It is certainly possible to build an AI that is capable of recognizing the writing style of another AI, such as ChatGPT. This kind of AI is often referred to as

It is certainly possible to build an AI that is capable of recognizing the writing style of another AI, such as ChatGPT. This kind of AI is often referred to as a "style transfer" or "style transfer model." To build a ChatGPT detector, you would first need to collect a large amount of text that was generated by ChatGPT. This could be done by providing a variety of different prompts to the ChatGPT model and collecting the responses. Next, you would need to train a machine learning model on this text. The most common approach for this kind of task is to use a deep learning model, such as a recurrent neural network (RNN). The RNN would be trained to take in a piece of text and predict whether it was written by ChatGPT or not. As for the accuracy of such a model, it would depend on a variety of factors, including the quality and quantity of the training data, the specific model architecture and hyperparameters used, and the skill of the person training the model. With a large and diverse training dataset, and appropriate model design and training, it is likely that a ChatGPT detector could achieve relatively high accuracy.