Over the last century, technology has touched and transformed our lives. The impact of technology was significant in industries such as finance, medicine, retail, hospitality, entertainment among others. When computers were initially introduced, they were little more than machines which could do simple arithmetic operations.
This was the first era of computing — the tabulating era. With the advent of the PC, computers proliferated and we entered the second era of computing — the programmable era. During this time, computers became smaller, miniaturized and more powerful, but they were still bound by rigid rules and decision-tree logic.
Enter the third era of computing – the Cognitive era
We are now entering the third era of computing beyond the Social, Mobile, Analytics, Cloud (SMAC) and IoT— the Cognitive era — and it is again fundamentally changing the way humans work with machines. In the past, users needed to code or format text in a way that the system would understand. This new type of technology allows people to interact with computers using Natural language.
What Is Cognitive Computing
In the simplest sense possible, Cognitive computing is the creation of self-learning systems that use data mining, pattern recognition and Natural Language Processing (NLP) to mirror the way the human brain works. The purpose of Cognitive computing is to create computing systems that can solve complicated problems without constant human oversight. Cognitive computing offers the opportunity to solve some of the biggest challenges humanity faces today.
It is enabling businesses in nearly every industry to better serve their customers. Cognitive computing is built on self-learning computer systems that use data mining and machine learning to simulate human thought processes. Cognitive computing applies sophisticated algorithms to Structured and Unstructured content to provide personalized, customized, and intuitive responses to a human users query.
Cognitive computing techniques are allowing humans and computers to collaborate in order to gain insights and knowledge from data by uncovering patterns and anomalies. Today, the technology of machine learning and Cognitive computing is approaching the level of simple Artificial Intelligence (AI) with the ability to understand the user’s intent and role. Tasks previously performed by people, such as interpreting doctor’s notes, and extracting important data, can now be performed by NLP engines and Machine learning algorithms, to deliver accurate and quick classifications and interpretations.
The Problem: Information Overload
Globally, data is growing at an astounding rate. With so much information readily available and the data pool growing exponentially, the challenge is to extract, analyze, and connect the dots between all of the available data. No individual could possibly process all this information, and as a result, business decisions are often made without taking into account all of the available information. Within organizations, workers too require tools that can help them generate insights, make better decisions, and develop expertise faster. Cognitive computing meets this need by sorting through vast quantities of Structured and Unstructured data and providing specific, personalized recommendations that are backed by solid evidence. And the Cognitive system continues to learn and get better over time with more data and feedback.
The Solution: Businesses Built on Cognitive Computing
To make sense of ever-growing data stores and make informed decisions, individuals and organizations need new solutions that are built on Cognitive Computing. New businesses are emerging today to fill that need. Using machine-learning technology, incumbent tech companies and tech start-ups are creating next-generation applications that enable individuals to make better decisions in all aspects of their personal and professional lives, from health to finance to fantasy football. Cognitive technology, tools from companies such as IBM Watson and others are available today in the market and they can be used to build state-of-the-art solutions for critical problems or help companies make better decisions, find hidden insights, and get answers to questions faster than ever before.
Cognitive computing, along with its engines: machine learning and predictive analytics, is radically transforming the way we interact with content and each other in our digital lives. Cognitive computing tools—adaptive and interactive systems enable computers to handle more complex, context-driven problems usually reserved for human intelligence. Further, they have the potential to profoundly change how subject matter experts function and make decisions across industries. Cognitive computing machine learning is already starting to play a significant role in industries such as financial services, healthcare, veterinary care, sports and others.
Specific uses cases for Cognitive Computing
- Industry: Financial services
- Investment managers have a difficult job. They need to absorb and understand huge volumes of information and use that information to make split-second, reliable decisions about where and when to invest client funds in a highly volatile market. Cognitive computing can provide accurate, fact-based investment recommendations to financial managers by examining tens of millions of pages of documents, explore available market intelligence, risk profiles, and financial profile data to provide better information in real time.
- Industry: healthcare industry
- Cognitive computing is finding a foothold in the healthcare industry, where scientists, doctors, payers, and patients are finding places to use this disruptive technology to optimize care, improve research discovery, and find waste and fraud. Cognitive computing can process vast volumes of data instantly to answer individuals’ questions and make intelligent, personalized recommendations.
- Industry: Veterinary Care
- Cognitive computing isn’t helping only humans; it’s also helping veterinarians take better care of the animals that come into their practices.
- Industry: Sports & Entertainment
- Some fantasy team managers are gaining an advantage on the competition by leveraging the Cognitive computing technologies to help them draft their teams. Cognitive computing can help sort through a wealth of data, news reports, social media comments, weather reports, and more to provide insightful answers that can help fantasy football team managers make better decisions.
Key Players Globally
Of late, the future of Artificial Intelligence (AI) has been a major topic of discussion in most recent technology debates. In general terms, AI refers to machines doing intellectual tasks at a level comparable to humans. That means reasoning, planning, learning, and using language to communicate at a high level. It also probably includes sensing and interacting with the physical world.
There’s an arms race going on in artificial intelligence, or Cognitive computing, the goal of which is to enable computers to learn from their experiences in order to deliver better results. Microsoft, Google, Apple, IBM and Amazon Web Services, and other tech majors are in the process of establishing their Cognitive computing practices for developing next generation products and services. Further, they are also gearing to buy innovative startups and grow their technological footprint in this space.
Market in India
- IBM has opened up its Watson ecosystem for business in India, by announcing partnership with companies that will use Cognitive technologies. In Manipal Hospital’s Oncology department, IBM’s Watson is helping make decisions about cancer care and treatment and it is drawing on its previous ‘knowledge’ of cancer cases globally trawling through vast amounts of medical data to arrive at diagnosis and advise treatment.
- Automation, Artifical Intelligence and Machine learning capabilites are becoming key to generate more revenues with less employees for the Indian IT service companies. Automation – using robots and machine learning to do tasks other wise doney by humans faster and cheaper – is shaping the future of US$ 150 billion IT industry in India, which employs 4 million people. The Big Five software exporters in India – TCS, Infosys, Wipro, HCL and Cognizant – together added net 24 per cent fewer employees in 2015 at 77,265, thanks to their automation drive. Even though each of these companies have their own automation platforms — Infosys has Infosys Automation Platform, Wipro has Holmes, HCL Tech operates Dry Ice, TCS has Ignio and Cognizant has its Trizetto platform — their focus on this line of business has seen emergence of many independent players offering automation services or virtual engineers.
- Wipro Holmes, the Artificial Intelligence (AI) platform developed by the Indian IT major, can mimic human actions and is being used by financial institutions to automate tasks like KYC and credit-risk appraisal. It can read and analyze multiple sources of information (Structured and Unstructured) documents, ingest data and assist the analyst in decision making.
- Not surprisingly, machine learning is catching the eye of the Governments in India too. The government of Andhra Pradesh uses Microsoft’s cloud-based predictive analytics service, Azure Machine Learning, to find out the students who are at a high risk of dropping out. The project with Andhra Pradesh Government involves collecting and analyzing data on particulars like teachers, school infrastructure, students’ socioeconomic background etc and training a model based on the data. The insights are helping the State Government allocate resources judiciously.
Global Market sizing
Experts believe the rise of the truly intelligent machines may be some way off, but there’s no doubt smart machines and systems are going to play an ever-increasing role in the way enterprises function. Research from IDC found that the current US$4.5 billion value of the AI industry will more than double by 2019, and that’s inspiring technology majors to aggressively pursue their interest in this area to grab a greater share of the market pie.
To sum up, Cognitive computing is a logical extension to the analytical suite of services being offered by the IT services industry. It’s the next step for any organization that has been pursuing traditional analytics, i.e., analytical models driven by human hypotheses. Any organization that wishes to improve the speed and scale of its analytical activities should be exploring at least some Cognitive capabilities now.
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