In 2014, IBM launched the Watson Developer Cloud, making the power of cognitive computing available to developers across the world through a set of APIs on IBM's BlueMix platform. We've seen volumes of applications built by companies covering everything from personal health and fitness to travel and entertainment to financial services. It was amazing to see these early adopters jump onboard and showcase the power of cognitive computing. We want to make it even easier for developers to learn how to build and deploy cognitive applications – and even more importantly, to distinguish themselves for having developed these critical skills. That's why today, IBM is announcing a new program -- the IBM Watson Application Developer Certification -- designed to help developers all across the world build and validate their skills as well as connect with companies looking to leverage their unique talents. We watch every day as individuals explore and apply Watson in new ways -- from building natural language interfaces in a variety of languages so consumers can get answers faster to helping doctors uncover critical new insights from medical imagery.

But physics and chemistry give us a clear definition of the element magnesium -- which we can then use in the Wolfram Language to have a well-defined "magnesium" entity. It's very important that the Wolfram Language is a symbolic language -- because it means that the things in it don't immediately have to have "values;" they can just be symbolic constructs that stand for themselves. And so, for example, the entity "magnesium" is represented as a symbolic construct, that doesn't itself "do" anything, but can still appear in a computation, just like, for example, a number (like 9.45) can appear. There are many kinds of constructs that the Wolfram Language supports. Like "New York City" or "last Christmas" or "geographically contained within." And the point is that the design of the language has defined a precise meaning for them. New York City, for example, is taken to mean the precise legal entity considered to be New York City, with geographical borders defined by law.

I was quite surprised to read the other day a statement by a former FBI Chief. He said: "We're not going to solve it (cyber security), folks, not in our lifetime, but we have to constantly manage it." He went on to say that we owe it to future generations to manage cyber security effectively or leave a legacy that will make cyber security far easier to manage in the future. At best we will be locked into an arms race where each side ups their game to get ahead of the other. At the moment the bad guys are way ahead of us and I agree that how we manage cyber security effectively is the best way forward for now and in the future.

This is a problem for scientists working toward the creation of Artificial Intelligence (AI) systems capable of performing complex tasks with minimal human supervision. In a step toward overcoming this hurdle, researchers at Google's DeepMind -- the company that developed the Go-playing computer program AlphaGo -- announced earlier this week the creation of a neural network that can not only learn, but can also use data stored in its memory to "logically reason" and make inferences to answer questions. DeepMind's new system -- called a Differentiable Neural Computer (DNC) -- combines deep learning, wherein it can learn from examples and make sense of complex input it has never received before, with an external memory, which, as the DeepMind researchers Alexander Graves and Greg Wayne explain in a blog post, allows it to "store knowledge quickly and reason about it flexibly." In order to achieve this, the researchers first trained the neural network using randomly generated map-like structures -- a process that allowed the DNC to learn how to store connections between various parts in its external memory. After this, when it was confronted with a new map, the DNC was able to provide answers that were not explicitly stated in the data set.

When I see my parents use computers, it's clear that there's something that gets lost in the communication between computer and person. I think often that a big part of this is a lack of understanding of bugs/exceptions. In a way, there is a lack of fault tolerance in how my parents interact with their computers. When an app crashes, an email doesn't send, or a screen freezes, there's a sense of bewilderment, even incredulity. But when you grow up natively with computers, your fault tolerance is higher and you learn to navigate the bugs that inevitably arise because you understand at an almost innate level how they work.

In this session from the Microsoft Machine Learning & Data Science Summit, explore how parallelized ML algorithms in Azure HDInsight R Server and Spark machine learning library contrast and complement each other. The session also covers advanced algorithms such as deep neural network learning libraries available in the broader Spark ecosystem.

We have moved from the age where organizations had to jump through hoops to get relevant data about their customers, business segments, market, etc. With the onset of massive digitization across the business world, getting and collecting information is no longer a challenge, but processing them into meaningful insights is. Enterprises in this competitive business landscape are focusing towards an integrated data driven approach to enable rapid and accurate decision making. Machine learning, no longer lying in the realms of sci-fi, with its multi-faceted applications and benefits is emerging as a front-runner to overcome this challenge. Enterprises implementing machine learning can easily get new market insights, predict customer behavior or preferences, and reduce operating costs by improving the effectiveness and efficiency of the business processes.

With the increasing volume of interactions with customers over social media channels, KLM Royal Dutch Airline is the first airline to test how artificial intelligence could assist customer service agents. "We have 100,000 mentions a week on social media," says Tjalling Smit, senior vice president of Digital at KLM Royal Dutch Airlines. "We handle around 15,000 customer service cases a week and we answer our customers 24/7 in 10 different languages." As social channels proliferate, KLM makes sure it is present where its customers live online. "We were the first airline to allow customers to get their boarding passes and flight confirmation through Facebook Messenger," says Smit. KLM is piloting DigitalGenius' GPU-accelerated AI system that is integrated directly into KLM's Customer Relationship Management tool, and provides a layer of deep learning and artificial intelligence to service agents in real-time.

Designed with strong technical expertise and high intelligence, it's not so far-fetched that the robots of the future could outperform human managers. This article titled "Why a robot could be the best boss you've ever had" was written by Tomas Chamorro-Premuzic, for theguardian.com Would you like to work for a robot? Although the automation of skilled jobs is a reality, your boss is probably (still) a human. Even though the most optimistic artificial intelligence (AI) enthusiast would struggle to persuade us that the technology to create non-human leaders is upon us just yet, robots could be managing people in the decades to come.

"Let me at least pull the hosts who had contact with him," Elsie asks Bernard.