Is the fragrance industry ready for artificial intelligence? Are you?
Once Philyra was up and running, the team refined the algorithm by layering in “success criteria,” such as what’s popular in the market. But the additional intel didn’t simplify matters: Philyra was still spitting out thousands of potential formulas. “We had to feed her some seeds,” says Apel, as if talking about a beloved pet. The “seeds” included types of perfumes that were popular with younger customers in Brazil. That reduced the output to a thousand options, including 12 top choices.
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