DailyDirt: AI Image Recognition Is Still A Bit Buggy
from the urls-we-dig-up dept
As artificial intelligence gets more and more advanced, the differences between how computers recognize patterns and how humans do may become harder and harder to discern. However, it's obvious there are differences -- which might matter significantly if we're going to put these image recognition algorithms in control of autonomous cars or military threat detection systems. Check out a few of these image processing algorithms.- You can fool some of the people some of the time, but you can fool some AI all of the time. Apparently, it's possible to create self-training software that can fool state-of-the-art image recognition algorithms with images specifically evolved to generate false positive recognition (and that look nothing like the objects that were supposedly represented). It's almost like making a kind of Rorschach test for AI. [url]
- Several tech companies are developing advanced image recognition systems: Baidu, Google, IBM, Yahoo, Facebook, Twitter, Dropbox, etc. Baidu's Deep Image team has recently claimed to be the top-ranked system, beating out the performance of Google's team in the 2014 ImageNet computer vision competition. [url]
- When detectives in a show look at a photo and say "enhance" on a small part of an image, there really isn't any magic technology that can reconstruct reflections off a disco ball... or not yet, at least. SparkleVision is an image reconstruction algorithm that can unscramble images from some kinds of distorted reflections. Complex image processing is getting a lot better, but it's not quite as good as Hollywood makes it look. [url]
Filed Under: ai, artificial intelligence, autonomous cars, image processing, image recognition, imagenet computer vision competition, neural networks, pattern recognition, self-learning algorithms, sparklevision
Companies: baidu, dropbox, facebook, google, ibm, twitter, yahoo
