Traditionally, computers store data using an address system. Upon complete presentation of the address, a computer can retrieve the desired data. In contrast, neural networks (brain-inspired computing) are able to retrieve complete data from an incomplete presentation of the data itself. This is similar to how the brain works, since if you are presented with an incomplete data point such as "To be or not ----," "Live and let ----," etc., you will be able to completely retrieve the data from your memory. One of the first examples of this principle being used in computers comes from Hopfield, where a system of basic "neurons" with little structure was able to develop emergent memories over time. This example is a useful model for biological memory and computation, "*The bridge between simple circuits and the complex computational properties of higher nervous systems may be the spontaneous emergence of new computational capabilities from the collective behavior of large numbers of simple processing elements.*"[^1] [^1]: [Neural networks and physical systems with emergent collective computational abilities](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC346238/pdf/pnas00447-0135.pdf)