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

Our key AI research areas

Power efficiency

Model design, compression, quantization, activation, algorithms, and efficient hardware. 

Personalization

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

Efficient learning

Robust learning through minimal data, unsupervised learning, and on-device learning.

System architecture

Multi-task and multi-modal learning, sensor fusion, and cloud-edge systems.

Webinar: Enabling power-efficient AI through quantization

May 1, 2020

1:01:18

Webinar: 5G+AI: The Ingredients Fueling Tomorrow's Technology Innovations

Feb 19, 2020

58:52

AI Research Video

Dec 6, 2019

2:46

Leading research and development across the entire spectrum of AI

Download the presentation

Watch the webinar

AI Research Papers

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

Efficient Learning

Power Efficiency

Personalization

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.

The latest

Press Note

May 10, 2020

Qualcomm Addresses Growing Demand for 5G by Announcing New Snapdragon 768G Mobile Platform
Qualcomm Addresses Growing Demand for 5G by Announcing New Snapdragon 768G Mobile Platform
Qualcomm Addresses Growing Demand for 5G by Announcing New Snapdragon 768G Mobile Platform
Qualcomm Addresses Growing Demand for 5G by Announcing New Snapdragon 768G Mobile Platform
Qualcomm Addresses Growing Demand for 5G by Announcing New Snapdragon 768G Mobile Platform
Qualcomm Addresses Growing Demand for 5G by Announcing New Snapdragon 768G Mobile Platform

Documents

Presentation: Enabling power-efficient AI through quantization
May 1, 2020
5G+AI: The Ingredients for Next Generation Wireless Innovation
Feb 19, 2020

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Are you a machine learning specialist eager to start a new challenge and have a global impact on the industry? Come join us as we make AI breakthroughs.

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References to "Qualcomm" may mean Qualcomm Incorporated, or subsidiaries or business units within the Qualcomm corporate structure, as applicable.

Qualcomm Incorporated includes Qualcomm's licensing business, QTL, and the vast majority of its patent portfolio. Qualcomm Technologies, Inc., a wholly-owned subsidiary of Qualcomm Incorporated, operates, along with its subsidiaries, substantially all of Qualcomm's engineering, research and development functions, and substantially all of its products and services businesses. Qualcomm products referenced on this page are products of Qualcomm Technologies, Inc. and/or its subsidiaries.

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