Cognitive Computing

Check for current information on cognitive computing including events, publications and our blog.  The Consortium is an outgrowth of our Cognitive Computing Working Group, a group of industry leaders, academics, and analysts who created the following definition for cognitive computing.

Cognitive Computing Definition


This definition of cognitive computing was developed in mid-2014 by a cross-disciplinary group of experts from BA-Insight, Babson College, Basis Technology, Cognitive Scale, CustomerMatrix, Decision Resources, Ektron, Google, HP Autonomy, IBM, Microsoft/Bing, Next Era Research, Oracle, Pivotal, SAS. Saxena Foundation, Synthexis, and Textwise/ This project was led by Sue Feldman at Synthexis and Hadley Reynolds of NextEra Research. It was sponsored by CustomerMatrix, HP Autonomy, and IBM. The goal of the project was to define how cognitive computing differs from traditional computing and to provide a non-proprietary definition of cognitive computing that could be used as a benchmark by the IT industry, researchers, the media, technology users and buyers.


Cognitive computing makes a new class of problems computable. It addresses complex situations that are characterized by ambiguity and uncertainty; in other words it handles human kinds of problems. In these dynamic, information-rich, and shifting situations, data tends to change frequently, and it is often conflicting. The goals of users evolve as they learn more and redefine their objectives. To respond to the fluid nature of users’ understanding of their problems, the cognitive computing system offers a synthesis not just of information sources but of influences, contexts, and insights. To do this, systems often need to weigh conflicting evidence and suggest an answer that is “best” rather than “right”.

Cognitive computing systems make context computable. They identify and extract context features such as hour, location, task, history or profile to present an information set that is appropriate for an individual or for a dependent application engaged in a specific process at a specific time and place. They provide machine-aided serendipity by wading through massive collections of diverse information to find patterns and then apply those patterns to respond to the needs of the moment.

Cognitive computing systems redefine the nature of the relationship between people and their increasingly pervasive digital environment. They may play the role of assistant or coach for the user, and they may act virtually autonomously in many problem-solving situations. The boundaries of the processes and domains these systems will affect are still elastic and emergent. Their output may be prescriptive, suggestive, instructive, or simply entertaining.

In order to achieve this new level of computing, cognitive systems must be:

  1. Adaptive. They must learn as information changes, and as goals and requirements evolve. They must resolve ambiguity and tolerate unpredictability. They must be engineered to feed on dynamic data in real time, or near real time.
  2. Interactive. They must interact easily with users so that those users can define their needs comfortably. They may also interact with other processors, devices, and Cloud services, as well as with people.
  3. Iterative and stateful. They must aid in defining a problem by asking questions or finding additional source input if a problem statement is ambiguous or incomplete. They must “remember” previous interactions in a process and return information that is suitable for the specific application at that point in time
  4. Contextual. They must understand, identify, and extract contextual elements such as meaning, syntax, time, location, appropriate domain, regulations, user’s profile, process, task and goal. They may draw on multiple sources of information, including both structured and unstructured digital information, as well as sensory inputs (visual, gestural, auditory, or sensor-provided).

Cognitive systems differ from current computing applications in that they move beyond tabulating and calculating based on preconfigured rules and programs. Although they are capable of basic computing, they can also infer and even reason based on broad objectives.

Beyond these principles, cognitive computing systems can be extended to include additional tools and technologies. They may integrate or leverage existing information systems and add domain or task-specific interfaces and tools as required.

Many of today’s applications (e.g., search, ecommerce, eDiscovery) exhibit some of these features, but it is rare to find all of them fully integrated and interactive.

Cognitive systems will coexist with legacy systems into the indefinite future. Many cognitive systems will build upon today’s IT resources. But the ambition and reach of cognitive computing is fundamentally different. Leaving the model of computer-as-appliance behind, it seeks to bring computing into a closer, fundamental partnership in human endeavors.

Note: This definition is available for public distribution and re-use under the Creative Commons Attribution-ShareAlike License (CC-BY-SA), version 3.0


Smart Machines: IBM’s Watson and the Era of Cognitive Computing. Columbia Business School Publishing by John E. Kelly III, Steve Hamm

The Answer Machine. By Susan Feldman. Morgan & Claypool, 2012.

Surfing Toward the Future. By Peter J. Denning. 
Communications of the ACM, Vol. 57 No. 3, Pages 26-29 10.1145/2566967

IBM’s TrueNorth processor mimics the human brain by Daniel Terdiman.

Ferrucci, D. et al. (2010) Building Watson: an overview of the DeepQA Project. Association for the Advancement of Artificial Intelligence, Fall 2010, 59–79.

Cognitive Computing: Beyond the Hype. By Susan Feldman and Hadley Reynolds.

Cognitive Computing: Why Now and Why it Matters to the Enterprise. By Guy Mounier. KMWorld, Sept. 2014

Another Face of Cognitive Computing. By Jennifer Zaino May 27, 2014

IBM Watson. Jeopardy full episode day 1. (2011). com/watch?v=qpKoIfTukrAandfeature=related

IBM Watson. Jeopardy! – Watson game 2. kDA-7O1q4ooandfeature=related

IBM Watson. Jeopardy! IBM Watson day 3 part 2/2. (2011, February 16). Retrieved July 26, 2012 from

Will IBM’s Watson Usher in a New Era of Cognitive Computing? Scientific American. Nov 13, 2013 |By Larry Greenemeier

What is cognitive computing? IBM Research.

Cognitive Computing and the Synthexis Cognitive

Computing Consortium

The Cognitive Computing Consortium is a group of organizations and individuals from the IT, academic and analyst communities.  Its goal is to define what cognitive computing means, and to conduct research on the market and technologies associated with it. We believe that soliciting input from a cross-industry group of recognized thought leaders to establish a common definition can help accelerate understanding and appreciation of the value propositions of cognitive computing. This effort will help to clarify an emerging market and allow innovators and market leaders to describe their products with a strong independent definition as a framework.

Working group members are individuals affiliated with:

    • BA-Insight
    • Babson College
    • Basis Technology
    • Cognitive Scale
    • CustomerMatrix
    • Decision Resources
    • Emu/TechCrunch
    • Google
    • HP Autonomy
    • IBM
    • IBM  Watson
    • Microsoft/Bing
    • Next Era Research
    • Pivotal
    • RAMP
    • SAS
    • Saxena Foundation
    • Synthexis
    • Textwise


Innovations happen when three elements converge: market needs, available technologies, and an environment of experimentation and adventure. Cognitive computing represents a series of innovations emerging from exactly this confluence of forces:

– A significant market demand for intelligent computing systems is emerging, as the quantity of data and the pervasive spread of computers into the furthest corners of everyday life have dramatically increased the complexity individuals must face in order to manage their data environments. These new environments have often left individuals powerless to make sense of the information they need to accomplish tasks and achieve goals.

– Continuing advances in computer technologies—both hardware and software— have lowered barriers to achieving effective computer support in all kinds of environments. Hardware speed, storage capacity, miniaturization, network presence and reliability, and mobility are achieving unprecedented levels of performance and integration. At the same time, advances in software development infrastructures and techniques, availability of robust open software solutions, and a generation of developers raised on internet technology have revolutionized the speed with which new solutions are created, enhanced, and then superseded by more innovative approaches.

– Powered both by the presence of a vigilant and ambitious venture investor community and by the drive of a new generation of dominant technology firms to out-innovate their competitors, today’s technology markets are exceptionally adventurous. From self-driving cars, to book-delivering drones, to sci-fi eyewear, Dick Tracy power watches, and TV game-playing supercomputers, we are clearly in a period eager for experimentation.

Today IBM’s Watson investments represent a single vendor’s bet on a potentially powerful alternative style of analytic applications. Other vendors have or are developing similar platforms and applications built on the principles we have outline above. These new platforms will become a springboard for for future innovation in the industry, and they will offer opportunities to many businesses and technology firms to enhance their own performance. But in order to fulfill its promise, this emerging platform requires several pieces currently missing from the conversation and the hype, including:

  • Understanding of its foundation elements,
  • Definition of its potential market value,
  • Technical and management education to dispel skepticism among industry players and customers alike.

An open source approach to creating new ideas about these missing elements will bring together leading industry and academic thinkers and create a credible process to advance industry and market understanding of the nature and importance of cognitive computing.

The Cognitive Computing Consortium is a phased project that will develop research in this area. Phase I of this project will form a working group of experts in many areas that pertain to cognitive computing.  In Phase II, members of this initial working group will draft and distribute a definition of cognitive computing.  The members of the group have expertise in search, analytics, machine learning, text analytics, intellectual property, and technology market research.  The definition will be posted as conspicuously as possible in blogs, on Twitter, LinkedIn, Wikipedia, and in industry publications in order to solicit and comments from a wider group of experts.

Phase III of this project will use this definition as a basis for defining a cognitive computing market, and for initiating further research on the technologies, business and social implications of cognitive computing.  This phase will be ongoing.

Phase IV will further the conversation by presenting and discussing research findings  at a series of cognitive computing conference.

Consortium Sponsors



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With additional support from IBM

For information on sponsoring the Cognitive Computing Consortium, please contact Sue Feldman,

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