One of the greatest and most uncharted technological advancements in the past decade has been the rise of machine learning. In a small scale sense, machine learning is simply a program or device that can recognize patterns and messages from the data in which they’re collecting and learn from it. On the larger scale, machine learning will take data collection and other important functions that computers are used for to the next level, and perhaps one in which we need to manually operate less and less.


There are many forms of machine learning that are being used now. So well, in fact, that it almost seems like it’s nothing complicated at all. According to tech data group SAS, machine learning is everywhere already. Recommendations prompted by Netflix after you just watched your favorite show or items you might be interested in prompted by Amazon after you’ve made a purchase are actually some of the earliest forms of machine learning in our technologically advanced world. Twitter has employed aspects of machine learning in their analytics tools. Many fraud detection cases are recognized by machine learning as well, prompting us that account activity is off or unrecognizable.


Some of the newest advancements in machine learning are coming in the forms of recognizing context. This is a step up from simply recognizing patterns; this is taking patterns and recognizing how they could correlate to a situation. Businesses around the world have even begun using this in their customer service practices.


While personal and data security has enjoyed a nice bump in safety through machine learning, things will be elevated in 2017 and beyond. Forbes recently published an article discussing how security will play an impact with machine learning and pointed out a few interesting points about security as it’s protected now. From their findings, almost all malware codes used now to protect data are only about 2-10% different from the version it previously upgraded from. With newer machine learning, anomalies in malware data findings can be reported in order to predict security breaches and not just when one happens. With so much to detect – hundreds of thousands of new malware files arise every day – machine learning will be crucial.


Machine learning is going to be used in so many unique forms that it’s difficult to write about all of the exciting new uses without writing a book! Over the next few months, stay tuned to my blog to see my take on new advancements in technology, wins and losses in the machine learning community, and what all of this means for our daily lives.