Combining principles of biological cognition and machine learning to devise, empirically test and prove novel algorithms that can achieve general intelligence.

“Quantum computing” via Sparse distributed coding?

David Rawlinson

Oct 8, 2015

Feb 16, 2015

Aug 19, 2017

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

Gideon Kowadlo

Nov 10, 2019

Hippocampus and the Episodic confusion (for machine learning)

David Rawlinson

Mar 18, 2019

AI is already harming us — but not the way you think — Project AGI

As AI/ML researchers, we have obviously pondered the risks of AI. We even wrote about it. But what might surprise you is the risks that keep AI/ML folk awake at night aren’t the ones you hear about in the media…

Abdelrahman Ahmed

Feb 28, 2019

Optimization using Adam on Sparse Tensors

Adaptive optimization methods, such as Adam and Adagrad, maintain some statistics over…

David Rawlinson

Nov 28, 2018

Predictive Capsules Networks — Research update

Gideon Kowadlo

Oct 7, 2018

New ML/Neuroscience Research Projects — ‘Self Organising Architectures’ and ‘Bicameral Brains’

Abdelrahman Ahmed

Sep 12, 2018

Experiment Infrastructure at Project AGI

It’s such a joy to be able to test an idea, go straight to the idea without wrestling…

David Rawlinson

Aug 20, 2018

Understanding Equivariance

We are exploring the nature of equivariance, a concept that is now closely associated with the capsules network…

Gideon Kowadlo

Jul 24, 2018

Exciting New Directions in ML/AI

Over the last few years, there have been several breakthroughs and exciting new research directions in…

David Rawlinson

Jun 12, 2018

Convolutional Competitive Learning vs. Sparse Autoencoders (2/2)

This is the second part of our comparison between convolutional competitive learning and convolutional or fully-connected sparse autoencoders. To understand our motivation for this comparison, have a look at the first…