People are now more accustomed to artificial intelligence than earlier. Currently, AI is used in every platform ranging from supercomputers present in the defense and aerospace sector to a simple YouTube algorithm. The use of AI is unparalleled and various companies like Google, Amazon and Facebook, are constantly innovating new AI-based platforms to further diversify its uses.
But startups like Unbabel, play the role of a dark horse by making some significant ripples in the AI space. Recently, the company was in the spotlight when it closed a Series C round for $60 million, led by Point72 Ventures.
According to credible cites, the funding round saw active participation from Greycroft, Indico Capital Partners and e.ventures. Reportedly, the latest round brings its total funding to $91 million, which consists the $23 million from 2018’s Series B funding round.
Commenting on the recent developments, Sri Chandrasekar, Partner, Point72 Ventures, said that the company is impressed with the human-in-the-loop translation tech developed by Unbabel and is inspired by its vision to offer enterprise-level translations at just a click of a button.
Chandrasekar added that the group believes that the AI startup has the potential to transform the translation industry, and it is looking forward to conducting a successful business. Earlier in May, the company made headlines when it bagged the ‘shared task’ event at WMT19, a prominent machine translation symposium, making it the world’s leading translation-as-a-service firm.
For the record, WMT19 a yearly competition where QE (Quality Estimation) systems from numerous participants, both industry and academic side, are assessed and judged on the same data, to determine the candidate that is the most accurate at automatically assessing machine translation quality.
João Graça, CTO, Unbabel, stated that it is great news for the company, which is extremely proud of the team that helped it regain its title at WMT19. Additionally, this showcases the company’s constant hard work with regards to machine translation and quality estimation.