Content & Social Media Manager
According to the Statista’s report ‘What part of your IT budget for 2017 is earmarked for machine learning?’, 26% of businesses surveyed indicated that more than 15% of their IT budgets went on developing machine learning solutions. A figure that already points to an exponential growth in the next five years.
In view of this data, the following question might come to your mind… what is so special about this technology?
The more data we feed the algorithm with, the better, because it will gain greater experience, learning for itself.
Siri & Cortana
Speech recognition systems use machine learning and other technologies, such as neural networks and natural language processing (NLP), in order to imitate human interaction. As they progress, they learn to understand the nuances and semantics of our language.
The speech recognition training process entails different techniques, and the level of complexity depends on its nature (from templates that are adapted to human behavior, like Siri, to the ability to understand jokes through dynamic learning, like Cortana).
Another interesting example is the facial recognition algorithm of Facebook. If you use it on a regular basis, you must have realized that before you can tag friends in a photo Facebook got in ahead of you and identified them. This is a form of adaptive technology in which the algorithm memorizes those patterns that characterize the people you have tagged in the past.
Still on the field of Social Media, Facebook is not the only one using this technology to improve its services. Pinterest also makes use of machine learning to enhance its user engagement by delivering more accurate results, in which it prioritizes local interests and personal tastes and habits according to the interactions recorded.
Since Google is one of today’s biggest data collectors with its search service, how could it not be using a technology such as learning machine? The company uses machine learning algorithms in almost all its services, the most famous of all being the search engine optimization based on an intuitive neural network that is able to identify the intention of users’ requests.
Apart from Google Search, other products apply this technology; like Gmail, which applies it to its “Smart Reply” and mail classification services, or Google Maps, which uses algorithms to identify street names and numbers based on photographs taken by the Street View vehicles, which help the app improve its results.
PayPal uses machine learning algorithms to detect and combat fraud by analyzing large amounts of data from clients, whom it classifies by their activity categorizing the risks of their transactions.
Netflix has used learning machine for years for its very well-known recommendation and personalization system. In recent years, this content distributor has started to further apply learning machine to new applications, such as content marketing, price model, programmatic marketing, effective content delivery…An authentic bet on this technology that has led it to value the ROI of its algorithms at $1 billion per year.
Machine learning is an essential part of Uber’s business model, which uses these algorithms to predict and determine the arrival time of its vehicles and the prices for each ride, as well as for its food service. This is possible thanks to an exhaustive analysis of data collected from previous rides (duration, route, cost, preparation and delivery time, etc.).
If you aren’t hooked on Spotify’s “Discover Weekly” yet, you must be one of the few… The music company uses different recommendation models based on the analysis of your activity and the rest of its users’ activity but also based on the analysis of texts and audios that identify other users’ tastes that might be similar to yours.
The giant Amazon is another company using machine learning algorithms to improve its services. Particularly, in its search engine, in which the products catalog is organized according to customers’ preferences, in its recommendation system, based on other customers’ interests, and as a fraud-prevention system for the credit card payment service.
As you can see, the versatility of this technology makes it applicable to almost every industry. Thinking about what it can do for your business? Learn more about our product Terminus7, aimed to develop Artificial Intelligence and Machine Learning solutions for businesses.
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