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WhatsApp is testing an image search tool to combat fake news
WhatsApp appears to be working on a new feature to help users identify whether an image they receive is legitimate or not. While picking apart update 2.19.73, WABetaInfo discovered a "search by image" function that will let you upload a received image directly to Google to reveal "similar or equal" images on the web. With this info, you should be able to more accurately judge whether the picture is real, or fake news.
Google tests shoppable ads in image searches
Google is borrowing a few cues from Instagram and Pinterest to encourage more shopping in its search results. The internet giant is testing shoppable ads within image searches -- find a picture of your ideal desk and you can tap a shopping tag button to see basic details as well as a link to buy it. This only applies to sponsored ads, thankfully, so you don't have to worry about ads covering the images you want to see.
Bing adds licensing rights refinement to image search
Here's a nice little feature for those of us who love to post images on the internet. Bing has added the ability to refine image results by license. The addition's simple enough to use -- just do a search and pull the appropriate license from a drop down on the top of the results page, alongside options for date, size and color. Selections include public domain and options like "free to modify, share and use," based on the Creative Commons licensing system, so there's no doubt as to precisely how you can incorporate them into your own posts. Google's had a similar option on its own search engine for some time -- albeit one's that's a bit less prominently displayed.
NEC's Gaziru takes image recognition to the cloud, looks a lot like Goggles (video)
While Google's remained relatively quiet on the Goggles front, NEC's picking up where that image recognition left off with its own product, dubbed Gaziru. Showcased at Wireless Japan 2012, the company's angling its service, which aims to leverage both hardware- and cloud-based processing for smartphone queries, towards enterprise and consumer markets, highlighting its usefulness across a range of services from marketing to search. Much like the aforementioned Mountain View version, users would need only to snap a picture of an object with their phones to receive relevant search data, access product manuals or, in one scenario, car and real estate listings. Given its planned commercial launch this June, it won't be long before we'll get a chance to test this software en vivo. For now, content yourself with a translated video tour after the break.
Google image search results crammed into picture dictionary
Though not quite a replacement for Mountain View's ill-fated dictionary, this 1,240 page tome contains the first Google image search result for each word in a run-of-the-mill dictionary. With a PHP script, London-based artists Felix Heyes and Ben West scraped the image from each search and compiled an alphabetically ordered PDF brimming with 21,000 images -- safesearch-disabled warts and all. "It's really an unfiltered, uncritical record of the state of human culture in 2012," West told Creative Applications Network. Alas, the volume isn't destined for mass distribution -- presumably to avoid copyright issues -- but the pair is considering sending a small batch of soft cover copies to print.
Google Images get spruced up, don't need no stinkin' text
Those alchemists over in Mountain View have been fiddling with their search engine again and the product has been one of the biggest redesigns ye olde Google has received to date. Gone are the little captions and size measurements under each image -- well, not gone, just hidden away until you hover over a pic -- to be replaced by a densely packed compendium of your results, which just keeps going and going. Seriously, the new Images search can fit up to 1,000 pictures on one page, with thumbnails loading in a logical top-to-bottom order. A new landing page has also been implemented, showing you the image you selected superimposed on top of the website it belongs to, making for a more streamlined search experience overall. We like it, it's fast and it's pretty cool, but is anyone working on result relevance at all? Try looking for an iPhone 4 snapshot and you'll have to scroll past 43 mockups before finding the real thing.
Google working with D-Wave on what may or may not be quantum computing
When we first mentioned D-Wave way back in early 2007 we immediately compared it to Steorn -- less than optimal beginnings. The company was promising quantum computing for the masses and, while it did demonstrate a machine that exhibited qubit-like behavior, the company never really silenced critics who believed the underpinnings of the machine were rather more binary in nature. Those disbelievers are surely shutting up now, with word hitting the street that Google has signed on, building new image search algorithms that run on D-Wave's C4 Chimera chip. The first task was to learn to spot automobiles in pictures, something that the quantum machine apparently learned to do simply by looking at other pictures of cars. It all sounds rather neural-networkish to us, but don't let our fuzzy logic cloud your excitement over the prospect of honest to gosh commercial quantum computing.
