Core Viewpoint - A new watermark removal technology called UnMarker can effectively remove almost all AI image watermarks in under five minutes, rendering existing watermark technologies like Google's HiDDeN and SynthID less reliable [1][3]. Group 1: Technology Overview - UnMarker is open-source on GitHub and can be deployed locally using consumer-grade graphics cards, significantly lowering the barrier for users [3][11]. - AI image watermarks differ from visible watermarks; they are embedded in the image's spectral features, specifically in the magnitude of the frequency spectrum [4][6]. - UnMarker targets the frequency spectrum rather than pixel values, allowing it to disrupt watermarks across various types, achieving removal rates between 57% and 100% depending on the watermark method used [9][10]. Group 2: Performance Metrics - UnMarker can completely remove HiDDeN and Yu2 watermarks, and it successfully removes 79% of watermarks from Google's SynthID [10]. - For newer watermark technologies like StegaStamp and Tree-Ring Watermarks, UnMarker can still remove about 60% of the watermarks [10]. - While effective, UnMarker may cause slight alterations to the images during the watermark removal process, which can be mitigated by cropping the images [10]. Group 3: Industry Implications - A recent study by Microsoft indicates that the average success rate for identifying AI-generated images is only 62%, highlighting the challenges in distinguishing between real and AI-generated content [13]. - The emergence of technologies like UnMarker poses a challenge to existing watermarking solutions, which were expected to provide a reliable means of verifying AI-generated images [13].