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15-Mar-2018 06:21 by 3 Comments

Society relationships dating personals 900 numbers

"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.

"The one thing I knew was numbers and analytics, so we started building a numbers team here," he told me. The same principles work, no matter what kind of numerical problem you're solving."The way the Match algorithm learns, he says, is similar to the way the human brain learns.

We sat in a conference room ­overlooking a floor full of computer engineers gazing at their monitors, and with a Power Point presentation, she endeavoured to show me how Match uses cutting-edge ­technology to cultivate age-old emotions.

With the number of paying subscribers using Match approaching 1.8 million, the ­company has had to develop ever more ­sophisticated programs to manage, sort and pair the world's singles.

Coloured lights flash from the ceilings, workers lounge on circular banquettes, dance music plays from hidden speakers.

Despite being in a mid-rise office tower overlooking a turnpike in the dry, landlocked city of Dallas, Texas, the Match offices are evocative of a racier environment, where anything might happen.

It is a subtle shift, but one with profound implications.

"Before, matches were based on the criteria you set.But what you say and what you do can be different."Academics call this "dissonance"."It's a theme that runs through social psychological literature," says Andrew Fiore, a visiting assistant professor at Michigan State University, who works on ­computer-mediated communication.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.People were doing something very different from the things they said they wanted on their profile."As a result, Match began "weighting" variables differently, according to how users behaved.

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