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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. Now, though, new research claims that locally run bots using specially trained image-recognition models can match human-level performance in this style of CAPTCHA, achieving a 100 percent success rate despite being decidedly not human.

ETH Zurich PhD student Andreas Plesner and his colleagues' new research, available as a pre-print paper, 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 in favor of an "invisible" reCAPTCHA v3 that analyzes user interactions rather than offering an explicit challenge.

Despite this, the older reCAPTCHA v2 is still used by millions of websites. And even sites that use the updated reCAPTCHA v3 will sometimes use reCAPTCHA v2 as a fallback when the updated system gives a user a low "human" confidence rating.

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[-] Guest_User@lemmy.world 1 points 2 months ago

Finitebanjo is right. Yes they are used to fight spam and bots but they way they do it us is picked intentionally to train ai.

https://medium.com/@yennhi95zz/how-google-trains-ai-with-your-help-through-captcha-876cb4eb4d01

Also from the Wikipedia article "Google profits from reCAPTCHA users as free workers to improve its AI research." https://en.m.wikipedia.org/wiki/ReCAPTCHA

[-] aidan@lemmy.world 0 points 2 months ago

they do it us is picked intentionally to train ai.

Yes like I said, the challenges were picked to be useful. But some form of challenge would've been chosen regardless.

this post was submitted on 27 Sep 2024
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