Fresh supplies are due to ship out late Tuesday for the International Space Station, where the shelves finally are getting full after a string of failed deliveries. An unmanned Atlas V rocket is scheduled to blast off at 11:05 p.m. by the light of a nearly full moon. Orbital ATK's Cygnus capsule holds nearly 8,000 pounds of food, equipment and scientific research for NASA, including a commercial-quality 3-D printer anyone can rent and experimental robotic grippers modeled after the thousands of sticky hairs on geckos' feet. There's also a fire experiment that will remain on the Cygnus. Researchers will ignite a large-scale blaze, in a contained box, to see how it spreads in weightlessness. The fire will not be set until the Cygnus departs the space station in May, full of trash for a destructive re-entry.

So called predictive policing has long been thought of as a possibility, whether it was the Orwellian thought police or the technical wizardry highlighted in Hollywood films like Minority Report. Such capabilities are increasingly possible however. Last year I wrote about the ATHENA project that is being run by West Yorkshire police. The project is aiming to bring the public into policing a lot more than is currently the case by using social and mobile tools as a force for good. The project team concede that the public are usually first on the scene of an incident, and are often therefore well placed to relay crucial information to officials.

During President Obama's 2016 State of the Union Address, Vice President Joe Biden was called to lead a new, national "Moonshot" initiative to eliminate cancer. Last month, the White House announced a new 1 billion initiative to jumpstart this effort. Moonshot's most valuable asset, and greatest challenge, is the volume and variety of "big cancer data". According to Vice President Biden, the biggest challenge impeding the cancer research progress is the siloed nature of clinical data. In response, Tamr has offered a solution to these challenges.

As a species, we humans are awfully obsessed with the future. We love to speculate about where our evolution is taking us. We try to imagine what our technology will be like decades or centuries from now. And we fantasise about encountering intelligent aliens – generally, ones who are far more advanced than we are. Lately those strands have begun to merge. From the evolution side, a number of futurists are predicting the singularity: a time when computers will soon become powerful enough to simulate human consciousness, or absorb it entirely. In parallel, some visionaries propose that any intelligent life we encounter in the rest of the Universe is more likely to be machine-based, rather than humanoid meat-bags such as ourselves.

In 1981, science essayist Jeremy Bernstein wrote a piece for The New Yorker that touched upon a historic backgammon game two years earlier, in which reigning champ Luigi Villa lost to a computer. It was the first time an artificial-intelligence program had defeated a world champion at a board or card game. In the essay, Bernstein wrote: "What does this mean for us, for our sense of uniqueness and worth -- especially as machines evolve whose output we can less and less distinguish from our own?" He might have asked that decades ago, but the question is now more relevant than ever. Google's AlphaGo recently won four out of five matches against Go master Lee Sedol.

Mr Toyoda Toyota president announced that the car company would be launching a research company in silcon valley to develop artificial intelligence for use in cars and robotics. The Toyota research institute according to the company press release would make drive accessible to everyone regardless of inability. However the new company, which will have 200 employees and launch in 2016, will be looking to go "beyond" autonomous cars. Health, mobility and personal well being robotics to improve all aspects of human life. Toyota has previously said its first self-driving car will be out by 2020 and it has produced some robots which includes a series of nursing bots to help those with physical impairments.

In open sourcing its artificial intelligence engine--freely sharing one of its most important creations with the rest of the Internet--Google showed how the world of computer software is changing. These days, the big Internet giants frequently share the software sitting at the heart of their online operations. Open source accelerates the progress of technology. In open sourcing its TensorFlow AI engine, Google can feed all sorts of machine-learning research outside the company, and in many ways, this research will feed back into Google. But Google's AI engine also reflects how the world of computer hardware is changing.

Some of Japan's banks and insurance companies have started using artificial intelligence to handle customers' inquiries more efficiently over the phone and online. Bank of Tokyo-Mitsubishi UFJ's smartphone app features MAI, a virtual bank teller, who can respond to customers by understanding the nature of their queries. For instance, if a customer says, "I lost my ATM card," MAI will recognize the situation and tell the customer what to do. The Android version of the app has already been released. The iPhone version is expected to become available by the end of this month.

It might not happen anytime soon, but then again, it might. In Japan, a short novel co-written by an artificial intelligence program (its co-author is human) made it past the first stage of a literary contest, the Japan News reports. The Nikkei Hoshi Shinichi Literary Award is named after Hoshi Shinichi, a Japanese science fiction author whose books include "The Whimsical Robot" and "Greetings from Outer Space." Judges for the prize weren't told which novels were written by humans and which were penned by human-computer teams. The award is unique in that it accepts entries from "applicants who are not human beings (AI programs and others)."

Why did I bother writing this? Well, here is one of the most trivial yet life-changing insights and worldly wisdoms from my former professor that has become my mantra ever since: "If you have to do this task more than 3 times just write a script and automate it." By now, you may have already started wondering about this blog. I haven't written anything for more than half a year! Okay, musings on social network platforms aside, that's not true: I have written something – about 400 pages to be precise. This has really been quite a journey for me lately. And regarding the frequently asked question "Why did you choose Python for Machine Learning?" I guess it is about time to write my script. In the following paragraphs, I really don't mean to tell you why you or anyone else should use Python. To be honest, I really hate those types of questions: "Which * is the best?" (* insert "programming language, text editor, IDE, operating system, computer manufacturer" here).