Scott: Michael, for someone surrounded by technology 24/7, I’d wager you see a lot of proclamations about the next big thing. Help us cut through the hype. As a technology CEO, what do you think is the most exciting innovation in the field of content?
Michael: Great question. I believe the most exciting innovation in the content world is cognitive computing. Why? Because traditional computing technology, while impressive, is also somewhat idiotic. Today’s computer software can tabulate and calculate, store, manage, and deliver files faster than human beings. And, while computers are much better at remembering details, they can’t provide many of the content capabilities needed by today’s businesses. However, that is about to change.
Cognitive computing, according to the folks at TechTarget, is “the simulation of human thought processes in a computerized model. Cognitive computing involves self-learning systems that use data mining, pattern recognition and natural language processing (NLP) to mimic the way the human brain works. The goal of cognitive computing is to create automated IT systems that are capable of solving problems without requiring human assistance.”
Cognitive computing will empower computers to learn, comprehend, adapt, and interact with content in ways we could only imagine until recently. Cognitive content solutions will provide business with amazing differentiating capabilities—digital differentiators that will allow businesses to gain insights and intelligence that are currently hidden in our content. That’s why I believe cognitive computing will play a starring role in the future of content.
Scott: That is exciting. And, you’re right, cognitive computing presents new opportunities for cities and governments, medicine and healthcare. And, it opens the door to innovation in energy production, insurance, banking and finance, business intelligence and analytics, and marketing. And it will create new jobs in every single business sector. Companies will begin expanding their research and development efforts to include cognitive computing in hopes of identifying potential competitive differentiators. The opportunities are almost endless. Why do you think a new approach to solving problems with content and computers is needed?
Michael: Traditional computing systems like the ones we use today rely on us to know what we want them to do ahead of time. We must program them in advance to do the work we require of them. Traditional computing architectures designed in this way are troublesome. They can lead to what’s known as the von Neumann bottleneck (a processing-heavy approach in which discrete processing tasks are completed linearly, one at a time). This situation makes it difficult for us to create scalable solutions to big data—and big content—problems. And, it prevents us from uncovering hidden value in our content assets.
Cognitive computing and machine learning technologies are designed to help us overcome issues of scale. And, they can help us discover solutions to problems. By adding semantic context to the content—making content intelligent—machines can learn and process content on our behalf. They’ll even be able to help us determine risk, spot hidden potential, and make better choices. And they’ll be able to automatically assess probability, recommend courses of action, and guide us toward business decisions. Just imagine what that will mean for customer support solutions, cancer research, and education.
Scott: Thomas Malone, director of the MIT Center for Collective Intelligence, has said that one of the biggest questions associated with cognitive computing is: “How can people and computers be connected so that collectively they act more intelligently than any person, group, or computer has ever done before?” In your view, why would intelligent content (modular, structured, semantically rich, reusable, format-free content) be of value to help cognitive computing technologies make sense of the exploding availability of content coming at us from an increasing number of sources?
Michael: The need for intelligent content is paramount when thinking in terms of advanced solutions like cognitive computing. We can teach systems what they need to know about unstructured content. That’s one option. Or, we can provide systems with intelligent content equipped with semantic metadata. Metadata helps cognitive computing systems understand the content without our needing to intervene as trainers. Companies that have invested in intelligent content solutions are ahead of the curve in this area. Intelligent content and artificial intelligence systems go hand-in-hand.
Scott: I know that many people hear words like cognitive computing and jump to the conclusion that it’s all about artificial intelligence and replacing humans with robots. I realize you’re not talking about that, although there is a grain of truth in those fears. Artificial intelligence will allow us to innovate and to create better solutions. Those innovations may indeed lead to job losses. But, there’s an entire world of new jobs that are being created at the same time. Do you see this transformation the same way as I do?
Michael: Yes, Scott. I do. First, it’s important to note that the cognitive computing revolution is not about replacing humans with machines. It’s about shifting gears and providing humans with the better results by leveraging computers to do what they do best. The volume and velocity of content being produced by organizations, shared and curated by people via social media, and collected by sensors connected to the Internet of Things, is huge. Thus cognitive computing power is required to help us make sense of the volumes of content around us. Combined with intelligent content, cognitive computing can help us solve many of the global challenges we face today.
Even with all the advancements made in cognitive computing, there will always be debate on how far technology can take us. During the 2016 Wimbledon tennis tournament, IBM Watson predicted the number of first service points and aces that would be needed in order for one player to win against his opponent. Unfortunately, Watson’s predictions weren’t always spot on. I guess Watson will have to go back to the drawing board to figure out how athletic ability, speed, and endurance relate to scoreboard pressure, nerves, and emotion. There’s still plenty of room for improvement.
Scott: Good point. Although, IBM used Watson at Wimbledon to cull through all sorts of other data that did provide some useful data points. For example, Watson used facial recognition to attempt to understand what people were cheering about (or not) during the matches. And, Watson was pointed at social media channels to decipher what Wimbledon fans were sharing and chatting about on the web.
That said, I think you’re spot on with your prediction about cognitive computing and the future of content. It will be interesting to see where these new capabilities lead us. There will be a few stumbles along the way.
Thanks for sharing your views with our audience.
Michael: I’ll leave you with this quote from IBM CEO Ginni Rometty. “This era will redefine the relationship between man and machine.” Cognitive computing, while still relatively new, holds many possibilities. I’m excited to see what we can make happen.
Thanks for the opportunity to share my thoughts with your audience, Scott. I appreciate it.