Quantcast

Google Reveals New Program That Can Solve reCAPTCHAs

April 17, 2014
Image Caption: House numbers are a type of reCAPTCHA that Google's new algorithm can read. Credit: Thinkstock.com

Brett Smith for redOrbit.com – Your Universe Online

Ever get frustrated trying to determine what the heck a reCAPTCHA says just so you can post to a comment section of a message board?

Well, a newly-developed computerized vision system from Google has been able to solve distorted-text reCAPTCHAs with 99 percent accuracy – a development which could make the bot-sniffing security measure obsolete in its current form.

In a blog post on the technology, Google said its new vision system will also make determining addresses for its Google Maps and Street View much easier.

“Translating a street address to an exact location on a map is harder than it seems,” Vinay Shet, product manager in Google’s reCAPTCHA, wrote in the post. “To take on this challenge and make Google Maps even more useful, we’ve been working on a new system to help locate addresses even more accurately.”

According to the Google team’s report at the International Conference on Learning Representations (ICLR), the new system is able to pick up house numbers based in Street View with 90 percent accuracy.

For those who might be alarmed by the computerized system’s accuracy rate in solving reCAPTCHAs, the search giant made assurances that “reCAPTCHA is more secure today than ever before” due to the recent reduction in dependence on distorted text.

“This has also allowed us to simplify both our text CAPTCHAs as well as our audio CAPTCHAs, so that getting through this security measure is easy for humans, but still keeps websites protected,” Shet wrote.

The days of a visual text confirmation may be coming to an end as a start-up company called Vicarious announced in October that it had developed software capable of reliably solving both CAPTCHAs and reCAPTCHAs – at a rate of around 90 percent.

“Recent AI (artificial intelligence) systems like IBM’s Watson and deep neural networks rely on brute force: connecting massive computing power to massive datasets,” said Vicarious co-founder D. Scott Phoenix. “This is the first time this distinctively human act of perception has been achieved, and it uses relatively minuscule amounts of data and computing power. The Vicarious algorithms achieve a level of effectiveness and efficiency much closer to actual human brains.”

“Understanding how the brain creates intelligence is the ultimate scientific challenge,” said Vicarious co-founder Dr. Dileep George. “Vicarious has a long term strategy for developing human level artificial intelligence, and it starts with building a brain-like vision system. Modern CAPTCHAs provide a snapshot of the challenges of visual perception, and solving those in a general way required us to understand how the brain does it.”

“We should be careful not to underestimate the significance of Vicarious crossing this milestone,” Facebook co-founder and board member Dustin Moskovitz said about the Vicarious development. “This is an exciting time for artificial intelligence research, and they are at the forefront of building the first truly intelligent machines.”

In a statement, Vicarious said it expects this technology “will have broad implications for robotics, medical image analysis, image and video search, and many other fields.”


Source: Brett Smith for redOrbit.com - Your Universe Online



comments powered by Disqus