Sort of reminds me of Factor Tables: https://github.com/RowColz/AI/blob/master/Factor_Tables.pdf https://github.com/RowColz/AI/blob/master/Factor_Tables.pdf On

Sort of reminds me of Factor Tables: https://github.com/RowColz/AI/blob/master/Factor_Tables.pdf https://github.com/RowColz/AI/blob/master/Factor_Tables.pdf One can "compress" the Factor Tables using statistical "stereotyping" as a kind of a lossy learning technique. You have systemic control over the size-versus-accuracy tuning of the hashing (indexing). Similarly, we learn to recognize or respond to patterns without remembering each specific instance of the pattern we encounter, which can be seen as a lossy form of hashing also.