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The Forward-Forward Algorithm🤖
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. 
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:)
I must say reading&Implementing a godfather paper feels quite fulfilling:)
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Thank you Prof. Geoffrey Hinton.
Thank you Prof. Geoffrey Hinton.
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Code: 
Code: 
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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
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