How does the Mind store Information?

TL;DR

This paper explores a novel conceptual and algorithmic approach to storing information in the mind using recursive sketching data structures, forming an implicit knowledge graph for efficient retrieval.

Contribution

It introduces a memory architecture based on recursive sketching, bridging deep network computations with concise, indexable sketches for information storage.

Findings

Proposes a recursive sketching-based memory architecture.

Creates an implicit knowledge graph for information retrieval.

Utilizes subspace embeddings to capture deep computations.

Abstract

How we store information in our mind has been a major intriguing open question. We approach this question not from a physiological standpoint as to how information is physically stored in the brain, but from a conceptual and algorithm standpoint as to the right data structures to be used to organize and index information. Here we propose a memory architecture directly based on the recursive sketching ideas from the paper "Recursive Sketches for Modular Deep Networks", ICML 2019 (arXiv:1905.12730), to store information in memory as concise sketches. We also give a high level, informal exposition of the recursive sketching idea from the paper that makes use of subspace embeddings to capture deep network computations into a concise sketch. These sketches form an implicit knowledge graph that can be used to find related information via sketches from the past while processing an event.