If you’re like most people, chances are you didn’t always get what you wanted for Christmas when you were growing up. A wool sweater is no substitute for a bike, but you have to give your parents credit for keeping you warm during harsh winters.
Today, knowing what your kids want under the tree is as easy as watching the trends. Or, you can enlist the help of a supercomputer that can do that for you. One example is Watson, IBM’s machine learning effort that can reveal insights from unstructured data and tell you what’s hot and what’s not, using natural language processing.
Harnessing the collective knowledge of billions of people on the planet and tailoring that data to provide shopping insight is no walk in the park, even for Big Blue’s supercomputer. The challenge is not collecting the data, but understanding it. Specifically, the nuances of natural language that humans exercise both verbally and virtually. Watson, according to its makers, is up to the task.
Machine learning has been around for a while, but Watson has an ace up its sleeve that other computers don’t. It learns like a human. It understands things like context, tone, and meaning, and can condense this understanding into actionable insights. If it sounds crazy, consider this. Your kids use social media to share what they like or comment on what they don’t like, every day. Their timeline is their wish-list as well as their credo. All you have to do is decode it.
For now, machine learning can only make shopping recommendations that may or may not be 100% in line with your family’s passions and desires. It calls to mind a crime-prediction tool portrayed by Sci-Fi that may, or may not draw the future before it happens. The question is, do we really want to trade possibility for probability?