Data science interviews are daunting, complicated gauntlets for many. But despite the ways they're evolving, the technical portion of the typical data science interview tends to be pretty predictable. The questions most candidates face usually cover behavior, mathematics, statistics, coding, and scenarios. However they differ in their particulars, those questions may be easier to answer if you can identify which bucket each one falls into. Here's a breakdown, and what you can do to prepare.

Hot on the heels of confirmed reports that China is getting ready to equip cruise missiles with artificial intelligence targeting capability, a "summer study" on autonomy done by the Defense Science Board shows that the U.S. has already been thinking of weaponizing artificial intelligence. The DSB is a federal advisory committee to the U.S. Secretary of Defense, also known as SecDef, a post currently held by Ashton Carter. He is also the CEO of the United States Department of Defense. According to the publicly available DSB study, it "offers important recommendations to identify the science, engineering, and policy problems that must be solved to permit greater operational use of autonomy across all warfighting domains." The report also outlines various projects that the government can undertake that will utilize the power of artificial intelligence, machine learning and data analytics to automate several dangerous processes that are currently carried out manually, such as "offensive maritime mining" and "mine counter measure" missions.

Sometimes, smaller is better, especially with robots. That's what researchers developing mini-robots have in mind. Robots that cost 10 to 100 are cheaper to make and more useful to deploy in emergency situations than big robots with limited mobility. Researchers at the University of California, Berkeley, are developing sophisticated robots that are up to 10 centimeters long, and can run, climb, fly, and communicate with emergency personnel. Once the multi-leg robots serve their purpose, they can be disposed of without regrets.

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For thousands of years humans believed that authority came from the gods. Then, during the modern era, humanism gradually shifted authority from deities to people. Jean-Jacques Rousseau summed up this revolution in Emile, his 1762 treatise on education. When looking for the rules of conduct in life, Rousseau found them "in the depths of my heart, traced by nature in characters which nothing can efface. I need only consult myself with regard to what I wish to do; what I feel to be good is good, what I feel to be bad is bad." Humanist thinkers such as Rousseau convinced us that our own feelings and desires were the ultimate source of meaning, and that our free will was, therefore, the highest authority of all.

Seated against a deep red backdrop, gazing intently at hand-held mirrors, two eunuchs in sparkling saris inspect their appearance before Raksha Bandhan celebrations in the red light district of Mumbai. The photograph from the Reuters news agency is an arresting contemporary scene, but a new Tate Britain project is aiming to inspire deeper reflections with images from its own collection of paintings. Launching on Friday, Recognition is the winner of 2016's IK Prize – an annual award, this year supported by Microsoft, for a project that embraces digital technology to explore and showcase Tate's collection of British art. This year, the challenge was to do it with artificial intelligence. The team behind the winning project, from Italy-based communication research centre, Fabrica, say their inspiration came from an intriguing conundrum: how can you apply rational thinking to a subject like art? Recognition matches stunning photographs from the 24/7 news cycle with centuries-old artworks, and presents them online.

Insurance giant John Hancock and a small Boston startup are teaming up in the hopes of using artificial intelligence to guide the company's investment decisions. John Hancock -- and its Canadian parent company Manulife -- have started working with indico data solutions, a startup that makes AI software designed to create easily digestible trends, themes and other important information out of the mountains of data that financial analysts have to keep track of. "These guys are all drowning in data," said Vishal Daga, chief customer officer for indico. "The idea is to build an application using these deep learning techniques that can help analysts whittle down that stack of reading material in a useful manner." Indico's software can analyze word choices from stock analyst reports and automatically detect whether the language is positive or negative.

At Recode's annual Code Conference in June, venture capitalist Elon Musk made the provocative argument that reality is not reality at all, but a massive simulation built on top of some other reality. "There's a billion-to-one chance we're living in base reality," he said. Musk's idea isn't a new one: Philosophers and science fiction authors have been toying with versions of it for years. But part of what made Musk's notion interesting was that it rested entirely on a simple extrapolation from the trajectory of the video game industry. "Forty years ago we had Pong," he said.

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I'm looking to build a MDP and a reinforcement program in Python which works on generating text based on reward points in training data which is text sentences. I could not find any basic example program models which gives idea on how to build MDP on text sentences training data or identify which reinforcement model to use to generate texts. Can you please provide some suggestions / advice.