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New HTM paper – “Why Neurons Have Thousands of Synapses, A Theory of Sequence Memory in Neocortex”

The artificial neuron model used by Jeff Hawkins and Subutai Ahmad in their new paper (image reproduced from their paper, and cropped). Their neuron model is inspired by the pyramidal cells found in neocortex layers 2/3 and 5. It has been several years since Jeff Hawkins and Numenta published the… Read More »New HTM paper – “Why Neurons Have Thousands of Synapses, A Theory of Sequence Memory in Neocortex”

Sparse Distributed Representations (SDRs)

TL;DR: An SDR is a Sparse Distributed Representation, described below SDRs are biologically plausible data structures SDRs have powerful properties SDRs have received a lot of attention recently There are a few really great new resources on the topic: Presentation by Subutai Ahmad of Numenta Older introductory presentation by Jeff Hawkins Excellent… Read More »Sparse Distributed Representations (SDRs)

Toward a Universal Cortical Algorithm: Examining Hierarchical Temporal Memory in Light of Frontal Cortical Function

This post is about a fantastic new paper by Michael R. Ferrier, titled:   Toward a Universal Cortical Algorithm: Examining Hierarchical Temporal Memory in Light of Frontal Cortical Function   The paper was posted to the NUPIC mailing list and can be found via:   http://numenta.org/community-content.html   The paper itself… Read More »Toward a Universal Cortical Algorithm: Examining Hierarchical Temporal Memory in Light of Frontal Cortical Function

Recent HTM projects

It’s exciting to see growing interest and participation in the AGI community. This is another brief post to share two examples. In this case, they both build on one approach to AGI, and that is HTM. FXAI – Explorations Into Computational Intelligence A blog that is pretty well described by… Read More »Recent HTM projects

Cortical Learning Algorithms with Predictive Coding for a Systems-Level Cognitive Architecture

This is a quick post to link a poster paper by Ryan McCall, who has experimented with a Predictive-Coding / Cortical Learning Algorithm (PC-CLA) hybrid approach. We found the paper via Ryan writing to the NUPIC theory mailing list. What’s great about the paper is it links to some of… Read More »Cortical Learning Algorithms with Predictive Coding for a Systems-Level Cognitive Architecture

A Unifying View of Deep Networks and Hierarchical Temporal Memory

Browsing the NUPIC Theory mailing list, I came across a post by Fergal Byrne on the differences and similarities between Deep Learning and MPF/HTM. It’s a great background into some of the pros and cons of each. Given the popularity and demonstrated success of Deep Learning methods it’s good to understand… Read More »A Unifying View of Deep Networks and Hierarchical Temporal Memory

On Predictive Coding and Temporal Pooling

Introduction Predictive Coding (PC) is a popular theory of cortical function within the neuroscience community. There is considerable biological evidence to support the essential concepts (see e.g. “Canonical microcircuits for predictive coding” by Bastos et al). PC describes a method of encoding messages passed between processing units. Specifically, PC states that… Read More »On Predictive Coding and Temporal Pooling