5th WBAI Hackathon
The Whole Brain Architecture Initiative (WBAI) aims to foster research into architectural approaches to general intelligence. They have held a series of events – the… Read More »5th WBAI Hackathon
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… Read More »AHA! an ‘Artificial Hippocampal Algorithm’ for Episodic Machine Learning
Hippocampus and the Episodic confusion (for machine learning)
The standard definitions of Episodic and Semantic Memory hide some important subtleties that impact the development of Machine Learning algorithms for AI (particularly those building Episodic Learning capability). This article explores this issue and provides a context for upcoming articles work to take us a step closer to 'animal-like' 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… Read More »Biologically-plausible learning rules for artificial neural networks
Learning partially-observable higher-order sequences using local and immediate credit assignment
One of our key projects is a memory system that can learn to associate distant cause & effect while only using local, immediate & unsupervised… Read More »Learning partially-observable higher-order sequences using local and immediate credit assignment
Cerebral networks for conscious access and decision making
Originally published in March 2019 in an electronic journal in Japanese Introduction The purpose of this essay is to survey the relationship between decision making… Read More »Cerebral networks for conscious access and decision making
Learning distant cause and effect using only local and immediate credit assignment
We’ve uploaded a new paper to arXiv presenting our algorithm for biologically-plausible learning of distant cause & effect using only local and immediate credit assignment.… Read More »Learning distant cause and effect using only local and immediate credit assignment
AI is already harming us – but not the way you think
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… Read More »AI is already harming us – but not the way you think
Optimization using Adam on Sparse Tensors
Adaptive optimization methods, such as Adam and Adagrad, maintain some statistics over time about the variables and gradients (e.g. moments) which affect the learning rate.… Read More »Optimization using Adam on Sparse Tensors
Predictive Capsules Networks – Research update
We recently talked about Capsules networks and equivariances. NB: If you’re not familiar with Capsules networks, read this first. Our primary objective with Capsules networks is… Read More »Predictive Capsules Networks – Research update