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We both thoroughly enjoyed ourselves after the whirlwind of meeting so many clients and we left feeling exhilarated.
With seven ‘second dates’ lined up for the next few weeks, we’re thrilled to conclude that our hard work paid off in the short time we had with each brand.
Then I found out that I didn’t have to write a profile at all: All I needed to do was fill out some basic personal information. One day, I received an email from the service with a picture of my ideal match. In some cases, machine learning excels at spotting patterns and making predictions.
Pay Pal utilizes machine learning to fight financial fraud; some companies use the technique to predict who will pay back their loans; and clinical scientists employ machine learning to identify which symptoms of depression are most effectively treated with antidepressant medication.
In Ingenuity’s words, they ‘help brands find the best agency partners to tackle their business challenges’ and ‘help agencies of all shapes and sizes to find, meet and win new clients.’ Which is rather helpful of them.
We had a week to prepare for our ‘dates,’ which we spent frantically researching and fleshing out dozens of ideas in preparation for the big day.
If we’re not so good at predicting what we’ll like in our partners, it isn’t such a surprise that machines also struggle.
So maybe online dating services that use this kind of algorithm will have a tough time identifying two people who will find each other romantically desirable.
Although I eventually married the woman a computer identified as my top match, I also went on dates with other women the computer thought I would like—and I didn’t.
But by taking action to join online dating sites, my dating pool expanded, increasing my chances of meeting the right person.
I soon found that this was an excerpt from his book, Date-onomics: How Dating Became a Lopsided Numbers Game that was published by Workman in 2015.