Minecraft is to become a testing ground for artificial intelligence experiments. Microsoft, owner of the popular video game, revealed that computer scientists and amateurs will be able to evaluate and develop AI software using its virtual landscapes from July. The company says Minecraft is more "sophisticated" than existing AI research simulations and cheaper to use than building a robot. "This is the state-of-the-art," said Prof Jose Hernandez-Orallo from the Technical University of Valencia, one of a small group of academics given early access to the software. "At this moment there is nothing comparable, and this is just in its beginnings, so I see many possibilities for it."

Fighting cyber attacks with artificial intelligence The next frontier of anti-virus software is leveraging artificial intelligence (AI) to not only predict what threats are out there, but to also actively fight back before they strike. This is according to American-based Cylance's chief marketing officer, Greg Fitzgerald, speaking at the NetEvents Press and Analyst Summit in Rome, Italy.The company says it is "revolutionising cyber security through the use of AI and machine learning to proactively prevent advanced persistent threats and malware". Cylance today announced it is expanding into the Europe, the Middle East and Africa (EMEA) with the establishment of a London-based team led by Evan Davidson, former enterprise sales director at FireEye. It also established a channel partnership with CoreSec Systems, which supplies cyber security and networking solutions in Sweden and Denmark.

The term Artificial Intelligence was originally coined by John McCarthy in 1955, defining it as "the science and engineering of making intelligent machines". Now more than a half a century old, the field of AI and machine learning is finally achieving some of its oldest goals by being used successfully in areas such as data mining, industrial robotics, logistics, speech recognition, banking software, medical diagnosis and search engines. Tech giants have all been investing heavily in AI and Machine Learning. In 2010 Facebook introduced facial recognition technology, and in 2013 Mark Zuckerberg dedicated a lab to AI research. In 2014 Google bought artificial intelligence startup DeepMind for 400 million ( 263 million), making it one of the largest tech acquisitions to date.

In 2012, IBM Watson went to medical school. So said The New York Times, announcing that the tech giant's artificially intelligent question-and-answer machine had begun a "stint as a medical student" at the Cleveland Clinic Lerner College of Medicine. This was just a metaphor. Clinicians were helping IBM train Watson for use in medical research. But as metaphors go, it wasn't a very good one.

It was hailed as the most significant test of machine intelligence since Deep Blue defeated Garry Kasparov in chess nearly 20 years ago. Google's AlphaGo has won two of the first three games against grandmaster Lee Sedol in a Go tournament, showing the dramatic extent to which AI has improved over the years. That fateful day when machines finally become smarter than humans has never appeared closer--yet we seem no closer in grasping the implications of this epochal event. Late last year, SpaceX co-founder Elon Musk warned that AI could take over the world, sparking a flurry of commentary both in condemnation and support. For such a monumental future event, there's a startling amount of disagreement about whether or not it'll even happen, or what form it will take.

Social networking giant Facebook is using its artificial intelligence (AI) technology and resources to map the entire Earth and launch the world's most detailed population maps that will help it beam cheap internet to remote areas. To begin with, the Facebook AI team crunched 14.6 billion images of maps from across 20 countries, including India, covering 21.6 million sq kms to come up with the first detailed map of human settlement for these countries. "This is an impressive project from our team developing solar-powered planes for beaming down internet connectivity and our AI research team. Many people live in remote communities and accurate data on where people live doesn't always exist," wrote Facebook CEO Mark Zuckerberg in a latest post. The 20 countries mapped were Algeria, Burkina Faso, Cameroon, Egypt, Ethiopia, Ghana, India, Ivory Coast, Kenya, Madagascar, Mexico, Mozambique, Nigeria, South Africa, Sri Lanka, Tanzania, Turkey, Uganda, Ukraine and Uzbekistan.

Each are British artificial intelligence and machine learning startups bought by US tech giants--HP, Google, Microsoft, and Apple, respectively. Alongside growing VC funding in AI, US tech firms are snapping up British-founded startups, leading to concerns that the UK is losing the best of its artificial intelligence to Silicon Valley just as it becomes a key technology. Simon Walker, partner in corporate technology at law firm Taylor Wessing, said the sale of AI startups to US firms isn't new and doesn't look like it'll stop soon. "It is obviously disappointing that the AI cannot be retained in the UK," he said. "However, top-of-the-market AI, such as that developed by companies such as SwiftKey and DeepMind, requires huge investment and a significant platform for its use and it is only very large tech companies which have the necessary resources and platforms."

Lawrence Wintermeyer, CEO of Innovate Finance, expects to see more innovators trying to tap into the unbanked and unrepresented consumer market. He said: "The firm Pockit, for example, gives customers an account and card that they can use to manage their money and make payments. Users can deposit money into their account at thousands of locations across the UK or have their salaries or benefits paid into their account. Pockit users also get cash back deals on the high street and online." So-called "challenger banks" are popping up and Monese is the latest to make waves.

The fear of Artificial Intelligence technology replacing the human workforce is old news. Chances are, you've never heard of rag-pickers, gandy dancers, or leech collectors- that's because modern technology has eliminated the need for them. More recently, jobs like elevator operators and lamplighters are almost completely phased out. One study at the University of Oxford estimated that 47% of total American jobs could be automated and replaced by computers by 2033. The question is, do these facts spell doom for the workforce?

Drone images accumulate much faster than they can be analyzed. Researchers have developed a new approach that combines crowdsourcing and machine learning to speed up the process. Who would win in a real-life game of "Where's Waldo," humans or computers? A recent study suggests that when speed and accuracy are critical, an approach combing both human and machine intelligence would take the prize. With drones being used to monitor everything natural disaster sites, pollution, or wildlife populations, analyzing drone images in real-time has become a critically important big data challenge. Publishing in the journal Big Data, researchers, including Stéphane Joost from EPFL, present a new approach to rapidly interpret aerial images taken by camera drones that combines human crowdsourcing and machine learning.