Automatic translation emerged in the 1960s. It was developed by humans and its main purpose was to produce first-draft translations to be later improved on by human translators.
In the 1990s, MT based on statistical models started being used. While this was a major advance, errors were still very significant. As a consequence, this method became intertwined with the previous one, creating more popular machine translation that came to be used worldwide.
Recently, in 2017, machine translation had a huge breakthrough thanks to the use of artificial intelligence through the application of neural networks and ai translation.
Statistics and probability in translation are therefore a thing of the past. At present, an AI translator runs a neural and artificial computer process based on how neurons in the human brain are interconnected to obtain reasoning and analysis that resembles
that of a person.
For language learning, or in any other area, machine translation in AI entails a number of advantages:
Of course, there are always disadvantages, especially since this neural method in AI translation still needs further testing and a more complete database. Some of these disadvantages are:
It should be kept in mind that AI machine translation is based on human reasoning, but does not possess the ability to understand the emotional or cultural meaning of expressions. For example, the translation of ironic sentences is not usually very successful.
The breakthrough in the processing methods performed by an AI translator has generated several current technologies. Their usage includes:
More and more companies and sectors are joining AI translation services. Do you know the most typical uses in machine translation? We show it in this list:
AI translation has brought with it great advances for the development of technologies that benefit us all, for language learning and for the understanding of any type of content anywhere in the world.
Consequently, the various technologies employing AI translation are advantageous both for reinforcing learning within a classroom and for self-learning.
But while the future of AI language translation may be evolving, the truth is that it still does not surpass the power of analysis, creativity, socialization, and understanding and expressing emotions that the human brain possesses.
Perhaps, in the future, an autonomous intelligence will be developed… Or maybe the human brain is insurmountable.
The truth is, AI translations still require human supervision. And in teaching, the presence of educators who help understand everything that builds a language beyond its words is essential.