Automatically identifying that an image is not suitable/safe for work (NSFW), including offensive and adult images, is an important problem which researchers have been trying to tackle for decades. Since images and user-generated content dominate the Internet today, filtering NSFW images becomes an essential component of Web and mobile applications. With the evolution of computer vision, improved training data, and deep learning algorithms, computers are now able to automatically classify NSFW image content with greater precision. Defining NSFW material is subjective and the task of identifying these images is non-trivial. Moreover, what may be objectionable in one context can be suitable in another.

President Barack Obama has set a goal of sending humans to Mars by the 2030s and getting them safely home again. In a commentary appearing on CNN.com, Obama set an ultimate goal of setting up a habitat on Mars so astronauts can live there for an extended time. "When our Apollo astronauts looked back from space, they realized that while their mission was to explore the moon, they had'in fact discovered the Earth,' " Obama wrote. "If we make our leadership in space even stronger in this century than it was in the last, we won't just benefit from related advances in energy, medicine, agriculture and artificial intelligence, we'll benefit from a better understanding of our environment and ourselves." Talking about his "sense of wonder" about the U.S. space program, Obama wrote about the country's next chapter in space exploration – Mars.

When Microsoft bought Mojang, the makers of the insanely popular Minecraft, in a surprise 2.5 billion deal in September 2014, nobody knew what to think. The game seemed an odd fit for Microsoft, whose biggest moneymakers are its productivity software and Windows PC operating system. Minecraft's millions of players fretted that the game was destined to be ruined under its new corporate parent, or that Microsoft would restrict the game to its own Xbox and Windows platforms. Two years later, Minecraft is more popular and widely available than ever. Since the beginning of this year, Mojang says, people have bought 53,000 copies of Minecraft every single day.

Guest blog post by Christopher Dole and other contributors, originally posted here. Deep Learning is one of the most revolutionary and disruptive technologies ever developed in Data Science. Essentially, this is a class of algorithms inspired by how the human brain works, and it has the ability to automate and replace most of the world's jobs. This is what enables self-driving cars to function and what allows Spotify to create very customized playlists and recommendations. This is how YouTube is able to identify faces and animals in videos and how Siri can understand and process free speech in milliseconds.

Because the materials from a 3D printer aren't the most functional, their output has largely been limited to prototyping in the past. That should change in the near future with devices like MIT's own MultiFab, which can print up to 10 different materials at a time, but it still doesn't solve the problem of how to design such complex objects. That's where the new program called Foundry, created by MIT's Computer Science and Artificial Intelligence Laboratory comes in. According to MIT CSAIL, Foundry can import objects designed with traditional CAD programs like SolidWorks and then assign specific materials or properties to different parts of the object. While creating a multi-material object in the past might have required days of work and multiple 3D printers to create (assuming it was possible with existing technology at all), CSAIL says these sorts of designs can now be created in mere minutes.

Google has hired comedy writers from Pixar and The Onion in a bid to make its smart assistant more likeable. It hopes to use their talent to'infuse personality' into its AI helper, which will be used in the firm's new Pixel phones, Duo app and Home speaker. The ultimate goal is to make users feel more emotionally connected to their personal software agent and the firm believes a livelier disposition could make this happen. In a world of order-taking machines, Google Assistant aims to be a comedian. The search giant has recently hired comedy writers from Pixar and The Onion, a satire newspaper, in order to'infuse personality' into its virtual assistant that will live in Google Home (pictured) Earlier this month, Google unveiled its Pixel smartphones and eagerly awaited Home speaker that will both be designed with the smart assistant.

Just days after threatening to jail a political opponent should he win the presidency, Donald Trump's got a new campaign website that's so very … Trumpian. "Together, we are making waterboarding part of the Republican Party again," it declares. Truer words have never come out of Trump's mouth. A Trump AI generated all of the site's copy on its own. This is the work of MIT researcher Brad Hayes, who's taken his tweeting AI called DeepDrumpf and turned up its political aspirations.

Additionally, computer processing power has grown at an incredible rate while the cost of processing this data has decreased significantly, making AI more accessible. In fact, AI is everywhere, in nearly every app and device that we use every day. Apple's Siri leverages natural language processing to recognize voice commands. Facebook's deep learning facial recognition algorithm can instantly identify a person with nearly 98 percent accuracy. And Amazon, Netflix and Spotify all utilize machine learning to understand how each item in their massive catalogs not only relate to one another, but also each customer's preferences.

Kover is an out-of-core implementation of the Set Covering Machine algorithm that has been tailored for genomic biomarker discovery. It produces highly interpretable models of phenotypes. The models are rule-based and rely on the presence/absence of k-mers. The identification of genomic biomarkers is a key step towards improving diagnostic tests and therapies. We present a new reference-free method for this task that relies on a k-mer representation of genomes and a machine learning algorithm that produces intelligible models.