Tabby's Star or KIC 8462852 was discovered by citizen scientists in 2015 The light from the star dims irregularly, and astronomers do not know why Some theories said it was due to passing comets or alien'megastructures' Now a new paper suggest the material inside the star is undergoing a phase transition Tabby's Star or KIC 8462852 was discovered by citizen scientists in 2015 Some theories said it was due to passing comets or alien'megastructures' Tabby's Star, known officially as KIC 8462852, (pictured in infrared, left and UV, right) has baffled experts since it was discovered in 2015, by scientists scanning the skies for exoplanets How to spot'Santa' in the night sky as the... Wind farms can be DEADLY for birds of prey: Migrating... Watch Mark Zuckerberg show off his artificial intelligence... Can YOU solve this Christmas conundrum? How to spot'Santa' in the night sky as the... Wind farms can be DEADLY for birds of prey: Migrating... Watch Mark Zuckerberg show off his artificial intelligence... Can YOU solve this Christmas conundrum? Tabby's star is a standard F-class star, located in the constellation Cygnus, approximately 1,276 light years from Earth. A paper published earlier this month suggested the star gives off jets that could be a source of energy for an alien civilisation. WHAT IS A DYSON SPHERE?

Machine learning is a process that applies advanced mathematical algorithms and powerful computing capabilities to quickly and efficiently analyze those data sets and identify patterns. In the case of IT security, correctly determining patterns helps create accurate predictions and detect behaviors that may be associated with malware or other attacks. Doing so in real time, or as near to real time as possible, can help prevent malware from infecting endpoints entirely. Why should MSPs care about machine learning? There might not seem like there's a direct connection, but it's the difference between reactive and preventative security.

You ask your smartphone virtual assistant to make an appointment for you. You receive a message alert from your bank enquiring if you made a certain transaction. You receive recommendations for music or movies or online purchases based on your past behaviour. These are all examples of Artificial Intelligence (AI) entering your daily life. There is no widely accepted definition of the term or what constitutes AI. Definitions are usually based on some variation of computerized systems or computers exhibiting behaviour or thought that is normally demonstrated by humans or requires intelligence (which itself is hard to define). It could involve rationally solving complex problems or taking appropriate actions to achieve objectives in real world circumstances.

The UK government is considering a "knowledge or situational awareness test" for all British drone owners, similar to a driving theory examination. The proposed quiz could be voluntary, according to the Department for Transport, or mandatory as part of a new drone registration system. It was referenced in a new consultation drawn up to keep casual pilots in check, while encouraging drone research by the private sector. "The safety of other airspace users and the general public is dependent on leisure drone users adhering to the rules and understanding the risks," ministers argue. Among the new proposals is an online registration scheme that pilots would need to complete for quadcopters weighing 250 grams or more.

Since cybersecurity threats have become a topic of nightly newscasts, no longer is anyone shocked by their scope and veracity. What is shocking is the financial damage the attacks are predicted to cause as they reverberate throughout the economy. Cybersecurity Ventures predicts global annual cybercrime costs will grow from $3 trillion in 2015 to $6 trillion annually by 2021, which includes damage and destruction of data, stolen money, lost productivity and theft of intellectual property, personal and financial data, embezzlement and fraud. That doesn't even include post-attack disruption to the normal course of business, forensic investigation, restoration and deletion of hacked data, systems and reputational harm. While traditional security filters like firewalls and reputation lists are good practice, they are no longer enough.

Artificial Intelligence (AI) as a subject has been around for years, however it is only now that AI as a real possibility is bleeding into public consciousness. Even the government has started to take notice - in October alone the UK and the US published two government reports on AI, focusing on national readiness and the challenges that lie ahead. Both recognize the importance of creating the skills required for a digital era and AI, and question how we can use automation to the best effect. Recently, the Government Office for Science published a report titled "Artificial intelligence: an overview for policy-makers", which pinpoints AI as a future technology driving the Fourth Industrial Revolution. One area drawn out within the report was the effect that AI and automation will have on the labor market, noting that the technology will have an impact on changes in skillset, and that many traditional roles will evolve as a result.

May 14, 2017, will be the 100th anniversary of the birth of someone you might not have heard of: William Thomas ("Bill") Tutte. During the Second World War he made several crucial contributions to decrypting the Lorenz cipher used to protect the Nazi high command's most crucial radio communications. This work provided the statistical method implemented electronically by Tommy Flowers, a telecommunications engineer, in the Colossus machines, which pioneered many of the electronic engineering techniques later used to build digital computers and network equipment.a The British code-breaking effort of the Second World War, formerly secret, is now one of the most celebrated aspects of modern British history, an inspiring story in which a free society mobilized its intellectual resources against a terrible enemy. That's a powerful source of nostalgic pride for a country whose national identity and relationship with its neighbors are increasingly uncertain. Tutte's centennial gives a chance to consider the broader history of Bletchley Park, where the codebreakers worked, and the way in which it has been remembered. Some kinds of people, and work, have become famous and others have not. Films reach more people than books. So statistically speaking, most of what you know about Bletchley Park probably comes from the Oscar-winning film The Imitation Game. This gives us a starting point: the film is a bad guide to reality but a useful summary of everything that the popular imagination gets wrong about Bletchley Park. One myth is that Alan Turing won the war pretty much by himself.

In a forecasting exercise, Gordon Earle Moore, co-founder of Intel, plotted data on the number of components--transistors, resistors, and capacitors--in chips made from 1959 to 1965. He saw an approximate straight line on log paper (see Figure 1). Extrapolating the line, he speculated that the number of components would grow from 26 in 1965 to 216 in 1975, doubling every year. His 1965–1975 forecast came true. In 1975, with more data, he revised the estimate of the doubling period to two years. In those days, doubling components also doubled chip speed because the greater number of components could perform more powerful operations and smaller circuits allowed faster clock speeds. Later, Moore's Intel colleague David House claimed the doubling time for speed should be taken as 18 months because of increasing clock speed, whereas Moore maintained that the doubling time for components was 24 months. But clock speed stabilized around 2000 because faster speeds caused more heat dissipation than chips could withstand. Since then, the faster speeds are achieved with multi-core chips at the same clock frequency. Moore's Law is one of the most durable technology forecasts ever made.10,20,31,33 It is the emblem of the information age, the relentless march of the computer chip enabling a technical, economic, and social revolution never before experienced by humanity. The standard explanation for Moore's Law is that the law is not really a law at all, but only an empirical, self-fulfilling relationship driven by economic forces. This explanation is too weak, however, to explain why the law has worked for more than 50 years and why exponential growth works not only at the chip level but also at the system and market levels. Consider two prominent cases of systems evolution.

An autonomous Uber malfunctioned while in "self-driving mode" and caused a near collision in San Francisco, according to a business owner whose account raises new safety concerns about the unregulated technology launch. The self-driving car – which Uber introduced without permits, as part of a testing program that California has deemed illegal – accelerated into an intersection while the light was still red and while the automation technology was clearly controlling the car, said Christopher Koff, owner of local cafe AK Subs. Self-driving cars: Uber's open defiance of California shines light on brazen tactics "It looked like the car ran the red light on its own," Koff, 49, said of the self-driving Uber Volvo, which has a driver in the front seat who can take control when needed. Another car that had the green light had to "slam the brakes" to avoid a crash, he said. Koff's story, which advocacy group Consumer Watchdog shared with state officials on Tuesday, directly contradicts Uber's public claims that red-light violations have been the result of "human error" and that the drivers, not the technology, have failed to follow traffic laws.

One of the most important things that the U.S. can do to improve economic growth is to invest in artificial intelligence, or A.I., said the White House, in a new report. A.I.-driven, intelligent systems have the potential to displace millions, such as truck drivers, from their jobs. But potential negative impacts can be offset by investments in education as well as by ensuring there is a safety net to help affected people, the White House argued, in what will likely be the Obama administration's final report on technology policy. Some of the report's recommendations, which include expanded unemployment help and access to healthcare, may be anathema to a Republican-controlled Congress with a focus on tax reductions and spending cuts. But this report -- "Artificial Intelligence, Automation, and the Economy" (PDF) -- which was in the works well before election day, also describes broader, technological-driven changes that will impact jobs and may pose issues for President-elect Donald Trump.