You already know what all of your friends are eating, so you might as well know how to make it, too. You already know what all of your friends are eating, so you might as well know how to make it, too. When someone posts a photo of food on social media, do you get cranky? Is it because you just don't care what other people are eating? Or is it because they're enjoying an herb-and-garlic crusted halibut at a seaside restaurant while you sit at your computer with a slice of two-day-old pizza?

The days of looking at food on Instagram in ignorant bliss are coming to an end. According to a new study from MIT's Computer Science and Artificial Intelligence Laboratory, a deep-learning AI algorithm called "Pic2Recipe" is able to retrieve the likely ingredients of a meal based on just a picture. Researchers gathered 1,029,720 recipes and 887,706 meal images from popular cooking websites such as All Recipes and Food.com and manually removed duplicate images as well as unwanted characters such as exclamation points or question marks. This culminated in a robust database of common meals and their ingredients. When the Pic2Recipe AI was asked to view an image of a meal, it was able to use the database to identify the correct ingredients 65 percent of the time.

The next time you come across a picture of a ravishing dish on Instagram or WeChat that whets your appetite but you can't exactly make out what it is made of, don't wrack your brain trying to guess the recipe. An AI system unwrapped earlier this week helps those with culinary curiosity find the right ingredients of an unknown dish and offers step-by-step instructions how to make it just by analyzing a photo they upload online. Researchers from the Polytechnic University of Catalonia, Massachusetts Institute of Technology (MIT) and Qatar Computing Research Institute have developed a deep-learning algorithm that can whip out a recipe just by "looking" at a photo of the dish. They fed the neural network one million recipes, along with one million photos of their final outcome, from popular websites like Allrecipes.com and Food.com to create a huge database they dubbed, Recipe1M, accessible through a web portal they called Pic2Recipe. With a single click of a button, the website allows users to upload a photo of the mystery dish and then the system, using machine learning, goes through the massive mounds of data to analyze it. It then predicts a list of possible ingredients along with their relevant recipes, then ranks them based on how certain the AI is they match the image.

Researchers from the MIT Computer Science and Artificial Intelligence Laboratory (CSAIL) have developed a neural network that can, in theory, "look" at an image and find the recipe for the food that's depicted. The CSAIL team calls the network Recipe1M, and it's described in detail in a paper that was published this week. Simply put: the researchers fed the AI more than 1 million recipes and nearly 1 million images. Over the course of that training, it made and refined associations between what goes into a recipe and how that relates to a food photo. The result is an interface called Pic2Recipe that's reminiscent of the lo-fi goofy TensorFlow projects we've seen, like edges2cats or Pix2Pix.

Have you ever seen (or eaten) a delicious meal and wished you had the recipe to make it? Now all you have to do is take a picture and give it to an algorithm developed by MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL). Their algorithm can find a recipe for you based on nothing more than a single picture of the finished product. The researchers built their algorithm by combing through over a million different recipes collected from various recipe websites. They combined this recipe encyclopedia with image recognition software to identify the type of food in a photo and match it with its corresponding recipe.

MIT has created an artificial intelligence algorithm which can accurately tell you the recipe behind a dish after being shown no more than a picture. With the emergence of social media, it is not only the spread of information which has grown but also the popularity of image sharing. Everything from cat pictures to cupcakes bombards the internet every day, but there may now be a use for the latest delicious meal your friend has shared on their social network accounts -- as you may be able to cook it yourself just by having access to the picture. On Thursday, MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL) said that a new artificial intelligence-based algorithm has been developed which can analyze still images of food in order to detect the likely ingredients and suggest a recipe to create the dish. The average recipe has nine ingredients and the most common ingredients found in today's dishes are salt, butter, sugar, olive oil, water, eggs, garlic cloves, milk, flour, and onion.

There are few things social media users love more than flooding their feeds with photos of food. Yet we seldom use these images for much more than a quick scroll on our cellphones. Researchers from MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL) believe that analyzing photos like these could help us learn recipes and better understand people's eating habits. In a new paper with the Qatar Computing Research Institute (QCRI), the team trained an artificial intelligence system called Pic2Recipe to look at a photo of food and be able to predict the ingredients and suggest similar recipes. "In computer vision, food is mostly neglected because we don't have the large-scale datasets needed to make predictions," says Yusuf Aytar, an MIT postdoc who co-wrote a paper about the system with MIT Professor Antonio Torralba.

If you've ever seen a tasty-looking meal and wanted to know the recipe to make it, then help could be at hand. Scientists have created an AI, dubbed Pic2Recipe, that can find a recipe for you based a single picture of the finished dish. The AI was trained by looking at more than a million different recipes collected from various recipe websites. Its image recognition software was then taught to identify the type of food in a photo and match it with a recipe and ingredients list. You can test the system for yourself by uploading an image of a dish below or on this demo page to see how to make it.