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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).
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