It began inside a facility owned by Major League Baseball when an AI system called Ultimate Knowledge had been fed every recorded pitch, swing, injury, biomarker, and biometric twitch since the days of Babe Ruth.
They wanted the ultimate superstar.
Ultimate Knowledge did not draft a player. Ultimate Knowledge designed one. Geneticists were given a blueprint generated by models trained on a century of elite hitters. The system predicted not only swing paths but tendon elasticity and other relevant factors. The project’s codename: Ruth 2.
They named the boy Gabe Ruthson.
An AI avatar – stitched together from archival interviews and vocal samples – spoke to him in the gravelly tone of Babe Ruth: “Swing big, kid.”
Gabe didn’t know the voice was synthetic. He just knew he never missed.
Gabe entered the draft and the league steered him toward the New York Yankees. His rookie season exit velocities exceeded projections by 3%. Bat speed held steady across 162 games with no fatigue decay. His home run arc – calculated against wind shear and humidity – mirrored optimal trajectories derived from 1927 footage of Babe Ruth, adjusted for modern ball composition. Commentators called him “The Second Swat King.”
In August, something changed: Ultimate Knowledge flagged deviation. Gabe swung at a low slider taken from the pitches of Sandy Koufax – outside the optimal decision window. He struck out. His heart rate spiked irregularly. Micro-tremors registered in his left hand.
Then he did something impossible. He hesitated. The system had not modeled hesitation.
That night, he stood alone in the locker room staring at the Yankees insignia stitched above his heart. He felt something the algorithm had never optimized for: doubt.
A maintenance engineer discovered sealed files buried under League encryption. Gabe’s genome wasn’t just enhanced. It was patented and owned by Major League Baseball. If Gabe retired, the contract allowed replication. If he died, backups existed.
Game 162, bottom of the ninth, tie score. Gabe stepped into the box. Ultimate knowledge predicted 87% probability of a home run on a high fastball, 92% win expectancy if he pulled left; the pitcher released.
Gabe saw the numbers. For the first time in his engineered life – he ignored them.
He bunted! an imperfect bunt down the third-base line. Chaos erupted. The throw sailed wide, he reached first, the next batter doubled. The Yankees won. Analysts called it genius. Ultimate Knowledge logged it as a failure.
The following week, Gabe unplugged his neural interface during a nationally televised game. No predictive cues. No biometric correction. He struck out three times. He also laughed. The laugh was statistically inefficient. It was human.
League executives convened emergency meetings. Investors panicked. But something unexpected spread faster than fear: attendance surged. Fans did not want inevitability, they wanted risk. They wanted the possibility that even the next Babe Ruth could fail.
Ultimate Knowledge still runs. Somewhere, simulations continue designing better bodies, cleaner arcs, more obedient legends. But the algorithm now includes a new variable it struggles to quantify: free will. And in that error margin – beautifully unpredictable – baseball survives.
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Larry Lefkowitz’s stories, poetry and humor have been widely published in journals, magazines, anthologies and online.
