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 By Ben Teoh

Research Roadmap: 2020-2021

We’ve just undertaken a review and refresh of our research roadmap! The topics and approach we will take in the coming year are all laid out in a new page: Research Roadmap Our primary topics for the coming year include: Continual Few-Shot Learning (CFSL) via our Episodic memory system Using… Read More »Research Roadmap: 2020-2021

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 Hackathons – that encourage and support the development of new models which provide working solutions to questions about the possible architecture of general intelligence in… 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 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

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
Experiment Setup Overview

Experiment Infrastructure at Project AGI

It’s such a joy to be able to test an idea, go straight to the idea without wrestling with the tools. We recently developed an experimental setup which, so far, looks like it will do just that. I’m excited about it and hope it can help you too, so here it is. We’ll go through the why we created another framework, and how each module in the experiment setup works.

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
TensorFlow Eager Execution

Eagerly awaiting TensorFlow Eager Execution?

Eager Execution is an imperative, object oriented and more Pythonic way of using TensorFlow. It is a flexible machine learning platform for research and experimentation where operations are immediately evaluated and return concrete values, instead of constructing a computational graph that is executed later.