The internal Google email chain also notes that several big tech players competed to win the Project Maven contract. Other tech firms such as Amazon were in the running, one Google executive involved in negotiations wrote. Rather than serving solely as a minor experiment for the military, Google executives on the thread stated that Project Maven was "directly related" to a major cloud computing contract worth billions of dollars that other Silicon Valley firms are competing to win. The emails further note that Amazon Web Services, the cloud computing arm of Amazon, "has some work loads" related to Project Maven. Jane Hynes, a spokesperson for Google Cloud, emailed The Intercept to say that the company stands by the statement given to the New York Times this week that "the new artificial intelligence principles under development precluded the use of A.I. in weaponry."

Allied Irish Bank CIO Tim Hynes has seen many emerging technologies reach the hype cycle's peak during his IT career, now well into its third decade. Their history tells him that artificial intelligence will only reach its potential if it's promoted and applied to realistic scenarios. "Artificial intelligence feels a little bit like a gold rush event," said Hynes at the AI Congress London. "That doesn't mean there's not value in it. What it does mean is that if you're going to get real value, you have to be pragmatic."

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.

How long before you come across some #FoodPorn? While pictures of food are everywhere on Instagram, the app doesn't allow links in posts so there's no easy way to find recipes. But that could be about to change. Pic2Recipe!, a website created by MIT electrical engineering and computer science student Nick Hynes, is a neural network that's been trained to recognise food from more than one million recipes on Food.com and AllRecipes. "It can look at a photo of a dish and be able to predict the ingredients and even suggest similar recipes," Hynes says.

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.

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.

Ever eaten a dish you didn't know them name of and wished you had the recipe so you could recreate it at home? Soon you might only need a picture of it. Researchers have devised a machine learning algorithm that looks at photos of food and predicts the recipe that created the dish. Nick Hynes at Massachusetts Institute of Technology and his colleagues trained the algorithm on one million recipes, each with an illustration of the finished result, from dozens of cooking websites. Given a fresh photo of a dish, the system picked the right recipe 65 per cent of the time.