Attendees came together to discover the latest advances in deep learning from leading innovators in the field, and explored how smart artificial intelligence will impact communications, manufacturing, healthcare & transportation.

IBM asked me to give a speech at their World of Watson event this week. In preparing my remarks, I realized what I will be talking about is so important, yet most don't understand what is happening. A once-in-a-lifetime shift in the way we communicate, gain, share and distribute information. And we are just in the first inning of this game. If you will be there, I look forward to saying hello in person.

Wealth Management is the highest growth businesses for any medium to large financial institution. It also is the highest customer touch segment of banking and is fostered on long term (read extremely lucrative advisory) relationships. This three part series explores the automated "Robo-advisor" movement in the first post. We will cover the business background and some definitions . The second post will focus on the overall business model & main functions of a Robo-advisor.

An artificial intelligence "judge" that can accurately predict many of Europe's top human rights court rulings has been created by a team of computer scientists and legal experts. The AI system--developed by researchers from University College London, the University of Sheffield, and the University of Pennsylvania--parsed 584 cases which had previously been heard at the European Court of Human Rights (ECHR), and successfully predicted 79 percent of the decisions. A machine learning algorithm was trained to search for patterns in English-language datasets relating to three articles of the European Convention on Human Rights: Article 3, concerning torture and inhuman and degrading treatment; Article 6, which protects the right to fair trial; and Article 8, on the right to a private and family life. The cases examined were equally split between those that did find rights violations and those that didn't. Despite the AI's success, the legal profession is safe for now.

Apple says their voice recognition app Siri is improved. USA TODAY's Jefferson Graham puts Siri through a few tests to find out. The Tap is similar to Echo, but requires you to press a button to speak to Alexa. AI is now mentioned and discussed at nearly every major tech company event these days, and it's incorporated into a rapidly growing percentage of the news these companies are generating. More importantly, the kind of "contextual intelligence" AI can enable is finally starting to become real for people.

A software platform that mines data and uses machine learning to boost household energy efficiency has taken out top honours at Energy Hack 2016 – a two-day energy and technology brainstorm held in Melbourne over the weekend. The event, hosted by the University of Melbourne's Energy Institute and upstart online electricity retailer Powershop, brought together 80 participants to form 20 teams to unlock ideas and stimulate entrepreneurship in the energy industry. Eight judges saw pitches for 13 creative technology ideas, ranging from an energy management chatbot, to a matchmaking service for renewable energy project owners and investors, to an app to educate primary school children, and an energy load matching algorithm. The winners, a team of PhD students called Planet Lovers, were chosen for their design of a platform that uses data mining techniques and machine learning to help consumers use energy more efficiently. "We believe that existing energy services don't use the full potential of big data to provide deep insights for consumers," said Planet Lovers co-founder Zahra Ghafoori.

For this setup we need adjusted data for all Dow-30 stocks since 01/2000. The DLPAL p-indicator workspace setup is shown below. We have applied a profit target and stop-loss of 2% because we are interested in short-term directional price action. We also marked "Show All results" because we then would like to calculate the P-Dow indicator value. The longer-term trend is removed from the results by checking "Detrend All results.

With the proliferating "smart" products such as smartphones, smart home devices, machines are currently being made "smarter" than humans. While this is the next "it" subject for the future generations, as with all aspects, there are risks that come with it. There are over 8,000 leading researchers and scientists including Stephen Hawking, Elon Musk, and Bill Gates, who signed an open letter insinuating the AI's possible detrimental effects to humanity. Tech Crunch writes, "Their main concern is that an existential risk faces humanity: an AI in control of autonomous weapons." In addition to that, Stephen Hawking says, "Success in creating AI would be the biggest event in human history," but he adds, "Unfortunately, it might also be the last, unless we learn how to avoid the risks." In an Observer Opinion report, there are U.S. scientists who are already using algorithms on computers, which can predict military strategies of terrorists.

A team of researchers has used an artificial intelligence system to correctly predict the outcome of hundreds of human rights cases. The AI, developed in collaboration between University College London, the University of Sheffield and the University of Pennsylvania, analysed a variety of cases heard in the European Court of Human Rights. It was then able to predict the correct verdict with an accuracy of 79%. While the results make a convincing case for the use of machine learning in legal settings, the researchers don't believe it will mark the end of lawyers and judges. "There is a lot of hype about AI but we don't see it replacing judges or lawyers any time soon," said Dr Nikolaos Aletras, leader of the study at UCL. "What we do think is they'd find it useful for rapidly identifying patterns in cases that lead to certain outcomes."

In recent months, security researchers have shown that machine learning algorithms can be reverse-engineered and made to expose user data, like personal photos or health data. So how can we protect that information? New research from OpenAI and Google shows a way to build AI that never sees personal data, but is able to function as if it had. Ian Goodfellow, a researcher at OpenAI, compares the system to medical school. "The doctors who teach in medical school have learned everything they know from decades of experience working with specific individual people, and as a side effect they know a lot of private medical histories," Goodfellow says.