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 . 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 :
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 .
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 .
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 :
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 .
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 . 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.
Users who have LIKED this post: