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Accelerating China’s popular short video & content-based social networking app on Snapdragon
Accelerating China’s popular short video & content-based social networking app on Snapdragon
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
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.
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.
CVPR 2021 demo: Real-time neural video decoding on a mobile device
Jun 18, 2021
5:17
Webinar : Intelligence at Scale through AI Model Efficiency
Apr 8, 2021
1:01:13
Webinar: Efficient video perception through AI
Jan 22, 2021
1:02:50
NeurIPS 2020 Demo: On-device group-equivariant CNNs
Dec 3, 2020
4:11
NeurIPS 2020 Demo: Efficient semantic segmentation of high-resolution video
Dec 3, 2020
5:11
NeurIPS 2020 Demo: Neural network quantization with AdaRound
Dec 12, 2020
4:04
Webinar: Pushing the boundaries of AI research
Sep 9, 2020
1:00:23
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
The latest
Jun 18, 2021
Documents
We’re hiring.
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.
Qualcomm AI Research is an initiative of Qualcomm Technologies, Inc.
AI Model Efficiency Toolkit is a product of Qualcomm Innovation Center, Inc.
Qualcomm Innovation Center, Inc. is a wholly-owned subsidiary of Qualcomm Technologies, Inc.
©2021 Qualcomm Technologies, Inc. and/or its affiliated companies.