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This is Scientific American's 60-second science. I'm Christopher in Taliatta.

The goal for a lot of tech companies today, figure out what you, their customer, want next, before you even ask.

It's driven by something called similarity search.

If you go to YouTube and you watch a video, they're going to suggest similar videos to that one that you're watching, right?

That's similarity search. If you go to Amazon and look for similar products to the one that you're going to suggest similar videos to that one that you're watching, right? That's similarity search. If you go to Amazon and look for similar products to the one that you're going to buy,

that's similarity search. Socket Novlika, a computer scientist at the Salk Institute. He says

we do similarity searches too, for example, when we scan faces in a crowd for the one we know.

And even fruit flies do a version related to smell.

So the fly is having to solve a similar problem of kind of searching through its database of

previous experiences and previous odors that it has smelled to determine what should be the most

appropriate behavioral response to that odor.

But flies tag incoming odors differently from the way modern search algorithms parse similarity.

A small group of neurons makes an initial evaluation of the smell,

then a much larger set of neurons is activated to make a final decision about the smell.

Rather than the way a computer similarity search does it,

which is taking something with many dimensions and simplifying it down to a few. So Novlika and his colleagues

tweaked computer similarity search functions to do it fly style, and then pitted the fly-inspired

...