We are very happy to announce that we’ve been awarded...
Read MoreCerenaut
Understanding animal intelligence
Improving machine intelligence
Research Strategy
We aim to discover new learning rules, architectures and representations from neuroscience and psychology to benefit AI and contribute insights back to these fields.
We are interested in the interactions of brain regions with complementary functions and timescales. For example, left and right hemispheres and slow and fast learning between neocortex and hippocampus.
Our focus is computational descriptions that are implementable.
FEATURED RESEARCH
Deep learning in a bilateral brain with hemispheric specialization
We created an architecture with hemispheric specialization to better understand the brain and uncover new principles for AI
Continual few-shot learning with Hippocampal-inspired replay
We found that replay improves continual few-shot learning significantly, for learning classes as well as specific instances
High-order partially-observable sequences
Recurrent Sparse Memory (RSM) is an unsupervised method for simultaneously learning spatial and sequential structure in partially-observable high Markov order data streams
Fast (One-shot) episodic learning
Our Artificial Hippocampus Algorithm (AHA) can learn to generalize classes from a single instance, while still discriminating between instances of the same class - all without any provided labels
NEWS
- Feb 2023: We have 2 new Monash Uni masters students starting. 1 on bilateral brain projects, and 1 on hippocampal inspired RL
- Sep 2022: Chandramouli (intern) begins a new chapter as a Masters student at USCD. Congratulations and good luck!
- Sep 2022: We complete two long awaited pre-prints: Deep Learning with a Bilateral (2 hemispheres) architecture, and continual few-shot learning
- Jul 2022: Yanfeng begins his Masters, extending the work on Bilateral Deep Learning
RECENT ARTICLES
Continual Few-Shot Learning with Hippocampal Replay
In continual learning, the neural network learns from a stream...
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Video Prediction using Recurrent Sparse Memory
We recently presented 2 papers at the International Joint Conference...
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One-shot learning for the long term: consolidation with an artificial hippocampal algorithm
We were really excited to present a couple of papers...
Read MoreFeatured Articles
Towards Biologically Inspired Executive Control
Executive Control is core to what most people recognise as...
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Research Roadmap: 2020-2021
We’ve just undertaken a review and refresh of our research...
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Sparse Unsupervised Capsules Generalize Better
We’ve just uploaded a spin-off research paper to arXiv titled...
Read MoreHow to build a General Intelligence: What we think we already know
Authors: D Rawlinson and G Kowadlo This is the first...
Read MoreAbout Us
Cerenaut (formerly ProjectAGI) is an independent research group that undertakes fundamental research at the intersection of AI, Neuroscience and Psychology. We’re based in Australia.
Our name reflects humanity’s journey towards higher cognition and intelligence: cere = of the brain, naut = journey
We co-supervise student research projects and collaborate with researchers on topics of shared interest. If you’d like collaborate, get in touch!