Analysis of the usage of machine learning on the example of digital platforms for video distribution

Strojno učenje grana je umjetne inteligencije čiji je cilj, pomoću algoritama, procesuirati podatke na temelju prijašnjih iskustava. Pojava umjetne inteligencije u literaturi bilježi se još 40-ih godina prošlog stoljeća, a svoju pravu primjenu doživjela je 2000-ih godina pojavom interneta i društvenih mreža. U današnjem svijetu, primjena strojnog učenja uočena je u brojnim industrijama među kojima su i digitalne platforme za distribuciju video sadržaja. Jedne od najistaknutijih i najpopularnijih tvrtki koje koriste mogućnosti strojnog učenja su Netflix i YouTube. Upravo zbog algoritama strojnog učenja, njihov sadržaj je individualiziran za svakog korisnika što doprinosi samom rastu tvrtke. Mnogi korisnici vide pozitivne učinke korištenja strojnog učenja na njihovim personaliziranim profilima, u isto vrijeme mnogi su u strahu zbog narušavanja njihove privatnosti. S obzirom na učestalo poboljšanje algoritama strojnog učenja, nikad nećemo moći predvidjeti njezin maksimalni potencijal.Machine learning is a branch of artificial intelligence whose goal, using algorithms, is to process data based on previous experiences. The appearance of artificial intelligence in literature was recorded in the 40s of the last century, and it saw its real application in the 2000s with the appearance of the Internet and social networks. In today's world, the application of machine learning has been observed in numerous industries, among which are digital platforms for the distribution of video content. Some of the most prominent and popular companies using machine learning capabilities are Netflix and YouTube. Precisely because of machine learning algorithms, their content is individualized for each user, which contributes to the growth of the company itself. Many users see the positive effects of using machine learning on their personalized profiles, at the same time many are afraid of the violation of their privacy. Given the frequent improvement of machine learning algorithms, we will never be able to predict its maximum potential