I.B.M. Exploring New Feats for Watson

I.B.M.’s Watson beat “Jeopardy” champions two years ago. But can it whip up something tasty in the kitchen? That is just one of the questions that I.B.M. is asking as it tries to expand its artificial intelligence technology and turn…

I.B.M.’s Watson beat “Jeopardy” champions two years ago. But can it whip up something tasty in the kitchen?

That is just one of the questions that I.B.M. is asking as it tries to expand its artificial intelligence technology and turn Watson into something that actually makes commercial sense.

The company is betting that it can build a big business by taking the Watson technology into new fields. The uses it will be showing off to Wall Street analysts at a gathering in the company’s Almaden Research Center in San Jose, Calif., on Thursday include helping to develop drugs, predicting when industrial machines need maintenance and even coming up with novel recipes for tasty foods. In health care, Watson is training to become a diagnostic assistant at a few medical centers, including the Cleveland Clinic.

The new Watson projects — some on the cusp of commercialization, others still research initiatives — are at the leading edge of a much larger business for I.B.M. and other technology companies. That market involves helping corporations, government agencies and science laboratories find useful insights in a rising flood of data from many sources — Web pages, social network messages, sensor signals, medical images, patent filings, location data from cellphones and others.

Advances in several computing technologies have opened this opportunity and market, now called Big Data, and a key one is the software techniques of artificial intelligence like machine learning.

I.B.M. has been building this business for years with acquisitions and internal investment. Today, the company says it is doing Big Data and analytics work with more than 10,000 customers worldwide. Its work force includes 9,000 business analytics consultants and 400 mathematicians.

I.B.M. forecasts that its revenue from Big Data work will reach $16 billion by 2015. Company executives compare the meeting in San Jose to one in 2006, when Samuel J. Palmisano, then chief executive, summoned investment analysts to I.B.M.’s offices in India to showcase the surging business in developing markets, which has proved to be an engine of growth for the company.

I.B.M. faces plenty of competitors in the Big Data market, ranging from start-ups to major companies, including Microsoft, Oracle, SAP and the SAS Institute. These companies, like I.B.M., are employing the data-mining technology to trim costs, design new products and find sales opportunities in banking, retailing, manufacturing, health care and other industries.

Yet the Watson initiatives, analysts say, represent pioneering work. With some of those applications, like suggesting innovative recipes, Watson is starting to move beyond producing “Jeopardy” style answers to investigating the edges of human knowledge to guide discovery.

“That’s not something we thought of when we started with Watson,” said John E. Kelly III, I.B.M.’s senior vice president for research.

I.B.M.’s Watson projects are not yet big money makers. But the projects, according to Frank Gens, chief analyst for IDC, make the case that I.B.M. has the advanced technology and deep industry expertise to do things other technology suppliers cannot, which should be a high-margin business and give I.B.M. an edge as a strategic partner with major customers. And the new Watson offerings, he said, are services that future users might be able to tap into through a smartphone or tablet.

That could significantly broaden the market for Watson, Mr. Gens said, as well as ward off potential competition if question-answering technology from consumer offerings, like Apple’s Siri and Google, improve.

“It will take years for these consumerized technologies to compete with Watson, but that day could certainly come,” Mr. Gens said.

John Baldoni, senior vice president for technology and science at GlaxoSmithKline, got in touch with I.B.M. shortly after watching Watson’s “Jeopardy” triumph. He was struck that Watson frequently had the right answer, he said, “but what really impressed me was that it so quickly sifted out so many wrong answers.”

That is a huge challenge in drug discovery, which amounts to making a high-stakes bet, over years of testing, on the success of a chemical compound. The failure rate is high. Improving the odds, Mr. Baldoni said, could have a huge payoff economically and medically.

Glaxo and I.B.M. researchers put Watson through a test run. They fed it all the literature on malaria, known anti-malarial drugs and other chemical compounds. Watson correctly identified known anti-malarial drugs, and suggested 15 other compounds as potential drugs to combat malaria. The two companies are now discussing other projects.

“It doesn’t just answer questions, it encourages you to think more widely,” said Catherine E. Peishoff, vice president for computational and structural chemistry at Glaxo. “It essentially says, ‘Look over here, think about this.’ That’s one of the exciting things about this technology.”

I.B.M. researchers began working with Thiess, a large contract mining company, in Australia last year. Thiess operates an equipment fleet worth $3 billion, mostly very large machines. Its hauling trucks, for example, have 12-foot diameter tires, and carry 250 tons in a single load.

Technology-enhanced predictive maintenance on machinery, like jet engines, has been developing for years. But the Thiess project seems to push things further to cover mine operations as a whole. The data include not only information from the 200 sensors on a truck that monitor trips, load weights, speed and driving styles, but also weather, terrain and economic models of mine operations.

Watson has been able to deliver complex predictive analytics, said Michael Wright, an executive vice president at Thiess. Data-driven changes in operations are being adopted, and savings will be measured over the next six months, he said.

In San Jose, I.B.M. plans to serve the assembled analysts a breakfast pastry devised by Watson, called a “Spanish crescent.” It is a collaboration of Watson’s software and James Briscione, a chef instructor at the Institute of Culinary Education in Manhattan.

I.B.M. researchers have watched and talked to Mr. Briscione as he works, selecting ingredients and building out dishes. Watson has read those notes, 20,000 recipes, data on the chemistry of food ingredients, and measured ratings of flavors people like in categories like “olfactory pleasantness.”

Watson’s assignment has been to come up with recipes that are both novel and taste good. In the case of the breakfast pastry, Watson was told to come up with something inspired by Spanish cuisine, but unusual and healthy. The computer-ordered ingredients include cocoa, saffron, black pepper, almonds and honey — but no butter, Watson’s apparent nod to healthier eating.

Then, Mr. Briscione, working with those ingredients, had to adjust portions and make the pastry.

“If I could have used butter, it would have been a lot easier,” said the chef, who used vegetable oil instead.

Michael Karasick, director of I.B.M.’s Almaden lab, had one of the Spanish crescents for breakfast recently. “Pretty good” was his scientific judgment.