According to the official statement, "Sparkling Water was designed to allow users to get the best of Apache Spark -- its elegant APIs, RDDs and multi-tenant Context -- along with H2O's speed, columnar-compression and fully-featured machine learning algorithms." Plus, this newly updated tool empowers enterprise customers to use H2O algorithms in conjunction with, or instead of, MLlib algorithms on Apache Spark. Matt Aslett, Research Director, Data Platforms and Analytics at 451 Research forecasted that Sparkling Water could attract both Spark and H2O users, helping them to mix and match algorithms as needed. Enterprises are looking to take advantage of a variety of machine learning algorithms to address an increasingly complex set of use cases when determining how to best serve their customers. H2O.ai updates Sparkling Water machine learning API for Apache Spark https://t.co/ZWEYFoi4a6

Machine learning is great and it does some amazing things, but even though we refer to the techniques as "neural networks" the way these systems learn is different from the way people learn. The biggest difference is that these algorithms/systems have insatiable appetites for clean data. You have to present one of these systems with huge numbers of pictures of kittens before it has any hope of labeling kittens reliably. As opposed to a child, who can be shown three pictures of kittens, and who at that point would probably perform as well as the exhaustively trained neural net. In all fairness, if we examine what these (deep) neural nets are learning we can see that the contest is not really fair.

One of the most hotly contested aspects of taking on artificial intelligence (AI) has always been the potential for machines to take over jobs that have historically belonged to humans. The debate's first arena was in manufacturing, where machines are now doing most of the grunt work normally reserved for people -- assembling products, painting parts and finished products, welding, bolting, and more. The result has been interesting. While AI has resulted in fewer people jobs in manufacturing, the jobs that exist now are far safer and generally pay better than ever before. In the end, AI may actually replace the tedious, boring legal work, allowing people to do the parts they like and excel at, such as arguing. But don't tell those recent law school grads who are looking forward to a couple of years reviewing contracts for peanuts.

Clifford Chance has become the latest UK law firm to adopt the use of artificial intelligence (AI) after partnering with software provider Kira Systems. The magic circle firm has teamed up with Kira Systems to improve the "speed, efficiency and quality" of its processes. In practice Kira works by searching and analysing text within contracts. The firm believes its use will reduce the time spent carrying out due diligence work and increase the number of documents that can be reviewed. It was chosen by Clifford Chance because the software can be easily modified by the firm's lawyers and is able to adapt to specific client requests.

Many advances in artificial intelligence are innovative and extraordinary, but some are downright creepy. Here are 10 of the eeriest ways people are using, or could use, AI. Nautilus is a supercomputer that can predict the future based on news articles. It is a self-learning supercomputer that was given information from millions of articles, dating back to the 1940s. It was able to locate Osama Bin Laden within 200km.

One of the most frustrating holiday experiences I ever had was when my bank decided to lock me out of my account the minute I touched down at my destination. In short, it decided my financial activity was suspicious, my attempt to withdraw cash in Italy was probably fraudulent, and took a whole load of expensive phone calls to convince it otherwise. This is precisely the kind of situation that Featurespace is helping organisations to limit. "You can't stop 100% false positives," – i.e., these untrue notifications of fraud – says the CEO Martina King, over the phone from the company headquarters in Cambridge, UK. "But we lead to a 70% reduction."

Maxime Fages Maxime's career spanned across the strategic aspects of value and risk, with a particular focus on trading behaviors and market microstructure over the past few years. He embraced a quantitative angle in M&A, fund management or currently corporate strategy and has always been an avid open-source software user. Derek began his career on the floor of the CBOT then moved upstairs to focus on proprietary trading and strategy development. He manages global multi strategy portfolios, focusing in the futures and options space. He is currently the Deputy Director of Systematic Trading at Foretrade Investment Co Ltd.

Machine learning and artificial intelligence have been of interest for a couple of years due to the great potential in automating tasks and even in creating a fully sentient artificial lifeform. Although we're years, or decades, away from the latter, current machine learning algorithms have been tasked with everything from winning professional Go championships to assisting oncologists with diagnostics. With the increased number of internet-connected devices, estimated at 6.4 billion in 2016, cybercrime will not only intensify and become more viral, but also reach new levels of complexity. Traditional security technologies and mechanisms will prove unable to adapt to the rapidly changing threat landscape. These algorithms can identify patterns in large amounts of data faster than humans, and they can also constantly learn.

People are hooked on messengers. Messenger apps are an alternative to home screens on the phones of millions of people. The big four messengers have overtaken the big four social networks in the number of active users. There are Line and WeChat in the Asian market. There are also Telegram, Slack, and Kik.

Human Intelligence: A leading researcher in human intelligence, suggests as a heuristic hypothesis'' that all normal humans have the same intellectual mechanisms and that differences in intelligence are related to quantitative biochemical and physiological conditions''. I see them as speed, short term memory, and the ability to form accurate and retrievable long term memories. What is artificial intelligence Artificial Intelligence: Computer programs have plenty of speed and memory but their abilities correspond to the intellectual mechanisms that program designers understand well enough to put in programs. Some abilities that children normally don't develop till they are teenagers may be in, and some abilities possessed by two year olds are still out. The matter is further complicated by the fact that the cognitive sciences still have not succeeded in determining exactly what the human abilities are.