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Understanding animal intelligence
Improving machine intelligence
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.
We added replay to a world model architecture for continual RL. We found that a distribution matching replay buffer used in the context of latent world models can successfully prevent catastrophic forgetting with significantly reduced computational overhead.
A bilateral neural network that mimics dual hemispheres in humans, applied to motor control. The bilateral model with specialised hemispheres outperforms the 'non-preferred' hand, and is as good or better than the 'preferred' hand.
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!