[vbychkovsky]

Classic caching algorithms like LRU use only last access time as a feature. You are correct that ML based on only that one feature won’t be much different than LRU. However, most of the time, data items have metadata that can be used as features, for example, image size and type. With this additional metadata ML algorithms can do a lot better than LRU that is only using access patterns. Also, think about how image content (sports car, an attractive person, etc) could predict if this image it likely to be accessed in the future.

[taeric]

I think some caching algorithms are a bit smarter than just LRU. Though, that is typically as much in having multiple caches as it is anything else.

More importantly, I know this is claimed a lot. But I thought the last few explorations of the idea I saw did not actually see fancier algorithms win. Indeed, the best strategy from my memory was random spreading of the data with an almost random replacement strategy. I think some of the win there was just the low overhead of the bookkeeping, but it was still one of the better bets.

(This is all off the table, of course, if you know what the access pattern will be. Then, by all means, set things up accordingly.)