Analytics, Algorithms, Artificial Intelligence, Big Data       

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Analytics, Algorithms, Artificial Intelligence, Big Data - overview


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Computer scientists have long dreamed of using data to extend the intellectual and cognitive capabilities of human beings. At IBM we have organized this quest along three lines:

  • Artificial intelligence, or the effort of human beings to create technologies that behave like human beings.
  • Big data, or locating valuable data that human beings can subject to deeper analysis.
  • Algorithms, or speeding up programs -- and solving problems not known to be solvable -- in order to get actionable business insight in real time.

Deep Blue and Watson are among the high-profile projects that have grown out of IBM's AI and analytics research vision. They offer up two examples where IBM asserted hard theoretical and practical problems and then challenged scientists to measure their progress against them. Moreover, such challenges had to be broad enough to apply to a larger domain.

With Deep Blue, researchers developed software that could evaluate the patterns in chess as well as patterns elsewhere. In short, IBM united the idea of a special purpose machine with a general purpose machine. Since 1996, the general purpose machine has been applied to several business areas that require massive amounts of processing and computational power, such as molecular dynamics, financial risk assessment and decision support.

With Watson, researchers created a computer system capable of answering questions posed in natural language. Watson debuted in 2011 when it competed with two highly skilled contestants on Jeopardy!, a TV game show based on rapid recall of facts across a variety of subjects. The "Deep QA" computing system has since found applications in hospital utilization management and healthcare insurance companies.

Organizations that have profited from IBM's AI and analytics research include:

  • The Government of Brunei, which worked with IBM to develop weather forecast models to help farmers maximize rice production and profitability.
  • Mueller, Inc., a manufacturer of pre-fab metal buildings and roofing products, which worked with IBM to track the strengths and weaknesses of its sales team in an effort to transform the company's B2B focus to a more retail-driven business. (pdf)
  • BodyMedia, Inc., the developer of weight-loss armbands, worked with IBM to build a wearable tracking system that monitors calorie burn and other factors that help users understand their weight management goals and lifestyle choices. (pdf)

IBM has long excelled at integrating large amounts of disparate data. In the future, this integration will play a critical role in analyzing terabytes of data so that organizations of all kinds can use relevant, actionable data to solve their business, consumer, operational, demographic and distribution problems. Read more about the impact of IBM's AI and analytics research and implementations.

At IBM, these professional interest communities (PICs) comprise Artificial Intelligence and Analytics:

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