INSA’s core substrate is an ultra high-performance vector graph database which encodes all of the system’s knowledge and skills. This knowledge graph is custom designed for this architecture and is 1000 times faster than any commercially available graph database.Vector node structures in the graph represent perceptual features, complete percepts, concepts, as well as symbols. They also encode context relationships, sequences, hierarchies, and other temporal and spatial constructs, both static and dynamic. This design lends itself well to importing and integrating symbolic and logical data such as ontologies, databases, and unstructured data in real-time. Furthermore, the use of vectors allows for fuzzy pattern matching to overcome brittleness.
Source: INSA: Integrated Neuro-Symbolic Architecture Aigo.ai – The Company with a Direct Path to AGI
