Total pages in book: 103
Estimated words: 97780 (not accurate)
Estimated Reading Time in minutes: 489(@200wpm)___ 391(@250wpm)___ 326(@300wpm)
Estimated words: 97780 (not accurate)
Estimated Reading Time in minutes: 489(@200wpm)___ 391(@250wpm)___ 326(@300wpm)
Jess turned expectantly to Fizzy, who had turned expectantly to Jess.
“Okay, well, I guess I’ll take the first shot,” Fizzy said, scoffing at Jess’s blank expression. “I’m thirty-four, and I enjoy dating. A lot. But I suppose I’ll eventually settle down, have some kids. It all depends on the person.”
Lisa nodded, smiling like this was a perfect answer, and then turned to Jess.
“I …” she began, flailing a little. “I assume there’s someone out there for me, but I’m not really in a rush to find him. I’m about to turn thirty. I have a daughter; I don’t have a lot of time.” Shrugging vaguely, she mumbled, “I don’t really know.”
Clearly Lisa was used to people with a bit more drive, but she rolled out her spiel anyway. “Have you ever wondered what a soulmate truly is?” she asked. “Is love a quality you can quantify?”
“Oooh, good question.” Fizzy leaned in. Hook, line, and sinker.
“Here, we believe it is,” Lisa said. “Matchmaking through DNA technology is exactly what we offer here at GeneticAlly, through the DNADuo. GeneticAlly was officially founded six years ago, but the concept of the DNADuo was first conceived in the lab of Dr. David Morris at the Salk Institute back in 2003.” Lisa swiped from the first image—the DNADuo logo—to an aerial view of the Salk, a stark collection of futuristic buildings just up the road. “The idea of genetic matchmaking is not new, but few companies have been able to create anything even a fraction as extensive as what Dr. Morris and his graduate student, River Peña, designed.”
Jess glanced at Fizzy, who looked back at her. If River and his mentor invented all of this, Jess figured she couldn’t give him too much shit for being a terrible pitch man.
Even if she could give him shit for being a bit of an asshole.
Lisa continued: “The reason the DNADuo has been so successful at identifying genuine love matches is that the idea didn’t start with DNA.” She paused dramatically. “It started with people.”
Jess stifled an eye roll as the slide became animated, zooming away from the Salk research buildings and along a street to a collection of computer-generated coeds standing on the patio of a bar, laughing and talking.
“Dr. Peña first asked whether he could find a complementary pattern in the DNA of two people who are attracted to each other.” Lisa’s slide zoomed in on a couple speaking closely, flirtatiously. “That is, are we programmed to find certain people attractive, and can we predict which two people will be attracted to each other before they ever meet?” She grinned. “In a study of over one thousand students from UC San Diego, a series of nearly forty genes were found to be tightly correlated with attraction. Dr. Peña then pointed the lab in the opposite direction to look into lasting happiness. Could he find a genetic profile of people who had been happily married for longer than a decade?”
Lisa swiped the animation forward to show an older computer-generated couple sitting on a couch, cuddling. The view zoomed back to show a neighborhood, and then a city, and then farther until the city map looked like a double-helix strand of DNA. “From a study of over three hundred couples,” Lisa continued, “Dr. Peña found nearly two hundred genes that were linked to emotional compatibility long-term, including the same forty genes associated with attraction, as well as many other previously uncorrelated ones.” She paused, looking at them. “This was only the first generation of the DNADuo.”
Beside Jess, Fizzy was sitting up at full attention, completely plugged in. But Jess was skeptical. What Lisa was describing was essentially a slot machine with two hundred reels. Statistically speaking, landing on the right combination was an absurdly low-probability event. Even if GeneticAlly was just looking for pattern compatibility, with the number of variants of every gene in the human genome, this type of algorithm was so complex as to be nearly impossible to calculate manually. She couldn’t see how they would begin to process the amount of data they were facing.
Lisa seemed to read her mind. “Two hundred is a lot of genes, and the human genome is made up of at least twenty thousand. Of course, not all of these—maybe not even most—are involved in our emotional satisfaction. But Drs. Peña and Morris wanted to find every last one. They didn’t just want to identify compatibility, they wanted to help you find your soulmate. Which is exactly why Dr. Peña collaborated with Caltech to develop a novel deep neural network.”
She let these words sink in as the slide became animated again, diving into the double helix, highlighting base fragments as it whizzed along the length of the DNA strand.
“This project has encompassed personality tests, brain scans, longitudinal studies of relationship success, and—yes—well over one hundred thousand samples run through DNA sequencing and analysis.” She looked each of them dead in the eye. “The investors have put over thirty million dollars into the technology alone. The app developers have invested almost five million. Do I think we have a truly groundbreaking system?” She nodded. “Between us? In all honesty? I do.”