niagara fall
Artificial Intelligence Used to Analyze Opinions Through Brain Activity
Chris Aimone co-founded Muse with an ethos to create technology that expands our perspective of ourselves and the world around us. An artist and inventor at heart, Chris' creative and design practice has spanned many fields, including architecture, augmented reality, computer vision, music and robotics. Looking to bring innovative new experiences to life, Chris has built installations for the Ontario Science Centre and contributed to major technology art projects featured around the world (including Burning Man). Can you share with us how your love of Robotics and Brain-Machine Interfaces (BMI) began? When I was very young, instead of playing with popular/trendy children's toys, I was interested in tools – so much so, that my favorite book was actually a catalogue of tools (at 18 months) and I wanted a sewing machine for Christmas when I was 3. I was interested in what tools could do – how they could extend my reach into the impossible, and my love for robotics and BMI was simply an extension of that. I was so curious about what lay just beyond the limits of my body's capabilities, just beyond the range of my senses.
Niagara Falls on Mars?
NASA has released an image from one of its Mars rovers which shows a part of the red planet where ancient lava behaved once like liquid water. The government agency has dubbed it the "Niagara Falls of Mars." Thanks to the Mars Reconnaissance Orbiter (MRO), NASA has a 3D image of the northern rim of a 30-kilometer crater on the western part of the Tharsis volcanic province. The image shows that the lava surrounded the crater rim, ultimately breaching the crater rim at four locations to produce lava falls, one in the northwest and the rest in the north. "In a close-up image the rough-textured lava flow to the north has breached the crater wall at a narrow point, where it then cascades downwards, fanning out and draping the steeper slopes of the wall in the process," NASA said in a statement on its website.
The Crazy, Amazing Life Of Immigrant Nikola Tesla
The guitarist of the band'Lightningfan' Wang Hongbin (C) creates lightning with a Tesla Coil in a village outside of Fuzhou in China's Fujian province in June 2013. The Tesla Coil invented by Nikola Tesla in 1891 is a transformer that produces vast amounts of voltage at high frequencies that creates long bolts of electricity like lightning. Nikola Tesla was one of America's greatest inventors and carries a mystique unlike any other immigrant to the United States. Before he became the name of a car company and a character in modern science fiction novels, Nikola Tesla immigrated to the United States and turned into an inventor extraordinaire. Tesla is credited with many important innovations and his ideas are still talked about today.
Experimental Assessment of Aggregation Principles in Argumentation-enabled Collective Intelligence
Awad, Edmond, Bonnefon, Jean-François, Caminada, Martin, Malone, Thomas, Rahwan, Iyad
On the Web, there is always a need to aggregate opinions from the crowd (as in posts, social networks, forums, etc.). Different mechanisms have been implemented to capture these opinions such as "Like" in Facebook, "Favorite" in Twitter, thumbs-up/down, flagging, and so on. However, in more contested domains (e.g. Wikipedia, political discussion, and climate change discussion) these mechanisms are not sufficient since they only deal with each issue independently without considering the relationships between different claims. We can view a set of conflicting arguments as a graph in which the nodes represent arguments and the arcs between these nodes represent the defeat relation. A group of people can then collectively evaluate such graphs. To do this, the group must use a rule to aggregate their individual opinions about the entire argument graph. Here, we present the first experimental evaluation of different principles commonly employed by aggregation rules presented in the literature. We use randomized controlled experiments to investigate which principles people consider better at aggregating opinions under different conditions. Our analysis reveals a number of factors, not captured by traditional formal models, that play an important role in determining the efficacy of aggregation. These results help bring formal models of argumentation closer to real-world application.