Machines learning

A chaotic Ankh Morpork, choked with smoke, gears, pipes, and copper-clad towers. Foreground: eccentric scientists and engineers frantically operate AI machines, model pipelines, and glowing data cores. Steam vents, spinning cogs, and brass machinery abound.

In the twisted streets of Ankh Morpork, machine learning stumbles from hopeful notebooks to production chaos, guided by a motley crew of algorithms and the perils of MLOps. Models are born with bright promise, trained, containerised, and shipped into dashboards that everyone ignores, while data pipelines evolve like rival guilds and cloud bills spiral into the tens of thousands of euros. From small startups duplicating effort in cosy offices to bureaucratic giants where updates require sacrifices to compliance, the journey is one of trial, error, and occasional brilliance. Humans intervene, models learn, regress, and sometimes even survive, leaving behind a trail of technical debt, post-mortems, and slightly singed egos.

Disclaimer

No conspiracies are being summoned here, no apocalypses predicted, and no machines plotting, officially. These are the precise and dangerous reflections of Patrician Vetinari, a man who can foresee chaos before it thinks of itself. He writes lightly, observes sharply, and chuckles quietly while the world trips over its own hubris. Take this as guidance, or as a polite warning from someone who could make you disappear without anyone noticing.