A visual representation of digital cryptocurrency Bitcoin is displayed on February 16, 2018 in Paris, France. Well, there have been plenty of developments in artificial intelligence (AI) and machine learning (ML), but opinions about them have been quite varied. One can marvel at how AI was able to perform traditionally "human" activities such as winning at poker or writing music. And, Google's predictive search, which can sometimes make outlandish suggestions and be eerily spot on at times, might make one sceptical too. However, AI can also be scary, as imperfections in the technology could also lead to harm.

Brodies, Scotland's leading law firm, has deployed artificial intelligence platform Luminance, following a successful trial of the technology. Brodies, which was named Legal 500 Scotland Regional Firm of the Year 2018, selected Luminance due to its ability to create efficiencies in areas such as M&A due diligence and real estate transactions. "Our decision to implement Luminance is driven by our client-first agenda. As a firm we are continually investing in ways where we can deliver greater value for our clients. Implementing technology that allows us to drive efficiencies and streamline work, particularly across our offices is just one way of achieving that," commented Will McIntosh, Partner at Brodies.

Doomsday predictions about the impact of Artificial Intelligence (AI) workforce often predict huge job losses in the future as automation takes over many roles currently performed by humans. But shockingly they never mention the impact on the humble soccer groundsman. Understandably, the focus is on areas like manufacturing and retail rather than areas where relatively few people are employed, and it's unlikely the role will ever be replaced by AI and robotics. After all, the huge amount of money available at the elite level of sport mean that few organisations will ever see a desire to cut costs in pitch preparation. And at an amateur level, the impact of automation will have to wait until the costs of such technology become affordable.

In science news around the world, Congress approves a "right to try" bill giving patients with life-threatening illnesses a new means to obtain experimental treatments, a measure that President Donald Trump is expected to sign. A Swedish court blocks plans for a controversial new headquarters building for the Nobel Foundation on central Stockholm's waterfront, saying the design would harm the waterfront's historic character. NASA's Curiosity rover is once again sampling rocks after engineers found a new way to use a drill on its robotic arm that stopped operating properly in late 2016. The world's most sensitive dark matter detector fails to snare its quarry during a year of observations. A new package of instruments arrives at the International Space Station to help scientists study record-low temperatures and look for novel quantum effects.

Samsung Research America (SRA) is going to launch a new artificial intelligence centre at the MaRS Discovery District in Toronto. The new AI centre will be Samsung's second in North America, with the other in Mountain View, Cali. It also comes shortly after the announcement of two newly established AI centres in Cambridge, U.K. and Moscow, Russia. The Toronto centre will be led by Dr. Sven Dickinson, professor on leave and past chair of the Department of Computer Science at the University of Toronto. Dickinson is an expert in computer vision technologies.

The black box of the algorithm dictates that no one person really knows what data--or what combinations of data--will prove significant. While companies are generally up-front about what data is input to refine and upgrade the decision-making processes, the black box of the algorithm dictates that no one person really knows what data--or what combinations of data--will prove significant. With a little trial and error, for example, Joe Deville, a researcher at Lancaster University in the U.K., discovered that simply changing the screen resolution on his phone seemed to result in a different score for some algorithmic lenders, while others have suggested that actions as mysterious as charging your phone more often may produce a more favorable result. Meanwhile, the chief executive of Branch speaks whimsically of their machine-learning algorithm as a "robot in the sky" -- a kind of AI fairy that makes lending decisions based on whether its users are naughty or nice. If you're unhappy with the number that emerges from the black box, there's little you can do to change or dispute it.

Merchandising-related leaks happen, but they're not nearly so common as something like a retail listing. That's what we're dealing with today, though: it appears that next Assassin's Creed--apparently named Assassin's Creed: Odyssey and set in Ancient Greece-- was leaked by a keychain. It depicts, along with the name, a covered Greek-style helmet with a plume on top which, along with the name, strongly imply the Greek setting. Kotaku has its own image of the same keychain from a different source, and says that the Greek setting lines up with what it's been hearing from other sources. Kotaku also says that it's going to bring dialogue options and deep customization to the game for the first time.

Spanish police are introducing an artificial-intelligence system to detect liars.Credit: SubstanceP/Getty If you live in southern Spain, last June was not a good time to lose your smartphone and, as a way of getting an insurance payout, falsely claiming that you had been mugged. Ten police forces in Murcia and Malaga had some extra help in spotting your deceit: a computer tool that analysed statements given to officers about robberies and identified the telltale signs of a lie. According to results published in the journal Knowledge-Based Systems, the algorithm was so good at pointing officers towards false claimants that detection of such offences in one week was an impressive 31 and 49 for the respective regions, up from an average of 3 and 12 closed cases over the entire month (L. The government in Madrid is now rolling the system out across the country, and its developers are trying to apply its machine-learning methods to help detect other types of crime. In this case, the algorithm flagged up suspicious wording (based on a training set of statements known to be true and false), and left it up to the police to question suspects and get them to confess.

Dr. Ulrich Kampffmeyer is the Managing Director of Project Consult in Hamburg, Germany and a renowned expert on digital transformations, business intelligence and enterprise content management. I had the opportunity to sit down with him in May and discuss the GDPR, artificial intelligence and social issues emerging from the dense, digital fog we all find ourselves in. Ulrich, you write and teach extensively about the cultural and social changes in work environments that are a direct result of the emergence of digital transformations. Now that data is at the fingertips of everyone, what changes should society expect that the business world may have already? The pace of digital transformation accelerates day by day. Cloud technologies, artificial intelligence, IoT and other developments are happening so fast that there is a danger they'll get out of control.

Advancements in AI systems and neural networks have also influenced the fields of art and photography. We all want our pictures to be good in quality while sharing on social media or with someone but when we have low-quality cameras in our mobile phones, it seems to be a drawback. Whereas, the development of new neural network has solved the problem of average quality photos, it helps in improving the quality of photos matching to DSLR quality. According to the reports, scientists from Switzerland at ETH Zurich have created a tool using deep learning neural networks that will transform low-quality pictures taken by smartphone cameras into DSLR-quality pictures. Initially, researchers trained deep learning system with the pictures of same scenes taken by mobile camera as well as DSLR camera. In simple words, it is a software that is trained to feed any image into the system and utilize the picture quality of a targeted camera to give final results.