Human beings are the only ones in this planet with the ability of advanced problem solving and creative thinking. However, with the use of technology, we have also been able to pass on this ability to algorithms. The goal of the modern human race is to develop a system that can simulate the human thought process and come up with the same kind of solutions that we would have. This is the world of cognitive computing – a realistic means to develop artificial intelligence.

The investments and expectations have been so huge that the global cognitive computing market is estimated to earn revenue beyond $13.8 billion by the year 2020. Cognitive computing basically refers to new age systems that are capable of conversing in human language and simultaneously help business and organizations make better decisions. The one thing that makes cognitive computing or for that matter, artificial intelligence, better than us, is the amount of data they can process and the time they take for it. We are currently living in a world of connected devices and these systems have been designed to process even unstructured information like images, symbols and natural language to translate into feasible solutions. Google self driving cars for example process real time images and using GPS and satellite data, navigate through our roads without the need of a human driver. Sophia, the first robot citizen of Earth is constantly learning and growing using information that comes in the form of structured data and conversations she makes with real human individuals.

Cognitive Computing – In a Glimpse

Cognitive computing refers to self learning algorithms that use machine language to mimic the way the human brain works. It’s an adaptive solution that takes over basic human problem solving and makes our businesses more efficient. We gain by saving time and putting our creative resources in processes that need more than information.

Features

The core idea of cognitive computing is to minimize the necessity of human intervention in a wide variety of applications. It is:
Features
The core idea of cognitive computing is to minimize the necessity of human intervention in a wide variety of applications. It is:

Adaptive:

The algorithms constantly evolve using machine learning and data that that is being constantly added to the connected networks, including human preferences, behavior and needs.

Interactive:

The learning necessarily depends on human inputs, both natural languages and data that we are constantly uploading into the connected networks.

Iterative:

The algorithms are designed to remember previous interactions, inputs and choices to answer future problem solving. For this, these systems ask questions are find information for the Big Data repository we are constantly adding to.

Contextual:

The systems are also designed to identify, understand, and consequently extract relevant information depending upon the goal. The sources of information are multiple and come as both structured and unstructured information.

Where does it come from?

The sources, as we already stated are multiple. Every time, you time your air conditioner to power on before you come home, it’s a data to be remembered. The systems are designed to remember your holidays, analyze weather conditions, and analyze the number of people present in a room and similar information to make your air conditioner completely automatic. Once established, you can forget about picking up the remote ever again. Cognitive computing also draws from the World Wide Web.

What can it do?

Engage:

The systems helps develop contextual relationships and for its own hypothesizes and arguments. These are systems that can engage in a deep dialogue with humans. Retail chatbots for instance show what you prefer depending on your age, past choices, browsing history, social feeds you like and more.

Make Decisions:

Tracking popular decisions and matching it with your behavior and needs allows the systems to make decisions on your behalf.

Discover:

It’s about using the huge repository of information and finding new solutions to everyday problems. Deep learning is helped by the increasing volume of data everyday and thus addresses critical events.

Is the Cognitive Computing Landscape dominated by Larger Players?

Yes and the most important reason is their ability to set up and infrastructure (including a complicated hardware and software interface) that can handle constantly growing algorithm. Among the pioneer is IBM with $26 billion investment in analytics and big data. One third of IBMs budget is about R&D of cognitive computing.

Cognitive Computing – the Big Time Players

SparkCognition – inclined towards manufacturing, SparkCognition is AI for safe and secure OT, IT and IIoT.

Microsoft Cognitive Science – Also called the Project Oxford, developers here add emotion, speech recognition, vision, knowledge, language understanding and sentiment detection to make smarter applications.

IBM Watson – Uses transformation technologies like image recognition, virtual agents, text analysis and language processing to offer evidence based reasoning.

Numenta – Helps detect anomaly in applications and servers, geo-spatial data, human behavior and even classification of the natural language. The solutions extend to analyzing stock markets and prices.

Expert System – Learns unstructured content like images, videos, texts and symbols to help make businesses make better decisions.

CognitiveScale – Big Data interpretation to enhance customer engagement and machine augmented intelligence for predictions and actionable insights.

Google DeepMind – Concentrating on the health sector, Google’s DeepMind helps practitioners instantaneously diagnose and offer the right treatment plans.

Cisco Cognitive Threat Analysis – Filters out anomalous web traffic and pinpointing cyber attacks before sensitive data is exploited.

At the end of the tunnel, we expect cognitive computing to change the way we work, including industries like healthcare, retail, security, defense, BFSI, ecommerce and more. With the continuous growth of cloud based solutions, companies are coming up with high end hardware and software systems that foster the cognitive computing learning.