IoT, Big Data and Machine Learning Push Cloud Computing To The Edge

“The End Of Cloud Computing” – that’s the dramatic title for a talk given by Peter Levine at a16z Summit last month. Levine, a partner at Anderssen Horowitz (a16z) VC fund, worked out his investor foresight and tried to imagine the world beyond cloud computing. The result was an insightful and fluent talk, stating that the centralized cloud computing as we know it is about to be superseded by a distributed cloud inherent in a multitude of edge devices. Levine highlights the rising forces driving this change:

The Internet of Things (IoT). Though the notion of IoT has been around for a few decades it seems it’s really taking place now, and that our world will soon be inhabited by a multitude of smart cars, smart homes and smart everything, each with embedded compute, storage and networking. Levine gives a great example of a computer card found in current day’s luxury cars, containing around 100 CPUs in it. having several such cards in a car would make it a mini data center on wheels. Having thousands of such cars on the roads makes it a massive distributed data center.

Big Data Analytics. The growing amount of connected devices and sensors around us constantly collecting real world input generates massive amount of data of different types, from temperature and pressure to images and videos. And that unstructured and highly variable data stream needs to be processed and analyzed in real time in order to extract insights and make decisions by the little brains of the smart devices. Just imagine your smart car approaching a stop sign, and the need to process the image input, realize the sign and make the decision to stop – all in a matter of a second or less- would you send it over to the remote cloud for the answer?

Machine Learning. While traditional computer algorithms are well suited for dealing with well-defined problem spaces, the real world has a complex, diverse and unstructured nature of data. Levine believes that endpoints will need to execute Machine Learning algorithms to decipher the data effectively and make intelligent insights and decisions to the countless number and permutations of situations that can occur in the real world.

So should Amazon, Microsoft and Google start worrying? Not really. The central cloud services will still be there, but with different focus. Levine sees the central cloud role in curating data from the edge, performing central non-real-time learning which can then be pushed back to the edge, and long-term storage and archiving of the data. In its new incarnation, the entire world becomes the domain of IT.

You can watch the recording of Levine's full talk here.

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