What you need to know about AI Computing at the Edge

March 12, 2019

I recently wrote about Artificial Intelligence (AI) and edge computing in an article for Forbes. Today, more and more data is being collected by a growing number of IoT devices and there is growing interest in edge computing. What does that mean for the enterprise, and what does the future hold for AI at the edge?

There’s room for both the cloud and the edge

In the article, I discussed how edge computing will continue to co-exist with cloud computing. The fact is, cloud computing is not going away anytime soon and there’s a time and place for both computing in the cloud and at the edge. Cloud computing has become the gold standard for enterprise computing today because it solves the problem of storing and managing all types of applications, as well as the huge volumes of data required to develop and maintain algorithms for AI apps.

At the same time, there is a growing interest in enterprise edge computing, since it makes sense to develop AI functionality closer to a data source, especially when you may need to know, and possibly act on, information in real time – and when a situation may change rapidly. For example, consider a video surveillance application where you need to be able to identify if someone is acting suspiciously or aggressively, or predict dangerous behavior based on a person’s actions.

The challenges of AI at the edge

The article also explored the challenges involved in developing AI algorithms for edge computing. In addition to the typical issues of the shortage of data scientists to program the apps and the specialized GPU servers needed to crunch the data, the limitations of edge computing make it even more difficult for AI development. IoT and other edge devices currently lack the processing power and bandwidth that is needed for this process.

So, while there may be interest in AI at the edge, there is still not a feasible way to develop it – right now, that is. Many companies are busy working on this problem and testing new solutions that are on the horizon. Yet there’s no need to wait and put your AI plans on hold — there are a lot of business problems that you can solve right now using cloud AI to move your business forward.

For additional AI insights from Wovenware, you can read: Are You Prepared for AI in 2019? Key Trends Driving its Growth and AI is All Around Us – Sometimes Without Us Even Noticing It.

 

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