David Rawlinson

Consciousness & “Free Will”: The Elephants in the Room

By David Rawlinson and Gideon Kowadlo The aim of this post is to take a short departure from more technical issues and deal with some of the philosophical questions about Artificial General Intelligence (AGI). The Elephant in the room This metaphor implies willful ignorance of something blindingly obvious. Something that’s difficult… Read More »Consciousness & “Free Will”: The Elephants in the Room

Another look at the retina

by David Rawlinson and Gideon Kowadlo Why the retina is worth a deeper look Recently, we have been looking at the retina – light sensitive cell layers inside the eyeball, that detect wavelength and intensity, and compute some initial encoding of this data that is transmitted to the brain proper… Read More »Another look at the retina

The Arcade Learning Environment – a test suite for AGI

This might be our new test suite for the algorithms! http://www.arcadelearningenvironment.org/ “The Arcade Learning Environment (ALE) is a simple object-oriented framework that allows researchers and hobbyists to develop AI agents for Atari 2600 games. It is built on top of the Atari 2600 emulator Stella and separates the details of… Read More »The Arcade Learning Environment – a test suite for AGI

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

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