https://arstechnica.com/ai/2024/09/ai-defeats-traffic-image-captcha-in-another-triumph-of-machine-over-man/ [arstechnica.com]
Anyone who has been surfing the web for a while is probably used to clicking through a CAPTCHA grid of street images, identifying everyday objects to prove that they're a human and not an automated bot.
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ETH Zurich PhD student Andreas Plesner and his colleagues' new research, available as a pre-print paper [arxiv.org], focuses on Google's ReCAPTCHA v2, which challenges users to identify which street images in a grid contain items like bicycles, crosswalks, mountains, stairs, or traffic lights. Google began phasing that system out years ago [arstechnica.com] in favor of an "invisible" reCAPTCHA v3 that analyzes user interactions rather than offering an explicit challenge.
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To craft a bot that could beat reCAPTCHA v2, the researchers used a fine-tuned version of the open source YOLO ("You Only Look Once") object-recognition model [v7labs.com], which long-time readers may remember has also been used in video game cheat bots [arstechnica.com].