This is a ruby gem that lets you implement categorization systems with ease. **Associative memory neural networks** make it easy to identify probable patterns between sets of named data points. It can be cumbersome to interface with the neural network directly, however, as a typical convergence matrix has a fixed size and training period, which limits how useful they can be to an integrated system. associative_memory simplifies these kind of machine learning models by offering dynamically configurable input and output sets, and a convergence model that adapts to the inputs you give it each time. This allows your code to concentrate on extrapolating meaningful patterns rather than juggling bitmasks and transposition matrices. Under the hood, associative_memory implements a hetero-associative recurrent neural network designed according to Kosko's landmark paper (http://sipi.usc.edu/~kosko/BAM.pdf) establishing the model. The model then dynamically rebuilds and adapts this network to accomodate new inputs as necessary.