We offer an education model option that is fine-tuned for student content. Our education model has been trained with data that includes more student work than our regular model, increasing the accuracy of detecting AI for educational purposes. This model is well suited for differentiating ESL and AI-written text as well.

This part of our model checks if this text has been found to exist in text and internet archives. In contrast to other AI-detection services, we ensure that commonly used texts are not misclassified.

First, we developed and apply a ‘burstiness’ check to analyze how similar the text is to AI patterns of writing. A human written document will have changes in style and tone throughout the text, whereas AI content remains similar throughout the document.

We like to call this new component of our model GPTZero Shield, essentially a layer that defends against other tools looking to exploit AI detectors. We maintain a database of the most common methods to ‘by-pass’ AI detection, such as homoglyph and spacing attacks.

GPTZero X is a sentence-by-sentence highlighting and classification model we developed in March, as one of the first models that allows mixed-text highlighting. This model analyzes each sentence in the text in the context of the whole document and determines the probability that each sentence was created by AI.

Our perplexity test reverse engineers the generative AI model. We’ve developed an AI model similar to ChatGPT. After each word in the text, our AI model develops suggestions of what word is coming next. It checks if our suggestions match what is actually there in the text.