Back in the 1980s, Artificial Intelligence (AI) just had to look good in the movies and be able to power fancy talking cars, zappy spaceships and various forms of fantastical cyborgs who would one day roam the planet and possibly destroy the human race. Fast-forward to 2019 and we find ourselves deep in the AI renaissance (or perhaps first'real' birth of AI, rather than any form of rebirth) as we now have the processing power, memory capacity, cloud network breadth and sophisticated algorithmic intelligence to actually apply AI to our lives. But there's a problem -- we (the humans) who build the AI brains need to be able to construct them with a pure enough form of digital DNA such that they stay clean of any form of discriminatory bias. Major cloud networks have already been criticized for employing software that discriminates against women; a well-known search engine has been accused of featuring ethnic bias in results when looking for'unprofessional hairstyles'; an equally well-known social network has been criticized for showing certain job ads only to men; and the list goes on. The question the tech industry must now face is: how to we rid AI of bias in all its forms and ensure fair play for all in the age of computer-driven decision making? One set of answers comes from Women Leading in AI (WLinAI), a network of leaders working in tech, science, politics, business and think tanks – the group is demanding that the UK government takes back control of technology.

Chances are you've heard of artificial intelligence, which has found widespread adoption in our popular culture. Generally speaking, AI is a set of computer algorithms that can learn to make decisions without human intervention. That's AI, though I think we can all agree there is some room for improvement in that arena. It's fun to ponder what technological wizardry AI will offer future generations. Where it becomes daunting, however, is when we consider its long-term global implications and the structure necessary to harness its development.

Darktrace helped pave the way for using artificial intelligence to combat malicious hacking and enterprise security breaches. Now a new UK startup founded by an ex-Darktrace executive has raised some funding to take the use of AI in cybersecurity to the next level. Senseon, which has pioneered a new model that it calls "AI triangulation" -- simultaneously applying artificial intelligence algorithms to oversee, monitor and defend an organization's network appliances, endpoints, and'investigator bots' covering multiple microservices -- has raised $6.4 million in seed funding. David Atkinson -- the startup's CEO and founder who had previously been the commercial director for Darktrace and before that helped pioneer new cybersecurity techniques as an operative at the UK's Ministry of Defense -- said that Senseon will use the funding to continue to expand its business both in Europe and the US. The deal was co-led by MMC Ventures and Mark Weatherford, who is chief cyber security strategist at vArmour (which itself raised money in recent weeks) and previously Deputy Under Secretary for Cybersecurity, U.S. Department of Homeland Security.

In recent years, the concept of artificial intelligence (AI) has emerged from the annals of science fiction into everyday life, as society grapples with a range of technological issues from cyber security to driverless cars. Along with other terms, such as machine learning, neural networks and'the Turing test', AI has become a contemporary media buzzword in both fact and fiction – despite a general lack of understanding of what AI really means to the average citizen of Earth. Out in space, however, the use of AI is arguably more mature and well-understood, at least for current applications, while its integration into future manned space exploration is pretty much a'no-brainer', along with sibling technologies such as robotics, telepresence and autonomous systems. Most of us, if asked to consider the link between AI and space, would probably think of HAL, the miscreant computer from '2001: A Space Odyssey', rather than any real-life application. Certainly, it seems to tick the box for any current definition of AI, which typically involves'computer systems able to perform tasks normally requiring human intelligence'.

In this paper, we propose a robust sequential learning strategy for training large-scale Recommender Systems (RS) over implicit feedback mainly in the form of clicks. Our approach relies on the minimization of a pairwise ranking loss over blocks of consecutive items constituted by a sequence of non-clicked items followed by a clicked one for each user. Parameter updates are discarded if for a given user the number of sequential blocks is below or above some given thresholds estimated over the distribution of the number of blocks in the training set. This is to prevent from an abnormal number of clicks over some targeted items, mainly due to bots; or very few user interactions. Both scenarios affect the decision of RS and imply a shift over the distribution of items that are shown to the users. We provide a theoretical analysis showing that in the case where the ranking loss is convex, the deviation between the loss with respect to the sequence of weights found by the proposed algorithm and its minimum is bounded. Furthermore, experimental results on five large-scale collections demonstrate the efficiency of the proposed algorithm with respect to the state-of-the-art approaches, both regarding different ranking measures and computation time.

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A new code of conduct for artificial intelligence and other data-driven technologies will ensure that only the best and safest systems are used by the NHS. The code encourages technology companies to meet a gold-standard set of principles to protect patient data to the highest standards. It has been drawn up with the help of industry, academics and patient groups. The aim is to make it easier for suppliers to develop technologies that tackle some of the biggest issues in healthcare, such as dementia, obesity and cancer. It will also help health and care providers choose safe, effective and secure technology to improve the services they provide.

The American military wants to expand its use of artificial intelligence, or AI, for war. But it says the technology will be deployed in respect to the nation's values. The United States Defense Department released its first AI strategy this week. The strategy calls for increasing the use of AI systems throughout the military, from decision-making to predicting problems in planes or ships. It urges the military to provide AI training to change "its culture, skills and approaches."

In a new essay for The Conversation, University of Minnesota law professor Francis Shen grapples with the difficult legal and social issues raised by sexbots -- including the specter of ones designed to look like children. "Childlike sex robots are robots, not humans," Shen wrote. "Like virtual child pornography, the development of a childlike sex robot does not require interaction with any children. Yet it might also be argued that childlike sex robots would have serious detrimental effects that compel state action." There's already been federal legislation to outlaw childlike sex robots, Shen pointed out.

An incredible optical illusion that'breaks your brain' for 15-milliseconds and causes you to see a circular shape spin has been created by scientists. The geometric pattern, a variation of the Pinna-Brelstaff illusion made up diamond-like shapes, turns clockwise or anti-clockwise, depending on which way you move your head. The small, thick dashes appear to turn clockwise if you move your head towards the image, or anti-clockwise if you pull your head away from it. The reason this happens is due to a communication delay between the regions of your brain that process vision and movement. Scientists have cracked why an optical illusion'breaks your brain' for 15-milliseconds causing you to see a circular shape turn clockwise and anti-clockwise depending on which way you move your head.