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Technology companies are always looking for the next big thing, and at Merritt Group it’s our job to be on top of the latest trends, so our clients are always one step ahead when they’re strategizing the future of their companies. For the past few years, it’s been big data — a field that’s still having a huge impact. But now, it’s deep learning.

What is deep learning exactly? Similar to machine learning, deep learning is a branch of artificial intelligence that is able to provide insights based on a data set without necessarily being programmed to do so. Deep learning takes this one step further, applying artificial neural networks to machine learning algorithms so a model can be able to essentially train itself up to be smarter.

This is a breakthrough, especially in light of how just much data companies amass these days, because we’re no longer at a place where we have the manpower to both parse through data and train up algorithms with that data at the speed a company needs to process information in real time. Additionally, much of the data that companies are tracking these days has a higher level of complexity than ever before — videos, photos, social media feeds. Deep learning can learn to interpret images and sentiments, getting better at those tasks over time, and provide enterprises information on data sets that used to be difficult to capture.

It’s fairly obvious that this emerging sector has been seen widespread adoption by tech companies like Google, Facebook and Amazon. But any business with an extremely large data set can make gains in data interpretation through deep learning.

This is why we’re seeing such big adoption across so many fields — from health care to retail, from detecting fraud in financial services to aiding in data processing for internet of things devices. Deep learning promises to be able to review medical images to detect cancer with a higher accuracy than overworked radiologists, who have only seconds to spare to review CT scans and MRIs. It can help marketers place the exact right message in front of buyers at the moment they most likely desire. And it’s starting to be applied to cybersecurity to attempt to stop cyberbreaches before they start.

This is just the tip of the iceberg for deep learning and its applications. As data sets continue to grow, this field is going to become applicable to any industry that’s struggling to gain insights through its data in real time. At Merritt Group, we expect to see more convergence from deep learning and sectors that traditionally don’t have a history of robust data science. And as models get better at natural language and recommendations, consumers are going to increasingly expect companies to have deep learning solutions to provide cutting-edge customer service. Eventually, deep learning will touch every industry, and knowing how to promote and advance these applications now will be key to tomorrow’s success.

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