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Evolution has done so much of the dirty work for us; 3.5 billion years of attempts at creating robust living systems that work on a scale that begins inside of a membrane in a single cell and stretches out to the stratosphere. An industry-based data storage model in our current machines hold no similarity to the trials and tribulations, which is odd considering the fact that Mother Nature has 3.5 billion years of design under her belt, where as we have only had a Von Neumann machine for about 80 years. We need to be thinking about robust storage of information not in memory addresses based on a data structure, but instead, contained within the axons of artificial neurons that make mimic the design structure of the most robust organic hard drive we have; The human brain.

We've all seen what machine learning is capable of and the things it can help us do. Just take a look at this awesome machine learning example that Youtuber “SethBling” has designed to play the first level of Super Mario World: qv6UVOQ0F44

Machine Learning is an exciting field in computer science, but what is the robust first approach to machine learning? How can we use the same principals in the MFM to accomplish the same results? Is it even possible to accomplish machine learning, or do we need to think of a new form of computation for robust results?

Pictures Used: https://www.quora.com/What-are-the-parts-of-the-neuron-and-their-function