The continued motivation of this work is to understand the role of information in our universe. The author believes there are two levels to nature 1) an information level 2) a correlated energy level where organisms evolve. This belief is based on data that leads to an information-based proton mass model. This model helps us understand quantum mechanics. It describes the probability waves that position protons in time and space. Duplication creates the huge universe around us described by a straight-line expansion model. Artificial intelligence technology mimics some aspects of brain function and is causing some to question reality. The proton model consists of components that each have an information/energy interface. It is proposed that our viewing point is at the interface. The model consists of AI-like layers that multiply and divide probabilities. The probabilities can be interpreted as "language" that means the proton exists within specific dimensions. This agrees with the Copenhagen interpretation of quantum mechanics. Likewise, information layers (base pairs along the chain) associated with DNA protons contain probabilities that represent traits of plants and animals. The information level of nature consists of probability waves. They are the basis of memory, thought and reality. Nature is amazing. How do flowers and babies develop before our eyes? When a flatworm is cut in half, why does it generate two flatworms? Where is the frog image stored when nature decides that a tadpole must now form a frog? Nature’s process is almost perfect and we say, "well it’s their DNA." Right, but exactly how does DNA store plants and animal images and perform the incredible task of reproduction? This paper answers the question by showing how parent probability ratios are stored and remembered to accurately position cells for the next generation.