Classically speaking, any time you gave computers a goal to optimize for, it was called "AI"; a large amount of AI research in the 80's and 90's was about how t

Classically speaking, any time you gave computers a goal to optimize for, it was called "AI"; a large amount of AI research in the 80's and 90's was about how to optimize search. Thus SQLite's website, for instance, (correctly) says: "The query planner is an AI that tries to pick the fastest and most efficient algorithm for each SQL statement." Optimizing database queries was a common topic for artificial intelligence research in the 80's and 90's. It's just that now we're so used to the idea of a computer searching for the best flight, the best map, the best way to optimize your code, the best way to execute your SQL query, that it doesn't seem like "magic" any more. When you say "no dataset, no training" you're talking about machine learning. And when you say "layers", you're talking about deep learning. [1] https://sqlite.org/queryplanner.html https://sqlite.org/queryplanner.html