1. A method for sorting data into data gravity wells on a data gravity wells membrane, the method comprising: converting, by a hashing logic, raw data into a first logical address and first payload data, wherein the first logical address describes metadata about the first payload data; comparing, by a hardware exclusive OR (XOR) unit, the first logical address to a second logical address to derive a Hamming distance between the first and second logical addresses, wherein the second logical address is for a second payload data; creating, by a hardware data vector generator, a data vector for the second payload data, wherein the data vector comprises the Hamming distance between the first and second logical addresses; sorting, by a hardware data vector sorter, data vectors into specific data gravity wells on a data gravity wells membrane according to the Hamming distance stored in the data vector, wherein the data gravity wells membrane is a mathematical framework that 1) performs to provide a virtual environment in which multiple context-based data gravity wells exist; 2) populates the multiple context-based data gravity wells with synthetic context-based objects; and 3) performs to display the multiple context-based data gravity wells on a display; applying, by one or more processors, a context object to a non-contextual data object, wherein the non-contextual data object is a component of the raw data, wherein the non-contextual data object ambiguously relates to multiple subject-matters, and wherein the context object provides a context that identifies a specific subject-matter, from the multiple subject-matters, of the non-contextual data object; incorporating, by one or more processors, the context object and the non-contextual data object into the data vector for the second payload data; and sorting, by the hardware data vector sorter, the second payload data into specific data gravity wells on the data gravity wells membrane according to the context objects and the non-contextual data objects.