The Future of Mobile Computing

被引:1
|
作者
Gehlhaar, Jeff [1 ]
机构
[1] VP Technol Qualcomm Technol Inc, San Diego, CA 92121 USA
关键词
Artifical intelligence; sensor future; mobile computing; brain inspired computing; machine learning; neural networks; power efficient; embedded computing;
D O I
10.1145/2639108.2639417
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
Jeff Gehlhaar, VP of Technology for Qualcomm Technologies, Inc. will discuss the future of mobile computing which will entail a much more personalized user experience. As the world continues to shift towards a more connected world, people are using their mobile devices in new ways and having higher expectations of what they can do with those devices. This is leading to the next frontier of mobile being much more personalized with mobile devices becoming extensions of the user, understanding where you are, where you've been and what you want to do or act on next. This is also resulting in services and applications that have traditionally been delivered via the cloud, migrating to mobile which present unique challenges and opportunities in mobile. In this talk we will explore the new and exciting technologies that Qualcomm Research is working on to advance the frontier in personalized devices and help solve some of these challenges. Starting with always on sensor processing that make basic predictions about where you are and what actions you are performing, to research in brain inspired computing and embedded cognition, Qualcomm is working to make devices which are always with you, smarter and truly personal. To further this vision of transforming the future of mobile computing, Qualcomm Research has also been working in the area of brain inspired computation and neural networks for a number of years. Early work has focused on biologically inspired approaches, involving spiking neural networks and understanding the complex behaviors of the brain. Recent advances in the industry around deep neural networks have resulted in state-of-the-art performance in machine learning pattern matching tasks. As mobile SOCs continue to gain significant computational power, bringing applications powered by deep learning to mobile devices is becoming possible. We will explore the near term opportunities like object recognition, scene classification, applications for smarter mobile cameras, automotive, and robotics. We will also look at other aspects of brain inspired computing including the potential of a new kind of low power hardware. Join Jeff as he shares his insight on how Qualcomm Research has been spearheading research to make future mobile devices smarter with the ability to "sense" and "see" their environment as humans do in a power efficient manner.
引用
收藏
页码:53 / 53
页数:1
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