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.

What is driving the'robot age' and how can businesses leverage the capabilities being produced? Artificial intelligence is one of the 21st century's dominant fields of innovation. So it's no surprise that cutting-edge robots and other advanced smart machines fall under the rapidly expanding Internet of Things, which is projected to reach 25 billion devices by 2020. Every day we're reading headlines on machines getting'smarter' and robotics transforming a variety of industries, but what's driving this'robot age' and how can businesses successfully integrate and leverage this advanced automation? It's clear that artificial intelligence (AI) is a new industrial revolution, one that's driving the rise of robotics. But AI won't just be an industry – it will be part of every industry.

Imagine if computers could read and interpret documents. Humans could focus their efforts on understanding what analysis results mean to make better decisions. Our interest, at Dynamic Risk, is to improve the safety and reliability of energy pipeline networks by taking full advantage of the vast amounts of data locked in cumbersome formats, handwritten documents, drawings, photographs, and in paper archives. We want to fundamentally change how we ask questions and receive answers. Today, we ask questions based on the data we have available in structured databases.

Sources of inspiration is one thing we do not lack in machine learning. This is what, for me at least, makes machine learning research such a rewarding and exciting area to work in. We gain inspiration from our traditional neighbours in statistics, signal processing and control engineering, information theory and statistical physics. But our fortune continues, and we can take further inspiration from biological and evolutionary systems and, of importance to this series, the cognitive sciences of sociology, psychology and neuroscience. I previously explored important inspirations for machine learning offered by neuroscience and unpacked the role of prediction, sparsity, modularity and complementary learning in building learning systems.

IBM Research is engaged in a research program in symbiotic cognitive computing to investigate how to embed cognitive computing in physical spaces. This article proposes 5 key principles of symbiotic cognitive computing. We describe how these principles are applied in a particular symbiotic cognitive computing environment and in an illustrative application.

IBM Research is engaged in a research program in symbiotic cognitive computing to investigate how to embed cognitive computing in physical spaces. This article proposes 5 key principles of symbiotic cognitive computing.  We describe how these principles are applied in a particular symbiotic cognitive computing environment and in an illustrative application.  

Ubuntu is partnering with IBM Power Systems and OpenPOWER to bring the POWER8 architecture into the mainstream of dev ops practices and cloud operations. In this short video featured at IBM Interconnect, Mark Shuttleworth talks about the number one workload to create competitive advantage, and how the OpenPOWER foundation has enabled IBM to bring innovation back into the data centre.

IBM Research and the Department of Brain and Cognitive Sciences at the Massachusetts Institute of Technology have joined forces to further develop the scientific field of machine vision – a core aspect of artificial intelligence. Big Blue and MIT will build the IBM-MIT Laboratory for Brain-inspired Multimedia Machine Comprehension, or BM3C, in Cambridge, Mass. Together they plan to develop cognitive computing systems that mimic the human ability to understand and integrate input from multiple sources for use in a variety of computer applications in industries such as healthcare, education, and entertainment. MIT researchers will collaborate with IBM scientists and engineers who will provide technology expertise and advances from the IBM Watson platform. The BM3C will address technical challenges around both pattern recognition and prediction methods in the field of machine vision that are currently impossible for machines alone to accomplish.

Is your firm prepared to welcome in an era of legal practice using artificial intelligence (AI)? Where is this technology headed and why must law firm leaders fully understand how cognitive computing works in order to benefit from it? With the vast amounts of structured and unstructured data firms have to deal with, there is increasing pressure from nimble technologies and clients to attract AI and cognitive technologies. Understanding the market implications of digital business information and trends is now key to attaining the best possible performance, revenue gains and cost savings. Berwin Leighton Paisner was one of the first firms to embrace AI in the UK, developing its'contract robot' which promised to complete work in seconds that would have otherwise taken a team of paralegals months to do.