So how does this work? Each bottle of beer has instructions to a website that asks visitors a series of questions. The answers to the questions are then sent to ABI. ABI then uses that feedback to make modifications to the ingredients for the next batch of beer. IntelligentX has had tech event attendees in and around London try their beers.

Over a couple of drinks, you cover the usual suspects: favourite foods, dream jobs, where you each grew up. On the way home, you wonder: Were they into me? They were smiling a lot, so probably. But they also looked at their watch a few times, so probably not. Now imagine that the whole time you two were talking, scientists were sitting under the table transcribing the conversation.

Microsoft has made Project Malmo, a platform that uses the world of Minecraft as a testing ground for advanced artificial intelligence research, available for novice to experienced programmers on GitHub via an open-source license. The system, which had until now only been open to a small group of computer scientists in private preview, is primarily designed to help researchers develop sophisticated, more general artificial intelligence, or AI, that can do things like learn, hold conversations, make decisions and complete complex tasks. That's key to creating systems that can augment human intelligence -- and eventually help us with everything from cooking and doing laundry to driving and performing lifesaving tasks in an operating room. Katja Hofmann, a researcher in Microsoft's Cambridge, UK, research lab, who leads the development of Project Malmo, said the system will help researchers develop new techniques and approaches to reinforcement learning. That's an area of AI in which agents learn how to complete a task by being given a lot of room for trial and error and then being rewarded when they make the right decision.

Exponential Finance celebrates the incredible opportunity at the intersection of technology and finance. Apply here to join Singularity University, CNBC, and hundreds of the world's most forward-thinking financial leaders at Exponential Finance in June 2017. This is the year AI has hit the public consciousness hard. Whether calls for universal basic income in the face of an automation tsunami or alarms over the loss of privacy when everything you do can be monitored and analyzed, people are discussing and debating AI more than ever in an effort to quell their dystopian fears about humanity's future. Fueling the fire, it seems like every day someone is announcing a new AI beating another Turing test.

A huge shift is taking place in the business software market, and Dropbox CEO Drew Houston knows it: Software needs to be smarter and more predictive. According to a report in The Information, Houston reiterated this notion at the annual Allen & Co. Sun Valley Conference this week, saying machine learning capabilities that enable more sophisticated data analysis and automated predictive behavior is "something you sprinkle on products to make them better as opposed to a new platform or product." He pointed out that hiring machine learning experts has become "more important" as a result, and they'll play bigger roles as software like Dropbox seeks ways to automate a lot of functionalities such as notifications and messages in the future, the report said. Houston's comment is in line with the trend in the broader business software landscape. Salesforce, for example, has been doubling down on its machine learning capabilities by acquiring a bunch of artificial-intelligence startups lately.

It sounds like the stuff of science-fiction; computer-based systems that can learn behavior pattern and make predictions about future incidents in both the physical and virtual world. After all, just mentioning the term "artificial intelligence" typically conjures up thoughts of machines becoming self-aware and annihilating humankind vis-a-vis "The Terminator." But while some may brush off the idea that security systems leveraging artificial intelligence or AI, for short, will ever come to fruition, the reality is they are already being implemented in a variety of applications. Just last month, Armorway, which has patented an artificial intelligence platform that combines a variety of analytics with cognitive intelligence and deep machine learning, announced that it has received 2.5 million in funding from a variety of investors. The company, which has received support in the past from the University of Southern California, the Department of Homeland Security, Department of Defense and U.S. Army Research Office, said the money will help further develop its AI and prescriptive analytics solutions.

Hell, Microsoft issued an Education Edition of the popular PC game earlier this year targeted at use in a classroom setting. Turns out the game could also prove a useful tool for helping artificial intelligence be more, well, intelligent. Back in March, Microsoft Research showcased the work it was doing with Project Malmo, a platform designed to leverage Minecraft as a means of helping improve AI problem solving, using machines to accomplish tasks and create items in the blocky game. Now the company is bringing Malmo to the GitHub-using masses, courtesy of an open-source license in a private preview. Katja Hoffman of MS's Cambridge, UK lab highlighted the key of teaching AI fundamental connections that go build simple pattern recognition.

Video Friday is your weekly selection of awesome robotics videos, collected by your Chemputer -savvy Automaton bloggers. We'll also be posting a weekly calendar of upcoming robotics events for the next two months; here's what we have so far (send us your events!): Let us know if you have suggestions for next week, and enjoy today's videos. Here are highlights from the RoboCup 2016 finals, with Tech United up against Water (in pink). Don't worry about keeping score, because it goes to penalty kicks at the end.

Machine Learning is a hot topic in the science world right now. By combining the powers and capabilities of both computers and humans, perplexing and unimaginable problems are being resolved as we speak. Machines nowadays can more easily handle the ginormous amount of data constantly being produced and decipher the complexity of scientific discoveries. On the other hand, researchers have begun to recognise the potential this science can have in a vast variety of fields and finally it is being put into practice. On researching the topic, many of the techniques and algorithms will seem familiar to a lot of statisticians, engineers, programmers, mathematicians and quants.

In a normative environment an agent's actions are not only directed by its goals but also by the norms imposed on the agent. However, the potential conflicts within and between the agent's goals and norms makes decision-making in these frameworks a challenging task. The questions we are addressing in this paper are: (i) how should an agent act in a normative environment? We propose a solution in which a normative planning problem serves as the basis for a practical reasoning approach based on argumentation. The properties of the best plan(s) with respect to goal achievement and norm compliance are mapped to arguments that are used to explain why a plan is justified, using an existing proof dialogue game.