Ladies and gentlemen, place your bets, today we are going to do our best to beat one of the most frightening opponents that you can face in finance: a monkey. As you probably already know, in this blog we are all quite obsessed with predicting trends and returns, you can find other nice attempts in'Markov Switching Regimes say… bear or bullish?' by mplanaslasa or'Predict returns using historical patterns' by fjrodriguez2. Today, we are trying to predict the sign of tomorrow's return for different currency pairs, and I can assure you that a monkey making random bets on the sign and getting it right 50% of the time is going to be a tough benchmark. We are going to use an off the shelf machine learning algorithm, the support vector classifier. Support Vector Machines are an incredibly powerful method to solve regression and classification tasks.

Machine learning has been put to many uses that involve analyzing Big Data to solve issues or address opportunities. It's been applied to delivering personalized video or article recommendations, handling fraud detection, clustering news, and predicting customer churn, for example. Now it – along with other computer science breakthroughs – is playing a role in a solution aimed at reinventing the science of databases, the places where all the Big Data that informs analytics is stored from the start. Deep Engine from Deep Information Sciences "is an adaptive database kernel and information orchestration system that leverages machine learning to completely transform how scalability and performance are achieved," says chief strategy officer Chad Jones. The company initially is targeting the Deep Engine hybrid transactional and analytical processing (HTAP) solution that handles multiple simultaneous workloads on the fly for the structured data market.

Former trader Jerome Kerviel lost Societe Generale 4.9 billion ( 6.4 billion) in rogue trades. Top investment banks like Goldman Sachs and UBS are spotting insider trading and other rule-breaking using a machine learning platform that was first developed to help the US catch terrorists. Digital Reasoning has "more than half the bulge bracket firms using our technology to spot inside behaviours and insider threats," according to Kiran Narsu, senior vice president of commercial sales at the company. Digital Reasonings has developed a machine learning platform that can learn patterns of language rather than simply looking for key words, helping banks spot things like insider trading and price fixing with a greater degree of accuracy than traditional compliance tools. Its smart platform can be trained to spot trading abuse, collusion, and market manipulation.

Microsoft has broadened open-source access to its Computational Network Toolkit, in a move that underscores the ongoing arms race around machine learning technology. CNTK had initially been made available on Microsoft's Codeplex site in April 2015 through under an academic license, but now it has been... Constellation Research, Constellation SuperNova Awards, Connected Enterprise, and the Constellation Research logo are trademarks of Constellation Research, Inc. All other products and services listed herein are trademarks of their respective companies.

Chrissie Lightfoot takes a detailed look at how AI is used by law firms and what is on the horizon. As a futurist, an entrepreneur, and a lawyer, I always get asked, 'What do you think is the next big thing in the legal world?' I always begin my response with a catch-all reply: 'The next big thing is anything that helps you attract and keep a client. No client equals no business. A bit of a cliché, I know.

IBM's Watson artificial intelligence supercomputer is going to lend its insights to help enhance the fan experience at the U.S. Open Tennis Championships. It will do so via a new cognitive-based concierge feature in the tournament's official mobile app. To enhance the fan experience at the Billie Jean King National Tennis Center, the mobile app will pilot a Watson-enabled discovery tool that allows fans to input natural language questions and receive immediate responses about a range of tournament topics, such as transportation and directions, food and drink options, and on-site services and facilities. Accessible via the cloud, Watson will offer cognitive computing, cloud, and analytics. By tapping into the natural language software from the Watson platform, the A.I.-infused app will enable fans to ask questions in natural language and get the information they need to plan and navigate their tournament experience.

New York City-based Datorama, a marketing analytics provider, closed on a 32 million round of Series C funding led by Lightspeed Venture Partners. It plans to invest the funds in artificial intelligence (AI) technologies to support its machine-learning capabilities. Datorama has raised 50 million since it was founded in 2012. Before founding the company, Sarig spent nearly three years in at MediaMind (now Sizmek), most recently as vice president of research and development. He also worked for Swets Information Services and Pointech Information Systems and spent six years as an officer in the Israeli Navy.

Stephen Hawking and Elon Musk have warned us of the dangers of Artificial Intelligence, but is AI really going to be the downfall of humanity?

Cool, colorful, creative Perceptron Learning Algorithm in plain words https://t.co/LPmMTPsRHb Maximum Likelihood Estimate (MLE) and Logistic Regression simplified: https://t.co/CUdOhpP4ko

Mitsubishi Electric has developed what may be a crucial next step in the development of artificial intelligence systems. Its "compact AI" technology eliminates the need for large servers and can be embedded in a far wider scope of devices and machines than existing AI systems can. The company says that, by filtering information necessary for analysis, the new technology can drastically reduce the processes involved in computation for AI systems. The development can trim the computation needed for certain tasks by as much as 90%, according to Mitsubishi Electric. It plans to start offering applications for compact AI technology, such as autonomous driving systems and smarter industrial robots and machine tools, as early as 2017, a company source said.