"Red Pixel"
The early nineties. The university building, built in the late modernist style, seemed torn from another era - concrete, glass, silence. On the third floor, in the corner of a long corridor, was the Department of Applied Cryptography. It smelled of dust, overheated capacitors, and coffee brewed in an imported thermo pot. Yellowed schematics of encryption machines covered the walls, and on the tables lay bulky computers, punched tape, and the first IBM compatible PCs, assembled from whatever they could find.
The experiment began with something mundane - a random number generator. A program written in Pascal was run on an ancient machine with a black-and-green monitor. The researchers were trying to assess how "random" the random numbers were and whether patterns could be detected in them. The work was routine: startup, data collection, analysis, reporting. But at some point, someone suggested visualizing the process.
"What if we just display the numbers as pixels?" said Jonathan, a graduate student with a perpetual notebook tucked under his arm and a coffee stain on his shirt.
And so the first "static" appeared on the screen - chaotic, flickering, and completely illogical. Each number corresponded to the color of a pixel, and the screen filled with a mosaic, like a television that had lost its signal.
That evening, only two people remained in the lab - Jonathan and Professor Miller. The professor, a man with graying temples and a habit of commenting on everything out loud, sat at the next terminal, reviewing the generator's logs.
Jonathan, staring at the chaos of pixels, suddenly reached out to the screen and said with a grin, "Turn red!"
The professor, without taking his eyes off the code, waved him off, "To influence the program, you'll have to feed it data from your neurons."
Silence followed. Jonathan slowly lowered his hand. Then he turned around.
"What if we try?"
The professor looked up. His gaze was first tired, then thoughtful. He leaned back in his chair and laced his fingers together.
"We don't have access to neural interfaces. Even an EEG is a luxury. But..." he paused. "But we have signals. Electrical. Biological. We could try something simple. Skin reactions, pulse. Or even just a button controlled by intuition."
"Or brain noise," Jonathan added. "We're studying noise, after all. Why not use the noise of the person themselves?"
And so a new stage began. Unofficial. Not approved under the grant. They started small - connecting a simple analog sensor, assembled from readily available components, to a computer. They began writing code that would respond to external signals, however primitive.
Two more people joined them: Sarah, a statistician, and Tom, an engineer who could fix anything that could be soldered. In the evenings, the department filled with the quiet hum of fans, the clicking of relays, and muffled arguments.
No one knew exactly what they were doing. They were just trying. They were searching for a way to connect man and machine not through a keyboard, but directly - through noise, through chaos, through something that eluded conventional models.
The pixels continued to flicker chaotically on the screen, but now each one seemed a little more significant. As if order was beginning to emerge from this chaos.
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