Most modern neural networks are trained using backpropagation, but it is not the only way they can learn. Within our AGI research program, we are investigating how predictive coding's architectural flexibility and local learning rules could help mitigate catastrophic forgetting, support decentralized training, and enable more energy-efficient computation. On Tuesday, October 13, at 5 PM UTC, our host, Haley Lowy, will be joined by Matt Iklé, Matthew Behrend, and Guilherme Lamacie to discuss: • The scientific motivations behind our predictive coding research, the approaches under investigation, and their potential contribution to AGI. • The relationship between predictive coding and backpropagation, and how different learning mechanisms could support neural-symbolic architectures. • Open research questions, priorities for further experimentation, and opportunities to contribute through FabricPC. Watch live on the ASI Alliance’s X account or set a reminder on LinkedIn: