The place occupied by Natural Language Processing (NLP) companies on the technological landscape is increasingly prominent. In addition to being reflected in the demand for these services by diverse organizations, this technology continues to gain prominence in events of maximum relevance and in projects launched from public institutions. In February, we have an unbeatable example of how the two areas above go hand in hand.

This is the language technology ‘Hackathon’ organized by Red.es, the public agency responsible for innovation programmes in the telecommunications and information society field. This is the second event in this initiative that takes place as part of 4YFN (4 Years From Now), the platform dedicated to startups at the Mobile World Congress in Barcelona. This is where the final phase of the competition will take place on 27 February.

This event is designed to encourage the development of prototypes of solutions with specific functionalities based on different language technologies, and where Natural Language Processing occupies a prominent role. We are therefore faced with an ideal opportunity to encourage more people to explore the possibilities of developing a career in this field and contributing to the technological evolution of the NLP. In this second year, a separate category has been introduced as a new feature, especially dedicated to applications in health and biotechnology areas.

An application based on NLP technologies did in fact win the event last year: TextDigester, a prototype created by Francesco Ronzano that generates automatic summaries in different languages based on digital text analysis in HTML, XML or JSON formats.

It is worth mentioning that Serimag will be present at the great Barcelona technology event, since we will be one of the fifty companies with their own stand at the MWC’s Spanish Pavilion. There we will present the technological solutions developed by our team and which we are making available to our customers, integrating the benefits of Natural Language Processing together with Machine Learning and Computer Vision.