Communications of the ACM
This Startup Is Using AI to Unearth New Smells
Wiltschko's Google team worked to build what they call an "odor map," a way of categorizing scents so molecules that smell alike are clustered together. But instead of relying on human noses to make these distinctions, they used artificial intelligence.
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Alex Wiltschko opens a black plastic suitcase and pulls out about 60 glass vials. Each contains a different scent. One smells starchy with soft floral notes, like jasmine rice cooking. Another brings to mind ocean air and the white rind of a watermelon. One is like saffron with hints of leather and black tea. The next is the pungent aroma of fig leaves, boxwood, and basil. The most surprising one has the tang of a Thai chili pepper without the nostril-burning heat.
The molecules wafting into my nose are nothing like I've ever smelled before. In fact, I'm one of only a handful of people who have ever smelled them. And yet, before any person had sniffed them, a computer model predicted how they'd smell to us.
Wiltschko has been obsessed with scents since he was a teenager, and for the past several years he has been developing software at Google Research to predict the scent of molecules based on their structure alone. The vials he's invited me to smell are the basis of his new startup, Osmo, a spinout of Google Research based in Cambridge, Massachusetts. With $60 million in an initial funding round led by New York-based Lux Capital and GV (Google Ventures), Osmo aims to create the next generation of aroma molecules for perfumes, shampoos, lotions, candles, and other everyday products.
From Wired
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