A team of scientists at IBM Research in Zurich, have created an artificial version of neurons using phase-change materials to store and process data. These phase change based artificial neurons can be used to detect patterns and discover correlations in the areas of big data and unsupervised machine learning. The results of the decade-long research to use phase-change materials for memory applications were recently published in the journal Nature Nanotechnology. The research team is led by Evangelos Eleftheriou. The development of energy-efficient, ultra-dense integrated neuromorphic technologies for applications in cognitive computing is getting a lot of attention.

Each of us generates nearly a gigabyte of data per day. This huge volume of data contains an incredible amount of information that we are able to read and organize thanks to cognitive computing. Cognitive computing comes from a mashup of cognitive science -- the study of the human brain and how it functions -- and computer science. he goal of cognitive computing is to simulate human thought processes in a computerized model. Using self-learning algorithms that use data mining, pattern recognition and natural language processing, the computer can mimic the way the human brain works. The potential areas of application of cognitive computing are many.

Based on the increasing number of ways that artificial intelligence (AI) is finding application in – and powering industries, IBM has announced the introduction of an AI Nanodegree program that incorporates expertise from IBM Watson and covers the basics of artificial intelligence. "As artificial intelligence (AI) begins to power more technology across industries, it's been truly exciting to see what our community of developers can create with Watson. Developers are inspiring us to advance the technology that is transforming society, and they are the reason why such a wide variety of businesses are bringing cognitive solutions to market," said Rob High, IBM Fellow, Vice President & Chief Technology Officer of IBM Watson. Speaking in Las Vegas at World of Watson, High disclosed that AI is becoming more ubiquitous in the technology people use every day and he stressed the need for developers to continue to sharpen their cognitive computing skills. "They are seeking ways to gain a competitive edge in a workforce that increasingly needs professionals who understand how to build AI solutions.

It is a fact that healthcare is unsustainable. American health spending will reach nearly $5 trillion, or 20 percent of gross domestic product by 2021. The World Health Organization (WHO) estimates that there is a worldwide shortage of around 4.3 million physicians, nurses, and allied health workers. So how could we change it? The most likely solution is technology.

Cognitive systems learn from vast amounts of complex, ambiguous information and help us do amazing things, such as treat disease, manage finances, and transform commerce. Underneath these systems, the core fields of science & technology --from artificial intelligence to brain science to computer architecture to cognitive science-- are advancing rapidly and achieving breakthroughs not envisioned even a few years ago. IBM Research and its network of scientific partners are pursuing some of the hardest technical problems while creating practical solutions that make a difference to the world. Accompanied by special guests, Guruduth Banavar will highlight IBM's commitment to advancing the science and technology behind cognitive computing.

The ability to think is one of the things that marks us out as human, "I think therefore I am," as the philosopher René Descartes put it. But what if machines were able to mimic human thought processes? This is the basic premise behind cognitive computing. In order to replicate human thought processes, cognitive computing uses techniques like pattern recognition, data mining and natural language processing. The ultimate goal is to be able to make computer systems that are capable of solving complex problems without needing human assistance to prompt them in the right direction.

Next-generation cognitive computing is redefining how we live and work as more businesses are using all the data available to them to improve performance and customer service, and drive innovation and revenue. Today's business challenges have never been more complex, and the critical insights that can help address these challenges are often buried in an avalanche of data. Previously, these insights were beyond the capabilities of conventional computing solutions – programmable systems based on mathematical principles that harken back to the 1940s. But IBM Watson has changed the game. IBM Watson is built upon a new foundation called cognitive computing – a system that learns and reasons from interactions with humans, files, online interactions and its environment.

Jonas Nwuke discusses how IBM Watson's cognitive computing will tackle problems that are "uniquely human" At our PSFK 2015 conference, we were thrilled to have Jonas Nwuke of the IBM Watson team as one of our speakers. You're likely to have heard of Watson as the grand champion of Jeopardy!, from pieces about its culinary capabilities, or from PSFK and IBM Waston's Good Data contest, but these are just teases of what's in store for intelligent machines and cognitive systems. With some of the recent forward steps taken by AI and cognitive computing, we wanted to look back on how these technologies are being developed, and where we can still go. "grand challenge" of 2011 served to help prove a hypothesis that humans can create systems capable of navigating ambiguous, confusing, and complex environments like language. As Jonas mentioned, the objective, then, is to build a machine that helps us focus on things that make us uniquely human--"finding inspiration, leveraging creativity, and solving problems by making meaning of the seemingly meaningless."

Just about every major technology player is investing serious financial and human capital in pursuit of advances in cognitive computing. The National Science and Technology Committee on Technology released a much-anticipated report on how to prepare for the future where we have mature artificial intelligence systems. The report, Preparing for the Future of Artificial Intelligence, outlines specific implications that artificial intelligence will have when it comes to transforming our society and outlines twenty-three recommendations for federal agencies to consider. Computers that think and work like humans will change the nature of our public agencies, from how they are designed and managed to the delivery of public services and the management of public goods. We have good reason to believe that there will be significant benefits to be had from cognitive computing solutions.

The ability to think is one of the things that marks us out as human, "I think therefore I am," as the philosopher René Descartes put it. But what if machines were able to mimic human thought processes? This is the basic premise behind cognitive computing. In order to replicate human thought processes, cognitive computing uses techniques like pattern recognition, data mining and natural language processing. The ultimate goal is to be able to make computer systems that are capable of solving complex problems without needing human assistance to prompt them in the right direction.