If you are looking for an answer to the question What is Artificial Intelligence? and you only have a minute, then here's the definition the Association for the Advancement of Artificial Intelligence offers on its home page: "the scientific understanding of the mechanisms underlying thought and intelligent behavior and their embodiment in machines."
However, if you are fortunate enough to have more than a minute, then please get ready to embark upon an exciting journey exploring AI (but beware, it could last a lifetime) …
Gatwick has become the UK's first airport to confirm it will use facial-recognition cameras on a permanent basis for ID checks before passengers board planes. It follows a self-boarding trial carried out in partnership with EasyJet last year. The London airport said the technology should reduce queuing times but travellers would still need to carry passports. On Tuesday, a spokeswoman for Gatwick told BBC News it had taken the decision, first reported by the Telegraph newspaper, after reviewing feedback from passengers in the earlier test. "More than 90% of those interviewed said they found the technology extremely easy to use and the trial demonstrated faster boarding of the aircraft for the airline and a significant reduction in queue time for passengers," she said.
Artificial intelligence, alongside proper training and education, can manage even the worst of security breaches into a positive outcome for airports and their users, says Kristina Dores, Chief, Aerodromes & Ground Aids at Namibia Civil Aviation Authority, and Brad Hayes, CTO at Circadence Corporation. However, the key question is when (not if) will organisations take the steps to prepare for the coming wave of digitisation? Highly-interconnected and increasingly-digitised systems are a necessary part of modern airport infrastructure. Furthermore, vulnerabilities at these interfaces – through personnel and digital systems alike – lead to an increased threat of intrusion and potentially catastrophic disruption. This problem is not one that we can simply train and hire our way out of as these systems and their attack surfaces do not scale linearly in complexity.
The one-day event will take place at Lady Margaret Hall College in Oxford. Lady Margaret Hall was the first women's college at Oxford, and is alma mater to some of the UK's greatest women scientists.It retains its progressive approach, appointing the former editor of the Guardian, Alan Rusbridger, as its Principal in 2015. In 2016 it instituted a Foundation Year for under-represented students. Oxford is easily accessible by train from most directions. The station is on the western edge of the city and from there you can take a taxi to the College (taxis are located outside the station at the front entrance).
Chatbots, virtual assistants, augmented analytic systems typically receive user queries such as "Find me an action movie by Steven Spielberg". This is a Natural Language Understanding (NLU) task kown as Intent Classification & Slot Filling. State-of-the-art performance is typically obtained using recurrent neural network (RNN) based approaches, as well as by leveraging an encoder-decoder architecture with sequence-to-sequence models. In this article we demonstrate hands-on strategies for improving the performance even further by adding Attention mechanism. In 2014, after Sutskever revolutionized deep learning by discovering sequence to sequence models, it was the invention of the attention mechanism in 2015 that ultimately completed the idea and opened the doors to amazing machine translation we enjoy every day.
For anyone who has travelled through border control at an airport, or owns one of the latest smartphones, facial recognition technology isn't new. But using our faces to access a physical or digital service is about to become a more common occurrence in everyday life as companies across a wide range of sectors ramp up their investments in biometric technology. AI-powered biometrics has quickly established itself as the most pertinent means of identifying and authenticating individuals in a reliable and fast way, through the use of unique biological characteristics. As Singapore advances its Smart Nation vision, a study by Accenture revealed that AI could nearly double Singapore's annual economic growth rates by 2035, changing the nature of work and spawning a new relationship between man and machine. Building on that notion, the Singapore government has plans to roll out the National Digital Identity System for Singapore residents and businesses to transact digitally with the government and private sector in a convenient and secure manner in 2020 – heralding dramatic potential for economic growth.
This article is part of our collection about the 2019 state of IT. A CIO has always been busy running the IT and computer systems that support an enterprise. Now with artiificial intelligence (AI) turning every company into a data company, a CIO's job is more central and more complicated than ever before. A recent Gartner survey found that some of the world's biggest companies plan to double the number of AI projects within the next year, with four AI efforts already in place on average. Additionally, companies plan to spend more on AI, in the neighborhood of $77 billion in 2022, up more than 3x from the $24 billion spent in 2018, according to IDC.
If you've yet to hear about this IT phenomenon, it's likely you're not among the 44 percent of businesses implementing a digital-first approach to business processes, operations, and customer engagement. ZDnet defines today's digital transformation as, "using digital technologies to remake a process to become more efficient or effective. The idea is to use technology not just to replicate an existing service in a digital form, but to use technology to transform that service into something significantly better." As today's organizations embrace digital tools to create new processes or modify existing ones, they'll also inherently impact other important aspects, like workplace culture and customer experience. With digital transformation, companies are re-evaluating everything they do, from internal systems to online and in-person customer interactions.
We all see the headlines nearly every day. Whether primitive (gunpowder) or cutting-edge (unmanned aerial vehicles) in the wrong hands, technology can empower bad actors and put our society at risk, creating a sense of helplessness and frustration. Current approaches to protecting our public venues are not up to the task, and, frankly appear to meet Einstein's definition of insanity: "doing the same thing over and over and expecting a different result." It is time to look past traditional defense technologies and see if newer approaches can tilt the pendulum back in the defender's favor. Artificial Intelligence (AI) can play a critical role here, helping to identify, classify and promulgate counteractions on potential threats faster than any security personnel.
When you post a photo on Facebook, and the platform automatically tags the people in the image, you might not give much thought to the technology behind the convenience. However, when you discover that facial recognition technology could track you without your permission while you walk down a street in London, it might make you question the invasion of your privacy. Just like with any other new technology, facial recognition brings positives and negatives with it. Since it's here to stay and expanding, it's good to be aware of the pros and cons of facial recognition. What is facial recognition, and how does it work?
As Grushka-Cockayne explains, there was enthusiasm among key stakeholders at Heathrow to upgrade existing data systems at the airport, and a consensus about the opportunity to better leverage data to improve the experience of connecting passengers--who account for roughly one-third of all travelers who pass through Heathrow annually. The question was how to do this. "People want to use machine learning and big data--all of these buzz words," says Grushka-Cockayne, "but if they don't know how to focus in on a very specific task that can generate predictions, it is difficult to use the technology to actually improve decision-making." Grushka-Cockayne and her team spent several months working with partners at Heathrow to define the scope of their research--the development of a machine learning model that could predict a passenger's journey through Heathrow in route to his or her connecting flight. The goal was to be able to anticipate the number of people passing through immigration in real time (enabling more efficient staff allocation at immigration lines), and also to predict whether a passenger would be late for his or her flight (allowing the airport to proactively offer supporting services).