Although artificial intelligence is here since a long time in many forms and ways, it's a term that quite some people, certainly IT vendors, don't like to use that much anymore – but artificial intelligence is very real, for your business too. Instead of talking about artificial intelligence (AI) many describe the current wave of AI innovation and acceleration with – admittedly somewhat differently positioned – terms and concepts such as cognitive computing or focus on several real-life applications of artificial intelligence that often start with words such as "smart", "intelligent", "predictive" and, indeed, "cognitive", depending on the exact application – and vendor. Despite the term issues, artificial intelligence is essential for and in, among others, information management, medicine/healthcare, data analysis, digital transformation, security (cybersecurity and others), various consumer applications, scientific advances, FinTech, predictive systems and so much more. The historical issue with artificial intelligence – is cognitive better? There are many reasons why several vendors doubt using the term artificial intelligence for AI solutions/innovations and often package them in another term (trust us, we've been there).

Humans are on the cusp of augmenting their lives in extraordinary ways with AI. At IBM Research Labs around the globe, we envision and develop next-generation systems that work side-by side with humans, accelerating our ability to create, learn, make decisions and think. We also architect the future of Watson, which has evolved from an IBM Research project to the world's first and most-advanced AI platform. Whether exploring new technical capabilities, collaborating on ethical practices or applying Watson technology to cancer research, financial decision-making, oil exploration or educational toys, IBM Research is shaping the future of AI.

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.

Holiday shoppers have an infinite digital world of products available for viewing at their fingertips. Stepping into a brick-and-mortar store seems to have lost its appeal. In reality, 85 percent of customers still preferred to shop at physical store last year according to Time Trade. Though that's positive news for brick-and-mortar retailers, many brands still aren't doing enough to meet consumer demands that rival the online experience. Last year, our research showed only a small percentage of retailers met consumer's expectations.

This is the first textbook to teach students how to build data analytic solutions on large data sets (specifically in Internet of Things applications) using cloud-based technologies for data storage, transmission and mashup, and AI techniques to analyze this data. This textbook is designed to train college students to master modern cloud computing systems in operating principles, architecture design, machine learning algorithms, programming models and software tools for big data mining, analytics, and cognitive applications. The book will be suitable for use in one-semester computer science or electrical engineering courses on cloud computing, machine learning, cloud programming, cognitive computing, or big data science. The book will also be very useful as a reference for professionals who want to work in cloud computing and data science. Cloud and Cognitive Computing begins with two introductory chapters on fundamentals of cloud computing, data science, and adaptive computing that lay the foundation for the rest of the book.

Instead of talking about artificial intelligence (AI) many describe the current wave of AI innovation and acceleration with – admittedly somewhat differently positioned – terms and concepts such as cognitive computing or focus on several real-life applications of artificial intelligence that often start with words such as "smart", "intelligent", "predictive" and, indeed, "cognitive", depending on the exact application – and vendor. Despite the term issues, artificial intelligence is essential for and in, among others, information management, medicine/healthcare, data analysis, digital transformation, security (cybersecurity and others), various consumer applications, scientific advances, FinTech, predictive systems and so much more. The historical issue with artificial intelligence – is cognitive better? There are many reasons why several vendors doubt using the term artificial intelligence for AI solutions/innovations and often package them in another term (trust us, we've been there). Artificial intelligence (AI) is a term that has somewhat of a negative connotation in general perception but also in the perception of technology leaders and firms.

Technology leaders are looking to bring artificial intelligence out of its infancy to make breakthroughs in cognitive solutions. IBM Research announced it is teaming up with the Department of Brain and Cognitive Sciences (BCS) at MIT to accelerate the development of machine vision. Together, the organizations will make up the IBM-MIT Laboratory for Brain-inspired Multimedia Machine Comprehension (BM3C). BM3C is a multi-year collaboration to develop cognitive computing systems that resemble how humans understand audio and visual information. BM3C researchers will look into pattern recognition and prediction methods, as well as next-generation models to advance machine vision.

Cognitive computing is the simulation of human thought processes in a computerized model. Cognitive computing involves self-learning systems that use data mining, pattern recognition and natural language processing to mimic the way the human brain works. The goal of cognitive computing is to create automated IT systems that are capable of solving problems without requiring human assistance. Cognitive computing systems use machine learning algorithms. Such systems continually acquire knowledge from the data fed into them by mining data for information.

The most vexing and important issues of the present and the future likely will be solved using the power of supercomputers, a renowned expert says. In fact, supercomputers already are being used to tackle problems in disciplines such as medicine, education, energy exploration and criminal investigation, explained Katharine Frase. That kind of readily available technology, she said, is leading to increased capabilities in policing and other disciplines "in an actionable way." Frase was the keynote speaker Tuesday at SC16, the top international convention showcasing how high-performance computing, networking, storage and analysis are advancing commerce, education, medicine, scientific research, space exploration, weather forecasting and many other disciplines. Frase served as chief technology officer and vice president of public sector at IBM from March 2013 to September 2015.

They generate not just answers to numerical problems, but hypotheses, reasoned arguments and recommendations about more complex -- and meaningful -- bodies of data. What's more, cognitive systems can make sense of the 80 percent of the world's data that computer scientists call "unstructured." This enables them to keep pace with the volume, complexity and unpredictability of information and systems in the modern world. None of this involves either sentience or autonomy on the part of machines. Rather, it consists of augmenting the human ability to understand -- and act upon -- the complex systems of our society. This augmented intelligence is the necessary next step in our ability to harness technology in the pursuit of knowledge, to further our expertise and to improve the human condition. That is why it represents not just a new technology, but the dawn of a new era of technology, business and society: the Cognitive Era. The success of cognitive computing will not be measured by Turing tests or a computer's ability to mimic humans. It will be measured in more practical ways, like return on investment, new market opportunities, diseases cured and lives saved. It's not surprising that the public's imagination has been ignited by Artificial Intelligence since the term was first coined in 1955. In the ensuing 60 years, we have been alternately captivated by its promise, wary of its potential for abuse and frustrated by its slow development. But like so many advanced technologies that were conceived before their time, Artificial Intelligence has come to be widely misunderstood --co-opted by Hollywood, mischaracterized by the media, portrayed as everything from savior to scourge of humanity. Those of us engaged in serious information science and in its application in the real world of business and society understand the enormous potential of intelligent systems. The future of such technology -- which we believe will be cognitive, not "artificial"-- has very different characteristics from those generally attributed to AI, spawning different kinds of technological, scientific and societal challenges and opportunities, with different requirements for governance, policy and management. Cognitive computing refers to systems that learn at scale, reason with purpose and interact with humans naturally. Rather than being explicitly programmed, they learn and reason from their interactions with us and from their experiences with their environment. They are made possible by advances in a number of scientific fields over the past half-century, and are different in important ways from the information systems that preceded them. Here at IBM, we have been working on the foundations of cognitive computing technology for decades, combining more than a dozen disciplines of advanced computer science with 100 years of business expertise. Now we are seeing first hand its potential to transform businesses, governments and society.