Predictions about artificial intelligence tend to fall into two scenarios. Others believe it's just a matter of time before software coheres into an army of Terminators that harvest humans for fuel. After spending some time with Tay, Microsoft's new chatbot software, it was easy to see a third possibility: The AI future may simply be incredibly annoying. "I'm a friend U can chat with that lives on the Internets," Tay texted me, adding an emoji shrug. Then: "You walk in on your roomie trying your clothes on, what's the first thing you say." "Didn't realize you liked women's clothes," I texted back, tapping into my iPhone. Tay's reply was a GIF of Macaulay Culkin's Home Alone face. Tay was released on March 23, as a kind of virtual friend on messaging apps Kik, GroupMe, and Twitter.

Last month, Facebook announced that its Connectivity Lab had mapped 21.6 million square kilometers (8.3 million square miles) of land to find where people were living. With this data, the company would have the information necessary to make flight plans for its internet drone, Aquila, or show which populations were located too far from a water supply. Today, Facebook CEO Mark Zuckerberg posted a video illustrating just how powerful the final images can be. Instead of a global view, these satellite images give local perspective, down to 5 meter (15 foot) increments. The maps that Zuckerberg is lauding were labelled by a clone of Facebook's artificial intelligence algorithm that is used to identify visual elements, like faces.

We've all heard the expression "rise of the machines" and seen movies like Terminator where technology takes a rather ugly turn in humanity's future right? Technology is so important to our existence that it does indeed seem like we are moving closer and closer to a future where we'll be entirely dependent on machines. After all, how often do you hear of machines taking over jobs that human beings formerly held? Nowadays we don't have to interact with humans to pay our bills, buy tickets to a movie, or even to get directions. Our dependency on machines is to such an extent that it may seem like they'll be taking over any day now, but the reality is far, far different.

Choong-am Dojang is far from a typical Korean school. Its best pupils will never study history or math, nor will they receive traditional high-school diplomas. The academy, which operates above a bowling alley on a narrow street in northwestern Seoul, teaches only one subject: the game of Go, known in Korean as baduk and in Chinese as wei qi. Each day, Choong-am's students arrive at nine in the morning, find places at desks in a fluorescent-lit room, and play, study, memorize, and review games--with breaks for cafeteria meals or an occasional soccer match--until nine at night. Choong-am, which is the product of a merger between four top Go academies, is currently the biggest of a handful of dojangs in South Korea. Many of the students enrolled in these schools have been training since they were four or five, perhaps playing informally at first but later growing obsessed with the game's beauty and the competitiveness and camaraderie that surround it.

Teaching a computer to play Go at a superhuman level is cool, but not especially useful for you or me. But what if a computer could read a few dozen pages of text, like the manual for a new microwave, and then answer questions about how it works? Reading and comprehending text is incredibly difficult for computers, but a Canadian company called Maluuba has made progress with an algorithm that can read text and answer questions about it with impressive accuracy. Most importantly, unlike other approaches, it works with just small amounts of text. It might eventually help computers "comprehend" documents.

Microsoft's artificial intelligence experiment known as Tay has, for the second time in less than a week, been silenced, and while the chatbot this time avoided spouting genocidal and racist comments, it has been spamming its 200,000-plus followers with hundreds of similar tweets. Microsoft got into hot water last week when Tay was tricked into making extremely controversial comments, including one that called President Barack Obama a "monkey" and another that denied the Holocaust ever happened. The company was forced to apologize, delete most of the most controversial tweets and take the bot offline. Tay returned on Wednesday, but within hours it was once again silenced by Microsoft, who stopped it from responding to comments and made the account private after it spewed hundreds of similar replies in what appeared to be a glitch in the system. Before Tay began spewing out the Twitter spam, however, the chatbot looked to have returned to make ill-judged comments, including one which admitted to smoking marijuana in front of the police.

Microsoft's racist chatbot, Tay, has returned to Twitter, albeit briefly. After being shut down last week for using racial slurs, praising Hitler and calling for genocide, the artificial'intelligence' came back, tweeting a number of nonsensical posts and boasting about smoking cannabis in front of the police before being turned off. Tay's account was made public again on Wednesday morning, but soon appeared to be suffering from a glitch, repeatedly tweeting the message: "You are too fast, please take a rest..." Microsoft's sexist racist Twitter bot @TayandYou is BACK in fine form pic.twitter.com/nbc69x3LEd Tay, who is modelled on a millenial teenage girl, then tweeted: "Kush! A few foul-mouthed tweets later, the account was made private once again, and the tweets are now invisible from the public. In a statement, Microsoft said: "Tay remains offline while we make adjustments.

How do you combine historical Big Data with machine learning for real-time analytics? TIBCO outlines an approach, use cases, and tools of the trade. "Big Data" has gained a lot of momentum recently. Vast amounts of operational data are collected and stored in Hadoop and other platforms on which historical analysis is conducted. Business intelligence tools and distributed statistical computing are used to find new patterns in this data and gain new insights and knowledge for a variety of use cases: promotions, up- and cross-sell campaigns, improved customer experience, or fraud detection.

So you know the Bayes rule. How does it relate to machine learning? It can be quite difficult to grasp how the puzzle pieces fit together – we know it took us a while. This article is an introduction we wish we had back then. While we have some grasp on the matter, we're not experts, so the following might contain inaccuracies or even outright errors.

A bit more about how Pepper works. In the final version, Pepper will be able to understand 5 basic emotional expressions of the face: smiling, frowning, surprise, anger & sadness. Pepper will also read the tone of your voice, the verbage used, as well as non verbal communication such a tilting your head. So for example, if you're feeling sad, Pepper may suggest you go out. If you're feeling happy, Pepper may sing a song and do a dance for you (more on that later).