Cognitive Computing: More Human Than Artificial Intelligence

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Mistaking cognitive computing for just another AI misses the important contributions this computing platform offers. In 2011, two episodes of Jeopardy stunned the world when the best Jeopardy players in the history squared off against IBM's Watson Cognitive Computing System and were soundly beaten. For many, this was the moment when artificial intelligence probably became a very real thing in their minds; one contestant even scrawled "I, for one, welcome our future computer overlords" on his answer in his final losing round. He likely spoke for many in the audience. Watson dominated a game where nuanced wordplay was intrinsic to the challenge of the contest, where contestants needed to provide the question that fit an answer shrouded in double meaning.


Cognitive Computing: More Human Than Artificial Intelligence

#artificialintelligence

Mistaking cognitive computing for just another AI misses the important contributions this computing platform offers. In 2011, two episodes of Jeopardy stunned the world when the best Jeopardy players in the history squared off against IBM's Watson Cognitive Computing System and were soundly beaten. For many, this was the moment when artificial intelligence probably became a very real thing in their minds; one contestant even scrawled "I, for one, welcome our future computer overlords" on his answer in his final losing round. He likely spoke for many in the audience. Watson dominated a game where nuanced wordplay was intrinsic to the challenge of the contest, where contestants needed to provide the question that fit an answer shrouded in double meaning.


What is Cognitive Computing? Features, Scope & Limitations

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Human thinking is beyond imagination. Can a computer develop such ability to think and reason without human intervention? This is something programming experts at IBM Watson are trying to achieve. Their goal is to simulate human thought process in a computerized model. The result is cognitive computing – a combination of cognitive science and computer science.


Learning to trust artificial intelligence systems accountability, com…

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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.


Deloitte disruption ahead IBM Watson

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Disruption ahead: Deloitte's point of view on IBM Watson8 9. What makes Watson unique In technical terms, IBM Watson is an advanced open-domain question answering (QA) system with deep natural language processing (NLP) capabilities. At this point, the Watson Software as a Service (SaaS) platform is most effectively used to sift through massive amounts of text--documents, emails, social posts, and more--to answer questions in real time. Watson accepts questions posed by the user in natural language and provides the user with a response (or a set of responses) by generating and evaluating various hypotheses around different interpretations of the question and possible answers to it. Unlike keyword-based search engines, which simply retrieve relevant documents, Watson gleans context from the question to provide the user with precise and relevant answers, along with confidence ratings and supporting evidence. Its learning capabilities allow Watson to adapt and improve hypothesis generation and evaluation processes over time through interactions with users. Developers and other users can improve the accuracy of responses by "training" Watson. IBM is also continuing to expand Watson's capabilities to incorporate visualization, reasoning, ability to relate to users, and deeper exploration to gain a broader understanding of the information content. Watson recently launched a new platform service that has the ability to ingest and interpret still and video images, which is another significant type of unstructured data.