Google has officially launched its incredible “Night Sight” feature on the Pixel 3 camera app. Computational photography pioneer and Google Distinguished Engineer Marc Levoy co-wrote a blog describing all the different considerations that went into developing the jaw dropping technology that allows the Pixel to see in the dark. It’s worth a read.

The New York Times has teamed up with Google Cloud for digitizing five to seven million old photos in its archive. Google’s AI will also be tasked with unearthing “untold stories” in the massive trove of historical images.

So the BBC started looking into the video, which allegedly took place in Cameroon. In July, when the video first went viral, the government there dismissed the allegations as “fake news” on the basis that the soldiers depicted were not wearing the right gear or carrying the right weapons.

Consumer video sure ain’t what it used to be. The category now includes numerous variations, ranging from full-length to short-form narratives, plus what could be called “phodeos”: hybrids of photos and videos such as Boomerang clips, Instagram Stories, and even the (now venerable) GIF animations. Due in large part to these new options that free consumers from the “one (huge) size fits all” straightjacket of the past, motion imaging is more popular now than ever.

At Netflix, the Content Platform Engineering and Global Product Creative teams know that imagery plays an incredibly important role in how viewers find new shows and movies to watch. We take pride in surfacing the unique elements of a story that connect our audiences to diverse characters and story lines. As our Original content slate continues to expand, our technical experts are tasked with finding new ways to scale our resources and alleviate our creatives from the tedious and ever-increasing demands of digital merchandising. One of the ways in which we do this is by harvesting static image frames directly from our source videos to provide a more flexible source of raw artwork.

The Hungarian software company DIRE Studio has just launched Technical Camera, a new iOS camera app that’s designed for serious photographers who want a simple yet advanced tool for capturing still photos.

The 2018 edition of the LDV Vision Summit was, like its four predecessors, a refreshing display of creative ingenuity, stunning engineering and brilliant problem-solving. With successive keynotes never longer than 5 minutes each, subtlety interrupted by more extended fire chats or panels, there is no room for boredom. Even if a topic or speaker might not be in your field of interest, it is not long before another will keep you glued to your chair and wanting to know more. Which, thanks to the casual and friendly networking, is not hard to do. Speakers are all available to explain more if needed and do business, if appropriate. No superstars here leaving in limos the minute they step out the stage. Instead, a succession of people passionate about their work as much as the audience.

A group of scientists from Intel and the University of Illinois at Urbana–Champaign have published a paper called Learning to See in the Dark detailing a powerful machine-learning based image processing technique that allows regular cameras to take super-sharp pictures in very low light, without long exposures or the kinds of graininess associated with low-light photography.

While companies and researchers around the world work to build the most advanced and powerful AI systems, Facebook has a special treasure trove that most don’t: billions of tagged photos thanks to Instagram. Facebook has now used those photos to create a leading image recognition AI.

And beyond that, why is it — after multiple national tragedies politicized by hoaxes and misinformation — that such a question even needs to be asked?

A couple of research papers were recently published, both touching on advancement in computer vision and machine learning. While research papers are a common occurrence in this field, these two are worth reviewing a bit deeper, as their implication will have a wide impact once they mature.

Will stop here with our analysis because it seems to be clear that even if it is under the once respected name of Kodak, this project still has a lot to clear before becoming trustable. For one, and foremost, a working demo would go a long way to demonstrate exactly how this functions and if viable. As well, it would eliminate any doubts that this is not a get quick rich tech play that might leave a lot of photographers worst than where they are now.