Astronomers first discovered planets beyond our own solar system in the early 1990s. Since then, scientists have tagged 3,400 of these exoplanets. Now they want to determine which might be home to extraterrestrial life. But researchers sometimes spend days or even weeks analyzing a single exoplanet. New instruments like the James Webb Space Telescope, which launches in 2018, will soon be piping back so much information that scientists won't be able to manually process it.

Not so long ago the difficulty in working with data stemmed from the fact it came from different places in different forms, much of it was unstructured or at best semi structured. Getting this data into a shape where it could be analysed and used to provide insights was a tedious process, data cleaning and preparation can be time consuming processes. I have mentioned elsewhere about the "The dirty little secret of big data," being that fact, "that most data analysts spend the vast majority of their time cleaning and integrating data-- not actually analysing it." In the recent past the routines to get inside the data were repetitive and time time consuming, people were doing those very tasks that software was good at. The trouble was the software tools we tended to use did not have high levels of flexibility.

Ben Dickson is a software engineer and the founder of TechTalks. More posts by this contributor: Blockchain has the potential to revolutionize the supply chain Why it's so hard to create unbiased artificial intelligence Blockchain has the potential to revolutionize the supply chain Why it's so hard to create unbiased artificial intelligence Why it's so hard to create unbiased artificial intelligence While machine learning is introducing innovation and change to many sectors, it also is bringing trouble and worries to others. One of the most worrying aspects of emerging machine learning technologies is their invasiveness on user privacy. From rooting out your intimate and embarrassing secrets to imitating you, machine learning is making it hard to not only hide your identity but also keep ownership of it and prevent from being attributed to you words you haven't uttered and actions you haven't taken. Here are some of the technologies that might have been created with good-natured intent, but can also be used for evil deeds when put into the wrong hands.

When an app claims to be powered by "artificial intelligence" it feels like you're in the future. What does that really mean, though? We're taking a look at what buzzwords like AI, machine learning, and neural networks really mean and whether they actually help improve your apps. Just recently, Google and Microsoft both added neural network learning to their translation apps. Google said it's using machine learning to suggest playlists. Todoist says it's using AI to suggest when you should finish a task.

The hottest ticket in tech is an invitation to a banal South Florida business park, indistinguishable on the outside from countless other office buildings that dot America's suburban landscape. Humanoid robots walk down the halls, and green reptilian monsters hang out in the lounge. Cartoon fairies turn the lights on and off. Even the office equipment does the impossible. The high-definition television hanging on the wall seems perfectly normal. Incredibly, it is now levitating in midair. Get as close as you'd like, check it out from different angles.

Here is our selection for today. Many more articles and resources will appear in the Thursday digest. Apart from fighting web spam, credit card fraud and many more curious applications, machine learning is being widely used in the field of art to generate stuff. We collected a few open source projects and papers which help you understand how machine learning can be used in the field of music... Read More. Data Science Central shared its predictions for 2016.

The duo and its initial team was involved in deep research in image analysis using computer vision. They were certain that visual content was going to be pervasive across apps and websites. "With our proprietary research in hand, we set about thinking of how information available in images can be used to improve the customer experience. We decided to focus on fashion eCommerce which primarily uses images to engage and inspire their audiences."

The announcement at BlizzCon 2016 that met with the most muted response was arguably the most revolutionary. While new content for the likes of Hearthstone, Heroes of the Storm, Overwatch, and Diablo III drew appreciative roars from the Blizzard faithful, the news that Google's DeepMind branch--which is dedicated to developing sophisticated Intelligence--would be teaming up with the makers of Starcraft 2 to further its research on AI elicited more of a murmur. Perhaps the lack of enthusiasm was down to taste. After all, why would the plans of AI scientists be of interest to Starcraft 2 players? As it turns out, if the collaboration between DeepMind and Blizzard is what its developers hope it could be, players will see very tangible benefits--and so will many others outside the video game space.

Google has previously taught its artificial intelligence to play games, and it's even capable of creating its own encryption. Now, its language translation tool has used machine learning to create a'language' all of its own. In September, the search giant turned on its Google Neural Machine Translation (GNMT) system to help it automatically improve how it translates languages. The machine learning system analyses and makes sense of languages by looking at entire sentences – rather than individual phrases or words. Following several months of testing, the researchers behind the AI have seen it be able to blindly translate languages even if it's never studied one of the languages involved in the translation.

AI for short -- has already changed the way businesses operate. Its role in streamlining manufacturing and production is well-known. But AI is also transforming the way companies interact with customers. That's good news since the ability to consistently deliver an excellent customer experience is critical for companies in today's hyper-competitive economy. Here are five ways AI is changing the customer experience: Improving search engine results: People understand that search results are processed by computer programs, but the inner workings remain a mystery for most.