Meta has recently launched a new neural watermark system called VideoSeal, designed to help identify AI-generated videos, even if the videos have been edited, it can effectively trace their origin. This watermark is invisible to viewers but can be verified through detection methods to confirm the video's authenticity. Meta has released the entire system as open source software under the MIT license, including the VideoSeal watermark model, research papers, and training and inference code.

OpenAI faces a challenge: how to address the issue of students using ChatGPT to cheat? Despite developing a 'watermark' technology capable of detecting ChatGPT-generated content with 99.9% accuracy, the tool has not been publicly released due to widespread concerns about student use of AI for cheating. Internal discussions have continued for nearly two years, with key factors hindering the release including the balance between maintaining transparency commitments and user loyalty, as well as worries about negative impacts on non-native English speakers. There is an urgent demand in the education sector, with concerns about the potential consequences of AI cheating.

There has been an internal discussion at OpenAI regarding the introduction of watermark technology to tag text generated by ChatGPT and prevent student plagiarism. The watermark technology generates detectable patterns by adjusting the words and phrases predicted by the model, aimed at assisting teachers in detecting assignment plagiarism without affecting text quality. Although the technology boasts high accuracy and is resistant to simple rewrites, the use of other models to rewrite could bypass the watermark, raising concerns. Implementing watermarks may cause some users to feel stigmatized, potentially leading to reduced usage.