The Re-unification of Science
This is the fourth article in a series based on my original work on the theory of self-reproducing machines. In the first article I laid out the theory of self-replicating programs, the previous article dealt with my new conjecture in the P vs. NP problem. In this article I will explain how the theory of self-reproducing machines unifies the fields of computer science, biology, physics, and mathematics.
Self Reproducing Machines in Various Scientific Fields
Let’s briefly review the role that the theory of self reproducing machines plays in the fields of computer science, biology, physics, and mathematics.
In computer science, as we have seen in this series, these types of systems play a very important role in both modern research as well as in the early history of the subject.
In biology its clear that in the human nervous system, the self-replication process of cells is an example of a self reproducing machine. This forms the basis for the re-unification of these 4 fields of science, and provides clues about how to make progress where previously there was no road map.
In physics there are many applications of self reproducing machines, these applications yield a long sequence of results that build on each other which form the basis for many articles which will appear later in this series. The main guiding principle is to mimic the computational power of the human nervous system using self reproducing machines on a macroscopic scale.
In mathematics, as we have seen in the previous article, the theory of self reproducing machines is according to my conjecture, a more general theory of computation which contains turing machines as a special case, and may have applications for the solution of the P vs. NP problem, and an unknown number of other possible applications.
The Role of DNA in Self Reproducing Machines
One of the main results of Von Neumann in the theory of self reproducing machines is that a self reproducing machine must be encoded in some kind of form which facilitates the self-replication process. This provided much of the inspiration for Watson and Crick in the discovery of DNA. The fact that Von Neumann was led to this idea without even knowing DNA exists is remarkable, and demonstrates the incredible power of his approach to thinking about science and creating entirely new fields.
On the one hand, Von Neumann came at the problem of DNA from first principles, and did not even realize the human nervous system is based fundamentally on DNA. After the discovery of DNA by Watson and Crick, a brand new field of biology and microbiology was born. Later, Von Neumann’s work on computers led to the creation of the field of computer science, which also diverged in a completely different direction from the new biology, as well as from the mathematics and physics of the previous generations of scientists.
In fact many of the physicists who worked on the Manhattan Project started working in the exciting new field of biology that the discovery of DNA made possible, while others went over into computer science.
By appreciating the computational power of self reproducing machines, as demonstrated with simple javascript examples of bio-programs, its possible to bring all the pieces back together again in a way that is rather beautiful. It’s fitting that Von Neumann, who invented the fields of computer science and inspired the discovery of DNA which led to the field of modern biology, would also have invented the theory of self reproducing machines, so that everything comes together again at the beginning where it all started.
This is the basis of how the theory of self reproducing machines re-unifies all of science and provides a road map we can follow for continuing to make progress for many generations to come.
Nature, Evolution, and Self Reproduction
The most important aspect of my new results in self reproducing machines is a direct result of studying the biology of the human nervous system. This kind of road map is very helpful!
It suggest a picture that it should be possible to use first principles from the theory of self reproducing machines to understand evolution not as some kind of law of God, but rather as the result of global properties of ensembles of self reproducing machines, and how these types of systems tend to “evolve” over time based on the relationship between the “local encoding” (the DNA) and the global mathematical properties that govern a system of this type.
This would enable us to use first principles to understand human consciousness is ways that was never before possible, in my next article I will explain the outline of how the theory of self reproducing machines leads to a theory of the creation of new intelligent life forms.
tl;dr
Von Neumann started computer science and biology and for a long time 4 different branches of science totally diverged from each other, but he also invented the theory of self reproducing machines which ties everything up back together again in a very pretty way
