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Pentti Kanerva

sdm.ai team

Cognitive Sciences

This is a framework which can be adapted to any usage of a Sparse Distributed Memory (Kanerva, 1988): new theoretical results, new applications, new machine learning models, etc.

We have been working on Pentii Kanerva’s Sparse Distributed Memory:

• The first paper considered the range of dimensions that an SDM should have were it to respect i) chunking-by-averaging, and ii) the “magic number 7”;
• a second paper studied the critical distance as the memory becomes saturated;
• a third paper (underway) studies interaction effects between different attractors, and
• a fourth paper will document this highly-palallel SDM framework developed by Dr. Marcelo Brogliato.

We would really like to ask you for feedback, and, should you find it useful, please consider a link or citation:

Brogliato, M.S.; Linhares, A. (2017) Sparse Distributed Memory: a reference implementation. Working Paper, FGV, Vialink.