Locality-sensitive hashing

Locality-sensitive hashing (LSH) is like playing a game of "I Spy" where we're trying to find something by looking for its features in a big pile of similar things.

Imagine you have a bunch of LEGO blocks, some are red and some are yellow, and you want to find all the red ones. The first thing you might do is group all the blocks by color to make it easier to find the red ones. But what if you don't have time to sort through all the blocks?

This is where LSH comes in. It's like having a magic pair of glasses that let you quickly find all the red blocks without having to sort through every single one.

Instead of sorting the blocks by color, LSH groups them using a hash function, which is like a magic formula that turns each block into a number. Blocks that share certain features, like being red, end up with similar numbers.

Now, when we want to find all the red blocks, we only need to look at the numbers that the red blocks were hashed to, and we can quickly find them without having to look through every single block.

This helps us find things quickly, even if there are hundreds or thousands of similar items, by using a special trick to group them together based on their features. LSH is used in many fields like image and voice recognition, search engines, and shopping recommendations.