Twitter trolled Tay, the AI bot, so hard that it became the perfect troll.https://t.co/BGGRvGjtOo

A breakthrough year for artificial intelligence (AI) research has suddenly turned into a breakdown, as a new automated banking system that runs on AI has been caught embezzling money from customers. The surprising turn of events may set back by years efforts to incorporate AI into everyday technology. "This is the nightmare scenario," says Len Meha-Döhler, a computer scientist at the Massachusetts Institute of Technology in Cambridge who was not involved in the work. However, Rob Ott, a computer scientist at Stanford University in Palo Alto, California, who did work on the system--Deep Learning Interface for Accounting (DELIA)--notes that it simply held all of the missing money, some 40,120.16, in a "rainy day" account. "I don't think you can attribute malice," he says.

The robots are coming, or so media have proclaimed in recent months. The world of work is about to undergo a revolution as advances in technology mean that many jobs humans do now will likely be done by machines instead in a matter of years. How many roles will go and what sectors will be most affected is open to debate but it seems certain widespread change is upon us. According to a World Economic Forum (WEF) report published in January, more than seven million jobs are at risk from advances in technology in the world's largest economies over the next five years. If anything this is a conservative estimate.

On Wednesday, a Google deep-learning program beat the world's best player at Go -- an ancient Chinese game once considered too complex and nuanced for a computer to ever master. This game comes 20 years after IBM's Deep Blue computer first beat reigning world champion Garry Kasparow in a game of chess. Though pitting AIs against humans in games of strategy does offer some insight into how the field of machine learning is progressing, the increasing presence of AI in our daily lives shows that the technology is reaching a point where it will soon be hard to imagine what the world used to be like. Machine learning computers perform mundane tasks for us -- like completing our sentences, or finding the fastest route home. But they also do tasks we're incapable of doing, like sorting through and spotting patterns in incredibly large and complex data sets. Chicago is home to a number of companies doing big things in the AI and machine learning field.

A year ago today, on April 1, 2015, as part of a project on prediction at the New York Universe – Center for Data Superiority (NYU-CDS), I gathered together a political scientist, a data-driven journalist, a traditional campaign reporter for a major newspaper and an artificial intelligence application created by a major international business machine company to discuss the state of the primary contests and to collect their predictions for the eventual nominees. I promised to only reveal these predictions a year later. I also agreed to use pseudonyms for all four participants and – with some regret – allowed them to choose their own pseudonyms. What follows is a lightly edited transcript of our discussion. Me: Please let me thank you all for joining me today!

I do not have a head for it, but I do have love for it. Practically, I profit from it; philosophically, I endorse it.; Curiosity, inquiry and a willingness to be proved wrong, to bow to the better explanation when it comes along -- these are tonics against the inflexible fundamentalism, the epidemic unthinking, that makes the world a shakier place. And so I have been taking comfort and inspiration from what seems to be a great flowering of science-themed programming, much of it on the Internet, where subjects that mainstream commercial television dubs "not for everyone" may take root and flourish. Apart from PBS, home to "Nova" and "Nature," and some dedicated (or half-dedicated) cable networks like National Geographic Channel, Science and Discovery, television tends to like its science fictional. And while science fiction is a known gateway to a career in serious science and can be similarly stimulating, the workings of the nonfictional universe are more profoundly exciting and all the more amazing for being, you know, real.

Like innumerable children with imaginations fired by animated films, Hong Kong product and graphic designer Ricky Ma grew up watching cartoons featuring the adventures of robots, and dreamed of building his own one day. Unlike most, however, Ma has realised his childhood dream at the age of 42, by successfully constructing a life-sized robot from scratch on the balcony of his home. The fruit of his labors of a year-and-a-half, and a budget of more than 50,000, is a female robot prototype he calls the Mark 1, modelled after a Hollywood star whose name he wants to keep under wraps. It responds to a set of programmed verbal commands spoken into a microphone. Ma's journey of creation was a lonely one, however.

The European Union is looking to connected vehicles and autonomous driving to reduce traffic fatalities, after a disappointing year for road safety. Last year, 26,000 died on European roads, up 1 percent on the previous year. "The latest figures are disappointing. For the second year in a row, we have not managed to reduce the number of victims on our roads," said European Commissioner for Transport Violeta Bulc, presenting the EU's latest study of traffic accident statistics in Brussels on Thursday. Disappointing though the rise is, EU roads are still among the safest in the world, with traffic fatalities down 17 percent since 2010, after a reduction of 43 percent in the previous decade.

The internet, and more importantly how we consume data from the web, has evolved at an incredible pace in recent years. One thing that has been steadily growing, and is only now really starting to make the headlines is Machine Learning. "Artificial intelligence would be the ultimate version of Google. The ultimate search engine that would understand everything on the Web. It would understand exactly what you wanted, and it would give you the right thing. However, we can get incrementally closer to that, and that is basically what we work on."