Researchers from MIT and elsewhere set out to see if they could use machine learning to build better hash functions. Credits : Image: Christine Daniloff, MIT
Researchers from MIT and elsewhere set out to see if they could use machine learning to build better hash functions. Credits : Image: Christine Daniloff, MIT Researchers use machine learning to build faster and more efficient hash functions, which are a key component of databases. Close Hashing is a core operation in most online databases, like a library catalogue or an e-commerce website. A hash function generates codes that replace data inputs. Since these codes are shorter than the actual data, and usually a fixed length, this makes it easier to find and retrieve the original information. However, because traditional hash functions generate codes randomly, sometimes two pieces of data can be hashed with the same value. This causes collisions - when searching for one item points a user to many pieces of data with the same hash value.
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