IBM, Microsoft and Apple are among the companies large and small that are working to build cognitive computing capabilities into the latest applications.
When IBM launched its Watson cognitive computing project over a decade ago, it started as an effort deep in IBM's research labs to produce a system that could learn and think like humans.
Since then, Watson proved its mettle by winning the TV game show Jeopardy
in 2011 and spurring interest in cognitive technology across the industry.
IBM is not alone ushering in what Big Blue's CEO Ginni Rometty
has dubbed the "cognitive era." Several other companies have prominent cognitive technology offerings or projects in the works, including Amazon, Apple, Facebook, Google, HPE, Microsoft and SAS
, among others.
Driving this new era are data—particularly unstructured data—and cognitive systems that can ingest all types of data and work in natural language.
Cognitive systems can understand, reason and learn, Rometty said. In short, cognitive computing is the use of systems that can think and learn.
Indeed, cognitive computing encompasses various forms of artificial intelligence (AI), including machine learning, reasoning, natural language processing, speech and vision, human-computer interaction, dialog and narrative generation and more. However, cognitive computing is but a subset of AI.
Many attempts have been made over the years to deliver cognitive systems, but until recently these systems haven't been very prevalent or cost-effective. They are more cost effective now with the advent of low-cost, high-performance computing power and data storage.
Now businesses are increasingly looking to cognitive technology to help cull through reams of data to glean insights on everything from customer buying patterns, to medical diagnoses and treatment options, to financial advice. As demand for cognitive assistance grows, so has developer interest in building cognitive applications.
Cognitive Banking and Machine Learning
Capital One, which has emerged as a forward-looking, developer-centric financial services institution, is working on delivering cognitive applications to help its customers.
"Being a leader in this new world of banking is going to require competencies around the ability to innovate quickly, the ability to build software that is really compelling and well-designed and [has] the ability to understand data and analytics," said Robert Alexander, CIO of Capital One.
The financial industry will "apply modern methods of machine learning and analytics operating in real-time in a way that banking just doesn't know how to do," Alexander said.
Capital One is applying cognitive computing in a number of different areas, Alexander said, particularly in cyber-security. Capital One is using machine learning to help secure systems, starting with building a comprehensive data infrastructure of what's going on in their computing environment and building tools that offer insights into things that might be anomalies, he said.
"You can use machine learning and AI to discriminate normal behavior from abnormal behavior," Alexander said. "So we've applied machine learning in that context to help us identify malware or anomalous log-in behavior or other kinds of things that are indicators of threats in our environment. Other places are around fraud and risk decisions."
More and more, algorithms are taking over things that humans used to do, said Alex Backer, CEO of QLess
, a startup that produces an app that uses AI and machine learning that aims to eliminate the need for people to wait in line at stores, restaurants, government offices and more.
"The idea for QLess came from me standing in line and thinking that there ought to be a better way to get service than standing behind other people's butts," Backer said.