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Edging AI Into Our Lives

AI, artificial intelligence, edging, edging AI, online courses, data analysisWith the growth of the Internet of Things (IoT), artificial intelligence (AI) is already part of our daily lives. It’s a key component of our smartphones, our GPS systems, our personal digital assistants and more. Future growth depends on reducing latency and increasing bandwidth and privacy. That’s where edge computing comes in.

Coming to the Edge

Companies entrenched in AI, such as Google, Amazon and Apple, are working to make devices perform even faster and more securely with edge computing. Edge computing allows the work to be performed closer to where it’s created so that data can be analyzed in near real time. This reduces latency by eliminating the trip all the way to the cloud and back. Apple’s iPhone already does this, sending you from your cell phone store out into the world with a device equipped to recognize your face and voice without sending messages to the cloud and waiting for a reply.

For those who own an Amazon Echo device, you may not realize that your requests are resolved in the cloud. Amazon is rumored to be working on building AI chips for the Echo, which would allow Alexa to more quickly analyze information and get answers. Local processing done by Amazon will lead to quicker replies and increased privacy for the consumer.

One area in which edge computing is absolutely essential is in self-driving vehicles. For this technology to take off, local computing is a necessity. Your trip wouldn’t survive the latency of feeding all the numerous sensors of a self-driving vehicle to the cloud and back. Latency, privacy and bandwidth issues would be detrimental to this technology.

Security Concerns

Some argue that edge computing is more secure because it’s not traveling over a network. The less personal data that’s stored in a corporate data center or cloud environment, the less vulnerable that data is if one of those environments is compromised.

Others believe that edge devices themselves are more vulnerable. Apple offloads a majority of security concerns from the centralized cloud to user devices by doing encryption and storing biometric information on the device. Data encryption, access control and use of virtual private network tunneling are important elements in protecting edge computing systems.

Train Your Entire Workforce

Edge computing in the IoT is the key to growth for companies invested in AI. Get the foundational knowledge you need to take your organization to the next level with the Artificial Intelligence and Ethics in Design course program, a series of on-demand training courses for professionals working in engineering, IT, computer science and related fields across all industries. 

Resources

Butler, Brandon. (21 Sept 2017). What is edge computing and how it’s changing the network. Network World.

Miller, Paul. (7 May 2018). What is edge computing? The Verge.

Lynley, Matthew. (12 Feb 2018). Amazon may be developing AI chips for Alexa. TechCrunch.

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