Qualcomm have been investing in Artificial Intelligence (AI) for about 10 years now. Here is what they came up with so far. In short, Smartphones and IoT devices will be running future on-device AI applications.

We envision a world where devices, machines, automobiles and things are much more intelligent, simplifying and enriching our daily lives. They would be able to perceive, reason, and take initiative actions based on awareness of the situation, improving just about any experience and solving problems that to this point we either left to the user or to more conventional algorithms. Artificial intelligence (AI) is the technology driving this revolution.  – Tony O’Connor Analyst Relations Sr. Manager at Qualcomm

In 2007 Qualcomm Research initiated first AI project and invested into Brain Corp in 2009. In 2014 Opened Qualcomm Research Netherlands and acquired Euvision. In 2016 collaboration with Google on TensorFlow acceleration begun and Facebook Caffe2 support was announced in 2017, acquired Scyfer later in the year.


Intelligent device has to be able to perceive the world using cameras, audio and other sensors, use that information to make some kind of decision, and do something. They are only really useful if they can do something about that information.

Finding a comfortable balance between what makes sense to do in the cloud and on device can give your solution a competitive advantage.

  • Automotive workloads
  • Image classification workloads
  • Photographic workloads
  • Security

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What are the drivers behind investing into development of on-device AI solutions:

  • Privacy – sensitive data that you may not want to share with the cloud.
  • Reliability and time critical safety decisions.
  • Low latency, ability to respond in designated time.

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Follow the link to watch 45min webinar explaining what applications and workloads might be possible to run on Snapdragon 845:



Contact us to hear more about enabling high performance AI workloads on mobile devices through efficient hardware, advanced algorithms, efficient software tools for training frameworks, TensorFlow and Caffe2.