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).

The Unit for Natural Language Processing [1] of the Insight Centre for Data Analytics [2] at the National University of Ireland, Galway [3], invites applications for two PhD positions in Natural Language Processing and Linked Data. The positions are associated with the SFI funded research program on Text Mining with Linked Data. Candidates should preferably have a Masters degree in a relevant field of study with an emphasis on areas such as text mining, natural language processing, computational linguistics, machine learning etc. Please send your application, including CV and a research proposal of up to two pages (both in PDF only) before the closing date of April 25th, 2016 to Dr. Paul Buitelaar at paul.buitelaar@insight-centre.org

The idea that computers are people has a long and storied history. It goes back to the very origins of computers, and even from before. There's always been a question about whether a program is something alive or not since it intrinsically has some kind of autonomy at the very least, or it wouldn't be a program. There has been a domineering subculture--that's been the most wealthy, prolific, and influential subculture in the technical world--that for a long time has not only promoted the idea that there's an equivalence between algorithms and life, and certain algorithms and people, but a historical determinism that we're inevitably making computers that will be smarter and better than us and will take over from us. You'll have a figure say, "The computers will take over the Earth, but that's a good thing, because people had their chance and now we should give it to the machines."

With the best human player of boardgame Go being defeated this month by Google software, lawyers shouldn't make the mistake of believing their skills are beyond the reach of artificial intelligence (AI), write Stéphane Leriche and Michael Stojanovic. In early March, Google's DeepMind and its AlphaGo software beat the best human player of the ancient Chinese board game, Go, in a series of much-hyped matches. AI-powered legal tools are already a reality, and the success of AlphaGo demonstrates that the technology to make these tools better now exists. IBM's Watson cognitive computer won the TV game show Jeopardy! in 2011. Watson's question-answering technology has since been adapted to produce ROSS, a legal research virtual assistant that its developers promote as a'super intelligent attorney'.

The advent of audit analytics and cognitive technology does not mean the end of human auditors. It means an end to painstaking checking and crossfooting of debit and credit entries and the beginning of auditing careers that thrive on understanding, monitoring, and improving analytical and cognitive systems. I have worked for a couple decades with professional services firms that perform financial audits, but I have never done one--nor have I ever wanted to do one, to be honest. I'm not good with work that involves structured processes, details, and rigorous checking, and audits always seemed heavily infused with those kinds of tasks. Now, however, I am becoming quite interested in audits for two reasons.

Your Fitbit (or whatever it is the activity-enlightened wear these days) can make a pretty good guess at how many calories you're burning through. And it can do it without any input from you. But if you want to keep track of how many you're putting in, you'll still need to do some work yourself, even if it's only choosing from a menu on an app. Inspired by that asymmetry, State University of New York at Buffalo computer scientist Wenyao Xu and colleagues at Northeastern University in China developed Autodietary, a necklace-like gadget that attempts to tell what you're eating. The device senses sounds from your neck to categorize your meal.

UPDATE Mar 12th 2016: AlphaGo has won the third game against Lee Sedol, and has thus won the five-game match. That was the score, as The Economist went to press, in the latest round of the battle between artificial intelligence (AI) and the naturally evolved sort. The field of honour is a Go board in Seoul, South Korea--a country that cedes to no one, least of all its neighbour Japan, the title of most Go-crazy place on the planet. To the chagrin of many Japanese, who think of Go as theirs in the same way that the English think of cricket, the game's best player is generally reckoned to be Lee Sedol, a South Korean. Mr Lee is in the middle of a five-game series with AlphaGo, a computer program written by researchers at DeepMind, an AI software house in London that was bought by Google in 2014.

In today's digital world, Machine Learning is changing our lives. From speech recognition for smartphones and self-driving cars, to facial recognition and real-time fraud detection, Machine Learning plays a crucial part in the groundbreaking AI powering today's technology. At AMAX, our award-winning Deep Learning Solutions are the key driver for today's most groundbreaking technologies. These solutions harness NVIDIA GPU technology to accelerate the development of complex neural nets, powering machine learning algorithms with unprecedented speed and accuracy. AMAX solutions include GPU workstations for Deep Learning development, and a powerful server featuring up to eight NVIDIA GPU cards for 56 TFlops of single precision performance.

Phil Foglio, co-creator of the amazing Girl Genius comics, writes, "We are Kickstarting our latest Girl Genius collection; City of Lightning through April 12." "In this volume, we take Agatha to Paris, and begin to explore the complicated subterranean civilizations that honeycomb the earth beneath Europa. As always, we deal with assorted scientific ethical and philosophical conundrums regarding the nature of artificial intelligence, the impact of sudden technological advances upon established Geo-political structures, ramifications of endowing animals with human intelligence, and the unintended consequences of unsupervised bio-weapons. They always are, and the Foglios always deliver on their kickstarters, making this a sure bet.

"The fourth industrial revolution is unlike anything humankind has previously experienced. New technologies are merging the physical, digital and biological worlds in ways that create both huge promise and potential peril. The speed breadth and depth of this revolution is forcing us to rethink how countries develop, how organizations create value and even what it means to be human." We are living in an increasingly complex and uncertain world of constant change unlike anything in history. Advances in technology are outpacing implementation and these emerging technologies whilst presenting brilliant opportunities for a more positive world also present potentially detrimental threats.