Manuel Herranz was interviewed by Plazaradio for their current affairs and innovation podcast A Pie de Calle on July 14.
This time, the podcast on wheels parked up outside Innsomnia, the innovation and digitalization Hub for startups in the Valencian marina.
The episode centred on the importance of artificial intelligence in language processing and how it helps us in our daily lives.
Manuel spoke about how technology like the one developed by Pangeanic is behind the virtual assistants present in homes and all over the world. He also touched on anonymity for data protectiona, a crucial tool for today’s data-centric world.
During the interview, Manuel also talked about the important roles humans play in artificial intelligence and how algorithms are able to improve their language processing through the work of the linguist. For example, by identifying all kinds of vocabulary, synonyms and their uses in a specific language.
Haven’t listened to the whole interview yet?
Find out how Pangeanic and its unique combination of human intelligence and and technology are changing machine translation. And many other Language fields like Natural Language Processing.
Listen to the rest of the podcast now!
About Manuel Herranz, Pageanic’s CEO
With a degree in Entrepreneurship from MIT, Manuel gathered broad expertise in the automotive sector in the UK, with later work carried out in Argentina and Spain.
His background in machine translation stems from his work automating linguistic processes fo Japanese company B.I. Corp. He was European Director from 1998 to 2005. The Japanese company has since joined Pangeanic when its offices were taken over in July.
Manuel’s work has focused on the development of natural language processing technologies in order to extract knowledge in a scalable way (BigData), without linguistic barriers.
As a regular speaker at industry events, Manuel’s areas of interest include statistics, neural networks, deep neural networks, adaptive technologies, pattern recognition and deep learning applied to pattern recognition and applied deep learning.