Robots are people too: Google algorithm passes 'human' t
Source: Mahesh Sharma
Google researchers have developed technology that nearly perfectly deciphers the distorted combinations of numbers and letters commonly used on the internet to test whether or not someone is human.
Ian J. Goodfellow, Yaroslav Bulatov, Julian Ibarz, Sacha Arnoud, and Vinay Shet, set out to develop a more accurate method to identify numbers in images taken for Google Street View. Their model identified, with better than 90 per cent accuracy, tens of millions of numbers contained in Street View images taken in a dozen countries.
Using the model in conjunction with Google's infrastructure, it takes less than an hour to transcribe all the views of street numbers in France.
The technology was also pitted against the hardest category of the character-blurring forms known as CAPTCHA (Completely Automated Public Turing test to tell Computers and Humans Apart). It is based on the concept of the Turing test, which is a standard way to assess whether a human can identify, via verbal exchanges, whether a respondent is human or a computer.
Tested against reCAPTCHA, Google's own variation, Mr Goodfellow and his team achieved near perfect results.
"Today, distorted text in reCAPTCHA serves increasingly as a medium to capture user engagements rather than a reverse Turing in and of itself," the researchers wrote. "These results do, however, indicate that the utility of distorted text as a reverse Turing test by itself is significantly diminished."
Google's technology uses a system called DistBelief, which leverages a scientific concept called convolutional neural networks. Inspired by biology, these neuron structures mimic the complex arrangement of cells within the part of the brain that interprets images.
The researchers layered these networks on top of each other to identify the numbers and characters in Street View images and CAPTCHA.
While Google's technology can read between the blurred lines, CAPTCHA still stupefies some humans.
Blind Sydneysider Wayne Hawkins says CAPTCHA prevents him from using the web because the distorted text cannot be deciphered by screen reading software. Last year he started a petition to "kill CAPTCHA," which has been signed by 3816 supporters.
Mr Shet, Google reCAPTCHA product manager, wrote that the company had significantly reduced its dependence on text distortions to prove sentience. Instead, it was used to perform advanced risk analysis.
"Relying on distorted text alone isn’t enough," Mr Shet wrote on the company's blog. "However, it’s important to note that simply identifying the text in CAPTCHA puzzles correctly doesn’t mean that reCAPTCHA itself is broken or ineffective. On the contrary, these findings have helped us build additional safeguards against bad actors in reCAPTCHA."
Jon Borwein, laureate professor of mathematics at University of Newcastle, said Google's findings were impressive but would not have a bearing on the strictly administered Turing test.
"Algorithmic trading or chess are fantastic examples of things computers do better than us, but no indication of consciousness or of an ability to pass a real Turing test," Professor Borwein said.
In the 1950s, British researcher Alan Turing seriously interrogated the question of whether machines could think. He eventually decided it was meaningless to try and answer this and instead posited: Are there imaginable digital computers which would do well in the imitation game?
"I believe that at the end of the century the use of words and general educated opinion will have altered so much that one will be able to speak of machines thinking without expecting to be contradicted," Turing wrote in 1950, amidst significant philosophical and ideological objections.
Imitators, like Google's technology, abound but it seems that Turing's vision �C of universal acknowledgement of machines capable of thought �C is still some way off.
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