As businesses venture deeper into the Digital Age, they are finding new technologies can help them analyze the oceans of data being generated each day. One of the technologies to which many companies are turning is cognitive computing. A couple of years ago, analysts from the House of IT wrote, “Cognitive computing (CC) is the latest IT advancement which aims to create an automated thinking system and additional professional IT services that will solve problems and make decisions without requiring human assistance. The system is known as the path to the next great set of business possibilities. Cognitive computing is the simulation of the human thought processes in a computerised model. This involves self-learning systems that use data, natural language processing and pattern recognition to imitate the way the brain works by having an intent, memory, foreknowledge and cognitive reasoning. CC is a problem-solving approach that uses hardware and software to approximate the form and function of natural cognitive processes.” That definition goes a bit far when it claims cognitive computing is a “simulation of human thought processes.” It’s not. Cognitive computing is more of an approximation than a simulation.
What is Cognitive Computing?
Kanishk Priyadarshi (@kp_tweets), an innovation executive with IBM, correctly observes, “‘Cognitive Computing’ is defined differently by different institutions.” For example, IBM’s Watson is designed to respond to queries where the answer is found within a large corpus of documents. It analyzes massive amounts of data and provides a “best guess” answer (IBM calls it a “confidence-weighted response”) based on what it finds. In contrast, the Enterra® Enterprise Cognitive System™ (ECS) applies both semantic intelligence (i.e., a combination of artificial intelligence, machine learning, natural language processing, and ontologies) and computational intelligence (i.e., advanced mathematics) to derive an answer. Despite variations in approach, most cognitive computing systems have some common features, including advanced analytics, machine learning, and natural language processing. Priyadarshi writes, “Cognitive Computing is a computational science, which ‘mashes up’ the concepts of probabilistic programming, linguistics, and psychology.”
The Cognitive Computing Consortium explains, “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.”
How will Cognitive Computing help Businesses?
Serhiy (Serge) Haziyev, Vice President of the Technology Services Group at SoftServe, and Yuriy Milovanov, a computer science expert, aren’t really concerned that there is no universally-accepted definition of cognitive computing. “Our goal,” they write, “is not to explain the terminology, but rather to demonstrate how this concept can be applied to real business needs, and implemented with technologies available on the market.” Referring to the Cognitive Computing Consortium’s assertion that cognitive technologies can help with “human kinds of problems,” Haziyev and Milovanov offer a few examples. They include:
- Speech understanding
- Face detection
- Medical diagnosis
- Risk assessment
- Sentiment analysis
- Psychometrics to identify psychological profiles
They note, “Some of these problems are almost intractable for traditional computing techniques although people have been successfully solving them for thousands of years. On the other hand, the majority of them is still challenging even for a human mind.” Joe McKendrick (@joemckendrick) reports that cognitive computing is currently used by companies to analyze the performance of assets, facilities, and energy. In the near future, he predicts it will play a major role in connected transportation visibility and will also find its way into the fields of product quality monitoring and predicting failures. Diya Koshy George claims another area in which cognitive computing has found a home is marketing. “Marketers,” she writes, “are gaining deeper insight into customer preferences, discovering new patterns, getting to know each customer on unprecedented levels, and having the ability to fine-tune campaigns on the fly.” This is further enhanced with data from other sources such as social media.
Analysts from Persistence Market Research predict, “The most significant future prospect of smart machines is the impact on the global knowledge working community.” They also predict that the marriage of smart machines with the Internet of Things (IoT) will have significant impact. “The automated world is still awaiting a seamless collision of smart technology with Internet of Things. The merger of IoT and smart machines will develop new opportunities in various applicable fields, such as entertainment, smart urbanisation, healthcare, and even in disaster management measures. Furthermore, the incorporation of IoT and smart machines in the manufacturing processes will expedite the production capacity of goods. With the help of IoT, various industries will be more instrumented than the basic automation processes, and the yield metric and consumption level data assessed from smart analytical programs will ease a profitable rectification of any manufacturing setting.”
Another area in which cognitive technologies will play a significant role is retail. Shailendra Kumar (@meisshaily), CEO of Analyze-It Technologies, writes, “Cognitive technology will soon impact practically everything, and it already provides glimpses of a future that we have probably not yet dreamt of. No industry will remain untouched by cognitive technology. But one of the prime industries that are going to simply metamorphose as a result of cognitive analytics will be that of retail.”
As cognitive computing systems mature, executives in every industry will begin to see how they can be used to transform their businesses. Most analysts agree that in order to survive in the decades ahead, companies must break their industrial age organizational shackles and transform into digital enterprises. Cognitive computing platforms can provide the foundation on which a digital enterprise can be built. Haziyev and Milovanov explain, “Cognitive Computing doesn’t bring a drastic novelty into the AI and Big Data industry. Rather it urges digital solutions to meet human-centric requirements: act, think, and behave like a human in order to achieve maximum synergy from human-machine interaction.”
 Staff, “Cognitive Computing is a Big Thing in IT,” House of IT, 2015.
 Kanishk Priyadarshi, “What is Cognitive Computing?” Particle News, 7 February 2017.
 Serge Haziyev and Yuriy Milovanov, “Cognitive Computing: How to Transform Digital Systems to the Next Level of Intelligence,” Dataconomy, 11 January 2017.
 Joe McKendrick, “Really Thoughtful Data: Is ‘Cognitive Computing’ the Next Big Thing in Analytics?” Informatica Blog, 1 December 2016.
 Diya Koshy George, “Observant and intuitive, this intelligent technology is a game-changer for businesses to better understand their customers,” Your Story, 21 September 2016.
 Persistence Market Research Staff, “Smart Machines: The Future with Cognitive Computing,” PMR Blog, 8 September 2016.
 Shailendra Kumar, “Cognitive Retail: The Future Is Here,” Information Management, 30 June 2016.