The Time for Machine Learning Is Now!

Although many organizations have begun dabbling with machine learning, it’s safe to say that it’s still in the early stages of its evolution. Right now, Apple, Facebook, Google, IBM and Microsoft are pushing the boundaries of the technology.

In the months and years ahead, CIOs will face pressure to tap artificial intelligence (AI) and machine learning to push business and IT into entirely new territory.

One of the best ways to track a burgeoning technology is to follow the money. A Wall Street Journal piece notes that machine learning is now in the vision field of Silicon Valley venture capitalists. “Investors are looking for strong machine learning technology underlying the products of young companies across a range of markets,” the story points out.

Among the areas VCs are focused on: cyber-security, data center automation and infrastructure maintenance. These burgeoning technologies span tasks ranging from more effectively detecting and battling cyber-attacks to managing passwords and introducing new ways to authenticate users.

These systems, if used effectively, could trim corporate costs by 30 percent or more, according to experts.

What’s intriguing about this story—and the underlying trend—is that it offers a peek into the minds of the people looking for “the next big thing.” Obviously, if VCs are hoping to cash in on machine learning, CIOs should be paying close attention. Although most enterprises aren’t looking to fund or acquire startups, they should be thinking about how to plug in machine learning and create value through it.

Increasingly, this encompasses data streaming through e-commerce systems, websites, mobile apps, supply chains and much more—with the goals of better understanding users and delivering more tailored content. It means combining a growing tangle of digital tools, including internet of things (IoT) sensors, visual processing, speech processing, geolocation data, log files, social media streams and much more to create new data points and connect the digital dots in incredible ways.

For consumer-facing companies, it’s all about creating a more personalized and contextual experience. For industrial manufacturers, it’s about introducing far greater intelligence in systems and machines, and understanding maintenance requirements in deeper and broader ways. For others, machine learning revolves around putting big data and analytics to work in an automated way to get smarter and better at business.

Make no mistake, machine learning is about to become a lot more important. It’s about to redefine how everything—from marketing and sales to human resources to operations—takes place.


Samuel Greengard
Samuel Greengard
Samuel Greengard writes about business, technology and other topics. His book, The Internet of Things (MIT Press) was released in the spring of 2015.

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