Catch up on stories from the past week (and beyond) at the Slashdot story archive

 


Forgot your password?
Close
typodupeerror
×
AI Cloud Google Software

Google Has Made It Simple For Anyone To Tap Into Its Image Recognition AI (gizmodo.com) 42

Posted by BeauHD from the easy-peasy dept.
An anonymous reader quotes a report from Gizmodo: Google released a new AI tool on Wednesday designed to let anyone train its machine learning systems on a photo dataset of their choosing. The software is called Cloud AutoML Vision. In an accompanying blog post, the chief scientist of Google's Cloud AI division explains how the software can help users without machine learning backgrounds harness artificial intelligence. All hype aside, training the AI does appear to be surprisingly simple. First, you'll need a ton of tagged images. The minimum is 20, but the software supports up to 10,000. Using a meteorologist as an example for their promotional video was an apt choice by Google -- not many people have thousands of tagged HD images bundled together and ready to upload. A lot of image recognition is about identifying patterns. Once Google's AI thinks it has a good understanding of what links together the images you've uploaded, it can be used to look for that pattern in new uploads, spitting out a number for how well it thinks the new images match it. So our meteorologist would eventually be able to upload images as the weather changes, identifying clouds while continuing to train and improve the software.
This discussion has been archived. No new comments can be posted.

Google Has Made It Simple For Anyone To Tap Into Its Image Recognition AI More

Google Has Made It Simple For Anyone To Tap Into Its Image Recognition AI

Comments Filter:

  • They want the crowd to train their machine (Score:1)

    by Anonymous Coward

    because it's free....

    • Re:They want the crowd to train their machine (Score:4, Interesting)

      by TheRaven64 ( 641858 ) on Thursday January 18, 2018 @09:27AM (#55952311) Journal
      I wonder if that's actually true. On the one hand, they get a lot of training data for free. On the other hand, how well are the protected against adversarial training? If a botnet signs up for a million accounts, submits 20 photos with correct descriptions for 19 and incorrect ones for the remaining one, is it possible for the attacker to teach the Google algorithm some nonsense things? What if I'm more subtle and upload 100 pictures of dogs and tag them as dogs, but the pictures are carefully crafted to share more characteristics with other pictures of cars than of dogs? Can I train it to recognise all cars as dogs (last year researchers were able to alter a picture of a dog or a car by one pixel and have this system recognise it as the other). A system like this is only as good as its training set - remember that this is the same system that decided that all black people were gorillas because the only black face in its original training set of photos from Google employees was a gorilla at a zoo.
      • Adversarial training is not limited to Artificial Intelligence. Natural Stupidity also suffers from the same fundamental flaw.

        How else can you explain political parties training their flock to vote against their own self interest?

    • When I started out as a programmer, you never wanted to be anyone's beta tester. Now, people give up their free time to do so!

  • The thirty fourth rule. (Score:3)

    by queazocotal ( 915608 ) on Thursday January 18, 2018 @09:15AM (#55952279)
    'Using a meteorologist as an example for their promotional video was an apt choice by Google -- not many people have thousands of tagged HD images bundled together and ready to upload.'

    I suspect quite a few of us have tagged HD images bundled together and ready to upload.

    • I suspect quite a few of us have tagged HD images bundled together and ready to upload.

      My list of of twenty pictures:

      Hillary.
      Donald.
      A can of Cheez Whiz.
      A fractal cow: http://mndl.hu/2008-02-01-frac... [mndl.hu]
      A Bitcoin.
      A Jai Alai Cesta.
      John Small Berries.
      A build break.
      An iPhone battery.
      Bacon.
      Bigfoot.
      Queen Elizabeth's Crown Jewels.
      An ingrown toenail.
      Twenty years to life, with no chance of parole.
      "The Economist" international Big Mac index.
      A Nobel Peace Prize.
      An Ig Nobel.
      Winter Storm f "Friederike".
      A Ford F-450 Super Duty Limited.
      Slashdot.

      Ok, Google AI . . . get at it . . .

  • Did anyone else read that title where the second capital T was an F?

  • Serious question... is this really Artificial Intelligence? Or is this really Self-Adapting Algorithm? For that matter, is "Self-Adapting Algorithm" what "Artificial Intelligence" actually is?

    "AI" is such a hyped up, overused term that I just can't tell what's what anymore. I'm old.

    • Re: (Score:1)

      by Anonymous Coward

      "AI" is whatever we don't know how to get a computer to do.

      Once we know how to get a computer to do it, we give it a different label, and it becomes "no longer AI".

  • Admittedly, this concern may be a bridge too far even for the tinfoil hat crowd. But...

    If I were a bad guy, knew that intelligence agencies have compromised electronics down to the firmware and hardware levels and needed to securely communicate with other bad guys, then I'd develop image + label data to train Google's service to spit out plaintext results from certain image sets. My compatriots would run images of dogs, cats, etc. through OpenML and receive labels like "Bomb" "Building" "Corner" "Columbus

    • Comment removed based on user account deletion

      • A picture-based system is only as strong as the protection of its cipher, which can be compromised in its storage medium (i.e., somewhere, somehow there's a key saying "dog" equals "bomb"). With OpenML, which is meant to be a turnkey solution for mitigating complexity, the cipher is the hidden layers. The interesting aspect here is that the state of the art in AI can't fully explain how those hidden layers arrive at their probabilistic results. Hence a potentially strong system.

  • Did google ever fix the gorilla problem?

    http://www.dailymail.co.uk/sciencetech/article-5270891/Google-bans-word-gorilla-racist-Photos-app.html

  • the Google also taps into you.

Slashdot Top Deals

"The four building blocks of the universe are fire, water, gravel and vinyl." -- Dave Barry

Close