After learning about Clara's home life—and hearing her agree to be his girlfriend, albeit with the condition that they'd only officially start dating after her postgraduate exams—Tony Snow couldn't sit still.
He wanted to help her. And he wanted to help her now.
What did Clara need most?
Money.
Clara didn't need luxury or excess. But she deserved a life where she didn't have to ration her food, where she could buy a decent coat in winter, or eat a good meal without hesitation. With money, so many burdens could be lifted—from her own shoulders and her grandmother's too.
But Tony's family background was nothing remarkable. His parents still worked hard to make ends meet, and he had no inheritance, no wealthy relatives. If he wanted money, he had to earn it. And the only capital he had?
The knowledge inside his mind—knowledge from a simulated future.
But Tony also knew that this wasn't a superhero movie. He couldn't pull out some mind-blowing tech from the year 2080 and expect the world to understand it.
Technological advancement didn't happen in leaps—it happened in steps.
Everything was built on layers of previous discoveries. To reach the future he had seen, the world needed time and groundwork. Still, he could accelerate that process. Even if he couldn't release full-blown "black tech" yet, he could guide humanity in the right direction.
As he walked to the library, a guilty thought struck him.
Why didn't I ever think about earning money for my parents like this? They've worked so hard their whole lives. Why is it Clara's situation that finally lit a fire under me?
He mulled it over for a moment… then found a reason to forgive himself.
It's not too late. Helping Clara doesn't mean I can't help my family too. Everyone benefits if I succeed.
When he arrived at the library, Clara pulled out her usual stack of biology and chemistry books. Tony, on the other hand, flipped open his laptop.
He stared at the blank document for a while, thinking.
What kind of paper should he write?
The knowledge he gained from his last simulated life was primarily rooted in computational biology—an interdisciplinary field combining computer science, math, and biology. Tony had discovered that in the world of cutting-edge science, direction mattered far more than raw effort.
Pick the wrong direction, and years of research might yield nothing. Pick the right one, and even modest effort could lead to breakthroughs.
That's why simulations of biological systems, data analysis, and algorithm design played such a crucial role in modern biology. The umbrella field—computational biology—included everything from statistics and bioinformatics to neural modeling, ecological prediction, and even animation-based protein structure analysis.
Tony realized something interesting during his last simulation. His simulated self had pursued dual expertise in computer science and mathematics—not for some clever plan to benefit the real Tony, but because it was the optimal path for that version of himself.
The realization was sobering. From the simulator's perspective, every version of me is the real me. There is no privileged "original" self. Each version is living a full, complex life—whether or not I benefit from it later.
Eventually, Tony placed his fingers on the keyboard and typed the title of his next paper:
"A Discussion on an Algorithm for Training Neural Networks and Performing Advanced Computational Tasks"
It wasn't something the current generation would immediately understand. But thirty years in the future, an algorithm would emerge—completely different from all known neural network training models. That single discovery would trigger a new wave of AI breakthroughs.
Within twenty years of that algorithm's release, AI systems would become so advanced that consumer-grade robot assistants—similar to those in Bicentennial Man—became a reality. They didn't have emotions yet, but they were smart enough to replace human nannies, housekeepers, and even tutors.
Unfortunately, Tony's simulated self died shortly after this breakthrough, and never saw what came next.
Still, Tony knew he couldn't just publish that algorithm now. The prerequisites weren't there. The field wasn't ready.
He estimated it would take at least forty academic papers, published in just the right sequence, before anyone could even begin to understand that future algorithm. So he'd have to start small—guide the field gently—then, when the moment was right, he'd drop the real bombshell.
As he began to write, Clara glanced sideways, curiosity written all over her face.
She had noticed Tony was quiet at first, just staring at his screen. But now, she saw the title of his paper flash across the screen, and her confusion deepened.
Though Clara specialized in biology, she knew neural networks weren't something you dabbled in casually—especially not if you'd never studied computer science.
"Eyes on your own page," Tony whispered, catching her distracted gaze without even turning.
Clara pouted and turned back to her textbook, although she kept glancing sideways now and then.
The hours slipped by.
Tony's new paper was harder to write than his previous math one. Not because of the content—he knew exactly what he wanted to say—but because he needed to dig through dozens of reference papers to build a plausible foundation. That alone took up most of his time.
Still, the purpose of this paper was simple: to point the world in the right direction. Once someone followed his ideas and achieved something meaningful, others would swarm to that path, and Tony's paper would skyrocket in citations. It would become a cornerstone—a catalyst.
As they were packing up to leave the library, Clara asked casually, "So? How's the new genius paper coming along?"
Tony shrugged. "Slower than expected. Hunting references takes forever. But I should have it done by the end of the month."
He sounded calm, even a bit bored—nothing like the stressed-out students normally slamming together last-minute papers.
Back at the dorm, Tony had barely taken off his shoes when Liu Xiao popped up, clutching his notebook like it held the answers to life itself.
"Tony! Big bro! Can you help me with this advanced calc question?"
Over the past few weeks, Liu Xiao had developed an uncanny ability to sense Tony's return to the dorm—just from the sound of footsteps in the hallway.
It was the same kind of talent that kids developed when they tried to sneak in TV time before their parents came home—identifying footsteps, engine sounds, or even the way the door lock clicked.
Tony smiled tiredly and took the notebook. "Alright, let's take a look…"
It seemed the future wasn't just arriving faster—it was also getting a little more crowded.