British Airways is experimenting with a new tool for guiding passengers through its massive London Heathrow hub: guide robots. Starting in 2020, the flag carrier of the United Kingdom will deploy an array of autonomous robots in Terminal 5 of its London Heathrow base to help guide passengers through the airport and answer basic questions. The problem is harder to solve than it may initially sound. Getting around Heathrow requires deep knowledge of the dozens of storefronts, duty-free shops and lounges in the terminals as well as the ability to navigate through multiple floors and throngs of passengers who may not always be paying attention to their surroundings. To help guide passengers, the new robots will not only have to know where they are at all times but also be able to navigate through the airport without getting lost or running into travelers.

BRITISH Airways has announced its plans to cut delays with the help of artificial intelligence. Passengers travelling through Heathrow Terminal 5, the airline's base in London, will be among the first to notice the difference. There are 18 different activities that need to be completed before a plane can depart before its next flight and most of them start once the previous load of passengers have disembarked. It includes everything from cleaning the cabin to loading and unloading catering and luggage. As Sun Online Travel previously revealed, this turnaround process can be extremely tight - with just 45 minutes for short haul journeys on smaller planes - meaning every second counts.

Accurate time-series forecasting is vital for numerous areas of application such as transportation, energy, finance, economics, etc. However, while modern techniques are able to explore large sets of temporal data to build forecasting models, they typically neglect valuable information that is often available under the form of unstructured text. Although this data is in a radically different format, it often contains contextual explanations for many of the patterns that are observed in the temporal data. In this paper, we propose two deep learning architectures that leverage word embeddings, convolutional layers and attention mechanisms for combining text information with time-series data. We apply these approaches for the problem of taxi demand forecasting in event areas. Using publicly available taxi data from New York, we empirically show that by fusing these two complementary cross-modal sources of information, the proposed models are able to significantly reduce the error in the forecasts. Keywords: Deep learning, Data fusion, Cross modality learning, Time series forecasting, Textual data, Taxi demand, Special events, Urban mobility 1. Introduction Understanding what drives the travel behavior of people is a key research topic for developing effective and efficient intelligent transportation systems that adapt to the travel demand. However, typical approaches focus only on capturing recurrent mobility trends that relate to habitual/routine behaviour [1], and on exploiting short-term correlations with recent observation patterns [2, 3]. While this type of approaches can be successful for long-term planning applications or for modeling demand in non-eventful areas such as residential neighborhoods, in lively and highly dynamic areas that are prone to the occurrence of multiple special events, such as music concerts, sports games, festivals, parades and protests, these approaches fail to accurately model mobility demand [4]. As we move towards the deployment of autonomous vehicles, understanding and being able to anticipate mobility demand becomes crucial, especially in shared-mobility scenarios, as this allows for properly managing fleets and increasing user-satisfaction. In order to capture the effects of events, one can exploit the vast amount of information that is shared online about what is planned to take place in the city. However, most of this information is typically in the form of unstructured natural-language text.

Alan Turing's decades-old question still influences artificial intelligence because of the simple test he proposed in his article in Mind. In this article, AI Magazine collects presentations about the first round of the classic Turing Test of machine intelligence, held November 8, 1991 at The Computer Museum, Boston. Robert Epstein, Director Emeritus, Cambridge Center for Behavioral Studies, and an adjunct professor of psychology, Boston University, University of Massachusetts (Amherst), and University of California (San Diego) summarizes some of the difficult issues during the planning of this first real-time competition, and describes the event. Presented in tandem with Dr. Epstein's article is the actual transcript of session that won the Loebner Prize Competition--Joseph Weintraub's computer program PC Therapist. In 1985 an old friend, Hugh Loebner, told me The intricacies of setting up a real Turing Test excitedly that the Turing Test should be made that would ultimately yield a legitimate into an annual contest. We were ambling winner were enormous. Small points were down a Manhattan street on our way to occasionally debated for months without dinner, as I recall. Hugh was always full of clear resolution. Turing, proposed a variation on a simple Four years later, while serving as the director parlor game as a means for identifying a of the Cambridge Center for Behavioral Studies, machine that can think: A human judge an advanced studies institute in Massachusetts, interacts with two computer terminals, one I established the Loebner Prize controlled by a computer and the other by a Competition, the first serious effort to locate person, but the judge doesn't know which is a machine that can pass the Turing Test. If, after a prolonged conversation at Hugh had come through with a pledge of each terminal, the judge can't tell the difference, $100,000 for the prize money, along with we'd have to say, asserted Turing, that some additional funds from his company, in some sense the computer is thinking. Crown Industries, to help with expenses. The Computers barely existed in Turing's day, but, quest for the thinking computer had begun. I'll then describe that After much debate, the Loebner Prize Committee first event, which took place on November 8, ultimately rejected Turing's simple 1991, at The Computer Museum in Boston two-terminal design in favor of one that is and offer a summary of some of the data generated more discriminating and less problematic. Finally, I'll speculate The two-terminal design is troublesome for about the future of the competition--now an several reasons, among them: The design presumes annual event, as Hugh envisioned--and that the hidden human--the human about its significance to the AI community.

Alan Turing's decades-old question still influences artificial intelligence because of the simple test he proposed in his article in Mind. In this article, AI Magazine collects presentations about the first round of the classic Turing Test of machine intelligence, held November 8, 1991 at The Computer Museum, Boston. Robert Epstein, Director Emeritus, Cambridge Center for Behavioral Studies, and an adjunct professor of psychology, Boston University, University of Massachusetts (Amherst), and University of California (San Diego) summarizes some of the difficult issues during the planning of this first real-time competition, and describes the event. Presented in tandem with Dr. Epstein's article is the actual transcript of session that won the Loebner Prize Competition--Joseph Weintraub's computer program PC Therapist. In 1985 an old friend, Hugh Loebner, told me The intricacies of setting up a real Turing Test excitedly that the Turing Test should be made that would ultimately yield a legitimate into an annual contest. We were ambling winner were enormous. Small points were down a Manhattan street on our way to occasionally debated for months without dinner, as I recall. Hugh was always full of clear resolution. Turing, proposed a variation on a simple Four years later, while serving as the director parlor game as a means for identifying a of the Cambridge Center for Behavioral Studies, machine that can think: A human judge an advanced studies institute in Massachusetts, interacts with two computer terminals, one I established the Loebner Prize controlled by a computer and the other by a Competition, the first serious effort to locate person, but the judge doesn't know which is a machine that can pass the Turing Test. If, after a prolonged conversation at Hugh had come through with a pledge of each terminal, the judge can't tell the difference, $100,000 for the prize money, along with we'd have to say, asserted Turing, that some additional funds from his company, in some sense the computer is thinking. Crown Industries, to help with expenses. The Computers barely existed in Turing's day, but, quest for the thinking computer had begun. I'll then describe that After much debate, the Loebner Prize Committee first event, which took place on November 8, ultimately rejected Turing's simple 1991, at The Computer Museum in Boston two-terminal design in favor of one that is and offer a summary of some of the data generated more discriminating and less problematic. Finally, I'll speculate The two-terminal design is troublesome for about the future of the competition--now an several reasons, among them: The design presumes annual event, as Hugh envisioned--and that the hidden human--the human about its significance to the AI community.