May 14, 2017, will be the 100th anniversary of the birth of someone you might not have heard of: William Thomas ("Bill") Tutte. During the Second World War he made several crucial contributions to decrypting the Lorenz cipher used to protect the Nazi high command's most crucial radio communications. This work provided the statistical method implemented electronically by Tommy Flowers, a telecommunications engineer, in the Colossus machines, which pioneered many of the electronic engineering techniques later used to build digital computers and network equipment.a The British code-breaking effort of the Second World War, formerly secret, is now one of the most celebrated aspects of modern British history, an inspiring story in which a free society mobilized its intellectual resources against a terrible enemy. That's a powerful source of nostalgic pride for a country whose national identity and relationship with its neighbors are increasingly uncertain. Tutte's centennial gives a chance to consider the broader history of Bletchley Park, where the codebreakers worked, and the way in which it has been remembered. Some kinds of people, and work, have become famous and others have not. Films reach more people than books. So statistically speaking, most of what you know about Bletchley Park probably comes from the Oscar-winning film The Imitation Game. This gives us a starting point: the film is a bad guide to reality but a useful summary of everything that the popular imagination gets wrong about Bletchley Park. One myth is that Alan Turing won the war pretty much by himself.

The Presidential Medal of Freedom, America's highest civilian honor, is usually associated with famous awardees--people like Bruce Springsteen, Stephen Hawking, and Sandra Day O'Connor. So as a computer scientist, I was thrilled to see one of this year's awards go to a lesser-known pioneer: one Margaret Hamilton. You might call Hamilton the founding mother of software engineering. In fact, she coined the very term. She concluded that the way forward was rigorously specified design, an approach that still underpins many modern software engineering techniques--"design by contract" and "statically typed" programming languages, for example.

In the age of AI, how can we live with artificially intelligent machines and robots that may become more intelligent than us? An AI machine can be a computer or smart device; it can also be known as a robot that, with or without appendages, can emulate human life physically. There are still so many unanswered questions. How can we coexist comfortably and conveniently if one day, the machines we have created decide to think for themselves? Do you believe in technological singularity, and is it near?

How would you like it if you some stranger snapped your picture and then used that photo to find out your real name, your address and other information about you? If face recognition technology may not be brand new, anonymity in public could soon be a thing of the past. You may never again be just a face in the crowd. FindFace, a new application launched few months ago, by a Russian start-up has the power to identify total strangers on the street from pictures of their faces. It does so by matching the photos against profile pictures from VK --also known as VKontakte--a Russian social networking website like Facebook.

After introducing virtual butler Jarvis in a Morgan Freeman voice, Facebook founder and CEO Mark Zuckerberg is now seeking suggestions from his Facebook followers to make Jarvis more useful and make it do much more. In a video post, which shows Mark, Priscilla, his child Max and dog Beast, at home in different situations, the co-founder showcases some use cases of Jarvis and wants to do more. Named after the artificial intelligence system designed by Marvel comics' superhero Iron Man or Tony Stark, Jarvis can respond to text and voice commands and it could run music, air conditioning, doors, and other systems. It could recognize visitors, start a toaster and even shoot t-shirts from a cannon in his closet. The video also shows that Jarvis can make decisions like who to tickle next, in this case, it was Max.

Determining brain age from an MRI scan has always been a time-consuming business. Human cognitive abilities decline with age. And neuroscientists have long known that this decline correlates with anatomical changes in the brain as well. So it's no surprise to learn that it is possible to spot the signs of aging in MRI images of the brain and even to determine a "brain age." The difference between brain age and chronological age can reveal the onset of conditions such as dementia.

Much as they are today, people were enthralled by artificial intelligence in 1973 -- the year Michael Crichton released the film Westworld. The film became MGM's biggest box office hit of the year, yet launched the same year as the first AI winter: a massive event of depleted AI resources, dashed expectations, and dwindling interest over the ensuing decades. In 2016, Westworld is back, and the immense changes in deep learning, open source, and computing power are fundamentally shifting AI's future. Compute capacity and the technology's capabilities have now advanced far enough that AI can complement and accelerate society, versus the trough of disillusionment realized in 1973. HBO's new version of Westworld, produced by Jonathan Nolan and Lisa Joy, is one of the most popular shows on TV today.

There are plenty of headlines about how artificial intelligence (AI) is transforming everything from smartphones to our cars, but understanding how exactly to benefit from AI as an investor can be a little harder. AI encompasses a lot of different technologies, like natural language processing (when Google Assistant understands what you're saying), machine vision (semi-autonomous cars knowing the difference between a lamppost and a pedestrian), and even suggesting the next show you should watch (although if an AI suggests HBO's Westworld, you should be suspicious). All of these examples are more than just algorithms that make decisions. They're computing systems that actually learn while they're working. To help you get started in your AI investments, here are five things you should know before jumping into the space.

A wave of startups is emerging in famously risk-averse Japan as cash-rich corporations increasingly delegate the task of keeping pace with technologies such as artificial intelligence and robotics to smaller, nimbler businesses. Japan has been dry ground for startups, given the shame that entrepreneurs and investors associate with failure, but it is on track for a record funding year for unlisted startups, exceeding the dot-com bubble of 2000, according to a private research firm. "The fundraising environment has improved a lot compared with a few years ago," said Ken Tamagawa, 40-year-old CEO of Soracom Inc, which helps companies set up platforms allowing devices to communicate with each other via the "internet of things." It raised ¥3 billion ($25.6 million) from Mitsui & Co. and an investment fund in which Toyota Motor Corp. has a stake. Dozens of companies, including electronics maker Omron Corp. and real estate developer Mitsui Fudosan Co., have set up venture capital funds to seek returns or to team up with smaller companies.

In this article, I summarize the components of any data science / machine learning / statistical project, as well as the cross-dependencies between these components. This will give you a general idea of what a data science or other analytic project is about. This is the top, fundamental component. I have listed 24 potential problems in my article 24 uses of statistical modeling. It can be anything from building a market segmentation, building a recommendation system, association rule discovery for fraud detection, or simulations to predict extreme events such as floods.