The term “machine learning” has 23 entries in the IATE database and one of the definitions in IATE is the following: “application of artificial intelligence (AI) that provides systems the ability to automatically learn and improve from experience without being explicitly programmed”. As technology evolves, we have to make sure that we understand the relevant changes in our environment. As you may know, we already take advantage of the “machine learning” technology in our smartphones.
Every day, we use many music, traffic prediction, public transportation, video, online shopping applications and social media platforms. Their main function is to “learn” from us so they can produce the perfect result. In simple words, machine learning is the general term for the process during which computers learn from data. Furthermore, machines can learn in many different ways, running different algorithms. Imagine that you feed data to a machine creating some pairs of input-output. You repeat the above step many times and eventually, the algorithm picks up a pattern between the input and output. The next time you feed it new input the machine will predict the output for you. Or, imagine that you feed it only with input, really a lot of data. Eventually, again, the algorithm clusters your data into groups and the next time you will feed it with new input, it will automatically predict to which cluster the new input belongs.
Just think of the recommendation system of Netflix, the Google map navigation or the Facebook News Feed. They know what you like, what you reject, what time you leave home and the distance between you and your destination. These apps use this kind of information to propose the perfect result for you.
Of course, the application of this high-end technology does not stop at the level of everyday use. Can you imagine how “machine learning” technology couldenvironmental protection, by analysing environmental data from thousands of sensors and sources, health care, by helping in treating patients, and so many other applications in the banking sector or home security? In anticipation of these innovations and pioneering inventions, we have to look at technology with a critical eye in order to understand the evolution and to adapt it to our needs.
IATE. https://iate.europa.eu/search/standard/result/1571229980927/1, Accessed October 22, 2019
9 Applications of Machine Learning from Day-to-Day Life, 2017, https://medium.com/app-affairs/9-applications-of-machine-learning-from-day-to-day-life-112a47a429d0, Accessed October 22, 2019
Machine Learning Basics | What Is Machine Learning? | Introduction To Machine Learning, 2018, https://www.youtube.com/watch?v=ukzFI9rgwfU, Accessed October 22, 2019
Machine learning, Wikipedia, https://en.wikipedia.org/wiki/Machine_learning, Accessed October 22, 2019
Antonia Pappa – Communication trainee at the Terminology Unit
Born in Greece in 1992. She holds a Bachelor degree of Communication, Culture and Media and she worked, for three years, for a newspaper and food magazines in Greece. Antonia is now taking a Master’s degree in International Marketing and Communication and is working her thesis about social media advertising. In her free time, she likes travelling, doing yoga and going for a walk with her dog.