Many people seem to be under the impression that artificial intelligence is like a perpetual motion machine: once you get it started, it can run forever on its own without further input.
While this image makes for entertaining science fiction, it doesn’t come close to matching the reality of AI.
(As a side note, I blame this misconception largely on Hollywood, as my colleague Seth has already written about.)
Instead of a perpetual motion machine, think of an artificial intelligence like a car’s engine. At the start, it will run fast and run well. But over time, the various moving parts will wear down.
Without regular oil changes and other upkeep, an internal combustion engine will quickly fall apart.
In AI’s case, the moving parts are the data you feed it, the machine learning algorithms and neural networks it runs, and the ecosystem it operates in.
And just like a car, if you don’t maintain your AI system, it’ll end up parked on the lawn with a “For Sale, You Tow” sign in the windshield.
Maintaining your AI can be as easy as replacing the cabin air filter, or as complicated as rebuilding the transmission. That’s why it’s important to understand some basic AI maintenance best practices.
In this guest post for KDNuggets.com, I break down the steps you need to take in order to keep your AI in tip-top shape. By planning for problems, ensuring you respond to them quickly, and managing for changes in the industry, you can keep your AI firing on all cylinders.