Gideon Kowadlo

DSI Grant

Grant – Continual Few-Shot Learning

We are very happy to announce that we’ve been awarded an Artificial Intelligence for Decision Making Initiative grant from Defence Science Institute on Effective updating of deep learning models with limited new data. More specifically, the grant is for the Continual Few-Shot Learning project that we blogged about recently.

One-shot learning for the long term: consolidation with an artificial hippocampal algorithm

We were really excited to present a couple of papers recently at IJCNN, the International Joint Conference on Neural Networks. One of those papers was an extension to the work that we previously published on AHA, Artificial Hippocampal Algorithm based on Complementary Learning Systems by O’Reilly and McClelland (see that… Read More »One-shot learning for the long term: consolidation with an artificial hippocampal algorithm
PBWM Unit

Towards Biologically Inspired Executive Control

Executive Control is core to what most people recognise as true intelligence. For example, the ability to attend to relevant cues and maintain task dependent information whilst ignoring distracting details and taking appropriate actions.  Working Memory (WM) is a core component of Executive Control. “Working memory is a short-term repository… Read More »Towards Biologically Inspired Executive Control
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
Memory

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

Exciting New Directions in ML/AI

Over the last few years, there have been several breakthroughs and exciting new research directions in Reinforcement Learning, Hippocampus Inspired Architectures, Attention and Few-Shot Learning. There has been a move towards multi-component, heterogeneous, stateful architectures, many guided by ideas from cognitive sciences. Google DeepMind and Google Brain are leading the… Read More »Exciting New Directions in ML/AI

Datasets for Computer Vision

The dataset is an integral part of an ML engineer’s toolkit. We recently compiled useful information about a range of these well known datasets. It’s all in one place, and hopefully useful to others as well.