3 hours ago by Aaron Dubrow A vision for urban transportation in 2030. GM-Segway EN-V Laugh (Xiao) exhibited at the Shanghai Expo 2010. Credit: Wikimedia Commons <\/p>\n
For decades, researchers in artificial intelligence, or AI, worked on specialized problems, developing theoretical concepts and workable algorithms for various aspects of the field. Computer vision, planning and reasoning experts all struggled independently in areas that many thought would be easy to solve, but which proved incredibly difficult. <\/p>\n
However, in recent years, as the individual aspects of artificial intelligence matured, researchers began bringing the pieces together, leading to amazing displays of high-level intelligence: from IBM's Watson to the recent poker playing champion to the ability of AI to recognize cats on the internet. <\/p>\n
These advances were on display this week at the 29th conference of the Association for the Advancement of Artificial Intelligence (AAAI) in Austin, Texas, where interdisciplinary and applied research were prevalent, according to Shlomo Zilberstein, the conference committee chair and co-author on three papers at the conference. <\/p>\n
Zilberstein studies the way artificial agents plan their future actions, particularly when working semi-autonomouslythat is to say in conjunction with people or other devices. <\/p>\n
Examples of semi-autonomous systems include co-robots working with humans in manufacturing, search-and-rescue robots that can be managed by humans working remotely and \"driverless\" cars. It is the latter topic that has particularly piqued Zilberstein's interest in recent years. <\/p>\n
The marketing campaigns of leading auto manufacturers have presented a vision of the future where the passenger (formerly known as the driver) can check his or her email, chat with friends or even sleep while shuttling between home and the office. Some prototype vehicles included seats that swivel back to create an interior living room, or as in the case of Google's driverless car, a design with no steering wheel or brakes. <\/p>\n
Except in rare cases, it's not clear to Zilberstein that this vision for the vehicles of the near future is a realistic one. <\/p>\n
\"In many areas, there are lots of barriers to full autonomy,\" Zilberstein said. \"These barriers are not only technological, but also relate to legal and ethical issues and economic concerns.\" <\/p>\n
In his talk at the \"Blue Sky\" session at AAAI, Zilberstein argued that in many areas, including driving, we will go through a long period where humans act as co-pilots or supervisors, passing off responsibility to the vehicle when possible and taking the wheel when the driving gets tricky, before the technology reaches full autonomy (if it ever does). <\/p>\n
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Researchers improve artificial intelligence algorithms for semi-autonomous vehicles<\/a><\/p>\n","protected":false},"excerpt":{"rendered":" 3 hours ago by Aaron Dubrow A vision for urban transportation in 2030. GM-Segway EN-V Laugh (Xiao) exhibited at the Shanghai Expo 2010. Credit: Wikimedia Commons For decades, researchers in artificial intelligence, or AI, worked on specialized problems, developing theoretical concepts and workable algorithms for various aspects of the field Continue reading