It's an exciting time to be involved the customer service and communications space. There are more ways to interact with a brand than ever before (email, Twitter, even Snapchat), but one of the most new and exciting advancements is chatbots. "Chat bots are computer programs that mimic conversation with people using artificial intelligence. They can transform the way you interact with the internet from a series of self-initiated tasks to a quasi-conversation." In the customer service space, chatbots are using the growing power of artificial intelligence to allow customers to interact with a brand as they would with a customer service representative.

A team of computer scientists may have developed a surprising way to curb wildlife poaching. Funded by the National Science Foundation (NSF), a team of computer scientists at the University of Southern California (USC) have developed a model for "green security games" that use game theory to protect wildlife from poachers. Game theory uses mathematical equations "to predict the behavior of adversaries and plan optimal approaches for containment," explains NSF, which would allow park rangers to patrol parks and wildlife sanctuaries more effectively. "In most parks, ranger patrols are poorly planned, reactive rather than pro-active and habitual," Fei Fang, a Ph.D. candidate in the computer science department at USC and a researcher involved with the project, tells NSF. "We need to provide actual patrol routes that can be practically followed."

On the 15th March 2016, an artificially intelligent (AI) software programme called AlphaGo, defeated the world champion of an ancient board game called Go. The game is immensely complex, with a total combination of possible moves numbering several hundred orders of magnitude more than the number of atoms in the universe. Winning the series four-to-one, AlphaGo's victory was emphatic. It also showcased significant advances in AI's ability to recognise obscure patterns, learn new ones and adapt strategies to changing circumstances. Yet, just two weeks after AlphaGo's impressive victory, a new chatbot called Tay, exposed a darker side to AI. Designed to engage in friendly conversation with people online and assist them with Microsoft services, Tay's unique design feature was that "she" learns from her online interactions.

As we go about our daily lives, we tend to assume that our perceptions--sights, sounds, textures, tastes--are an accurate portrayal of the real world. Sure, when we stop and think about it--or when we find ourselves fooled by a perceptual illusion--we realize with a jolt that what we perceive is never the world directly, but rather our brain's best guess at what that world is like, a kind of internal simulation of an external reality. Still, we bank on the fact that our simulation is a reasonably decent one. If it wasn't, wouldn't evolution have weeded us out by now? The true reality might be forever beyond our reach, but surely our senses give us at least an inkling of what it's really like.

We humans take for granted our remarkable ability to predict things that happen around us. For example, consider Rube Goldberg machines: One of the reasons we enjoy them is because we can watch a chain-reaction of objects fall, roll, slide and collide, and anticipate what happens next. But how do we do it? How do we effortlessly absorb enough information from the world to be able to react to our surroundings in real-time? And, as a computer scientist might then wonder, is this something that we can teach machines?

Aiming to better support machine learning and analytical environments, Pentaho Labs yesterday announced that it has developed a native integration for the Python language through Pentaho Data Integration (PDI). PDI is essentially a portable "data machine" for ETL, which you can deploy as a stand-alone Pentaho cluster or inside a Hadoop cluster through MapReduce or YARN. Will Gorman, vice president of Pentaho Labs at Hitachi subsidiary Pentaho, says the integration means data scientists can now use of the most popular and flexible open-source languages to increase productivity and data governance while supporting predictive analytics and machine learning. He says the integration will also make data science and predictive modeling more accessible to the developer community. "Python is the environment that is growing the fastest from a community perspective," Gorman says.

Tesla Motors Inc (NASDAQ:TSLA) is riding on a tidal wave of notoriety since the start of 2016. The firm is continuing to lead an industry in a transition away from internal combustion engines and toward all electric power. Most of the media attention lately comes from the introduction of the "affordable" Tesla Model 3. That car won't even begin delivery until late next year but over 400k people have paid 1000 each just to get in line to buy one. One of the features that will be available on the Model 3 is Autopilot. Tesla gets a lot of attention for its Autopilot feature that provides properly equipped Model S and Model X SUVs with self-driving abilities on highways.

Nasa has announced that it has found evidence of flowing water on Mars. Scientists have long speculated that Recurring Slope Lineae -- or dark patches -- on Mars were made up of briny water but the new findings prove that those patches are caused by liquid water, which it has established by finding hydrated salts. Several hundred camped outside the London store in Covent Garden. The 6s will have new features like a vastly improved camera and a pressure-sensitive "3D Touch" display

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Machine learning has come of age in public health reporting according to researchers from the Regenstrief Institute and Indiana University School of Informatics and Computing at Indiana University-Purdue University Indianapolis. They have found that existing algorithms and open source machine learning tools were as good as, or better than, human reviewers in detecting cancer cases using data from free-text pathology reports. The computerized approach was also faster and less resource intensive in comparison to human counterparts. Every state in the United States requires cancer cases to be reported to statewide cancer registries for disease tracking, identification of at-risk populations, and recognition of unusual trends or clusters. Typically, however, busy health care providers submit cancer reports to equally busy public health departments months into the course of a patient's treatment rather than at the time of initial diagnosis.