It has been a year since Microsoft released the Azure IP Advantage program – a service that "provides the industry's most comprehensive protection against intellectual property (IP) risks" by making 10,000 of their global patents available to Azure clients. A lot can happen in a year. With the pace of change in high tech, you may be wondering how well Azure IP Advantage has weathered in areas of major technological development since the portfolio was introduced. One of the most rapidly expanding and evolving areas of high tech is artificial intelligence (AI). First, let's look at how different the Azure IP Advantage portfolio looks now from when it was first introduced.

There can be no doubt, artificial intelligence (AI) helps defend government and business systems from cyberattacks, but conversely, AI systems can be used to augment attacks against government and corporate, even SMB systems. For TechRepublic and ZDNet, I'm Dan Patterson and it's a pleasure today to speak with Mark Gazit, the CEO of ThetaRay. One of the biggest targets for cybercriminals, and cybercriminals deploying AI solutions, is the financial service industries. I wonder if you could help us understand how financial crime is being transformed by technology and artificial intelligence.

In the famous sci-fi book (and movie), the "precrime" police is able to stop murders before they happen thanks to humans who predict the future. The concept is fascinating and is an interesting example of a possible use of Artificial intelligence. But we would leave the decision and control fully to the machines which we must not let happen in the real world. People have the right to own their future and no machine can be deciding on their behalf. When I read articles such as the recent one in La Stampa by Lorenzo Longhitano that a computer can predict what a chance of curing a sick person is and whether it is reasonable to admit her or him to the hospital, I think we need to draw a clear line.

For 40-year-old Mao Ya, the facial recognition camera that allows access to her apartment house is simply a useful convenience. "If I am carrying shopping bags in both hands, I just have to look ahead and the door swings open," she said. "And my 5-year-old daughter can just look up at the camera and get in. It's good for kids because they often lose their keys." But for the police, the cameras that replaced the residents' old entry cards serve quite a different purpose.

Security teams increasingly rely on machine learning and artificial intelligence to protect assets. Will a requirement to explain how they make decisions make them less effective?"But I'm not guilty," said K., "there's been a mistake. How is it even possible for someone to be guilty? Click here to view original webpage at www.csoonline.com

Artificial Intelligence has become a household word. It has also become a manipulator of all households. The unchecked explosion in AI across all businesses and business models has been a phenomenal driver of growth, but it raises questions that need to be answered. Data Scientists and AI Researchers will increasingly drive human behaviour, impact how businesses make decisions, and even steer government. Furthermore, those models will increasingly move from traditional human-understandable designs to complex Deep-Learning models that involve an incredible amount of complexity.

'We can't expect an elite KM group, no matter how large, to collect, assess, codify and turn the firm's work into a KM or exemplar database,' he says. 'The explosion of information exceeds a'human-centric' way of managing. Our work product needs to speak for itself, and existing technologies can give it a voice. Technology has to be able to get you to that intersection of what's meaningful [in] the task at hand,' he concludes. That is to say, collecting, sorting, presenting extracted data is all very nice, but if it cannot be delivered to the point of need and in a way that is truly functional and relevant, then it's not much use.

Over the past year, technology companies Uber and Waymo (the self-driving business spun out of Google) have been engaged in a battle of wills, culminating in a high-profile court case that commenced last week. Waymo has accused Uber of stealing trade secrets related to its self-driving technology. But on Friday, just four days after the trial began, Uber and Waymo announced they had reached a settlement. After a year of accusations and very public dirt-throwing, the case was ready to go to trial. But according to a report in the New York Times, Uber CEO Dara Khosrowshahi had been working behind the scenes for weeks, looking to took advantage of a golden opportunity.

In late August, Hercules Shepherd Jr, dressed in an orange jumpsuit, walked up to the dock in a Cleveland courtroom. Two nights earlier, an officer had arrested him at a traffic stop and found a small bag of cocaine, and Shepherd was about to be arraigned. Not long ago, the presiding judge would have decided Shepherd's near-term future based on a reading of court files and his own intuition. But in Cleveland and a growing number of other local and state courts, judges are now guided by computer algorithms before ruling whether criminal defendants can return to everyday life or have to stay locked up awaiting trial. In some states, the centuries-old process of releasing defendants on bail, long the province of judicial discretion, is getting help from artificial intelligence (AI).

Sentences handed down by artificial intelligence would be fairer, more efficient, transparent and accurate than those of sitting judges, according to Swinburne researchers. Dean of Swinburne Law School, Professor Dan Hunter, and Swinburne researcher Professor Mirko Bagaric say artificial intelligence (AI) could improve sentencing procedures by removing emotional bias and human error. In a paper for the Criminal Law Journal, Professors Bagaric and Hunter argue that AI sentencing would better identify, sort and calibrate all the variables associated with sentencing, including criminal history, education, drug/alcohol use, emotional motivations and employment. The pair argue that sentencing decisions are often influenced by more than 200 considerations, many of which are variables which have been established prior to court hearings. Professor Bagaric says subconscious bias plays a large part in sentencing in which judges or magistrates hand down harder penalties to offenders of a particular race or background.