Suppose that we wish to estimate a vector $\mathbf{x}$ from a set of binary paired comparisons of the form "$\mathbf{x}$ is closer to $\mathbf{p}$ than to $\mathbf{q}$" for various choices of vectors $\mathbf{p}$ and $\mathbf{q}$. The problem of estimating $\mathbf{x}$ from this type of observation arises in a variety of contexts, including nonmetric multidimensional scaling, "unfolding," and ranking problems, often because it provides a powerful and flexible model of preference. We describe theoretical bounds for how well we can expect to estimate $\mathbf{x}$ under a randomized model for $\mathbf{p}$ and $\mathbf{q}$. We also present results for the case where the comparisons are noisy and subject to some degree of error. Additionally, we show that under a randomized model for $\mathbf{p}$ and $\mathbf{q}$, a suitable number of binary paired comparisons yield a stable embedding of the space of target vectors. Finally, we also that we can achieve significant gains by adaptively changing the distribution for choosing $\mathbf{p}$ and $\mathbf{q}$.

Technically Incorrect offers a slightly twisted take on the tech that's taken over our lives I contacted Microsoft and asked a simple question: "Am I going bonkers?" I felt the company's spokeswoman all too readily to reply "you must be the last to know," before I added: "Has your Bing Translator page suddenly been featuring a big Microsoft logo?" You see, very occasionally, I lurch to Bing just to see what's going on there. And last week, when I clicked onto its Bing Translator link, I was confronted with a big "Microsoft Translator" at the top. I felt sure I hadn't seen this before.

Every decade seems to have its technological buzzwords: we had personal computers in 1980s; Internet and worldwide web in 1990s; smart phones and social media in 2000s; and Artificial Intelligence (AI) and Machine Learning in this decade. While artificial intelligence (AI) is among today's most popular topics, a commonly forgotten fact is that it was actually born in 1950 and went through a hype cycle between 1956 and 1982. The purpose of this article is to highlight some of the achievements that took place during the boom phase of this cycle and explain what led to its bust phase. The lessons to be learned from this hype cycle should not be overlooked – its successes formed the archetypes for machine learning algorithms used today, and its shortcomings indicated the dangers of overenthusiasm in promising fields of research and development. Although the first computers were developed during World War II [1,2], what seemed to truly spark the field of AI was a question proposed by Alan Turing in 1950 [3]: can a machine imitate human intelligence?

The Department of Computer Science at Cork Institute of Technology (CIT) is delighted to announce the launch of a new full-time master's degree in Artificial Intelligence (AI). This innovative programme provides a technical deep-dive into the area of AI. The programme aims to produce AI engineers with a highly relevant skillset in AI topics. Students will learn how to use and develop intelligent computer systems that can learn from experience, recognise patterns in vast amounts of data and reason strategically in complex decision-making situations. The programme content will deliver a comprehensive range of topics integral to the study of AI.

In a matter of months, General Data Protection Regulation (GDPR) will become a law throughout Europe, deeming a complete overhaul in the way artificial intelligence techniques are used in business settings. By May 25, the GDPR will become fully enforceable throughout the European Union, states the EU GDPR timeline. The coming deadline, which will be enforced in the next 100 days, has sparked a debate among the AI research community and tech giants who are now scrambling to meet the EU's data privacy and algorithmic fairness guidelines. Well, for the EU citizens, GDPR has strengthened their rights by ushering in a new era by unifying data protection rules and placing new obligations on tech enterprises on the process of collecting personal user data. The forthcoming regulations have firmly divided Europe into two different camps – a) one that welcomes the need for data privacy and algorithmic fairness in society, b) tech giants who are bristling at the thought of new challenges, such as asking for user consent in simpler terms and tackling the black box problem of AI, which would make eventually make it illegal, with fines imposed to the tune of 4 percent of global turnover, reportedly.

Machines are talking about you behind your back. So reads a notice on the wall at Hello, Robot: Design Between Human and Machine – an exhibition which could change the way you think about automatons. The show's already been a big hit in Vienna, Austria. This summer it travels to Winterthur, in Switzerland, then on to Lisbon in Portugal. Until April you can see it in Belgium, at Ghent's excellent Design Museum.

The Minister of State for Trade, Employment, Business, EU Digital Single Market and Data Protection Pat Breen is keeping abreast of pioneering work in cutting edge technology. On Friday, he visited the University of Limerick's Digital District at the Park Point Facility in the city for a briefing with Dr Mary Shire, vice president of research and enterprise and Dr Ann Ledwith, Dean of Graduate and Professional Studies. The Digital District will host a newly established Digital Skills Academy, the Nexus Digital Accelerator and the confirm centre for smart manufacturing. Ireland's first Masters in Artificial Intelligence (AI) was launched on January 25 by the Minister for Business, Enterprise and Innovation, Heather Humphreys. The programme will run in UL's Digital District from September, in association with the Irish Centre for High End Computing.

A first for German airports, Josie Pepper's brain is based on IBM Watson technology, a question and answer computer system specifically developed to answer questions from the quiz show Jeopardy. Passengers at Munich Airport will have an unusual welcome when they arrive at Terminal 2. From today, Josie Pepper, a 120-centimetre tall robot will be on hand to greet them and answer questions. The innovation is a joint Lufthansa-Munich Airport project. It is the first-ever test of a humanoid robot equipped with artificial intelligence at a German airport. For the next few weeks, Josie Pepper will welcome travellers to the non-public area of Terminal 2, which is jointly operated by Munich Airport and Lufthansa.

Deep learning is changing the way we use and think about machines. Current incarnations are better than humans at all kinds of tasks, from chess and Go to face recognition and object recognition. In particular, humans have the extraordinary ability to constantly update their memories with the most important knowledge while overwriting information that is no longer useful. The world provides a never-ending source of data, much of which is irrelevant to the tricky business of survival, and most of which is impossible to store in a limited memory. So humans and other creatures have evolved ways to retain important skills while forgetting irrelevant ones.

A new kind of doctor has entered the exam room, but doesn't have a name. In fact, these doctors don't even have faces. Artificial intelligence has made its way into hospitals around the world. Those wary of a robot takeover have nothing to fear; the introduction of AI into health care is not necessarily about pitting human minds against machines. AI is in the exam room to expand, sharpen, and at times ease the mind of the physician so that doctors are able to do the same for their patients.