinforcement learning, and Bayesian optimization.

AI Research Papers

Novel papers are one of the ways Qualcomm Technologies contributes impactful research to the larger community of AI research. Below are papers that Qualcomm AI Research has written or co-authored.

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Computer vision

Data compression and generative modeling

Machine learning fundamentals

Optimization and reinforcement learning

Personalization and federated learning

Power efficiency

Radar and RF sensing

Speech, audio, and language processing

Open source project: AI Model Efficiency Toolkit (AIMET)

Qualcomm Innovation Center open sourced AIMET, which includes state-of-the-art quantization and compression techniques. The goal for this open source project is to collaborate with other leading AI researchers, provide a simple library plugin for AI developers, and help migrate the ecosystem toward integer inference.

Learn more about AIMET

Join the AIMET GitHub project

Learn more about AIMET Model Zoo

Check out the AIMET Model Zoo GitHub project

Webinar: Efficient video perception through AI

Jan 22, 2021