Row 42976

Row ID: 42976 | Dataset Entry | Axioma AXP Content Repository

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“Why Large Language Models Sometimes Provide Different Answers

While large language models can be incredibly accurate, they can also provide different answers to the same questions. This is because the models are probabilistic, meaning that they generate responses based on a probability distribution. When a user inputs a prompt, the model generates multiple possible responses and ranks them by likelihood. This means that even small changes in the prompt can lead to different responses.

In addition, large language models can also be influenced by biases in the training data. For example, if the model is trained on text that contains biased language or stereotypes, it may generate responses that reflect these biases.”

Additionally OpenAI is probably throwing “noise” into the system in order to generate “NEW” responses

Just like old school games auto generated game levels from random number pulled from the Clock

FieldValue
text “Why Large Language Models Sometimes Provide Different Answers While large language models can be incredibly accurate, they can also provide different answers to the same questions. This is because the models are probabilistic, meaning that they generate responses based on a probability distribution. When a user inputs a prompt, the model generates multiple possible responses and ranks them by likelihood. This means that even small changes in the prompt can lead to different responses. In addi…
label r/artificial
dataType comment
communityName r/artificial
datetime 2024-05-22
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Raw Record

{
  "text": "“Why Large Language Models Sometimes Provide Different Answers\n\nWhile large language models can be incredibly accurate, they can also provide different answers to the same questions. This is because the models are probabilistic, meaning that they generate responses based on a probability distribution. When a user inputs a prompt, the model generates multiple possible responses and ranks them by likelihood. This means that even small changes in the prompt can lead to different responses.\n\nIn addition, large language models can also be influenced by biases in the training data. For example, if the model is trained on text that contains biased language or stereotypes, it may generate responses that reflect these biases.”\n\nAdditionally OpenAI is probably throwing “noise” into the system in order to generate “NEW” responses \n\nJust like old school games auto generated game levels from random number pulled from the Clock",
  "label": "r/artificial",
  "dataType": "comment",
  "communityName": "r/artificial",
  "datetime": "2024-05-22",
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