In 2011, Square Enix appeared to achieve the impossible, creating a new game in the Deus Ex canon that received both critical and public acclaim for a much lauded and iconic series. Human Revolution stayed true to the themes and gameplay mechanics of the original game and updated them for modern players without dumbing down. Mankind Divided is a direct sequel and certainly doesn't reinvent the wheel. If you loved Human Revolution, you'll love this, no question. Thematically the game excels, creating a near-future universe where advanced technology and poverty co-exist, against the backdrop of the threat of terrorism from a group representing'augs', humans with robotic limbs and implants. The display of segregation, paranoia and media-led hysteria is well framed, seemingly using current real world invents as inspiration.

You've probably heard of Prisma, one of the hottest apps this year. Downloaded more than 50 million times since June and powered by artificial intelligence, it uses filters to transform any photo into a stunning work of art evocative of say, Pablo Picasso or a Renaissance master. It's trending in the App Store: ranked fourth in the free photo and video category behind Snapchat, Instagram, and YouTube. But you've probably heard less about the Prisma bot with similar features and the same name, launched less than a month ago on Telegram. It's notable that one of today's most popular mobile apps waited only about a month before launching a bot, and it begs the question: Are bots replacing apps?

"People who understand superintelligent AI call it the last invention we'll ever make--the last challenge we'll ever face." This level of detail is rarely attained in an article that can be understood by anyone. Honour it be reading the whole thing, Part 2 included. Imagine taking a time machine back to 1750--a time when the world was in a permanent power outage, long-distance communication meant either yelling loudly or firing a cannon in the air, and all transportation ran on hay. When you get there, you retrieve a dude, bring him to 2015, and then walk him around and watch him react to everything. It's impossible for us to understand what it would be like for him to see shiny capsules racing by on a highway, talk to people who had been on the other side of the ocean earlier in the day, watch sports that were being played 1,000 miles away, hear a musical performance that happened 50 years ago, and play with my magical wizard rectangle that he could use to capture a real-life image or record a living moment, generate a map with a paranormal moving blue dot that shows him where he is, look at someone's face and chat with them even though they're on the other side of the country, and worlds of other inconceivable sorcery.

I also look after our NVIDIA Inception Program. Inception has been designed for start-up companies in the field of AI who are interested in having a relationship with NVIDIA that allows them to leverage our technical and go-to-market expertise. They also receive early access to software and hardware releases to help them better develop their products and platforms. What are the key factors that have enabled recent advancements in deep learning? Competition in the research and data science space has been very important in driving progress.

In 2014, Google acquired the artificial intelligence startup DeepMind, but it wasn't cheap. With a price tag of 500M, there must have been something special that Google saw in DeepMind that was worth acquiring. While the company hasn't produced any actual products for commercial use, they have focused on machine learning. Machine learning is a type of artificial intelligence that aims to provide computers with the ability to learn new information without being directed to do so. Machine learning involves the development of computer programs that have the ability to teach themselves to grow and alter themselves when presented with new data.

"Figuring out how to build ethical autonomous machines is one of the thorniest challenges in artificial intelligence today," researchers from the University of Toulouse and MIT's Media Lab argue in their paper in the journal Science on a survey that tries to work out how moral people want their self-driving cars to be. But is it the thorniest challenge? I'd argue the thorniest problem is working out some form of AI that is even capable of making ethical decisions. Self-driving algorithms have some way to go before we can even begin to consider whether they can weigh up the ethics of a situation along similar lines to Isaac Asimov's famous three laws. And you then have the knotty problem of determining what is truly ethical.

Guitarist Jeff Beck revisits an old flame, a hot rod Ford he rebuilt himself before selling to a Los Angeles area aficionado. The prospect leaves the guitar legend and lifelong hot rod aficionado steaming mad. "There's driverless cars all over the place right now, with drivers in them," says Beck, cooling off before sound check on the latest stop of a tour he's co-headlining with his blues idol, 80-year-young Buddy Guy (next stops are Saturday at Maryhill Winery in Goldendale, Wash., and Sunday at the Woodland Park Zoo Amphitheater in Seattle). "Really, (autonomous cars are) the most ridiculous thing I've ever heard. I can't imagine wanting to buy one and those involved in building this should be locked up," says Beck, who is just getting revved up on the heels of news this week that Ford and Uber are both pushing aggressively to deliver self-driving vehicles.

After the Eyjafjallajökull volcano erupted in Iceland in 2010, flight cancellations left Miranda Cheng stranded in Paris. While waiting for the ash to clear, Cheng, then a postdoctoral researcher at Harvard University studying string theory, got to thinking about a paper that had recently been posted online. Its three coauthors had pointed out a numerical coincidence connecting far-flung mathematical objects. "That smells like another moonshine," Cheng recalled thinking. "Could it be another moonshine?" She happened to have read a book about the "monstrous moonshine," a mathematical structure that unfolded out of a similar bit of numerology: In the late 1970s, the mathematician John McKay noticed that 196,884, the first important coefficient of an object called the j-function, was the sum of one and 196,883, the first two dimensions in which a giant collection of symmetries called the monster group could be represented.

A fascinating new simulation finds that self-driving cars will terraform cities: 90% of cars will be eliminated, acres of land will open up, and commute times will drop 10%. A team of transportation scientists at the Organization for Cooperation and Development took data on actual trips in Lisbon, Portugal and looked at how a fleet of self-driving, shared "taxibots" would change city landscape [PDF]. These "taxibots", the researchers imagine, are a marriage of mass carpooling and UPS delivery intelligence: they constantly roam throughout cities and match carpool routes with mathematical elegance. Ultimately, they estimate, 9 out of 10 cars would be completely unnecessary -- as would public transit. "Nearly the same mobility can be delivered with 10% of the cars TaxiBots combined with high-capacity public transport could remove 9 out of every 10 cars in a mid-sized European city," the paper concludes.

China's next generation missiles to adapt to war situation according to Artificial Intelligence