At the start, I had to choose one of four options, and I immediately picked the Brahmin from the cou

Of course, if we have to apply some kind of mystical setting, being blessed by these two computer pioneers at Sequence Zero level might not be a good thing at all—after all, in this field, the "contamination" brought by true gods is extremely terrifying.

The first one to be "contaminated" was Xiao Zhou.

This young man, who had just graduated from university a year ago and whose biggest hobby was playing mobile games in his rented room after get off work, suddenly proposed an idea at the morning meeting that made everyone quiet for half a minute after sleeping less than ten hours for four consecutive days.

"I want to change the core algorithm of the matching engine from a decision tree to a graph neural network."

His eyes shone brightly when he spoke, and his voice was hoarse, but he enunciated each word with extreme clarity, as if he had rehearsed it countless times in his mind.

"While the current decision tree model can run, the classification boundary degenerates once the feature dimension exceeds 200. The resume parsing we're doing is essentially structured data in non-Euclidean space, which is naturally suited to graph neural networks. Last night, I came across a paper published in March of this year on GitHub. The authors are from MIT, and they used graph attention networks for semantic role labeling, pushing the accuracy from 91 to 96 on the standard test set. I reproduced their core idea, applied it to our resume feature graph, and the F1 score jumped by 0.04."

Dr. He placed the coffee cup back on the table, the sound of the bottom of the cup hitting the table being particularly clear in the quiet office.

He didn't say anything, but walked to Xiao Zhou's workstation and bent down to look at the code on the screen.

After looking at it for about two minutes, he straightened up, took off his glasses, and wiped the lenses with the hem of his shirt—a habitual action he took when he encountered a problem, but at this moment he wiped the lenses at least twice as often as usual.

"Did you use bidirectional or unidirectional attention for the node definition in your graph?"

"It's bidirectional, and it also includes residual connections. With unidirectional connections, long-distance dependencies will decay. Some key information in a resume, even if separated by several paragraphs, still echoes each other—such as the technical stack in education and project experience—can be highlighted by bidirectional attention."

"On which layer should the residual join be added?"

"Each layer. The standard Transformer architecture has six layers of encoders plus residuals, but I compressed it to four layers because the complexity of resume text is much lower than that of general natural language scenarios, and more layers would lead to overfitting. However, each layer retains residual connections to ensure that gradients do not decay in deeper layers during backpropagation."

Dr. He put his glasses back on, paused for a moment, then turned to Chen Qiming: "If I had reviewed his proposal a month ago, I would have sent it back for rewriting. It's not that the idea is bad, it's that the workload is too large—the training cost of graph neural networks is an order of magnitude higher than that of decision trees, and the accuracy will collapse if there isn't enough labeled data. But how much labeled data have we accumulated now?"

"We just got over 50,000 last week, and with the batch of resumes you transferred from the provincial talent market last week, that's enough." Chen Qiming walked over from the whiteboard, a marker still in his hand. He looked down at the code on the screen, his brow furrowing slightly before slowly relaxing, finally settling into a complex expression—a mixture of admiration and wariness. "Xiao Zhou, when did you start reading papers on graph neural networks?"

"Last month... no, it was last week, I think. I can't quite remember."

Xiao Zhou scratched the back of his head, his fingers hovering over the keyboard, the code cursor still bouncing in the auto-completion suggestion box on the screen. "Anyway, recently, I've been looking at research papers every night when I can't sleep. As I read, things become clearer. Before, the same paper seemed like gibberish, but now I can derive the formulas in my head after reading it once. Then I thought, since graph neural networks can do semantic annotation, why can't they do resume matching? A resume itself is a natural attribute graph—the job seeker is the node, and work experience, education background, and skill tags are all attribute edges. Transforming the matching problem into a connection prediction problem on a graph is much more elegant than brute-force feature dimensions using decision trees."

Chen Qiming tossed the marker into the pen holder, pulled up a chair, and sat down next to Xiao Zhou. He stared at the code on the screen silently for several minutes, then turned to look at Dr. He. Dr. He nodded slightly at him—a very small gesture, but Chen Qiming understood—it was feasible.

"Do prototype verification." Chen Qiming's voice returned to its usual calm, but the knuckles of his fingers, clenched on his knees, were slightly white. "Run a small-scale test first, keeping the sample size under two thousand resumes, and compare the F1 scores of the graph neural network and the decision tree. I need to see the comparison data within three days. If the F1 score can really create a difference of more than 0.04, we'll change direction for this round of architecture iteration."

Xiao Zhou nodded vigorously, his fingers already typing on the keyboard.

His movements were so fast that Xiao Zhang, the backend engineer next to him, peeked over and muttered, "This hand speed is fast enough for e-sports."

But Xiao Zhou was clearly not just typing randomly—the code on the screen flowed line by line, the function names were clear, the comments were more standardized than any usual commit, and there were almost no pauses. Every variable name followed the team's existing coding standards perfectly, and the imported packages were arranged neatly in the order of standard libraries, third-party libraries, and local modules. Normally, this level of coding standard would require at least three or four revisions during the code review process, but this time it passed on the first try.

When Chen Qiming got up to get water, he passed by the printer and found that the paper tray was already piled with a thick stack of printed papers.

The top one is the MIT paper on graph attention networks, with dense red annotations next to it. The annotations are written in varying thicknesses; the thin ones were written by Xiao Zhou the day before yesterday, while the thick ones are additions he made yesterday morning.

Turning to the last page, a line of crooked pencil writing appeared in the blank space: "The third layer of the encoder can be removed and replaced with a fully connected layer, and the feature loss can be controlled within 0.01." The handwriting was messy, obviously written in a half-asleep state, but the logic was flawless—Dr. He had verified this simplified solution this morning, and the results were completely consistent.

Xiao Zhou's change didn't happen overnight. It was Xiao Zhang, the backend engineer sitting opposite him, who first noticed that Xiao Zhou no longer napped at his desk during lunch breaks. Instead, he wore headphones, stared at the screen, his fingers flying across the touchpad, a faint smile playing on his lips. Xiao Zhang assumed he was slacking off by watching videos, but while getting water, he peeked behind him. The screen was covered in dense code—but it wasn't the intelligent recruitment system they were developing; it was a completely unfamiliar project.

"What are you writing?" Xiao Zhang leaned closer. The colorful code highlights on the screen made his eyes blurry, but he could barely recognize a few keywords: vertex shader, texture mapping, and skeletal animation.

"A real-time rendering pipeline for a VTuber, something I wrote for fun when I had nothing else to do." Xiao Zhou didn't even look up, his fingers still typing rapidly on the keyboard. On the screen, a cartoon girl in a fluffy dress was slowly turning in a plain virtual background. The physics engine simulated the skirt's hem extremely naturally, and the lighting and shadow rendering of each frame was accurate down to the reflection point of the earring.

Xiao Zhang stared blankly at his water glass for a while, then pulled out a chair and sat down, looking at Xiao Zhou with an expression of utter disbelief. "Didn't you only know how to write backend code? Last time, when frontend developer Xiao Li asked you to help adjust some CSS, you complained about the hassle. When did you start learning real-time rendering?"

"I haven't learned it." Xiao Zhou finally stopped coding and looked down at the cartoon girl on the screen that was rotating automatically. His expression was even more confused than Xiao Zhang's. "I just came across a clip of a VTuber's live stream yesterday and thought it was funny. Suddenly, all this rendering pipeline architecture started popping into my head. I don't know where these things came from—it's like I already knew them, but I just forgot them before."

Xiao Zhang took this as a Versailles experience unique to programmers and didn't ask any more questions.