While true Artificial General Intelligence is still far away, in the short term we can augment machine learning with ‘general’ capabilities and features. Unlike most AI/ML, general intelligence should not require tailoring to specific problems. Instead, it learns continuously from interactions with a world, developing an internal representation by exploring and exploiting what it already knows. Algorithms with general intelligence features are applicable to a wider range of problems and tasks.


Sep 3rd 2018: New RFRs published on Bicameral Machine Learning models and self organising architectures.

Jun 14th 2018: We are thrilled to announce that we have begun a collaboration with Elkhonon Goldberg of Luria Neuroscience Institute, and that he is now an Advisor to Project AGI.

Jun 6th 2018: Published ‘Requests for Research‘ in conjunction with WBAI

Apr 18th 2018: Released ArXiv paper “Sparse Unsupervised Capsules Generalize Better”