Artificial Intelligence (AI) has slowly made its way into the business world and has changed its landscape considerably. The technology has the potential to completely revolutionise the way businesses function. It is a broad concept which is generally perceived as being limited to the use of humanoid robots due to its depiction in Hollywood movies. However, there is more to AI than just highly intelligent robots. It encompasses any technique which allows the computer to imitate human intelligence.

The Square Kilometre Array (SKA) has a celestial ambition. The project aims to discover the origins of the universe through the lens of the world's largest radio telescope. The telescope will search outer space for signals travelling through the cosmos and could reveal how the first stars and galaxies were formed after the big bang and the nature of the mysterious force of dark energy. It may even answer the question that humans have pondered since the dawn of civilisation: are we alone in the universe? It will also provide the scientific foundations for more practical applications.

Mist's Bob Friday: An AI-driven network maximises the user experience through better performance and reliability while lowering IT costs through better efficiencies. Artificial intelligence (AI) – it's a nebulous term that means many things to different people. What is true is that one day in the near future, machines will be likely to possess'human-level' intelligence, providing organisations with efficiencies that they have never seen before. But what role is AI playing inside organisations today, particularly when it comes to providing a good experience for internal users and external customers across their wide area networks? Tech execs gathered in Sydney in September to discuss the benefits of using artificial intelligence technologies inside their wired and wireless networks.

Six of us are huddled together in Cavendish Square Gardens in central London, fighting a horde of warrior skeletons. To passersby, however, we must look like a bunch of adults pointing our smartphones at nothing while shouting about incoming monsters. What we're doing is playing a beta version of Minecraft Earth, an augmented reality (AR) spinoff from the multimillion-selling block-building game – and very soon, parks all over the world will be filled with people just like us. This month, Minecraft is launching an early-access version of the game in a select few territories around the world, ahead of a global roll-out. Microsoft has yet to reveal exactly when and where, but soon thousands of fans used to playing on their console, PC or tablet, are going to be taking their creations to the streets.

Big changes are happening in the business world and one of these great shifts is directly owing to the contribution of machine learning (ML). The grid of algorithms and statistical models is a revolutionary application of AI. The technology has the ability to learn automatically and bring about changes and improvements from experiences. The self-learning capacity of ML makes it an important ingredient of businesses nowadays. It is used to solve varied problems in an organization and veers it towards the high-paced world of transformation. Machine learning drives the innovative phenomenon of a company to make it excel in an arena of hyper-converged data, mediums, content, and technology.

At a conference at the Vatican last week, Pope Francis warned a group of Silicon Valley execs that in the wrong hands, artificial intelligence could have devastating consequences for humanity. "If mankind's so-called technological progress were to become an enemy of the common good, this would lead to an unfortunate regression to a form of barbarism dictated by the law of the strongest," he said, according to Reuters. The development of advanced AI can "raise increasingly significant implications in all areas of human activity," the Pope said. He also called for "open and concrete discussions" to develop "both theoretical and practical moral principles." The conference also grappled with the March 2019 attacks in Christchurch, New Zealand, and how social media platforms helped spread footage taken during the shootings, according to TIME.

In International Conference on Computer Aided Verification (2015), Springer 449–465.

One of the most coveted and recognizable dogs, the labradoodle, may actually be a'monster,' says the breed's progenitor. According to Wally Conron, an Australia native who was the first person to breed the labradoodle - a cross between a poodle and a labrador - the dog opened up a'Pandora's Box.' 'I bred the labradoodle for a blind lady whose husband was allergic to dog hair,' Conron told Australia Broadcast Network. 'She wanted to know if we could come up with a dog that she could use as a guide dog and her husband wouldn't be allergic to.' The issue, says Conron, who was working for the Royal Guide Dogs Association of Australia at the time, wasn't in finding a breed less harsh on one's allergies, it was finding one that was hypoallergenic and had the right temperament. Poodles, though they met the shedding criteria, didn't quite have the same friendliness factor as labradors, so Conron decided to mix the two.

If you've had a driver's licence photo or passport photo taken in Australia in the past few years, it's likely your face will end up in a massive new national network the federal government is trying to create. Victoria and Tasmania have already begun to upload driver's licence details to state databases that will eventually be linked to a future national one. Legislation before federal parliament will allow government agencies and private businesses to access facial IDs held by state and territory traffic authorities, and passport photos held by the foreign affairs department. The justification for what would be the most significant compulsory collection of personal data since My Health Record is cracking down on identity fraud. The home affairs department estimates that the annual cost of ID fraud is $2.2bn, and says introducing a facial component to the government's document verification service would help prevent it.

Time is deeply woven into how people perceive, and communicate about the world. Almost unconsciously, we provide our language utterances with temporal cues, like verb tenses, and we can hardly produce sentences without such cues. Extracting temporal cues from text, and constructing a global temporal view about the order of described events is a major challenge of automatic natural language understanding. Temporal reasoning, the process of combining different temporal cues into a coherent temporal view, plays a central role in temporal information extraction. This article presents a comprehensive survey of the research from the past decades on temporal reasoning for automatic temporal information extraction from text, providing a case study on how combining symbolic reasoning with machine learning-based information extraction systems can improve performance. It gives a clear overview of the used methodologies for temporal reasoning, and explains how temporal reasoning can be, and has been successfully integrated into temporal information extraction systems. Based on the distillation of existing work, this survey also suggests currently unexplored research areas. We argue that the level of temporal reasoning that current systems use is still incomplete for the full task of temporal information extraction, and that a deeper understanding of how the various types of temporal information can be integrated into temporal reasoning is required to drive future research in this area.