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One Man's Face, 12.5 Years

Photographer Noah Kalina has been taking a picture of himself every day since January 11, 2000. He's so dedicated to his "Everyday" project that he made an app for it. Today he released a video compiling all the photographs so far -- 4,514 photos in sequence, showing his unsmiling face staring into a camera. If you pause it at various points, you can spot Kalina in kitchens, airplanes, and what I take to be his apartment in various stages of disorder. The 7-minute video is interesting partly because you can watch Kalina age -- it may not be apparent as you watch, but if you zip back to the beginning and compare areas of his face (check the forehead), the early photos are positively childlike in comparison. It's also interesting that his neutral facial expression hasn't change in over a decade. Kalina continues working on the project, so tune in years from now for more.

If the video looks familiar, it may be because he released six years' worth in 2006, and The Simpsons aired an homage the following year (wow).

See also: He Took a Polaroid Every Day, Until the Day He Died.

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Dive into the world of Shark, a new book by award-winning photographer Brian Skerry.

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AI Algorithm Tells You the Ingredients in Your Meal Based on a Picture
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Your food photography habit could soon be good for more than just updating your Instagram. As Gizmodo reports, a new AI algorithm is trained to analyze food photos and match them with a list of ingredients and recipes.

The tool was developed by researchers at MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL). To build it, they compiled information from sites like All Recipes and Food.com into a database dubbed Recipe1M, according to their paper. With more than a million annotated recipes at its disposal, a neural network then sifted through each one, learning about which ingredients are associated with which types of images along the way.

The result is Pic2Recipe, an algorithm that can deduce key details about a food item just by looking at its picture. Show it a picture of a cookie, for example, and it will tell you it likely contains sugar, butter, eggs, and flour. It will also recommend recipes for something similar pulled from the Recipe1M database.

Pic2Recipe is still a work in progress. While it has had success with simple recipes, more complicated items—like smoothies or sushi rolls, for example—seem to confuse the system. Overall, it suggests recipes with an accuracy rate of about 65 percent.

Researchers see their creation being used as a recipe search engine or as a tool for situations where nutritional information is lacking. “If you know what ingredients went into a dish but not the amount, you can take a photo, enter the ingredients, and run the model to find a similar recipe with known quantities, and then use that information to approximate your own meal,” lead author Nick Hynes told MIT News.

Before taking the project any further, the team plans to present its work at the Computer Vision and Pattern Recognition Conference in Honolulu later this month.

[h/t Gizmodo]

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