Machine Learning

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Ethan slipped into the back of the conference room in Building 5 without being noticed. Fifty researchers and administrators, jammed into the room lab-coat-to-suit, all faced the projection stage. Today, of course, it would be set for maximum display. The CEO of the company was here, his six-foot-three frame looming over the crowd. Beside him, invisible to Ethan in the crush, would be tiny Anne Gonzalez, R&D chief. For five years a huge proportion of the Biological Division’s resources—computational, experimental, human—had been directed toward this moment.

Anne’s clear voice said, “Run.”

Some people leaned slightly forward. Some bit their lips or clasped their hands. Jerry Liu rose onto the balls of his feet, like a fighter. They all had so much invested in this: time, money, hope.

The holostage brightened. The incredibly complex, three-dimensional network of structures within a nerve cell sprang into view, along with the even more complicated lines of the signaling network that connected them. Each line of those networks had taken years to identify, validate, understand. Then more time to investigate how any input to one substructure could change the whole. Then the testing of various inputs, each one a molecule aimed at the deadly thing near the center of the cell, the growing mass of Moser’s Syndrome. All this hard work, all the partnering with pharmaceutical companies, in order to arrive at Molecule 654-a, their best chance.

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