When IBM’s advanced artificial intelligence program Watson beat Jeopardy champion Ken Jennings in 2011, it was an impressive feat for a computer–but still, it was only processing information that humans already knew in order to answer trivia questions.

As IBM attempts to turn Watson into a new line of business and make it useful in a wide range of industries that are dealing lately with an overwhelming amount of data, it’s now working to push the software, which excels at learning and interpreting human language, forward into the realm of the unknown.

We’re talking about a computing system that inspires people.

“It’s not giving answers that people know anymore, it’s pointing people in directions that they should investigate,” says IBM Watson group vice president John Gordon. “We’re talking about a computing system that inspires people.”

At an event in New York today, IBM showed off the ways some of its early customers are using the Watson “Discovery Advisor” in research, development, and innovation, especially in the realm of biotech and life sciences. Watson’s aim is to speed up discoveries by teams of researchers by, for example, scanning and interpreting millions of scientific books, articles, and data points–far more than any person’s brain could analyze–and generating new hypothesis or leads that might be fruitful to investigate. Or, as Gordon puts it, Watson gives researchers “smarter hunches.”

Scientists at the Baylor College of Medicine and IBM Research have already used Watson to discover new pathways to cancer therapies, which they reported in a study presented at an academic conference this week. Watson looked closely at 70,000 scientific articles on a protein, called p53, that’s involved in more than half of all cancers. From its analysis, it picked out 6 different proteins that might function as a switch to turn on and off the p53 function–and therefore might be possible good targets for new drugs and cancer therapies. For comparison, says IBM research scientist Scott Spangler, human beings have only discovered about 1 new p53 target a year over the course of a decade.

Drug companies, too, which are struggling today to develop new commercial drugs, are some of the earliest users of Watsons predictive capabilities. Sanofi is using Watson to look through the research literature and its own data to find new uses for its existing drugs on the market. And Johnson & Johnson has developed a system that analyzes clinical studies to compare the efficacy and safety of different treatments.

Imagine we can teach Watson to do that for us. So instead of six months, Watson can do it in minutes.

Soledad Cepeda, Johnson & Johnson’s director of epidemiology, used the example of back pain, for which there are 27 treatments studied in more than 3,000 clinical trials. “[Analyzing this] is slow, it’s tedious, it’s expensive, and it’s prone to errors,” she says. “Now imagine we can teach Watson to do that for us. So instead of six months, Watson can do it in minutes.”