Welcome to the QDN blog! We regularly post blogs on a wide array of topics for our developers. From AI, gaming, XR, robotics, IoT, Snapdragon tools, and even 5G. Scroll down to see our most recent posts, and review our Blog Topics in the right navigation.
In his recent webinar, Accelerating Distributed AI Applications, Ziad Asghar, our Vice President, Product Management, Qualcomm Technologies, Inc., gave an insightful and pragmatic overview where distributed AI is today and the Snapdragon® mobile platforms behind it.
Let’s take a quick look at some of the key highlights and insights from the webinar and resources that developers can use to build distributed AI solutions today.
Even with a well-designed app and a robust marketing campaign, you can always do more to reach your target level of success. That’s why many developers outside of game development are now using gamification in their apps to further build their user base while increasing user engagement and retention.
Centralized machine learning (ML) is the ML workflow that most of us are familiar with today, where training is allocated to powerful servers which update model parameters using large datasets. The trained model may then be deployed to edge devices over the cloud for inference at the edge, or edge devices may collect and send data to the server for inference and receive back the server’s prediction(s).
Opinions expressed in the content posted here are the personal opinions of the original authors, and do not necessarily reflect those of Qualcomm Incorporated or its subsidiaries ("Qualcomm"). The content is provided for informational purposes only and is not meant to be an endorsement or representation by Qualcomm or any other party. This site may also provide links or references to non-Qualcomm sites and resources. Qualcomm makes no representations, warranties, or other commitments whatsoever about any non-Qualcomm sites or third-party resources that may be referenced, accessible from, or linked to this site.