We caught up with Stephen Boyle following the IBM Watson Health event he ran at our Digital Health and Wellbeing Festival to see how IBM Watson Health is using Cognitive Computing to change the face of healthcare. I'm also a nurse by background so I have a long clinical career. This is my thirtieth year in healthcare – which I shouldn't admit to anybody! My role really, is to start to think about how we can work with cognitive computing in healthcare to really make that difference that we're all trying to achieve. A: IBM Watson Health is part of the giant organisation that is IBM, we're the part that is looking to utilise cognitive computing in healthcare.

More than fifty years of research in molecular biology have demonstrated that the ability of small and large molecules to interact with one another and propagate the cellular processes in the living cell lies in the ability of these molecules to assume and switch between specific structures under physiological conditions. Elucidating biomolecular structure and dynamics at equilibrium is therefore fundamental to furthering our understanding of biological function, molecular mechanisms in the cell, our own biology, disease, and disease treatments. By now, there is a wealth of methods designed to elucidate biomolecular structure and dynamics contributed from diverse scientific communities. In this survey, we focus on recent methods contributed from the Robotics community that promise to address outstanding challenges regarding the disparate length and time scales that characterize dynamic molecular processes in the cell. In particular, we survey robotics-inspired methods designed to obtain efficient representations of structure spaces of molecules in isolation or in assemblies for the purpose of characterizing equilibrium structure and dynamics. While an exhaustive review is an impossible endeavor, this survey balances the description of important algorithmic contributions with a critical discussion of outstanding computational challenges. The objective is to spur further research to address outstanding challenges in modeling equilibrium biomolecular structure and dynamics.

While many people in the world are worrying that robots will take over human jobs once artificial intelligence (AI) is fully developed, it's a safe bet that no one put "author" at the top of the robot job list. Yet, now that a Japanese AI program has co-authored a short-form novel that passed the first round of screening for a national literary prize, it seems that no occupation is safe. The robot-written novel didn't win the competition's final prize, but who's to say it won't improve in its next attempt? The novel is actually called The Day A Computer Writes A Novel, or "Konpyuta ga shosetsu wo kaku hi" in Japanese. The meta-narrative wasn't enough to win first prize at the third Nikkei Hoshi Shinichi Literary Award ceremony, but it did come close.

Marc Carrel-Billiard, Managing Director Global Technology R&D, AccentureBangalore: AI can double annual economic growth rates by 2035 by changing the nature of work and spawning a new relationship between man and machine, according to Accenture Research. The impact of AI technologies on business is projected to boost labour productivity by up to 40 percent by fundamentally changing the way work is done and reinforcing people's role to drive growth in business. In an interview with ETCIO, Accenture's Managing Director Global Technology R&D, Marc Carrel-Billiard talks about company's technology labs and its focus areas, new technologies and its impact and key tech trends that CIOs and businesses need to look for and much more. Marc is with Accenture for the past 18 years and currently oversees the Accenture Technology Labs, Accenture Open Innovation, Accenture's global technology R&D organization which explores new and emerging technologies, across seven locations around the world. Which are the key technology domains that you are trying to focus on?

Svetlana Alexievich, winner of the 2015 Nobel Prize in literature, called the nuclear catastrophes at Chernobyl and Fukushima events that people cannot yet fully fathom and warned against the hubris that humans have the power to conquer nature. The 68-year-old Belarusian writer was in Tokyo at the invitation of researchers at the University of Tokyo, where she gave a lecture on Friday. More than 200 people attended. The Nobel laureate, who writes in Russian, is known for addressing dramatic and tragic events involving the former Soviet Union – World War II, the Soviet war in Afghanistan, the 1986 Chernobyl nuclear disaster and the 1991 collapse of the communist state. Her style is distinctive in that she presents the testimonies of ordinary people going through traumatic experiences as they speak, without intruding on their narratives.

But deciding to build an app in the first place was driven by a broader purpose. As one doctor put it, "If you want to do world-class sociology research, build Facebook."

Here I offer a few off-the-beaten-path interesting problems that you won't find in textbooks, data science camps, or in college classes. These problems range from applied maths, to statistics and computer science, and are aimed at getting the novice interested in a few core subjects that most data scientists master. The problems are described in simple English and don't require math / stats / probability knowledge beyond high school level. My goal is to attract people interested in data science, but who are somewhat concerned by the depth and volume of (in my opinion) unnecessary mathematics included in many curricula. I believe that successful data science can be engineered and deployed by scientists coming from other disciplines, who do not necessarily have a deep analytical background yet are familiar with data.

Can you tell us a bit about MindMeld? MindMeld is a leading Conversational AI company, now offering Deep-Domain Conversational AI. The company has pioneered the AI technology behind the emerging generation of intelligent voice and chat assistants and currently powers advanced conversational experiences used by some of the world's largest media companies, government agencies, automotive manufacturers, and global retailers. MindMeld's customers and investors include Google, Samsung, Intel, Telefonica, Liberty Global, IDG, USAA, Uniqlo, Spotify, In-Q-Tel and others. What does Deep-Domain Conversational AI mean?

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?"

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?"