Since the dawn of computing, the goal of engineers, designers and developers has been to imbue machines with greater intelligence so they can think more like humans. Today, marked leaps in processing power and incredible advances in artificial intelligence (AI) are pushing the concept from the pages of science fiction novels to our homes and workplaces.
“The growing complexity of computing and information—and the need for more intelligent automation—is leading to the next wave of transformation, including cognitive systems,” says Paul Brody, technology sector strategy leader for the Americas at consulting firm EY.
Systems such as IBM’s Watson, as well as interfaces such as Apple’s Siri, Microsoft’s Cortana and Google Voice, are transforming the way data and information are routed to people. At the same time, advanced cognitive and deep learning systems—which aim to think and act in human-like ways and, in some cases, mimic neural brain networks—are able to collect and digest massive amounts of data. This leads to new insights and the ability for these systems to learn and evolve on their own.
The value is enormous, says Lanny Cohen, chief technology officer for consulting firm Capgemini. Cognitive tools “essentially put a human ‘face’ on systems and analytics, so [organizations] can better understand the needs of the end customer, regardless of the business or industry.”
How is cognitive computing unfolding and what is now possible? How does machine learning change the stakes? And what industries or sectors benefit the most? Cohen believes the field is advancing rapidly and executives must tune in to these cognitive computing trends or risk digital disruption.
“Machine intelligence and AI need to be evaluated on an opportunistic, strategic and operational level,” he explains. “They should be viewed as something to implement within systems, business intelligence and processes, rather than something that is separate or siloed from the business.”
The Start of the Journey Into AI
Cognitive computing burst onto the scene after IBM showcased Watson at the television game show Jeopardy! in 2011. The AI system sorted through mountains of data and navigated steep linguistics challenges on the way to generating responses that beat human contestants.
Since then, the technology has advanced, and adoption is accelerating. Allied Market Research predicts that the market will grow by an annual rate of about 33 percent, reaching $13.7 billion by 2020. The appeal is clear.
“Banks are able to guide their customers to better financial health based on behavioral patterns; health care companies can improve outcomes by detecting patterns in treatment; and many supply-demand or logistical challenges can be addressed by finding relevant data and recommending next best actions,” Cohen says.
Fueling the growth of cognitive computing and deep learning systems is the enormous growth of both structured and unstructured data. According to Gartner, the overall volume of global information will swell by 800 percent from 2014 through 2019. What’s more, 80 percent of this data now arrives from social streams, email, text files and other unstructured sources.
Sifting through all this data is difficult enough, but applying it in contextual and relevant ways is becoming next to impossible with conventional methods and tools. As a result, many organizations are now searching for better systems and interfaces, ranging from smart agents to security software that adapts to threats dynamically.
Integrating Cognitive Computing Features
The Leading Hotels of the World (LHW), a hospitality firm that operates more than 375 luxury hotels and resorts in 75 countries, is among the businesses traveling into new territory with cognitive computing. It has turned to Watson and partnered with travel platform Wayblazer to integrate cognitive computing features into its LHW.com Website, where customers explore travel possibilities and book rooms.
The recently introduced Trip Discover Experience allows a visitor to use natural-language processing to find desirable properties. For example, a person might enter: “Display hotels with golf, a spa and nearby wine tasting or show me hotels near a beach that are pet-friendly and family-friendly with good weather in December.” The system then displays relevant information, photos, maps and more information that can help the traveler make a decision.
