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Then, while still at i2, she became involved with an engineer at the company who was born halfway across the world. "If I had laid out a criteria for what I was looking for, it would not have been a guy from south India," she told me. You're constantly making trade-offs about who's too tall, too short, too smart and too dumb.People come in and tell us a bit about what they're looking for.Indeed, says Thombre, "the politics one is quite interesting.

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"I brought over a bunch of people who I thought could help solve one of the most difficult problems out there, which is how to model human attraction," she says.

A key recruit was Amarnath Thombre, a soft-spoken engineer from Pune, India.

On a hazy Monday in June, I came to meet Mandy Ginsberg, the president of US, the world's largest online dating site.

Petite, preppy and freckled, with long brown hair, Ginsberg was wearing sandals, tight black jeans and a loose blouse.

"We don't know ourselves very well on a descriptive level."The same is true for the millions of Match users, says Ginsberg, and she tried to incorporate dissonance into the algorithm.

"I might come in and say I'm looking for a nice Catholic guy between 30 and 40 who is non-married," she says."When you give it stimuli, it forms neural pathways," he says. It's learning as you go." The same principles are powering the recommendation engines at popular sites around the web.Amazon uses similar ­technology to recommend new products for people to buy, Pandora learns from likes and dislikes to customise its internet radio stations, and Netflix famously offered

"I might come in and say I'm looking for a nice Catholic guy between 30 and 40 who is non-married," she says."When you give it stimuli, it forms neural pathways," he says. It's learning as you go." The same principles are powering the recommendation engines at popular sites around the web.Amazon uses similar ­technology to recommend new products for people to buy, Pandora learns from likes and dislikes to customise its internet radio stations, and Netflix famously offered $1m to anyone who could improve the effectiveness of its algorithm by 10 per cent.His wife is also Indian, and they were introduced through family.Yet Thombre says his experience at i2, where he spent years finding ways to move products around the country more efficiently, was perfect preparation for the online dating industry."But after weeks of looking at people, I might get an e-mail from a guy who has kids, and I might accept that. All that data goes into algorithms and affects who we put in front of you."To sort expressed ideals from actual desires, Ginsberg realised she would need some technical help.

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"I might come in and say I'm looking for a nice Catholic guy between 30 and 40 who is non-married," she says.

"When you give it stimuli, it forms neural pathways," he says. It's learning as you go." The same principles are powering the recommendation engines at popular sites around the web.

Amazon uses similar ­technology to recommend new products for people to buy, Pandora learns from likes and dislikes to customise its internet radio stations, and Netflix famously offered $1m to anyone who could improve the effectiveness of its algorithm by 10 per cent.

His wife is also Indian, and they were introduced through family.

Yet Thombre says his experience at i2, where he spent years finding ways to move products around the country more efficiently, was perfect preparation for the online dating industry.

"But after weeks of looking at people, I might get an e-mail from a guy who has kids, and I might accept that. All that data goes into algorithms and affects who we put in front of you."To sort expressed ideals from actual desires, Ginsberg realised she would need some technical help.

||

"I might come in and say I'm looking for a nice Catholic guy between 30 and 40 who is non-married," she says.

"When you give it stimuli, it forms neural pathways," he says. It's learning as you go." The same principles are powering the recommendation engines at popular sites around the web.

Amazon uses similar ­technology to recommend new products for people to buy, Pandora learns from likes and dislikes to customise its internet radio stations, and Netflix famously offered $1m to anyone who could improve the effectiveness of its algorithm by 10 per cent.

His wife is also Indian, and they were introduced through family.

m to anyone who could improve the effectiveness of its algorithm by 10 per cent.His wife is also Indian, and they were introduced through family.Yet Thombre says his experience at i2, where he spent years finding ways to move products around the country more efficiently, was perfect preparation for the online dating industry."But after weeks of looking at people, I might get an e-mail from a guy who has kids, and I might accept that. All that data goes into algorithms and affects who we put in front of you."To sort expressed ideals from actual desires, Ginsberg realised she would need some technical help.

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