We propose a decentralized Maximum Likelihood solution for estimating the stochastic renewable power generation and demand in single bus Direct Current (DC) MicroGrids (MGs), with high penetration of droop controlled power electronic converters. The solution relies on the fact that the primary control parameters are set in accordance with the local power generation status of the generators. Therefore, the steady state voltage is inherently dependent on the generation capacities and the load, through a non-linear parametric model, which can be estimated. To have a well conditioned estimation problem, our solution avoids the use of an external communication interface and utilizes controlled voltage disturbances to perform distributed training. Using this tool, we develop an efficient, decentralized Maximum Likelihood Estimator (MLE) and formulate the sufficient condition for the existence of the globally optimal solution. The numerical results illustrate the promising performance of our MLE algorithm.

This turns out to have been an awkward thing for Wells Fargo Chief Executive Officer John Stumpf to have said about Carrie Tolstedt, Wells Fargo's head of Community Banking, when she announced her retirement in July: "A trusted colleague and dear friend, Carrie Tolstedt has been one of our most valuable Wells Fargo leaders, a standard-bearer of our culture, a champion for our customers, and a role model for responsible, principled and inclusive leadership," said John Stumpf, Wells Fargo's chairman and chief executive officer. It turns out that Wells Fargo's community banking culture involved creating millions of fake accounts for customers to satisfy the bank's frenzy for cross-selling products and services. And Tolstedt now gets to bear the standard for that culture, as the Senate investigates, Fortune reports that "she will be walking away with 124.6 million in stock, options, and restricted Wells Fargo shares," and shareholders have called for her to be held responsible for the fake accounts by clawing back her pay: Another investor said: "If this person presided over this, why no accountability? We have share-based pay so that it can be clawed back when people have been earning bonuses under false pretences, and if fraudulently opening client accounts isn't false pretences, then I don't know what is." Wells Fargo's cross-selling scandal is so odd because it is both at the absolute core of the bank's business, and also curiously irrelevant.

Wells Fargo -- The bank will eliminate product sales goals for retail bankers and strengthen oversight, controls, and training. Wells Fargo will be the subject of a Senate Banking Committee hearing into its sales practices, after the bank settled a case with regulators by paying a 185 million penalty. The panel wants to question CEO John Stumpf about the practices that led to the case. UnitedHealth Group -- The health insurer's Optum unit and Quest Diagnostics formed a partnership aimed at reducing billing complexity, as well as providing more transparency into health care costs. Separately, UnitedHealth was rated as a "top pick" at Jefferies because of attractive valuation and a best-in-class management team.

Lumiata, a healthcare analytics company, said it will launch a tool called Risk Matrix that takes a patient's electronics record, combines it with artificial intelligence and risk algorithms to predict health over time for people with chronic conditions. The software, designed for insurers and healthcare providers, is designed to analyze models based on 175 million patient record years and provide clinical rationale for each prediction. Risk Matrix provides real-time predictions for more than 20 major diseases including congestive heart failure and diabetes. Insurers and companies are offering programs for chronic conditions, but often identify too many people as risks.

After receiving her diploma, recent UT PGE graduate Katy Hanson went to work side-by-side the world's most recognized technology platform. In 2011 IBM's Artificial Intelligence (AI) platform, Watson, went up against the all-time most winning JEOPARDY! Within a few categories Watson's depth and breadth of knowledge surpassed the human brain providing Watson with the win. At that moment, Watson demonstrated to the world the powerful role AI will play in the 21st century. Watson hung up his game-show career, but has been incredibly busy over the past five years gaining vast amounts of insights on many fields, including oil and gas.

We have seen how the internet of things and the growing phenomenon of'big data' will throw up major problems for consumers and citizens, problems that have as yet barely been grasped by most policy-makers. In this world of growing complexity, the potential for an unintended consequence becomes greater and greater from machines performing an action that was not anticipated. There are key issues, too, about our reliance on data at a time of massive data generation, data storing and data preservation which have the potential to both obscure results and generate injustices. Perhaps the greatest issue that we now face is caused by our blind faith in machines. We have invested them with certainty and – as we have pointed out – we trust them. Part of the reason for this is an odd confusion that has conflated the machines of the industrial age with the machines of the information age.

What better way to demonstrate the capabilities of IBM's artificial intelligence system, Watson, than to show it working its hardest, and when it really matters? For the film IBM partnered with oil and gas company Woodside, and creative agency the Barbarian Group, to create '70 Miles from Shore with Watson: Woodside Energy and IBM'. The result is a two-minute journey that shows IBM's Watson working and learning, on one of the toughest work sites in the world – an oil rig. To produce a film on such an especially challenging scale required an experienced set of hands, and PSN Australia was enlisted for the job through Production Service Network's U.S. Liaison Carolyn Hill. Choosing to shoot on the rig for real as opposed to a studio levied some strict safety regulations on the team that had not been previously encountered.

Symmetry Master evaluated they symmetry of each person's face and AntiAgeist estimated the difference between the chronological and perceived age. Once these parameters were determined, the fifth robot, called MADIS, compared each selfie to models and actors within their age and ethnic groups were are stored in a database. 'We are very pleased with the Ai's performance in achieving 100 percent accuracy in predicting the I'm a Singer competition's results,' Dr. Min Wanli, Alibaba Cloud's chief scientist for artificial intelligence, said in a statement following the show, according to the Wall Street Journal. '[The result] is very random and almost impossible to predict using human intelligence,' said Min Wanli, chief scientist for artificial intelligence at Alibaba Cloud.