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AI Magazine

The algorithm successfully detects and tracks 11 objects (5 teammates, 5 opponents, and 1 ball) at 30 frames a second. The algorithm determines the position and orientation for the robots. In addition, a Kalman-Bucy filter (Kalman and Bucy 1961) is used as a predictor of the ball's trajectory. This prediction is an integral factor in our robots' control and strategic decisions. Before developing strategic behaviors, the robots need a general control mechanism.


Artificial Intelligence And Big Data: Good For Innovation?

#artificialintelligence

China's 19-year-old Go player Ke Jie reacts during the second match against Google's artificial intelligence programme AlphaGo in Wuzhen, eastern China's Zhejiang province on May 25, 2017. Artificial intelligence is firmly embedded throughout the economy. Financial services firms use it to provide investment advice to customers, automakers are using it in vehicle autopilot systems, technology companies are using it to create virtual assistants like Alexa and Siri, and retailers are using artificial intelligence (AI) together with customers' prior sales histories, to predict potential purchases in the future, to name but a few examples. The potential of AI to boost economic growth has been discussed in numerous forums, including by Accenture, the Council on Foreign Relations, the McKinsey Global Institute, the World Economic Forum, and President Obama's Council of Economic Advisers, among others. The most dramatic advances in AI are coming from a data-intensive technique known as machine learning.


Video Friday: RoboCup, Drone Magic, and NotBot Is Pedro

IEEE Spectrum Robotics Channel

Video Friday is your weekly selection of awesome robotics videos, collected by your Automaton bloggers. We'll also be posting a weekly calendar of upcoming robotics events for the next two months; here's what we have so far (send us your events!): Let us know if you have suggestions for next week, and enjoy today's videos. After seeing this video, I'm convinced that RoboCup 2017 in Nagoya will be the best robot competition in the history of the universe. NASA's humanoid robots are too big and expensive to spend their time doing human-robot interaction studies, so students at Rice University built NotBot to take their place: It's not at all surprising that a human in a robot suit is much more capable than an actual robot for many (if not most) applications.


Artificial Intelligence And Big Data: Good For Innovation?

#artificialintelligence

China's 19-year-old Go player Ke Jie reacts during the second match against Google's artificial intelligence programme AlphaGo in Wuzhen, eastern China's Zhejiang province on May 25, 2017. Chinese netizens fumed on May 25 over a government ban on live coverage of Google algorithm AlphaGo's battle with the world's top Go player, as the programme clinched their three-match series in the ancient board game. Artificial intelligence is firmly embedded throughout the economy. Financial services firms use it to provide investment advice to customers, automakers are using it in vehicle autopilot systems, technology companies are using it to create virtual assistants like Alexa and Siri, and retailers are using artificial intelligence (AI) together with customers' prior sales histories, to predict potential purchases in the future, to name but a few examples. The potential of AI to boost economic growth has been discussed in numerous forums, including by Accenture, the Council on Foreign Relations, the McKinsey Global Institute, the World Economic Forum, and President Obama's Council of Economic Advisers, among others.


esig

AAAI Conferences

Models of physical systems can differ according to computational cost, accuracy and precision, among other things. Depending on the problem solving task at hand, different models will be appropriate. Several investigators have recently developed methods of automatically selecting among multiple models of physical systems. Our research is novel in that we are developing model selection techniques specifically suited to computer-aided design. Our approach is based on the idea that artifact performance models for computer-aided design should be chosen in light of the design decisions they are required to support. We have developed a technique called "Gradient Magnitude Model Selection" (GMMS), which embodies this principle. GMMS operates in the context of a hillclimbing search process.