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Artificial Intelligence and the Manufacturing of Reality


One characteristic human foible is how easily we can falsely redefine what we experience. This flaw, called the Thomas Theorem, suggests, "If men define situations as real, they are real in their consequences."[2] Put another way, humans not only respond to the objective features of their situations but also to their own subjective interpretations of those situations, even when these beliefs are factually wrong. Other shortcomings include our willingness to believe information that is not true and a propensity to be as easily influenced by emotional appeals as reason, as demonstrated by the "North Dakota Crash" falsehood.[3] Machines can also be taught to exploit these flaws more effectively than humans: artificial intelligence algorithms can test what content works and what does not over and over again on millions of people at high speed, until their targets react as desired.[4]

Optimising Utilisation Forecasting with AI and Machine Learning


What IT team wouldn't like to have a crystal ball that could predict the IT future, letting them fix application and infrastructure performance problems before they arise? Well, the current shortage of crystal balls makes the union of artificial intelligence (AI), machine learning (ML), and utilisation forecasting the next best thing for anticipating and avoiding issues that threaten the overall health and performance of all IT infrastructure components. The significance of AI has not been lost to organisations in the United Kingdom, with 43 per cent of them believing that AI will play a big role in their operations. Utilisation forecasting is a technique that applies machine learning algorithms to produce daily usage forecasts for all utilisation volumes across CPUs, physical and virtual servers, disks, storage, bandwidth, and other network elements, enabling networking teams to manage resources proactively. This technique helps IT engineers and network admins prevent downtime caused by over-utilisation.

Revolutionary Artificial Intelligence warship contracts announced


The funding aims to revolutionise the way warships make decisions and process thousands of strands of intelligence and data by using Artificial Intelligence (A.I.). Nine projects will share an initial £1 million to develop technology and innovative solutions to overcome increasing'information overload' faced by crews as part of DASA's Intelligent Ship – The Next Generation competition. The astonishing pace at which global threats are evolving requires new approaches and fresh-thinking to the way we develop our ideas and technology. The funding will research pioneering projects into how A.I and automation can support our armed forces in their essential day-to-day work. Intelligent Ship is focused on inventive approaches for Human-AI and AI-AI teaming for defence platforms – such as warships, aircraft, and land vehicles – in 2040 and beyond.

AI Expert Claims We Need 'Greta Thunberg of Robot World' to Prevent Emergence of Dangerous Robots


Dr David Levy, an expert on artificial intelligence (AI), said in an interview with the Daily Star that the way technology is developing nowadays, the world might soon face a serious challenge from AI-equipped robots of all types. Levy complained that governments are acting too slowly when it comes to introducing new laws and addressing the new challenge, recalling how the Dutch Ministry of Defence had ignored his warnings regarding the potentially malign use of drones and, less than a year later, simple drones were able to paralyse the work of Gatwick Airport in the UK during Christmas season. The AI expert argues that in order to draw more attention to the problem, a "Greta Thunberg of the robot world" is needed, adding that dangerous robots are likely to harm humanity sooner than climate change. Thunberg, a famous teenage environmental activist, rose to prominence globally in recent years by rallying students around the world to take part in her "strikes for climate", which are designed to draw attention to ecological problems. She also made an appearance at a UN committee devoted to the topic, delivering a passionate speech in which she accused global leaders of doing too little to address climate change.

Apply – UKRI Centre for Doctoral Training in Artificial Intelligence and Music


We are on the lookout for the best and brightest students interested in the intersection of music/audio technology and AI. For this round of applications we are offering a number of scholarships to applicants who are ordinarily resident in the UK (i.e. have lived and studied/worked in the UK at least the last three years – this includes EU nationals) and a smaller number of scholarships to international students. We have a large number of 4-year PhD studentships available for home, EU and international students starting in September 2020 which will cover the cost of tuition fees and will provide an annual tax-free stipend (£17,009 in 2019/20). The CDT will also provide funding for conference travel, equipment, and for attending other CDT-related events. Please see the international PhD scholarships page for full details of Queen Mary's international funding partners, including other schemes not listed here.

Acquiring minds want to know: A peek inside Apple's most recent corporate acquisitions


If you've heard it once, you've heard it dozens of times: "Apple buys smaller technology companies from time to time, and we generally do not discuss our purpose or plans." When it comes to its corporate acquisitions, Cupertino likes to play its cards very close to its chest. Of course, that doesn't stop industry watchers from peering at the tea leaves to see if they can divine exactly what the company might be working on. And, hey, I'm no different than those folks, because Apple does so little to telegraph its plans that even a boilerplate statement confirming an acquisition is a rare peek behind the curtain. Apple CEO Tim Cook said not long ago that the company makes an acquisition every two to three weeks, and not even all of those make it into the public eye.

Living in Alan Turing's Future


More than a decade has passed since the British government issued an apology to the mathematician Alan Turing. The tone of pained contrition was appropriate, given Britain's grotesquely ungracious treatment of Turing, who played a decisive role in cracking the German Enigma cipher, allowing Allied intelligence to predict where U-boats would strike and thus saving tens of thousands of lives. Unapologetic about his homosexuality, Turing had made a careless admission of an affair with a man, in the course of reporting a robbery at his home in 1952, and was arrested for an "act of gross indecency" (the same charge that had led to a jail sentence for Oscar Wilde in 1895). Turing was subsequently given a choice to serve prison time or undergo a hormone treatment meant to reverse the testosterone levels that made him desire men (so the thinking went at the time). Turing opted for the latter and, two years later, ended his life by taking a bite from an apple laced with cyanide.

On classifying sepsis heterogeneity in the ICU: insight using machine learning


Current machine learning models aiming to predict sepsis from electronic health records (EHR) do not account 20 for the heterogeneity of the condition despite its emerging importance in prognosis and treatment. This work demonstrates the added value of stratifying the types of organ dysfunction observed in patients who develop sepsis in the intensive care unit (ICU) in improving the ability to recognize patients at risk of sepsis from their EHR data. Using an ICU dataset of 13 728 records, we identify clinically significant sepsis subpopulations with distinct organ dysfunction patterns. We perform classification experiments with random forest, gradient boost trees, and support vector machines, using the identified subpopulations to distinguish patients who develop sepsis in the ICU from those who do not. The classification results show that features selected using sepsis subpopulations as background knowledge yield a superior performance in distinguishing septic from non-septic patients regardless of the classification model used.

AI is transforming medicine – but it can only work with proper sharing of data


It is not often that one witnesses a transformational advance in medicine. But the application of artificial intelligence (AI) to improve the early detection of disease is exactly that. I was a co-author of the paper recently published in Nature showing that an AI system developed by Google was better at spotting breast tumours than doctors. Now, researchers in the US have reported that AI-supported laser scanners are faster than doctors at detecting brain tumours. These are very exciting developments that will, ultimately, have a big impact on the accuracy, logistics and speed of diagnosis.

EU eyes temporary ban on facial recognition in public places

The Guardian

The EU could temporarily ban the use of facial recognition technology in public places such as train stations, sport stadiums and shopping centres over fears about creeping surveillance of European citizens. A prohibition lasting between three and five years is seen as a way for Brussels to manage the risks said to be posed by the breakneck speed at which the software is being adopted. The option is contained in an early draft of a European commission white paper obtained by the news website Euractiv. The final version is due to be published in February as part of a wider overhaul of the regulation of artificial intelligence. The draft document points to the right under the General Data Protection Regulation for EU citizens "not to be subject of a decision based solely on automated processing, including profiling."