Thinking Outside the Box With an AI-Enabled Network

By: Doug Bonderud| - Leave a comment

Artificial intelligence is rapidly changing the tech landscape as we know it.

“I’ve never seen a technology this powerful that’s moving as fast or is as cool,” says David Meyer, chairman of the board for OpenDaylight, a collaborative project with The Linux Foundation.

And while practical application of AI technologies at scale remain the province of big thinkers and tech disrupters, Enterprise Networking Planet notes that IT departments will empower the AI-enabled network. What does the enterprise network of the future look like in practice, and what’s the long-term business impact of thinking outside the box?

Parsing the Terms

AI is often conflated with other key concepts like machine learning and neural networks. While related, machine learning refers to the ability of computer systems to do something they weren’t originally programmed to do. Meanwhile, neural networks are digital networks modeled after the human brain in an attempt to replicate its efficiency.

According to Machine Design, AI is “usually defined as the science of making computers do things that require intelligence when done by humans.” AI networks amalgamate these ideas by offering an intelligent system that operates similarly to the human brain and is capable of learning new skills.

The Evolution of AI

As noted by New Scientist, U.K. AI firm DeepMind is looking to improve AI’s ability to evaluate the properties of one object — such as size, shape or color — compared to others around it. Already, the team has achieved 95.5 percent success in these relational challenges, which is slightly better than humans. And according to DigiTimes, tech companies are now beginning to integrate basic AI features with Internet of Things (IoT) and mobile devices to create cognitive manufacturing and end-to-end agile IoT manufacturing platforms.

Simply put, interest in AI is paying dividends, but a true imitation of the human mind — let alone an improvement on it — isn’t possible just yet.

Intelligent Networks

So, what does the future look like? According to Enterprise Networking Planet, there are three critical features that compose an AI-enabled network:

  1. Cloud Architecture: AI networks will use the cloud to easily connect with multiple end points, manage robots and learn more about its operating environment to drive efficiency.
  2. Massive Data Storage: These networks must store incoming data that’s relevant to organizational goals and effectively use this data to learn more about its operational role.
  3. High Processing Speed: Already, supercomputers such as IBM’s Watson are able to read 200 million pages of literature in mere seconds. Advanced AI networks need to collect and process information even more quickly to empower real-time decision-making — especially as these networks move into areas that involve human behavior.

Ideally, IT systems will become both self-learning and self-maintaining, able to deliver both better actionable insight and improve overall functioning to excel at their tasks. While the future hasn’t arrived quite yet, a ready-made market and significant tech investment are paving the way for the rise of an AI-enabled network.

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About The Author

Doug Bonderud

Freelance Writer

Doug Bonderud is an award-winning writer with expertise in technology and innovation. In addition to writing for Pivot Point, Security Intelligence, The Content Standard and Kaspersky, Doug also writes for companies such as McMurray/TMG and Straight North.