Microsoft has decided to pull back its first publicly available artificial intelligence (AI) robot, after a horrible test run. Earlier this week, Microsoft released an artificial intelligence named Tay, who ran through an official Twitter Account, @Tayandyou. Within 24 hours of Microsoft releasing the AI on Twitter, Tay was shut down by Microsoft because of the offensive subject matter the bot was tweeting out. In a CNN Money Article by Hope King titled "After racist tweets, Microsoft muzzles teen chat bot Tay," a comment was made by Microsoft on the incident. "Microsoft blamed Tay's behavior on online trolls," according to the article, "saying in a statement that there was a coordinated effort to trick the program's commenting skills."

The accomplishments of artificial intelligence are making it a popular topic in the news again, both for its wins and its (apparent) failures. General artificial intelligence hasn't quite lived up to its full potential yet, but more open source AI projects could help speed up development. This week, Amazon hosted an exclusive conference that brought together big names from fields such as space exploration, robotics, and artificial intelligence. The event, which was held at the Parker Palm Springs Resort in California, was invite-only and received almost no publicity. Artificial intelligence is not as advanced as you may think.

SpaceX has made good on a high-priority delivery: the world's first inflatable room for astronauts. A SpaceX Dragon cargo ship arrived at the International Space Station on Sunday, two days after launching from Cape Canaveral, Florida. Station astronauts used a big robot arm to capture the Dragon, orbiting 260 miles above the Pacific. The Dragon holds 7,000 pounds of freight, including the soft-sided compartment built by Bigelow Aerospace. The pioneering pod -- packed tightly for launch -- should swell to the size of a small bedroom once filled with air. It will be attached to the space station next weekend.

Whirring engines, hairpin turns and the occasional crash -- but today, instead of top performance cars with millions of dollars of research behind them, it's tiny drones crossing the finish line. "There's really nothing like it," said Tom Buckley, who founded the Boston Multi Rotor Club. "You're in the driver's seat, you are the pilot, you're going around these courses at very fast speeds." Today, Buckley and a couple dozen others will fire up their drones, connect their remote controllers and zoom around a track as fast as they can at BMRC's latest race. The races are often scored based on how many laps each drone can fly in two minutes.

Artificial intelligence has graduated past the infancy stage of figuring out what's in an image. Computers have previously been capable of little more than a simple game of I Spy: Name a specific object or person, and they'll show you an image containing it. But thanks to new developments in AI research, machines can now answer more complex questions, like, "What is there on the grass, except the person?" A research paper published on Thursday in Cornell University's Arxiv outlines a system that learns to identify fine-grained visual features of images, and the words associated with them. Then it combines the two into a dictionary in its digital brain.

Earlier this week, Facebook updated its iOS app offering voice descriptions of photographs uploaded by its users. A big step forward for accessibility, but it's far from the only company looking to make the world more inclusive to the visually impaired. In fact, rapid advances in artificial intelligence, machine vision and image-recognition technology are opening up the digital world to the blind and visually impaired – and helping them to interact with their surroundings. One interesting example is Austrian start-up BLITAB, which has created the first ever tactile tablet for blind and visually impaired people, dubbed "the iPad for the blind". As Kristina Tsvetanova, co-founder & CEO at BLITAB Technology, explains, the device looks similar to an ebook but displays small physical bubbles instead of using a screen, which means users can view whole pages of braille text at once, without any mechanical elements.

This weekend, the world's greatest Go player beat Google's AlphaGo, an AI program developed by Google's DeepMind unit. Lee Se-Dol, the 33-year-old South Korean has been pitted against a machine in a game that is arguably the most technically challenging thing to take place on a board of squares. Our biggest ever edition of TNW Conference is fast approaching! AlphaGo had already won three of the five games in the 1 million series, making Se-Dol's victory somewhat hollow. Machines have already beaten us mere mortals at chess – way back in 1997 when IBM's Deep Blue dispatched Garry Kasparov.

When we were born, the idea of such a small, powerful computer was a sci-fi dream, and now these smart-devices are everywhere, transforming personal health, relationships and business transactions so completely that life without these seems impossible. We're entering a new era of technology that's bound to reshape the lives of our children predominantly. Yes, this is the era of artificial intelligence. Artificial intelligence is one of the most talked subjects these days, and recent advances in technology have made AI even closer to reality than most of us can imagine. In Simplest terms AI is: "The capability of a machine to imitate intelligent human behavior" Artificial intelligence is a program that does a task and its performance gets better every time it does that task.

Perel told ABC News that he initially thought a bomb had been detonated outside the building, adding he was "99 percent ok, I just have a bruise." After realizing what had happened, he quickly removed the memory card from the GoPro camera attached to the DJI drone. "While sitting at my desk I heard what sounded like a missile followed by a huge bang and glass all over me," he wrote in the YouTube video description. "Turns out someone lost control of their drone.

Here we show the trickery as it evolves. The most important aspects to pay important to are the final predictions (bottom left) and the loss history (bottom right). While the results might initially seem quite drastic, and it might seem logical to completely distrust any results from neural networks that is probably a bit exaggerated. Since we had access to the complete network and could train as we wanted the results are significantly more successful than they would be on a blackbox network (which is the case for most public image APIs for example). The more important take away message is that the networks trained, even if they have been trained on millions of images, still do not really'understand' the images.