The Forward-Forward Algorithm🤖
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The Forward-Forward Algorithm🤖
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FFA replaces the forward and backward passes in backpropagtion  with two forward passes - one with positive (real) data and another with negative data. Each layer has its objective function - to increase or decrease a “goodness" metric. The positive pass uses real data and adjusts weights to increase “goodness” in every hidden layer. The negative pass does the opposite. 
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FFA replaces the forward and backward passes in backpropagtion  with two forward passes - one with positive (real) data and another with negative data. Each layer has its objective function - to increase or decrease a “goodness" metric. The positive pass uses real data and adjusts weights to increase “goodness” in every hidden layer. The negative pass does the opposite. 
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I must say reading&Implementing a godfather paper feels quite fulfilling:)
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I must say reading&Implementing a godfather paper feels quite fulfilling:)
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Thank you Prof. Geoffrey Hinton.
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Thank you Prof. Geoffrey Hinton.
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Code: 
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Code: 
https://github.com/Jaykef/ai-algorithms/blob/main/mnist_the_forward_forward_algorithm.ipynb
https://github.com/Jaykef/ai-algorithms/blob/main/mnist_the_forward_forward_algorithm.ipynb
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The Forward-Forward Algorithm🤖

FFA replaces the forward and backward passes in backpropagtion  with two forward passes - one with positive (real) data and another with negative data. Each layer has its objective function - to increase or decrease a “goodness" metric. The positive pass uses real data and adjusts weights to increase “goodness” in every hidden layer. The negative pass does the opposite. 

I must say reading&Implementing a godfather paper feels quite fulfilling:)
Thank you Prof. Geoffrey Hinton.

Code: https://github.com/Jaykef/ai-algorithms/blob/main/mnist_the_forward_forward_algorithm.ipynb
👀
John6666
👍
GigaBoy