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by brindidrip
1290 days ago
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We need to start developing software to detect AI responses. To detect a response generated by ChatGPT, we could first analyze the content of the response to see if it contains any unnatural or repetitive language. We could also check the formatting of the response to see if it follows the typical conventions used by human responders on the platform. Additionally, we could check for any unusual patterns in the timestamps of the response, as AI-generated responses may be posted more quickly or regularly than responses written by humans. Finally, we could also use machine learning algorithms to train a model to identify responses generated by ChatGPT based on these and other characteristics. Quick, someone ask ChatGPT to generate the stubs. |
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whatever your idea (i skimmmed cuz) the discriminator will find it and have the generator apply it to the next generation.
>The core idea of a GAN is based on the "indirect" training through the discriminator, another neural network that can tell how "realistic" the input seems, which itself is also being updated dynamically.[5] This means that the generator is not trained to minimize the distance to a specific image, but rather to fool the discriminator. This enables the model to learn in an unsupervised manner.
https://en.wikipedia.org/wiki/Generative_adversarial_network