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| people:demitri_maestas:project [2017/09/13 03:05] – chucho2 | people:demitri_maestas:project [2017/09/13 04:33] (current) – chucho2 |
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| ==== An Artificial Neuron ==== | ==== 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. |
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| ==== Robustness in Machine Learing ==== | ==== Robustness in Machine Learing ==== |
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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? |
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| | The one that can keep up with any decent human player, because it becomes more intelligent with the more resources it is allotted? |
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| | What is our robust equivalent? |
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| | **How would the MFM //play// tic-tac-toe with a human opponent?** |
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| | We need to start thinking with portals.... |
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| | --- //[[chucho2@unm.edu|Demitri D Maestas]] 2017/09/12 22:27// |
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| Pictures Used: | Pictures Used: |
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| https://www.quora.com/What-are-the-parts-of-the-neuron-and-their-function | https://www.quora.com/What-are-the-parts-of-the-neuron-and-their-function |
| | http://react-tictactoe.stefanwille.com/ |
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