Hey-Olly

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City: London

State: England

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Country: United Kingdom

Founded in London, UK in 2014, Emotech is the world&s;s first AI company dedicated to exploring proactivity and multimodality in robotics and emotion AI. Their vision is improve the relationships between humans and technology. They believes as robots populate their lives, they must be built to be empathetic, promoting balanced lifestyles, through innovative, efficient interactions. Their first product, four time CES Innovation Award-winning Olly, is world’s first robot with individual personality. The company brings together more than 30 top artificial intelligence scientists, engineers, designers, etc., including experts of the well-known team Google DeepMind, outstanding doctoral students and postdoctoral fellows in artificial intelligence at many top universities, e.g. UCL, Imperial College, the School of Computer Science of Carnegie Mellon University. John Shawe Taylor, head of computer statistics and machine learning at the University of London and one of Europe’s most prestigious professors of computer science, was also invited to become an advisor for the project. Emotech not only has excellent and innovative product design concepts, but also ranks first in the world in core artificial intelligence technology. As one of a very few teams in the world that has multimodal integration of voice and computer vision technology, Emotech has a number of world&s;s best technologies and a number of international patents in this area. For example, rivaling Google and Microsoft’s world’s most advanced speech recognition technology, Microsoft&s;s world-leading voiceprint identification technology surpasses Adobe&s;s world&s;s most advanced rotoscoping technology, as well as IBM Waston&s;s world&s;s most advanced character analysis algorithms, and has won numerous awards at the world&s;s top artificial intelligence conference. Such as Visual Object Tracking Challenge 2016 Best realtime tracker (Published in CVPR2016), IEEE ICRA 2015 Best Computer Vision Paper Award Finalist, IEEE SLT 2014 Best Paper, etc.

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