Startup Weekend took place for the fourth time in Reykjavík. IIIM visiting researcher Benjamin Blumer participated in this event and we are happy to announce that his team was awarded the 1st place prize for its project “Nuus’s news”: an app for iOS that gathers news and information in one place. Similar to Spotify, but for news. Continue reading IIIM Researcher Ben Blumer Wins Startup Weekend
IIIM News
News about the institution, its research & recent advances
Everything you wanted to know about Watson from IBM
Talk on Friday the 1st of November at Reykjavík University in room V102 at 12:00-13:00
Next Friday Christopher Perrien will answer questions about Watson, IBM’s artificially intelligent computer system capable of answering questions posed in natural language. The computer system was specifically developed to answer questions on the quiz show Jeopardy!. In 2011, Watson competed on Jeopardy! against former (human) winners and received the first prize of $1 million. Continue reading Everything you wanted to know about Watson from IBM
Simulated Self-Directed Growth of Human Tissue – IIIM Open Day Presentation
In this presentation Guðrún Fema Ólafsdóttir, research assistant at IIIM, is introducing her project on simulated self-directed growth of human tissue. She aspires to create a new method for creating simulations of complex processes in the absence of a full mathematical model. Results of this project could benefit not only scientific but also medical understanding of biological processes.
This presentation is part of a series of presentations that were held on IIIM & CADIA Open Day in spring 2013. Continue reading Simulated Self-Directed Growth of Human Tissue – IIIM Open Day Presentation
IIIM & CADIA Open Day video presentation – A New Kind of AI by Dr. Kristinn R. Thórisson
During his presentation Dr. Kristinn R. Thórisson introduced the RU-led, EU-funded HUMANOBS project that produced a radically new approach to machine learning. Rooted in cybernetics, this approach allows computer agents to learn complex tasks by observation, without the detailed information needed up-front in prior approaches.