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Apple Makes Push to Live Life on the Edge of AI

January 23, 2020

As Kara Kennedy, market director at G2, noted over two years ago:  

"Edge computing is evolving around the developing need to move much of the processing nearer to IoT sensors themselves to decrease that latency and improve efficiency."

What is edge computing?

Edge computing is a mesh network of data centers which process and store data locally prior to being sent to a centralized storage center or cloud. Edge computing optimizes cloud computing systems to avoid disruptions or slowing in the sending and receiving of data.

Last week, we saw just how serious Apple is about making this a reality. The company acquired Xnor.ai, a startup focused on on-device AI, for a cool $200 million. Founded in 2017, Xnor.ai was born inside the Allen Institute for Artificial Intelligence, a startup incubator founded by Microsoft cofounder Paul Allen.

Although Apple has not revealed its big plans for how the company will leverage Xnor.ai’s technology, we can think of a couple of exciting frontiers.  

Better, faster, stronger AI

There are two key ways that Apple can incorporate this technology into its broader tech stack, providing users with a quicker, more powerful product. 

  1. Siri out of the cloud: Currently, to interact with Siri, users must be connected to the internet. When a user speaks to Siri, their voice data is transferred to the cloud and a (hopefully) desired output is returned. Incorporating Xnor.ai’s technology can sidestep the cloud and process the data on a user's device. 
  2. Quick, clear camera clicks: A great camera is now considered a must-have on smartphones. Ken Hyers, a director at Strategy Analytics, notes that Xnor.ai's technology can significantly improve the iPhone's camera by analyzing users' photos and making on-the-fly, AI-powered enhancements to them.

Another upside of the above is data privacy. Processing voice and image data locally allows one to feel safe and secure that their data is in their own hands and not that of a large corporation. 

For another approach to edge computing for AI, have a look at Google’s Coral project, a complete toolkit to build products with local AI.

“Coral is a platform of hardware and software components from Google that help you build devices with local AI — providing hardware acceleration for neural networks ... right on the edge device.”
Vikram Tank, product manager at Coral

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