Artificial Intelligence for IT Operations

Kalpana Vijayakumar

Is it possible for a computer to think and act without human intervention? The answer is yes, and that is called Cognitive computing.

Cognitive computing includes technology platforms that combine machine learning, reasoning, natural language processing, speech, vision, and human computer intervention that mimic the human brain, and solve problems without human assistance. Cognitive computing involves deep learning algorithms and big data analytics to provide insights.

The purpose of cognitive computing is to build a computing framework that can solve complicated problems without frequent human intervention. To implement it, cognitive computing consortium has recommended the following features.

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Scope of Cognitive Computing

We do have to accept that computers have been faster at calculations and processing than humans for decades. But, in a few cases, they have failed to accomplish the tasks that humans take for granted, like understanding the natural language and recognizing unique objects in the images and processing them. Cognitive computing solves all these challenges. They can act in complex situations and have a far-reaching impact on our lives.

Pera study by the IBM Institute for business value – cognitive computing involves three capabilities. These capabilities are related to the ways people think and demonstrate their cognitive abilities in their day-to-day life.

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The current cognitive computing landscape is dominated by large players – IBM, Microsoft, and Google. IBM being the pioneer of this technology has invested $26 bn dollars in big data and analytics, now spends close to one-third of its R&D budget in developing cognitive computing technology. IBM and Google have acquired some of their rivals and the market is moving towards consolidation. Below are the leading players in this market.

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IBM Watson

Watson assistant is IBM’s AI product that allows you to build, train, and deploy conversational simulators into any applications, device, or channel.

Most chatbots try to mimic human interactions, which can frustrate the end-user when a misunderstanding occurs. Watson Assistant aims to resolve that. It knows how to handle the end-user sensibly and when to direct queries to a human executive. It can be deployed on any cloud or on-premises environment.

Watson supercomputer processes at a rate of 80 teraflops (i.e. trillion floating-point operations per second).To replicate a high functioning human’s ability to answer questions, Watson accesses 90 servers with a combined data store of over 200 million pages of information, which it processes against six million logic rules.

Microsoft Cognitive Services

The machine-learned smarts that enable Microsoft’s Skype Translator, Bing and Cortana to accomplish tasks such as translating conversations, compiling knowledge and understanding the intent of spoken words are increasingly finding their way into third-party applications that people use every day. The democratization of AI is coming as part of Microsoft cognitive services, a collection of 25 tools that allows developers to add features such as emotions and sentiment, detection, vision and speech recognition and language understanding to their applications with zero experience in machine learning.

“Cognitive services is about taking all the machine learning algorithms and AI smarts that we have in this company and exposing them to developers through APIs so that they don’t have to invent the technology themselves”, Mike Seltzer, a principal researcher in the Speech and Dialog research group at Microsoft’s lab in Redmond, Washington.

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Google DeepMind

DeepMind was acquired by Google in 2014 and is considered to be a leading player in AI research. If you have used Google, there’s a high possibility that you’ve interacted with DeepMind in some way, as its deep learning tools have been implemented across the spectrum of Google products and services. Some of the most prominent uses for DeepMind AI includes speech recognition, image recognition, fraud detection, spam identification, handwriting recognition, translation, Google Maps Street View, and Local Search.

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Google devices like an Android Phone or Google Home, have invaded our homes and has impacted our lives. Every time you say, “Okay, Google” followed by a question, DeepMind helps Google Assistant understand what you are saying. Unlike Amazon’s Alexa, which uses eight microphones to understand voice commands, Google Home’s DeepMind-powered voice recognition system requires only two.

Cognitive Scale

Cognitive Scale founded by former members of the IBM Watson team provides cognitive cloud software for enterprises. Cognitive Scale’s augmented intelligence platform delivers insights-as-a-service and accelerates the creation of cognitive applications in healthcare, retail, travel, and financial services. They help businesses make sense from ‘dark data’ – messy, disparate, first and third-party data and drive actionable insights and continuous learning.

Spark Cognition Spark Cognition is an Austin-based start-up formed in 2014. Spark Cognition develops AI-Powered cyber-physical software for the safety, security, and reliability of IT, OT. The technology is more inclined towards manufacturing. It is capable of harnessing real-time sensor data and learning from it continuously, allowing for more accurate risk mitigation and prevention policies to intervene and avert disasters.

Cognitive Computing Use Cases

According to tech pundits, cognitive computing is the future. Many successful and established businesses have already integrated the technology into their business affairs. There are a number of successful use case scenarios and cognitive computing examples that show the world how to implement cognitive computing, efficiently. Let us look at some successful use cases of the technology.

Cora- Intelligent Agent by Royal Bank of Scotland

With the help of IBM Watson, Royal Bank of Scotland developed an intelligent assistant that is capable of handling 5000 queries in a single day. Using cognitive learning capabilities, the assistant gave RBS the ability to analyze customer grievance data and create a repository of commonly asked questions. Not only did the assistant analyze queries, but it was also capable of providing 1000 different responses and understand 200 customer intents. The digital assistant learned how customers ask general questions, how to handle the query, and transfer to a human agent if it is too complicated.

Healthcare Concierge by Welltok

Welltok developed an efficient healthcare concierge – CafeWell. It is a holistic population health tool that is being used by health insurance providers to help their customers with relevant information that improves their health. By collecting data from various sources and instant processing of questions by end-users, CafeWell offers smart and custom health recommendations that enhance the health quotient.

Personal Travel Planner by WayBlazer

Powered with cognitive technology, WayBlazer’s travel planner makes it easier for travelers to plan for trips by asking questions in natural language. The concierge asks basic questions and provides customized results by collecting and processing travel data as well as insights about traveler preferences.

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Such type of cognitive-powered tool helps travelers save time while searching for flights, booking hotels, and planning other activities. Travel agents have been successfully using such tools which have helped increase their revenues and customer delight at the same time.

Edge up’s Smart Tool to Manage Fantasy Football Teams via Mobile App

Fantasy Football is a very popular entertainment for more than 33 million people around the globe. With the help of cognitive learning and computing, Edge Up Sports developed a tool and integrated with their mobile app that helped users to draft their fantasy teams by asking simple questions.

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The questions, drafted in natural language, making it easier for users to take a decision which is then analyzed by the system by browsing through data about a player across social media, news reports, and gauging user sentiment that help team managers make better decisions.

Conclusion

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 like act, think, and behave like a human in order to achieve maximum synergy from human-machine interaction. It is believed that soon every digital system will be measured based on its cognitive abilities.

Cognitive computing will be a significant step towards digital humanism!

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About the Author

Kalpana is a database developer. She strongly believes that “It’s not that we use technology, we live technology.” Outside of her professional role, Kalpana is passionate about travelling and watching movies.