Numenta Platform for Intelligent Computing (NuPIC) - Now Open-Source
SeH
https://github.com/numenta/nupic
http://numenta.org/resources/HTM_CorticalLearningAlgorithms.pdf
What is NuPIC?
NuPIC, the Numenta Platform for Intelligent Computing, comprises a set of learning algorithms that were first described in a white paper published by Numenta in 2009. The learning algorithms faithfully capture how layers of neurons in the neocortex learn. The white paper has been translated into seven languages by volunteers and has generated considerable interest among developers and research scientists.
Why did we create the NuPIC Open Source project?
We created the NuPIC open source project because people read the white paper and want to work with these algorithms. They asked us to make them available in an open source project. For a detail explanation of our motivations, hopes and fears around this project, see Jeff’s Introduction to NuPIC.
What is unique about the algorithms in NuPIC?
At the heart of NuPIC is the Cortical Learning Algorithm or CLA. The CLA has a deep biological mapping which will be interesting to neuroscientists. From an algorithmic point of view there are three principle properties.
NuPIC is a library that provides the building blocks for online prediction systems. The library contains the Cortical Learning Algorithm (CLA), but also the Online Prediction Framework (OPF) that allows clients to build prediction systems out of encoders, models, and metrics.
For more information, see numenta.org.
OPF Basics
Encoders turn raw values into sparse distributed representations (SDRs). A good encoder will capture the semantics of the data type in the SDR using overlapping bits for semantically similar values.
Models take sequences of SDRs and make predictions. The CLA is implemented as an OPF model.
Metrics take input values and predictions and output scalar representations of the quality of the predictions. Different metrics are suitable for different problems.
Clients take input data and feed it through encoders, models, and metrics and store or report the resulting predictions or metric results.