Text-based options for verification purposes on websites and other digital forums are going to be a thing of the past, that too, pretty soon. So, get ready to identify objects like cars, parks, and storefronts form CAPTCHA image grids. CAPTCHA is the abbreviation for Completely Automated Public Turing test to tell Computers and Humans Apart. It is a kind of authentication test that is important to differentiate between humans and bots. However, the presence of so many fake accounts especially on social media platforms like Facebook clearly indicates that this mechanism isn't foolproof.
Academics from UK and China have developed a new machine learning algorithm that can break text-based CAPTCHA systems with less effort, faster, and with higher accuracy than all previous methods. This new algorithm -developed by scientists from Lancaster University (UK), Northwest University (China), and Peking University (China)- is based on the concept of GAN, which stands for "Generative Adversarial Network." GANs are a special class of artificial intelligence algorithms that are useful in scenarios where the algorithm doesn't have access to large quantities of training data. Classing machine learning algorithms usually require millions of data points to train the algorithm in performing a task with the desired degree of accuracy. A GAN algorithm has the advantage that it can work with a much smaller batch of initial data points.
Google is doing away with the time consuming tests on websites that ask you to verify you're not a robot. Captcha codes - which ask you to identify words or pictures - are designed to tell the difference between man and machine. The launch of Google's recaptcha v3 means users will no longer need to type in codes or tick boxes as the system will pick up suspicious traffic by itself. Google is doing away with the time consuming tests on websites that ask you to verify that you are a real person. Captcha (Completely Automated Public Turing test to tell Computers and Humans Apart) has become the standard term for simple human-or-robot tests.
Researchers have created an artificial intelligence system that can solve Captcha challenges, rendering them "broken" and "ineffective". The security check is designed to block potentially harmful bots from websites, and does so by presenting puzzles that are supposed to be easy for people to solve, but very difficult for computers. They've been around since the late 1990s and have long been considered extremely annoying, but experts believe it could soon be time for them to be replaced. The researchers, from a company called Vicarious, managed to build an AI system – called the Recursive Cortical Network (RCN) – that approaches Captcha challenges in much the same way that a human would. "With one model, we achieve an accuracy rate of 66.6% on reCAPTCHAs, 64.4% on BotDetect, 57.4% on Yahoo, and 57.1% on PayPal, all significantly above the 1% rate at which CAPTCHAs are considered ineffective," they wrote in a blog post.
Artificial intelligence software can beat the world's most widely used test of a machine's ability to act human, Google's reCAPTCHA, by copying how human vision works, a new study finds. These new findings suggest the need for more robust automated human-checking techniques, and could help improve computer perception for robotics tasks, scientists add. The founder of modern computing, Alan Turing, conceived of the Turing test, the most famous version of which asks if one could devise a machine capable of mimicking a human well enough in a conversation over text to be indistinguishable from human. In doing so, Turing helped give rise to the field of artificial intelligence. The most commonly used Turing test is the CAPTCHA, an acronym for "Completely Automated Public Turing test to tell Computers and Humans Apart."