Total pages in book: 102
Estimated words: 96454 (not accurate)
Estimated Reading Time in minutes: 482(@200wpm)___ 386(@250wpm)___ 322(@300wpm)
Estimated words: 96454 (not accurate)
Estimated Reading Time in minutes: 482(@200wpm)___ 386(@250wpm)___ 322(@300wpm)
I never met my grandma, and my mom’s version of cooking is heating up a frozen dinner.
“See, I told you I can share. Tell the nurse I want an update. I know. Bye.” Heath hangs the cell up and slides it into his pocket. “Hey, Ms. Jensen. I’m sorry about the wait. My grandmother can talk.”
Yep, he’s simply another hot guy who loves his grandma and knows how to code.
Unemployed. I need to fixate on that word. “It’s just Ivy. So Harper said you were having some trouble.”
“Just Ivy.” Darnell is still nodding and watching us like he’s waiting for something to happen. “That’s funny. You’re not just Ivy. You’re like an icon.”
People throw that word around a lot. So much that it’s lost all meaning. “I assure you I am not. I’m one more coder looking for my next gig.”
“Winter’s End is the best,” Darnell proclaims. “I have played that game a hundred times. Your zombies are the coolest. I’ve been trying to get my man here to play with me. He’s more into puzzle games than shooters. You know he put a game out a couple of years back. Maybe you’ve heard of it.”
“She has not,” Heath assures him. “No one has, hence the crappy apartment where we both live and work. It wasn’t a hit.”
“Rain and Fury,” Darnell continues like Heath has said not a word. “I helped him with the storyline. See, what I really want to do is write. Speculative fiction. I’m not quite there yet, but I’m querying.”
I turn Heath’s way because I do know that game, and now it’s my jaw dropping. “Are you serious? I bought that game as a Christmas present for all of my team. I mean, it was part of it. They also got bonuses. But I loved that game so much.”
Heath blushes—an action that does not lessen his hotness in any way. “So you’re the reason I sold a whole fifty copies in December two years back. You personally account for half my income off that game.”
There’s a reason it’s a rough business. A game can be brilliant and utterly ignored because something else is popular at the time. App stores have made it easier to get products out in the public, so there’s often a glut of games. Without a multimillion-dollar marketing campaign, good games get lost. “Sorry. It’s really well done. I loved the puzzles, and the graphics were beautiful.”
“Thanks. And I’ve filled out many a form that your work has made much easier,” he assures me, thereby killing all my fantasies that he doesn’t know my sad history. “Don’t take that for faint praise. My grandmother had cancer last year. She’s in remission and healthy now, but we’ve been in hospitals that use your system and ones that don’t. Your system genuinely makes life better.”
Those are not tears pulsing behind my eyes, threatening to spill over because it’s been that freaking long since I felt like I was worth something. I manage to shake them off and swear I’m going to get down to business. “That’s good to know. So, what is this app you’re working on?”
Heath seems a bit flustered by the turn of conversation, but he quickly recovers. I wait for him to explain his new freemium game or how he’s developed a better calculator app. “It’s a matchmaking app. Not for like hookups. Tinder has that down. This is for predicting long-term, happy marriages.”
“Ah, you’re fucking with me. Good one, buddy.” I wouldn’t have said he was a joker, but that was funny. He’s actually got me laughing. “So what’s the real app?”
That’s when I realize no one is laughing with me.
Spoiler alert—he was not, in fact, joking.
Chapter Three
Two hours later I’m a little in awe of what he’s doing.
“So you’re building an AI that can predict matches.” I say the words slowly, trying them out. Not really believing them. He’s not merely trying to match people up based on similar interests. It does more than that and matches more than people in relationships.
“Yes.” Heath sits at his computer. He’s been showing me some of his early work. He started with having the AI make simple choices based on input. He’d explained that he’d started with the basics—an app to help decide what to cook for dinner. “Like with the What’s for Dinner app but on a grand scale. Your perfect dinner match along with a recipe and the information on where to buy the ingredients.”
I like this. I’m not sure if it works for putting humans together, but my generation does not mind a screen telling them what to do. We are bombarded with choices every second of the day. Having them narrowed for us based on our needs can be a good thing. “This could be applicable to restaurants around the city, too. Like the user could answer simple questions. How far are they willing to go, what do they like, what level of service do they expect. This could be great when you’re traveling.”