Typically, according to McCormick's Chief Science Officer Hamed Faridi, to create flavorful formulas the process has typically meant adding, subtracting and changing ingredients, with as many as 150 iterations in some cases before a product is deemed commercially ready.
"You learn things about what the people in India do versus the people in North America or Europe," Richard Goodwin of IBM told USA Today. "And then you can try and cross-pollinate good ideas among the different labs whereas typically they wouldn't necessarily talk to each other on a daily basis."
McCormick has 20 food labs in 14 countries, and for more than 40 years, has collected millions of proprietary sensory science data points related to consumer taste preferences and palettes.
Goodwin said machine learning could help developers determine which ingredients complement each other so that people like them, and also under what circumstances functional substitutes may make sense.
USA Today reports that the two companies have teamed up on the project for about four years, and late this spring, consumers will finally get to sample the initial results from the partnership, through a set of One Skillet Recipe Mix flavors that include Tuscan Chicken, Bourbon Pork Tenderloin and New Orleans Sausage.