Fundamentals in Cognitive Computing: What Everyone Should Know

Michael Koch originally published this blog on his professional overview website. Check Michael’s website for weekly updates on AI, SaaS, PaaS, and overall leadership.


We live in a data-driven world, where the products we use, entertainment we consume, the business we run, even the traffic patterns on the way to work: all of it is logged and stored in digital form. Piles and piles of Data compile, so much data, that it is becoming increasingly difficult for manually programmed computer systems, with their preset functions and automated processes, to thrive and evolve to get the info needed….fast.

This is where Artificial Intelligence (or AI) will lead the way. To sort a cyberspace flooded with information, we must call upon cognitive computing to bridge the gap between our increasingly data-reliant demands, and what computer programming is actually equipped to complete. The result is a digital system possessing a level of artificial intelligence, able to analyze data and use logical assertions to alter performance accordingly. The future is now.

What is AI?

A form of cognitive computing, AI uses advanced statistical models to identify data patterns, and draw predictive inferences from those similarities, effectively “learning”. Born over sixty years ago, when scientists first taught a computer how to play checkers, AI has grown in complexity and power ever since and is a driver in today’s business world.

AI learning occurs when computers are provided a data set that categorizes certain types of qualitative information. For example, a computer might be given a group of pictures, each one marked as being “a zebra” or “not a zebra.” The computer would then use the similarities that define both categories to analyze and sort a new group of pictures, according to whether or not they showed a zebra. Each identified photo is then added to the computer’s learning set, rendering the computer “smarter,” or able to draw from more knowledge for better accuracy, with each completed task.

How is AI used today?

Beyond analyzing textual information in a variety of applications, computers can now comprehend and respond to human speech. Siri, Cortana, Google Now–all of these technologies are the flagships of an AI capable of actual, human-style communication. Computers can also communicate through written words, performing simple writing functions that require analysis and accurate description, such as financial news summaries, and data entry.

AI has medical applications as well. Computer-assisted diagnosis (CAD) is employed to review medical data for quick and accurate readings. One AI study analyzed mammogram results to find patients’ cancers, as much as a year before an official diagnosis could be made.

In recent years, AI has also made a striking debut in online marketing practices; besides enabling targeted online advertising, AI also provides customers personalized perks such as coupons and discounts and uses past shopping habits to recommends new products.

Other common AI applications include natural language processing (NLP) for more accurate language translation, as well as customer service in legal and financial fields, and smart cars that, while yet to master self-driving, are able to tailor to preference an automobile’s internal settings, such as temperature, music, seat adjustments, etc.

Conclusion

From our job description, to medical treatment, to the way we choose products and even drive, the widespread changes that AI promises will alter nearly every facet of daily life. It’s important to grow a healthy understanding of the realistic qualities and expectations of AI so that we can prepare ourselves for future advancements, and so we can benefit from AI in years to come.