Richard, its a step up, but its not a Turing Test. When it fools you into not 
knowing who you had a conversation with, especially, if you didn't know if a 
Turing challenge was being performed, then I'd say, yes.
-----Original Message-----

From: Richard Ruquist <yann...@gmail.com>
To: everything-list <everything-list@googlegroups.com>
Sent: Mon, Oct 28, 2013 12:22 pm
Subject: Fwd: Vicarious AI breaks CAPTCHA ‘Turing test’






---------- Forwarded message ----------
From: richard ruquist <yann...@yahoo.com>
Date: Mon, Oct 28, 2013 at 12:18 PM
Subject: Vicarious AI breaks CAPTCHA ‘Turing test’
To: "swi...@yahoogroups.com" <swi...@yahoogroups.com>, "yann...@gmail.com" 
<yann...@gmail.com>




Vicarious AI breaks CAPTCHA ‘Turing test’
October 28, 2013



[+]

Average recognition accuracy (per character) claimed for the Vicarious 
algorithms for different CAPTCHA styles (credit: Vicarious)

Vicarious, a startup developing artificial intelligence software, today 
announced that its algorithms can now reliably solve modern CAPTCHAs 
(Completely Automated Public Turing tests to tell Computers and Humans Apart).
Stanford University researchers have suggested that a CAPTCHA scheme (which are 
used by websites to verify that a visitor is human by asking them to transcribe 
a string of distorted letters) should be considered “broken” if an algorithm is 
able to reach a precision* (fraction of CAPTCHAs answered correctly) of at 
least 1% [1].
Breaking CAPTCHAs
Vicarious claims they can go way beyond that by leveraging core insights from 
machine learning and neuroscience, saying its AI algorithms achieve success 
rates up to 90% on modern CAPTCHAs.
“This advancement renders text-based CAPTCHAs no longer effective as a Turing 
test,” according to a Vicarious statement. (The Stanford study calls it a 
“reverse Turing test” because CAPTCHAs are intended to allow a website to 
determine if a remote client is human or not.)
“Recent AI systems like IBM’s Watson and deep neural networks rely on brute 
force: connecting massive computing power to massive datasets,” said Vicarious 
cofounder 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.”
A brain-like vision system
“Understanding how the brain creates intelligence is the ultimate scientific 
challenge. Vicarious has a long term strategy for developing human level 
artificial intelligence, and it starts with building a brain-like vision 
system,” said Vicarious cofounder Dileep George, PhD, who was formerly Chief 
Technology Officer at Numenta, a company he cofounded with Jeff Hawkins and 
Donna Dubinsky (Palm Computing, Handspring) while completing his PhD at 
Stanford University.
“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.”
Solving CAPTCHA is the first public demonstration of the capabilities of 
Vicarious’ Recursive Cortical Network (RCN) machine learning software,  which 
is based on the computational principles of the human brain. (Vicarious says it 
does not plan to release RCN or its algorithms publicly).
Vicarious’ RCN technology is a visual perception system that interprets the 
contents of photographs and videos in a manner similar to humans. “Although 
still many years away, the commercial applications of RCN will have broad 
implications for robotics, medical image analysis, image and video search, and 
many other fields,” according to a Vicarious statement.





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