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From underwear to airline tickets, Israeli startup Fetcherr harnesses AI to predict prices

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Israeli startup Fetcherr claims its artificial intelligence algorithm can provide that missing ingredient, at least when it comes to the world of pricing.


Banks Need To Do More For Millennials Desperate For Help

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Banks must embrace digital transformation to create an entirely new banking experience that meet the demands and expectations of today's Millennials. They are looking for help, and you can either jump in and provide the assistance they need... or watch them save with someone else. According to Bankrate, 24% of adults say they have no money saved for an emergency like a layoff or medical bill. Even though this is its lowest level since the survey began in 2011, a whopping 25% of Millennials say they have no emergency savings whatsoever. "A lot of Millennials have seen their parent suffer financially through the recession," explains Andrea Woroch, a consumer saving expert explains.


When a Robot Books Your Airline Ticket

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Jay Baer, a digital marketing consultant in Bloomington, Ind., spends half his time traveling on business. That means he also has to spend hours each week coordinating that travel. Help has arrived with the Pana app, which employs artificial intelligence to aid customers. Virtual travel assistant services -- some from established companies like Facebook, IBM and Expedia, and others from new entrants like Pana and HelloGbye -- are now popping up worldwide, just as major hotel chains like Starwood and Hilton are incorporating robots into their everyday operations. Many of the virtual assistant services use artificial intelligence, a branch of computer science that simulates intelligent human behavior.


ATTac-2000: An Adaptive Autonomous Bidding Agent

Kearns, M., Littman, M. L., Singh, S., Stone, P.

arXiv.org Artificial Intelligence

TAC was designed to create a benchmark problem in the complex domain of e-marketplaces and to motivate researchers to apply unique approaches to a common task. Their goals included providing a benchmark problem in the complex and rapidly advancing domain of e-marketplaces (Eisenberg, 2000) and motivating researchers to apply unique approaches to a common task. Another key feature of TAC was that participating agents competed against each other in a preliminary round and many practice games leading up to the nals. Thus, developers changed strategies in response to each others' agents in a sort of escalating arms race. Leading into the competition day, a wide variety of scenarios were possible. A successful agent needed to be able to perform well in any of these possible circumstances.