These crawls are part of an effort to archive pages as they are created and archive the pages that they refer to. That way, as the pages that are referenced are changed or taken from the web, a link to the version that was live when the page was written will be preserved.Then the Internet Archive hopes that references to these archived pages will be put in place of a link that would be otherwise be broken, or a companion link to allow people to see what was originally intended by a page's authors.The goal is to fix all broken links on the web . Crawls of supported "No More 404" sites. ||||| One of the most amazing things you can do with Wolfram Alpha is ask it what planes are overhead. If you're on your phone, it will pull your location, then cross reference that with a database of flights, including their altitude, angle, and even their flight number and aircraft type. But in many ways, Stephen Wolfram's latest search tool is more impressive. It's designed to identify anything in a picture. You just upload a photo, and get a computer-generated guess just a few seconds later. 
 
 "It won’t always get it right." 
 
 "It won’t always get it right, but most of the time I think it does remarkably well," Wolfram writes. "And to me what’s particularly fascinating is that when it does get something wrong, the mistakes it makes mostly seem remarkably human." In some brief testing, that's a pretty fair assessment. I plugged in things like Yosemite National Park's Half Dome and was told it was "elevation," while a photo of a gecko was identified as a "night lizard." Remarkably though, it identified a picture of a cow as "black angus," and two cups of ice cream as "frozen yogurt." Close enough. 
 
 How all this ascends beyond assaulting a website with photos of your last vacation or what's in your kitchen, is tantalizing. Wolfram says he imagines the project could be useful if applied to large collections of photos to attempt to identify and categorize them. The technology can also be used by others to build image identification into their apps. Think about the visual recognition found within Google+'s photos, but in other photo apps and services. 
 
 The system was trained with cats, sloths, and Chewbacca 
 
 In order to train the system, Wolfram says it was fed "a few tens of millions" of images so that it could learn what was what. That "seemed very comparable to the number of distinct views of objects that humans get in their first couple of years of life," he added. The system was also given tricky images like cats wearing spacesuits, sloths wearing party hats, and even Chewbacca — all things it failed at identifying correctly, but gracefully so: 
 
 Now it's capable of recognizing about 10,000 common kinds of objects, though Wolfram notes that it still has difficulty recognizing specific people, art, and things that are not "real everyday objects." 
 
 The new image project joins Google's Goggles and Amazon's Firefly as rapid identification tools, though is notably designed without the intent to try and sell you anything with what it finds. It also comes just a little while after Flickr's new Magic View, as well as Microsoft's research site that determines people's genders and age based on photos. Unlike Microsoft though, Wolfram says it keeps a thumbnail version of the photo after you've uploaded it (so it can be shared with other people), and that it's collecting the images to keep on training its system, so be mindful of what you send in. 
 
 Here's how it did against a handful of different images: 
 
 Reasonably close. 
 
 Welp. 
 
 I can kind of see it... 
 
 Which is pretty much just: ||||| A new website from Wolfram Alpha will attempt to identify any image you show it, though it’s more amusing than practical at the moment. 
 
 To check it out, head to ImageIdentify.com and drop in any photo from your computer or mobile device. The site will spend a few seconds mulling it over before taking a guess at what the picture is showing. 
 
 It’s pretty amazing when it works. Using the site, I was able to figure the breed of dog that kept following my wife and I around on our honeymoon (miniature pinscher) and the exact type of flower from a hike in Los Angeles (larkspur). It also does pretty well identifying simpler things, like the pizza photo I used in a Wednesday blog post. 
 
 But in my experience, those flashes of brilliance were the exception, not the rule. Wolfram’s tool is no good at identifying tech products (it thought an Apple TV remote was an alligator clip) and it came up with only vague or outright incorrect guesses for some of the other flora and fauna I showed it. Perhaps because of demand, more times than not the site threw up a “please try again” error. 
 
 In a blog post, CEO Stephan Wolfram readily admits that the tool has plenty of blind spots—some of which can be fairly amusing—and notes that it will get better with experience. To that end, users can help out by indicating when the system is right or wrong, and either choosing from a few next-best guesses or typing in the correct identification. It’s definitely worth trying out if you have a bunch of photos and a few minutes to kill. 
 
 Why this matters: Assuming the system improves over time, it has plenty of potential beyond your own amusement. Stephan Wolfram gives the example of a program that provides statistics on a large number of images. One could imagine some kind of tool to itemize all the things you discovered on a vacation, or translate an image of food into dietary information. Developers can build these sorts of things using Wolfram’s programming and cloud computing tools, so the basic ImageIdentify site is just the beginning.
– You probably can already identify the contents of most of your photos, but this is still fun. A new website from Stephen Wolfram, whom you may know from the search tool WolframAlpha, lets you drag and drop any photo; it will then in theory identify what's in it. Right now, ImageIdentify manages some impressive feats, the Verge reports: For instance, it was able to tell that a picture of a cow was a black angus. On the other hand, it thought a cupcake was a bottle cap. The Wolfram Language team is happy to acknowledge the mistakes. In a blog post, Wolfram notes that "somehow the errors seemed very understandable, and in a sense very human. It seemed as if what ImageIdentify was doing was successfully capturing some of the essence of the human process of identifying images." In the meantime, it does have some practical uses: At PC World, Jared Newman writes that "using the site, I was able to figure the breed of dog that kept following my wife and I around on our honeymoon (miniature pinscher) and the exact type of flower from a hike in Los Angeles (larkspur)." And we can expect ImageIdentify to get better at its job, since it keeps copies of the images you post and learns from them; its abilities come from the study of tens of millions of pictures, Wolfram says. You can also tell the site whether its analysis was correct. It's not the only such system, the Verge notes, pointing to efforts like Google Goggles. (What would it say about this smiley face in space?)