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Global warming and pollution are causing severe stress to coral reefs across the world. Researchers from the University of California Berkeley and University of Queensland developed a deep learning process that automatically analyzes reef photos that will help measure reef health and changes over time. Reefs provide food and shelter for more than a quarter of all marine species, and support fish stocks that feed more than a billion people and provide jobs to millions of people in coastal areas. The new technology "will allow the world's scientists to more quickly assess the health of coral reefs at scales never dreamed of before," said Ove Hoegh-Guldberg, chief scientist of the global reef record and a professor at the University of Queensland. With that information, they can more effectively take steps to protect and save them.

Recurrent neural networks, and in particular long short-term memory networks (LSTMs), are a remarkably effective tool for sequence processing that learn a dense black-box hidden representation of their sequential input. Researchers interested in better understanding these models have studied the changes in hidden state representations over time and noticed some interpretable patterns but also significant noise. We present LSTMVis a visual analysis tool for recurrent neural networks with a focus on understanding these hidden state dynamics. The tool allows a user to select a hypothesis input range to focus on local state changes, to match these states changes to similar patterns in a large data set, and to align these results with structural annotations from their domain. We provide data for the tool to analyze specific hidden state properties on dataset containing nesting, phrase structure, and chord progressions, and demonstrate how the tool can be used to isolate patterns for further statistical analysis.

LONDON - Market Publishers Ltd. is thrilled to remind you about MRMW North America Conference, which is scheduled for July 18th-19th, 2016. This forthcoming outstanding conference will be held at the Hilton Fort Worth (Texas, the USA). As one of the official media partners of MRMW North America 2016, Market Publishers, on behalf of the organising company, Merlien Institute, invites everyone interested in the latest mobile market research technologies and innovative market research to join this Event! This year, MRMW North America 2016 as always will welcome outstanding speakers, provide an abundance of business opportunities, cover an expanded range of topics and grant access to unique case studies and workshops from top research experts. The internet of things, smart data acquisitions, artificial intelligence and machine learning are amid the hottest issues on the agenda of MRMW North America 2016.

Ask Apple's Siri digital assistant if she's evil, and she'll respond curtly, "Not really." Repeat a famous line from the movie "2001: A Space Odyssey," in which a computer on a spaceship kills nearly all the human crew, and Siri groans. And who can blame her? We humans have a morbid fascination with machines rising up to wipe us out or to enslave us as cocooned, flesh-and-blood battery packs. You can see that vision of the future streaming over Netflix whenever you want.

For warehouse workers and truck drivers, the future does not look rosy. But those of us with more white collar gigs don't have to panic yet, right? Well, maybe some of us do. Sorry, lawyers, we know you're already spinning from a lousy job market and tons of law school debt, but it looks like you're going to face competition from artificial intelligence sooner rather than later. The brainchild of London-born Stanford University student Joshua Browder, the artificial intelligence-driven chatbot has already gotten 160,000 people out of parking tickets.

There's been a lot of press recently about Artificial Intelligence, or AI. Put simply, AI can be defined as the "capability of a machine to imitate intelligent human behavior" – in this case, the fairly unique human trait of intelligence. But intelligence can mean a lot of things – anything from finding the shortest distance from A to B to detecting a cancerous cell in a collection of thousands of slide photos. To understand why AI is such a popular news topic these days, we first have to understand what it is. The first thing to understand about AI is there are two distinct types: weak AI, which we can think of as specific intelligence, and strong AI, which we can think of as general intelligence.

Before U.K. voters went to the polls to decide whether to remain in the European Union, at least three prominent hedge funds sought ways to predict the outcome. Brevan Howard Asset Management, run by billionaire Alan Howard, used artificial intelligence technology to gauge sentiment on social media and conducted a poll prior to the June 23 referendum, a person with knowledge of the firm said. Robert Citrone's Discovery Capital Management developed a model using algorithms to track voting districts, while Crispin Odey's Odey Asset Management also surveyed citizens. The technologies and polling helped generate profits or minimized losses for the firms. Public surveys on the eve of the referendum suggested the vote was tight between the two camps, even as financial markets and betting odds indicated "Remain" was on course to win.

None of this rising popularity, however, would be possible without recent technological improvements. This goes beyond the improved machine learning tools that are now available to many businesses the world over, although that is certainly a significant development. When it comes to improving technologies that make it possible for machine learning to prosper, the first place to look is the spread of scalable computing power. Machine learning requires an immense amount of computing power to function correctly, a level that simply wasn't possible years ago. Now, in part due to the rise of the cloud, that computing power is more within reach than ever before.