Yes, AIs can write recipes and sometimes they're pretty good! But for my latest challenge, I wanted to build an AI that would compose recipes from iPhone snapshots and put them in the proper format for my recipe app. Not really, as it turned out. Now, it's not all that tricky to have, say, ChatGPT write on-the-fly recipes based on photos–you can even do it using Apple Intelligence on an iPhone. Just take a snap of a meal with Visual Intelligence, ask for a description (Siri will hand that task off to ChatGPT), then follow up with a request for a recipe.

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?

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.

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.

Google research scientist Kevin Murphy dropped a knowledge bomb on a crowd full of data scientists at the RE.WORK Deep Learning Summit Tuesday. While working on Google's image recognition programs -- algorithms that can analyze a photo and precisely identify items -- he thought of a unique application: Counting calories by analyzing photographs of food. Murphy explained that food photos are the most common type of photos on the web after pictures of actual people. With this developing software, a Google computer can look at an image of, say, eggs, pancakes and bacon, and identify each food. But Murphy's vision goes one step farther: He wants to create an app that looks at the photo, identifies the foods, analyzes the size of the foods, matches the nutritional information for each food, and then spits back the caloric intake of your meal. Snap a pic of your dinner (some of us already do it for Instagram), give it to Google and learn the caloric count of what you're putting into your body.

Whether by accident or design, the details of Google's plans for artificial intelligence (AI) have been elusive. In some cases, there's no real mystery, just nothing all that exciting to talk about. AI technology is the foundation of the company's search engine, and the most obvious reason for Google's high-profile, $400M acquisition of DeepMind in 2014 is to use the UK firm's expertise in deep learning--a subset of AI research, but more on that later--to bolster that core capability. But the Googleplex has absorbed other bright minds from the field of AI, as well as some of the most buzzed-about companies in robotics, with only some of that collective braintrust officially allocated to driverless cars, delivery drones or other publicly announced robotics or AI-related projects. What, exactly, are Google's AI experts up to?

Boston-based Lose It! (incorporated as FitNow Inc.) has released a new beta feature today called Snap It within its weight loss and calorie tracking app. As is easily guessed by the name, Snap It beta lets users take photos of their daily meals and snacks to automatically log them and derive approximate calorie counts. For now, users will be able to open the Lose It! app, pick a meal-type (breakfast, lunch, dinner or snack), take a photo of their food, submit and wait briefly for Snap It to analyze it. Snap It will present users with a few best guesses of what food was portrayed in the submitted pic. Users can then confirm the food seen in the photo, and add more detail.