Translate no longer translates literally? Artificial intelligence and machine learning the answer is artificial intelligence . In recent decades, progress has been made by leaps and bounds and the challenge that scientists have set themselves is to make machines capable of learning in an automated way. What we commonly know as machine learning . This ability to learn that has been transferred to machines allows machines to analyze samples, recognize patterns of behavior and even be capable of performing predictive analysis through data collection and subsequent analysis .
Machine learning has countless practical applications. It is already used both in search engines and in medical diagnoses and even in the detection of bank whatsapp number list fraud. In the case of the google translator, the results are evident. Not only does it translate word by word, but it is also capable of performing a very specific search for it. Through mapping, it detects behavior patterns to contextualize it, analyzes which words it usually appears with and relates it to a specific context or language. All this means that the results offered by this tool are of higher quality and reliability.
Inesem business school master in machine learning, artificial intelligence and big data more information advances and new challenges advances in machine translation are linked to the richness and improvement of digital databases. But also to the ability of machines to decipher patterns and keep each search as a reference, creating their own database. A process that in the past translators had to carry out manually and then store them in their own databases and assisted translation programs . Researchers from mit and google's artificial intelligence laboratory have teamed up to develop a system that allows dead languages to be deciphered through machine learning . The idea is that words are vectors and that the relationships that exist between