AI and Networks

How AI is Poised to Be the Ultimate Network Management Tool

Artificial intelligence (AI) will transform everything. That’s the buzz these days, and it’s not just hype. Technology advances forward, and with the widespread integration of smart tech, wireless connections, and the Internet of Things (IoT), AI is positioned to bring it all together into a sophisticated network unlike anything seen before.

Why AI Has So Much Potential

To understand what AI can do, one first has to understand what it is: AI is a neural network approach to programming and problem-solving. Neural networks used within the tech are modeled after the way the human brain works. Instead of a step-by-step, linear algorithmic approach to problem-solving, neural networks consist of nodes–analogous to brain neurons–with multiple connections to other nodes. The approach has been around for decades, but now hardware technology has caught up with the concept.

Today, promising AI works on a multi-layered neural network. In this scenario, one layer processes information through input and analyzes it for predictive results. If the results succeed, the information is passed to the next layer for analysis, much like a neuron fires a synapse to communicate with another neuron. This layering gives rise to the concept of “deep learning”, meaning how deep the layers are in the application.

AI is initially trained via human input, but once it begins to process, it can actually teach itself to produce more efficient analysis faster and more accurately. The exciting implications of AI are based on its potential to create new solutions that we humans have not thought of or are only in the beginning phases of understanding.

The Impact of AI on Networking

Once the stuff of science fiction, AI has arrived with real-world applications. Major companies like Google and Apple have deployed products using AI neural networks, from the iPhone X’s facial recognition feature to Google’s upgraded version of Translate called Neural Machine Translation.

From a network engineering point of view, AI has the potential to manage networks with speed and precision as well as integrate consumers into broader information and service networks. Doing so creates pathways for a new style of customer experience strategy that moves beyond mobile and into the real world.

Data transfer across wired and wireless infrastructure can be monitored for improvements and trouble-shooting at exponentially faster rates than an experienced network specialist. The need for human interaction will remain, but it will be deployed in more efficient ways. Instead of spending time, for instance, determining the source of a network issue, AI will likely zero-in on the issue quickly, leaving IT staff to handle the resolutions.

Consumer Demand Will Drive AI Growth

For consumers, the unifying aspect of AI network management will not only improve human and tech interaction, but also be able to handle the explosive growth of data traffic. The IoT world of interconnected consumer products and services continues to grow. As these devices and services become more integral to everyday life, users will demand speed and accuracy along with the convenience of integrated systems.

AI will also become more closely linked to predictive user interface applications. Everything from shopping to healthcare to financial management, which is already using machine learning algorithms, will take a leap in accuracy and data management with the added layer of anticipating needs and wants on an individual basis. Access to these services will also move beyond localized use to anywhere in the world.

The future impact of AI on networks is only now being explored. As AI proves–and improves–itself, innovations in networks themselves will likely come from AI-driven applications. With more AI integration, industries will also start to rethink their business models to exploit the coming efficiencies and invest in new applications with more granularity, more precise predictive applications, and solutions to business and structure issues that have not even been considered yet.

Post: 2018-01-25 22:22 by Serena Garner, Y Media Labs

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