Skip to content

neurobiology

Hippocampus

AHA! an ‘Artificial Hippocampal Algorithm’ for Episodic Machine Learning

We’re very happy to report that we recently published a preprint on AHA, an ‘Artificial Hippocampal Algorithm’ for Episodic Machine Learning. It’s the culmination of a multi-year research project and is a starting point for the next wave of developments. This article describes the motivation for developing AHA and a… Read More »AHA! an ‘Artificial Hippocampal Algorithm’ for Episodic Machine Learning

Biologically-plausible learning rules for artificial neural networks

Artificial neural networks (ANNs) – are conceptually simple; the combination of inputs and weights in a classical ANN can be represented as a single matrix product operation followed by an elementwise nonlinearity. However, as the number of learned parameters increases, it becomes very difficult to train these networks effectively. Most… Read More »Biologically-plausible learning rules for artificial neural networks

New approaches to Deep Networks – Capsules (Hinton), HTM (Numenta), Sparsey (Neurithmic Systems) and RCN (Vicarious)

  Reproduced left to right from [8,10,1] Within a 5 day span in October, 4 papers came out that take a significantly different approach to AI hierarchical networks. They are all inspired by biological principles to varying degrees. It’s exciting to see different ways of thinking. Particularly at a time… Read More »New approaches to Deep Networks – Capsules (Hinton), HTM (Numenta), Sparsey (Neurithmic Systems) and RCN (Vicarious)

How to build a General Intelligence: An interpretation of the biology

Figure 1: Our interpretation of the Thalamocortical system as 3 interacting sub-systems (objective, subjective and executive). The structure of the diagram indicates the dominant direction of information flow in each system. The objective system is primarily concerned with feed-forward data flow, for the purpose of building a representation of the… Read More »How to build a General Intelligence: An interpretation of the biology