When we as humans seek to understand something and make a decision we go through four key steps. First, we observe visible phenomena and bodies of evidence. Second, we draw on what we know to interpret what we’re seeing to generate hypothesis about what it means.

Third, we evaluate which hypothesis are right or wrong. Finally, we decide, choosing the option which seems best and acting accordingly.

Just as humans become experts by going through the process of observation, evaluation and decision making, cognitive systems use similar processes to reason about the information they read. Unlike humans, cognitive computing can do all of this at massive speed and scale. With today’s wealth of big data and the need for more complex, evidence based decisions, cognitive computing enables people to create a profoundly new model, finding answers locked away in volumes of data and deriving value from it to enhance human expertise.

Search engines are great for helping us find what’s out there, but what about things that haven’t been invented yet?

So what about search engines? Search engines are great for helping us find what’s out there, but what about things that haven’t been invented yet? That’s what cognitive computing is all about. Unlike a search engine, a cognitive system doesn’t just find old ideas, it thinks up new ones. For example, a cognitive system could help a chef combine existing ingredients to create brand new recipes. Or, it could help a researcher develop safer drugs for the life sciences industry.

The problems that we are facing today, are often too complex for a single human to figure out on their own. Cognitive computing systems by their very nature, expand human cognition, learn with use, and interact naturally with humans.