Humans have the extraordinary ability to learn continually from experience. Not only can we apply previously learned knowledge and skills to new situations, we can also use these as the foundation for later learning. One of the grand goals of AI is building an artificial “Continual Learning” agent that constructs a sophisticated understanding of the world from its own experience through the autonomous incremental development of ever more complex skills and knowledge. The Continual AI community, on the path of becoming an official non-profit research organization, aims at connecting people and and working better together on a topic we consider fundamental for the future of AI. We are currently working on three completely open-source collaborative projects: • Continual AI Website/Wiki: a central Hub of information for Continual Learning and AI. • Continual AI Colab: a number of notebooks and scripts (for demo, showcasing & tutorials) which can be directly imported in Google Colab and are related to Continual Learning. • Continual AI Avalanche: a comprehensive framework for Continual Learning Research. It aims at unifying a set of popular CL baselines, environments and benchmarks to help algorithm prototyping and experiment, with with flexibility, reproducibility, efficiency and maintainability in mind. Avalanche will be based on three main modules: datasets/environments, CL baselines and evaluation metrics/protocols. We are always happy to add new members and get some help with our projects or simply discuss about about CL, so join us today on slack: https://continualai.herokuapp.com/