AI and Machine learning use cases
Machine learning is a hot topic right now and for good reasons: it is a big step in how computers are able to learn. A machine learning algorithm uses a set of given data to answer different questions. For example, you can provide the network with a group of images, and then classify them with “this is a car” and “this is not a car”. Every time you show the computer a new set of photos it will automatically find elements according to those categories. In time it gets smarter and better at identifying and completing tasks.
But, is that all machine learning can do? Of course not! There are a lot more domains that use this sort of technology to solve specific tasks. Below I will give you some examples of use cases that will make you think of how incredible this technology is.
As you may know, malware is a growing and concerning problem today. In 2016, Kaspersky Lab detected 8,526,221 malicious installation packages only on mobile devices. Try to imagine how much new malware are created every year for all devices. But other researchers found that every new malware contains between 2 and 10 percent code variation, which means that the rest of it is identical to the previous version. By using machine learning patterns, we could find errors quickly, and treat security issues in a fraction of time it took yesterday.
Machine learning can spot patterns by processing information that humans cannot. One study used computer technology to helps radiologists detect small breast cancers, that could otherwise be missed. The computer spotted 52 percent of the cases, more than a year before the official diagnoses. The same algorithm has been used to identify a set of variables to predict diabetes.
As we are evolving, other ways of fraud are discovered. But machine learning is also getting better and better which means it can identify this kind of potential cases. PayPal, for instance, is using this technology to fight money laundering. The organization compares millions of transactions and can distinguish between legitimate and fraudulent operations.
Personalized marketing strategy
The more you understand your public, the better you can satisfy them with your products or services. You most likely had the experience to visit a particular website and then see web ads with the same products you previously clicked. That’s just one example of how machine learning is present in marketing, it might seem similar to technology you have seen in the past, the difference is the recommendations are so much more accurate and the decisions are being made in real time. Intelligent machine learning analyzes and compares your activity with other consumers, and this way it can determine what you would like to buy or see. The technology is getting better and can recognize if you buy certain things as gifts and not for yourself.
This information is only the tip of the iceberg, a great example of how machine learning is being used in our daily lives. What other ways of using machine learning are you excited about?
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