Row 15822

Row ID: 15822 | Dataset Entry | Axioma AXP Content Repository

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I AI-wrote a python script to perform a 2-input XOR. It worked, insofar as it trained to a "low loss" (sufficient for classification purposes) although Not Zero Loss, even with various hyperparameters in the hidden level(s). MLP Theory states that XOR cannot be implemented without non-linear "activation" such as RELU. I used Sigmoid as Activation for my 2-input XORs, and all the models worked for classification. I am not interested in "quantum" computers which are not logical and not linear. Your resort to "you have to learn quantum computing to transcend the limitations of Math and Binary Computations on Planet Earth" is not acceptable proof of your claims. Again, I ask you to provide a working Python Script (not dependent upon "quantum" theory) demonstrating your claims, or retract them. I will not accept on face value an assertion that "That’s a linear implementation of XOR."

FieldValue
text I AI-wrote a python script to perform a 2-input XOR. It worked, insofar as it trained to a "low loss" (sufficient for classification purposes) although Not Zero Loss, even with various hyperparameters in the hidden level(s). MLP Theory states that XOR cannot be implemented without non-linear "activation" such as RELU. I used Sigmoid as Activation for my 2-input XORs, and all the models worked for classification. I am not interested in "quantum" computers which are not logical and not linear.…
label r/machinelearning
dataType comment
communityName r/MachineLearning
datetime 2024-05-20
username_encoded Z0FBQUFBQm5Lakw4V0hiSGRMRzJCOUFDSzBGYWxWV1VmZ3NmeHJOeEdyMjRMNG1IVEpSWXA4aENfQmZZNEpHdDBJMWZOcmtCa2Z1bEg0N25tV3VzYzR5bUpQTXNyUTl6VkE9PQ==
url_encoded Z0FBQUFBQm5Lak9MYWg3RTFENzdKazNuZlQ2QWUyN1VPX21QRHB5WW5RbG9PS3lWdkhXV2dwcDJ2VVh5MDh5cnF5VWVxWjN1Q25ZeUtTOHJBWXpvVFN4bnNQNW5TUTRhenNUS0duS0hZcFlRVXd1MUJxaHd1aVBsbEdTWmY5dGg2TnJqUjd0YWZGcWFkWEJGX3ZJd2pGUVFuM09zTUlRQTR3WkdyWG16S2tNUk5odGJlWkhPdXZqSkYtQVVWSGxzWlo2Ml9LUF8ySUhDRXZPVlRKQVBYV3l0N0xwMmdiWXR3QkdaZXpCN0R4TGNOdlNEZlVjNVM2QT0=

Raw Record

{
  "text": "I AI-wrote a python script to perform a 2-input XOR.  It worked, insofar as it trained to a \"low loss\" (sufficient for classification purposes) although Not Zero Loss, even with various hyperparameters in the hidden level(s).  MLP Theory states that XOR cannot be implemented without non-linear \"activation\" such as RELU.  I used Sigmoid as Activation for my 2-input XORs, and all the models worked for classification.  I am not interested in \"quantum\" computers which are not logical and not linear.  Your resort to \"you have to learn quantum computing to transcend the limitations of Math and Binary Computations on Planet Earth\" is not acceptable proof of your claims.   Again, I ask you to provide a working Python Script (not dependent upon \"quantum\" theory) demonstrating your claims, or retract them.   I will not accept on face value an assertion that \"That’s a linear implementation of XOR.\"",
  "label": "r/machinelearning",
  "dataType": "comment",
  "communityName": "r/MachineLearning",
  "datetime": "2024-05-20",
  "username_encoded": "Z0FBQUFBQm5Lakw4V0hiSGRMRzJCOUFDSzBGYWxWV1VmZ3NmeHJOeEdyMjRMNG1IVEpSWXA4aENfQmZZNEpHdDBJMWZOcmtCa2Z1bEg0N25tV3VzYzR5bUpQTXNyUTl6VkE9PQ==",
  "url_encoded": "Z0FBQUFBQm5Lak9MYWg3RTFENzdKazNuZlQ2QWUyN1VPX21QRHB5WW5RbG9PS3lWdkhXV2dwcDJ2VVh5MDh5cnF5VWVxWjN1Q25ZeUtTOHJBWXpvVFN4bnNQNW5TUTRhenNUS0duS0hZcFlRVXd1MUJxaHd1aVBsbEdTWmY5dGg2TnJqUjd0YWZGcWFkWEJGX3ZJd2pGUVFuM09zTUlRQTR3WkdyWG16S2tNUk5odGJlWkhPdXZqSkYtQVVWSGxzWlo2Ml9LUF8ySUhDRXZPVlRKQVBYV3l0N0xwMmdiWXR3QkdaZXpCN0R4TGNOdlNEZlVjNVM2QT0="
}
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