Cognitive Computing: Augmenting Human Intelligence

What Exactly Is Cognitive Computing?


Cognitive computing (CC) is the simulation of human thought processes in a computer model. It is a technology platform based on the scientific disciplines of artificial intelligence and signal processing. In summary, a cognitive computer ploughs through un/structured data, to find hidden knowledge and present data in an actionable form. It is worth noting that CC is an iterative process, with humans verifying or discarding any new discoveries. This allows the system to ‘learn’ over time, and become better at identifying patterns.


Looking back at the origin of CC, it was first mentioned by Alan Turing in 1950, through his ‘Computing Machinery and Intelligence’ paper. He proposed the Turing Test, to assess a machine’s ability to exhibit intelligent human behaviour [1]. You may be wondering why CC has only picked up in the last couple of years? The science behind CC has only recently gained momentum, with advancements made within fields such as data mining and natural language processing. The graph below shows a timeline of the progression of CC [2]:



Real Life Example: IBM


Dr. Jeff Welser, Vice President and Lab Director from IBM Research, talked about how they have restructured to offer specific solutions from 4 subdivisions. These areas are: Cognitive Computing, Science and Technology, Computing as a Service, and Data (Industry and Solutions). Focusing on the first area of research, Cognitive Computing is all about building systems that do things the brain does, better. Dr. Welser pointed out that all of these things can be achieved through standard architecture, but to reach full brain-scale, we need to use alternative architecture.


IBM spends nearly one-third of its R&D budget on developing its cognitive learning platform: Watson. They are looking to see Watson dominate numerous industries, with its powerful analysis and database of experience. In fact, only 2 days ago (12th July) did IBM announce its Watson-based services platform, fully built on the IBM Cloud. The aim of this platform is to use artificial intelligence to predict and identify potential problems in a firm, to reduce business disruption and improve overall operation. 3 particular areas, that previously required human intervention, can now be automated with cognitive insight: continuous compliance, autonomous governance, and self-service and automated provisioning. This service is already being adopted early by Danske Bank, as part of a 10-year service contract [3].


Cognitive Computing Capabilities


According to a study from the IBM Institute for Business Value, there are 3 main areas for CC to have the biggest impact. The first is engagement, which is all about humans collaborating with the system. The systems capabilities can be extended by teaching it how humans provide expert assistance and present vast amounts of information in a usable way. This allows the cognitive systems to play the role of an assistant. The second is decision-making, which is about continuously evolving based on new information, outcomes and actions. At the moment, the cognitive systems act as an advisor, by suggesting options to the human users – who make the final decision. The third is discovery of insights that humans have not previously discovered. This aspect is still in the early stages, with the biggest advancement made within medical research – due to the sheer availability of information [4].


The Future of Cognitive Computing


There are a handful of firms dominating the enterprise solutions for CC. IBM Watson is, by far, the biggest player – focusing on deep analysis and evidenced based reasoning to solve problems, make the right decisions and reduce costs. Microsoft Cognitive Computers is focused on making intelligent APIs, to make products and services more engaging and discoverable. Google DeepMind offers a wide variety of solutions, by learning directly from raw experience and data. The graph below shows the key firms in CC, according to research conducted by Bloomberg [5]:



As CC develops over time, its potential applications will exponentially increase. In the Healthcare sector, CC will allow gigabytes of medical data to be analysed, to form specific treatment plans for each patient. For the Financial Services industry, CC will enable firms to identify risks that were previously overlooked, due to a lack of analytics tools/platforms. In Manufacturing, it can allow firms to alter production output and be more adaptable to the market conditions. CC can also be used more generally, for more accurate weather predictions, or more efficient use of utility reserves for instance [6].


According to an IBM study, 50% of surveyed CEOs plan to adopt CC by 2019. Whilst 73% stated that CC will play an important role in the future of their organisations [7]. The applications are truly limitless, and this is definitely a pioneering technology. In this interconnected world driven by Big Data, IoT and Cloud Computing, CC has tremendous potential to revolutionise countries and industries alike.












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6 comments on “Cognitive Computing: Augmenting Human Intelligence”

  1. I thought your blog post as very well researched.

    As an architect in the Networking and Data Center space, I specialize in Wireless, IoT, and Cybersecurity. With the evolution of how AI is used in the Cybersecurity space, I was forced to learn more about Cloud Computing. Due to my companies focus, the leaders according to the Garnter Quadrant for Cloud Computing are Amazon AWS, Google Cloud Platform and Microsoft Azure. With that said, I learned from your post that they are not necessarily the leaders in CC.

    According to the Huffington Post that the Top Cognitive Computing (Predictive Analytics) Companies for Enterprise Solutions are:

    1. IBM Watson – Leverage deep analysis and evidence based reasoning to quickly make the right decisions, solve problems, reduce costs, and arrive at optimal outcomes and so much more.
    2. Microsoft Cognitive Computers – Intelligent APIs that make products and services more intelligent, engaging, and discoverable.
    3. HPE Haven OnDemand – Big data platform in the cloud and on premise.
    4. Cisco Cognitive Threat Analytics – Detects and responds to security threats.
    5. Google DeepMind – Technology that learns directly from raw experience or data, and is general in that it can perform well across a wide variety of tasks straight out of the box.
    6. CognitiveScale – Learns a domain, understands end-user context, personalizes and adapts experiences, and improves continuously as it learns from data and actions.
    7. Customer Matrix – Serves on the front line of sales and customer service excellence
    8. Spark Cognition – Builds Artificial Intelligence systems that secure & optimize cyber-physical assets


    It was interesting to discover that Amazon Machine Learning was not even on the list. According to the Gartner report in February of 2017, Amazon and Microsoft were the leaders for IaaS and Tableau, Microsoft and Qlik were the leaders in Business Intelligence and Analytic Platforms. ( According to the GMQ, IBM comes in as 4th in the Visionary quadrant. Depending upon where you look, it’s interesting to see varying opinions with regard to whom the leaders are. IN my business, many corporations only invest in those companies that are considered to be leaders in their respective industries.
    If you were to evaluate all of the various MQ’s on Garners website (, you would see that there are no MQ’s associate to AI, ML or Cognitive Compute, they classify it as Analytics and Business Intelligence Platforms and indicate that IBM is not a leader. While I believe that IBM is doing several great things for this countries veterans, and in the Medical Industry with IBM Watson, “IBM’s revenue fell short of analysts’ projections, marking a 20th consecutive quarterly decline as growth in new businesses like cloud services and artificial intelligence failed to make up for slumping legacy hardware and software sales” – Posted April 18, 2017.


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  2. Thank you for your post I found it quit interesting.
    Although it’s amazing all of the technologies that we’re seeing now, how do you think innovations such as Watson could affect the human way of living? Do you think it will eventually replace humans in many jobs?


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    1. Thanks for your comment Irene! I think Cognitive Computing is a very interesting technology that will definitely supplement humans in everyday life. Artificial Intelligence is developing capabilities to make human decisions, and this will definitely replace humans in some fields. However, Cognitive Computing is focused more on giving humans better research and options, to then make a better informed decision. So it may still replace jobs, but I don’t think that’s the aim. I think the aim is to build upon human intelligence, rather than substitute it.

  3. This was such an immersive and insightful read! Another classmate, Victor, made a blog post about Brains vs Computers which I feel supplemented your blog read really well. That being said, I think cognitive computing in future will not be a stand alone solution but will in fact merge and link with AI, Big Data, Cloud, IoT and so on. And when that happens, the possibilities will be endless and limitless. Let me know your thoughts on it


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    1. I totally agree Saran! All of these buzzwords are definitely interconnected, and supplement one another. The future will look very different to what it is now, and all of these areas will revolutionise industries and countries alike.

  4. Dear Jaykishen, it is so interesting to read your post.
    Reading it, I wonder about the people creating and programming this new products and services, and I think: How is the process to find a way so that the limitations of the human mind are not reflected in the solutions?
    As you say, I think that bot will complement each other.
    The other big question in my head is: if we are now able to teach machines to do what humans do, how come that there is still not a consistent way to teach humans to do what other humans do? Some humans overcome phobias and others don’t, some human are motivated and other don’t, some humans are happy and others are depressed.
    Can CC and AI help us to come back to human intelligence and improve it, with predictable processes?
    This is a questions that Dr Richard Bandler, creator of NLP (another NLP: neuro linguistic programming, not natural language processing) has been answering with his creation and the evolution of it: Design Human Engineering.



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