In this research paper, Numenta proposes a novel theoretical framework for understanding what the neocortex does and how it does it. The framework is based on grid cells and has significant implications for neuroscience and machine intelligence.
This companion piece explains the Thousand Brains Theory of Intelligence, one of the big ideas introduced in the October 2018 research paper A Framework for Intelligence and Cortical Function Based on Grid Cells in the Neocortex by Jeff Hawkins, Marcus Lewis, Scott Purdy, Mirko Klukas, and Subutai Ahmad. Written by non-neuroscientists, it can be read as a standalone piece or as a primer for the full research paper.
This paper demonstrates how the application of Numenta’s brain-inspired, sparse algorithms achieves more than 100x speed-up on inference tasks compared to dense networks with no loss of accuracy.
Recent proposals suggest that the brain might use similar mechanisms to understand the structure of objects in diverse sensory modalities, including vision. In machine vision, object recognition given a sequence of sensory samples of an image is a challenging problem when the sequence does not follow a consistent, fixed pattern – yet this is something humans do naturally and effortlessly. We explore how grid cell-based path integration in a cortical network can support reliable recognition of objects given an arbitrary sequence of inputs.
This paper shows that a set of grid cell modules, each with only 2D responses, can generate unambiguous and high-capacity representations of variables in much higher-dimensional spaces.