Once, on a crisp cloudless morning in early fall, a machine learning engineer left her home to seek the answers that she could not find, even in the newly-optimized Google results.
She closed her laptop, put on her backpack and hiking boots, and walked quietly out her door and past her mailbox, down a dusty path that led past a stream, until the houses around her gave way to broad fields full of ripening corn.
She walked past farms where cows grazed peacefully underneath enormous data silos, until the rows of crops gave way to a smattering of graceful pines and oaks, and she found herself in a forest clearing, headed into the woods. She went deeper through the decision trees and finally stopped near a data stream around midday to have lunch and stretch her legs.
The sun made its way through the sky and eventually, she walked further, out of the forest. Finally, she found a path that started snaking its way up a mountainside, and she started to hike upwards, through the red rocks. After several hours she stopped and took a drink from her Klean Kanteen as she surveyed the sprawling random forest, the valley spread out below her and the sparkling data lake in the distance.