Since 2013 an artificial intelligence named NEIL has been scouring the Internet to learn to recognize the subjects of images.

 Thanks to the supercomputer that is our brain, we can make lightning-fast inferences and associations between images and situations. For a real computer, though, the same task is a bit harder. That kind of advanced visual processing requires significant artificial intelligence (AI) — the ability to perform humanlike cognitive tasks such as reasoning, generalizing and learning from past experience.

Yet, since summer 2013, NEIL — the Never Ending Image Learner — has been hard at work at Carnegie Mellon University analyzing and forming relationships between images from all over the Internet. The better the system gets, the closer we are to truly powerful AI and a new era of smart technology.

Made up of two computer clusters housing a total of 200 processing cores, NEIL is programmed to organize its database into three categories: objects (such as computer or Corolla), scenes (alley or church) and attributes (blue or modern).

Researchers left NEIL to itself to analyze online images, using an algorithm that allows it to build connections — the heart of its AI. Those connections include object-object relationships (“eye is part of baby”), scene-object relationships (“bus is found in bus depot”), object-attribute relationships (“pizza has round shape”) and scene-attribute relationships (“alleys are narrow”). NEIL then adds these relationships to its database, giving it more data so it can become even better at finding new associations.

“Gathering visual common sense is an extremely difficult problem,” says Abhinav Gupta, principal investigator on the NEIL project. “The problem is considered to be among the hardest in all of AI because the breadth and richness of common sense is enormous.”

It’s important to develop strategies, like NEIL’s learning algorithms, that allow computers to recognize, categorize and respond to images as the machines become more incorporated into our lives, Gupta says: “Over the past decade, AI researchers have made tremendous advances in the field of computer vision. For example, object and scene recognition. NEIL is a small step toward the long-term dream of making truly intelligent machines.”

While NEIL may one day learn to make new kinds of connection

s — and Gupta’s team hopes to develop novel applications of the software — there’s no real endpoint to the project. “In a manner similar to humans,” Gupta says, “we expect NEIL to keep learning in a never-ending fashion.” So far, NEIL has analyzed more than 10 million images and created 5,000 likely relationships between them. As some of the examples at right show, sometimes NEIL does a great job linking the concepts behind images, and sometimes … not so much.

Source: http://discovermagazine.com/

21 responses to “The Greatest Hits, and Misses, of an Image-Learning AI

  1. A lot of of what you mention is supprisingly precise and that makes me wonder the reason why I hadn’t looked at this with this light previously.This particular article really did switch the light on for me as far as this particular issue goes.However at this time there is actually one particular point I am not necessarily too cozy with so whilst I attempt to reconcile that with the core idea of the point, let me see exactly what all the rest of your subscribers have to point out.Nicely done. ออกแบบเว็บไซต์

  2. hello there and thanks for your information – I have certainly picked up anything new from right here. I did then again experience some technical issues the use of this web site, as I experienced to reload the site lots of times prior to I could get it to load properly. I were considering in case your web hosting is OK? No longer that I’m complaining, however sluggish loading cases occasions will sometimes affect your placement in google and could harm your quality ranking if ads with Adwords. Anyway I’m including this RSS to my e-mail and can glance out for a lot extra of your respective interesting content. Make sure you update this again very soon..

  3. Fantastic items from you, man. I’ve be mindful your stuff prior to and you’re simply extremely magnificent. I really like what you have obtained here, certainly like what you are saying and the way in which by which you say it. You make it enjoyable and you still take care of to keep it sensible. I can’t wait to read far more from you. This is really a terrific web site.

Leave a Reply

Your email address will not be published.

Shares