February 24, 2016

Top 10 Tech Trends: Advanced Machine Learning

As 2015 draws to a close, tech experts are looking to the future – and high on the list of talking points are Gartner’s Top 10 Tech Trends for 2016. But what are these innovations all about? How will they impact us and are they as important as they’re cracked up to be?

We’ll be looking at each of these much-trumpeted tech trends in turn to figure out just what kind of impact they’re likely to have over the coming year. In our last post, we analyzed the Internet of Everything; today, we look at the fifth trend on the list: Advanced Machine Learning.

What is Advanced Machine Learning?

Machine learning essentially means teaching a computer to recognize patterns and comprehend data in order to draw out useful insights. Advanced machine learning applies this analysis to multiple layers across big data sets, creating algorithms that mimic the workings of the human brain by making abstract calculations across different points in a network of connected numbers and inputs.

Called deep neural nets (DNNs), this approach to managing and processing information goes well beyond old school computing. The systems it creates can begin to perceive and learn about the world autonomously, classifying and interpreting data on their own. It’s this that makes smart machines appear to be intelligent.

What Does this Mean in Practice?

Advanced Machine Learning methodology can be used to drive a huge range of functions and programs. The capacity to run these kinds of complex, multi-layered algorithms means a computer can learn to analyze speech, pictures and video, maps and handwriting as well and cross-reference the patterns they identify with findings from big data sets from multiple sources.

This is laying the groundwork for all kinds of apps and technologies that not only handle problems and read information in ever-more impressive ways, but can also start to generate prediction models. It’s no coincidence that innovators from the most maverick Silicon Valley startups to world-leading technology corporations like Google, IBM and Facebook are all exploring, embracing and applying advanced machine learning techniques to help tackle complex problems in their fields.

What Gartner Says:

DNNs enable hardware- or software-based machines to learn for themselves all the features in their environment, from the finest details to broad sweeping abstract classes of content. This area is evolving quickly, and organizations must assess how they can apply these technologies to gain competitive advantage.”

What We Say:

As companies grapple with increasingly large data sets, advanced machine learning will be increasingly invaluable. As we talked about previously in our discussion of the Internet of Everything, we’re in an era of information overload, where the sheer amount of data available to harvest is far too onerous to handle. The businesses that will thrive are those striving the hardest to figure out how best to process data, select appropriate insights and apply these findings in actionable ways, fast tracking product development and meeting the specific needs of their client base.

By automating the process in intelligent ways, advanced machine learning will help the most ambitious organizations to do precisely that – and more. It will help to model overarching patterns and predict the future with ever-growing accuracy.

While we’re talking further ahead than 2016, there’s every likelihood that, as DNNs continue to advance, we will eventually reach a point where technologies and programs can adapt, improve and evolve by themselves, perhaps even learning to program of their own accord. Here’s hoping humans will be able to keep up.

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