Yann LeCun (deep learning expert) offers a skeptical view:

AI startup Vicarious claims to have a system that can solve CAPTCHAs with
> "succes rate up to 90%".
> Beware: It's a textbook example of AI hype of the worst kind
> Hype is dangerous to AI. Hype killed AI four times in the last five
> decades. AI Hype must be stopped.
> Perhaps Vicarious can get "up to 90%" accuracy on some CAPTCHA dataset
> they cooked up, but
> - (1) breaking CAPTCHAs is hardly an interesting task, unless you are a
> spammer;
> - (2) it's easy to claim success on a dataset you cooked up yourself.
> There is no risk someone else will beat you.
> - (3) recognizing object in images is much, much harder than breaking
> CAPTCHAs. Some deep learning systems can already do this with decent
> accuracy. Some such systems have been deployed by Google and Baidu.
> - (4) doing simultaneous segmentation and recognition of character strings
> is hardly a breakthrough. See demos of a 20 year-old system here:
> http://yann.lecun.com/exdb/lenet/index.html
> The sad thing is that this announcement is being picked up by a number
> publications, including MIT Tech Review, Forbes, etc.
> Here is an advice to scientific/tech journalists: please, please do not
> believe vague claims by AI startupsunless they produce state of the art
> results on widely accepted benchmarks.
>
> This is particularly true for claims in image and speech recognition for
> which good benchmarks exists. For image recognition, a good example of such
> benchmark would be the ImageNet Large Scale Visual Recognition Challenge.
> Whenever a startup claims "90% accuracy" on some random task, do not
> consider this newsworthy.  If the company also makes claims like "we are
> developing machine learning software based on the computational principles
> of the human brain" or uses impressive-sounding names like "Recursive
> Cortical Network", be even more suspicious.
>
> There are extremely impressive applications of deep learning out there
> (e.g. deployed by Google, Baidu, Microsoft, IBM, and a few startups), but
> this is not one of them.
> Google's automatic photo tagger and Baidu's image retrieval system are
> much, much more impressive than the system in this announcement. Even if we
> just talk about challenging character recognition tasks, Google's system
> for picking out house numbers in StreetView images is way more impressive
> than this.
>
> AI "died" about four times in five decades because of hype: people made
> wild claims (often to impress potential investors or funding agencies) and
> could not deliver. Backlash ensued. It happened twice with neural nets
> already: once in the late 60's and again in the mid-90's.
> Don't let it happen again. Beware of hype.
> And by the way, no one is interested in breaking CAPTCHAs except spammers
> and computer security researchers. That's why you won't find many computer
> vision papers on the topic. That's also why it would be easy to break
> records, even if a standard dataset existed.


Dileep George's rebuttal:

Hi Yann,
> (1) CAPTCHA contains many of the problems that make general vision
> hardhttp://tinyurl.com/mkhllyu. We will be publishing results on standard
> benchmarks in the future as well.
> (2) We get 90% pass rate on a validation set of 10,000 captchas downloaded
> from reCAPTCHA on Nov 5 at 11:25AM. You can download the data for yourself
> here:https://www.dropbox.com/s/sqr7b6ck0bzt0ur/recaptcha10k.zip
> (3) We recognize objects in images too, this is just one demo of our
> system.
> (4) Looks like you linked to the wrong video, because the letters in that
> video look pretty well separated and easily segmented out. I'd like to see
> any current system parse modern CAPTCHAs.
>
> Out of curiosity, did you also have this reaction to the news about
> Watson? It's good to (sometimes) post results that the average person can
> connect with.



Source: https://plus.google.com/104362980539466846301/posts/Qwj9EEkUJXY



On Mon, Oct 28, 2013 at 5:03 PM, Azat <[email protected]> wrote:

> http://www.kurzweilai.net/vicarious-ai-breaks-captcha-turing-test
>
> Azat
>
> _______________________________________________
> nupic mailing list
> [email protected]
> http://lists.numenta.org/mailman/listinfo/nupic_lists.numenta.org
>



-- 
Pedro Tabacof,
Unicamp - Eng. de Computação 08.
_______________________________________________
nupic mailing list
[email protected]
http://lists.numenta.org/mailman/listinfo/nupic_lists.numenta.org

Reply via email to