Figure 1.

Mapping different modalities of information to the same space of long binary vectors allows knowledge of the world to coexist and combine together symbolically as well. A dog may be seen and heard, recognized by two separate data-driven learning systems. The output of each, representing the presence of a dog, is mapped to a binary vector representing the current data. The closer this mapping is to a learned representation of all dogs, the more likely it is to be a dog. In the same space, linguistic knowledge of dogs can also be mapped to symbolic representations. Combining all three modalities by purely hyperdimensional computations gives a single symbolic representation of everything pertaining to the concept of dogs.