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--- people:demitri_maestas:project [2017/09/13 03:04] – chucho2
+++ people:demitri_maestas:project [2017/09/13 04:33] (current) – chucho2
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 ==== An Artificial Neuron ====
-Evolution has done so much of the dirty work for us; 3.5 billion years of attempts at creating robust living systems {{ :people:demitri_maestas:project:assets:neuron.jpg?direct&100|}}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.
+Evolution has done so much of the dirty work for us; 3.5 billion years of attempts at creating robust living systems {{ :people:demitri_maestas:project:assets:neuron.jpg?direct&100|}}that work on a scale that begins inside of a membrane in a single cell and stretches out to the stratosphere. The industry-based data storage model in our current machines holds no similarity to the trials and tribulations that these living systems have endured, 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.
 ==== Robustness in Machine Learing ====
-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:
+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:{{ youtube>qv6UVOQ0F44?large }}
- {{ youtube>qv6UVOQ0F44?large }}
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+==== Common Algorithms as a Process ====
+Machine learning is great at patterns. The Machine Learning algorithms we use today can become the best players in{{ :people:demitri_maestas:project:assets:tic.png?nolink&100|}} the world at beating Sonic The Hedgehog games, recognizing an "a" amidst 200 different styles of calligraphy, and solving complex math problems.
+But what about the Min-Max paradigm that is implemented to solve tic-tac-toe?
+The one that can keep up with any decent human player, because it becomes more intelligent with the more resources it is allotted?
+What is our robust equivalent?
+**How would the MFM //play// tic-tac-toe with a human opponent?**
+We need to start thinking with portals....
+----
+ --- //[[chucho2@unm.edu|Demitri D Maestas]] 2017/09/12 22:27//
 Pictures Used:
 https://www.quora.com/What-are-the-parts-of-the-neuron-and-their-function
+http://react-tictactoe.stefanwille.com/