Every day seems to bring a new outrageous headline with promises of artificial intelligence's superpowers. The hype is very high right now, with headlines conveying the sense that disruption is imminent and everything will soon be overtaken by these technologies. The reality, however, is very different. Yes, artificial intelligence (AI) does have a lot of potential and it's an exciting field. However, not every organization has the right foundation in place to deliver real results.

The workforce crisis is looming, a situation that could hit the global economy to the tune of $10 trillion, according to some studies. The crux of the problem relates to a mismatch between supply and demand, with some economies facing a workforce shortage and others a surplus. "An equilibrium in supply and demand is rapidly becoming the exception, not the norm," a report from the Boston Consulting Group (BCG) noted. "Between 2020 and 2030, we project significant worldwide labor-force imbalances -- shortfalls, in particular. One significant implication is the potential aggregate value of GDP squandered, because either these nations cannot fill the jobs available or they cannot create enough jobs for the workers they have."

For a very long time, women working in the fields of science, technology, engineering and math were unwelcome and underappreciated. Take for example the story of Katherine Johnson and her colleagues, who made remarkable contributions to the early years of NASA's space program. The world had not even heard of her name until two years ago, when the movie, Hidden Figures, hit the screens. Sadly, it is still a man's world in the STEM fields, and women struggle every day to find a strong foothold in it. The disparity between the number of men and women with successful careers in STEM is unfortunately large.

Do we still need humans to power customer experiences? In its Digital CX Trends 2018 report (fee charged) released today, Forrester researchers found that "while AI, intelligent agents, and chatbots were central to the business conversation in 2017, most companies discovered they lack the design acumen and technical chops to seize the opportunities." This, researchers found, has led to widespread struggles with the basics and few leaders "innovating the way forward." It's fair to say not everyone is excited about artificial intelligence's invasion into customer experience, even those who profit from it. Yet many organizations are still turning to AI to power customer experiences.

Short Bytes: The resurgent debate on the impact of AI on humanity in the (near)future has drawn a lot of attention in recent times; Especially after the opposing remarks made by Elon Musk and Mark Zuckerberg. Here, we shall discuss the arguments and assertions put forth in the light of the current AI backdrop. These are some of the exciting news generated by the field of AI recently. These surely are noteworthy results that transcend the applications that we previously hadn't thought about. These results indirectly expound the techniques and the mechanisms that were developed over the years.

Due to exponential increases in computer power and data storage over the past couple of decades, we have witnessed the rise of artificial intelligence systems that meet and exceed human abilities. At the forefront of recent A.I. technology is an approach termed machine learning. In the financial services world, insurance firms and investment banks have employed ML-based systems to automate areas such as claims processing and contract validation. The asset management industry will be no exception. ML has begun to make inroads as asset managers realize that the ability to extract value from big data is going to be a key differentiator -- and that traditional industry practices will struggle to stay afloat in this mounting flood of real-time data.

A cow stands in a pasture on Seven Oaks Dairy in Waynesboro, Ga. On the cow's neck is a device called IDA, or "The Intelligent Dairy Farmer's Assistant," created by Connecterra. It uses a motion-sensing device attached to a cow's neck to transmit its movements to a program driven by artificial intelligence. SAN FRANCISCO (AP) -- Is the world ready for cows armed with artificial intelligence? No time to ruminate on that because the moment has arrived, thanks to a Dutch company that has married two technologies -- motion sensors and AI -- with the aim of bringing the barnyard into the 21st century.

Sage have reported that this global trend is boosting international collaboration between startups across all continents, such as the European Commission-backed Startup Europe Comes to Africa (SEC2A) which was held in November 2017. While the majority of chatbots are being created to assist business industry, from hospitality and retail to banking and services, developers around the world are also finding innovative and inspirational ways to use chatbots to improve society. Here are some of our favorites. Developed to assist Nigerian students preparing for their secondary school exam, the University Tertiary Matriculation Examination (UTME), SimbiBot is a chatbot that uses past exam questions to help students prepare for a variety of subjects. It offers multiple choice quizzes to help students test their knowledge, shows them where they went wrong, and even offers tips and advice based on how well the student is progressing.

Since then, big data security analytics sort of morphed into machine learning, which led to the creation of a new security technology category, user and entity behavior analytics (UEBA). UEBA was designed to monitor user behaviors like logins, remote access, network connections, etc., model "normal" behavior, and then detect anomalies that may indicate an attack in progress. UEBA proponents claimed that based upon this new capacity, new machine learning-based technology was destined to become a huge market as it replaced SIEM as the system of record for security analytics and operations.

In this article, Timoshenko and Hauser explore how machine learning can be used to identify a rich set of customer needs from user generated content (UGC). Specifically, they detail how customer needs identified using their innovative machine learning algorithm are comparable to those identified through traditional research methods. They discuss how, when UGC is readily available, the machine learning process requires substantially less time, effort and expense than standard research methods.