"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.
Her jewellery was limited to a diamond bracelet and a wedding band.
Confident and casual, she seemed as good a person as any to be the face of online dating.
"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.
You meet her criteria, and she meets yours, so you're a good match," Thombre explained.
"But when we researched the data the whole idea of dissonance came into focus.
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.
"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.