Artificial intelligence (AI) and the future of food have been on convergent paths for some time now, and AI-driven technologies with recipes at the core are proliferating. As noted here, Microsoft is just one of many companies increasing its investments in AI, and is betting on a bot with probably the world’s most famous chef.

Smaller companies are eyeing the intersection of AI and recipes as well. Chicory, a New York-based food technology company paving the way for grocery ecommerce, has announced the release of its artificial intelligence engine, “Dolores.” Dolores intelligently matches digital recipe ingredients to purchasable products that consumers are or will be looking for. Consumers can then buy the shopping list with just the click of a mouse via one of Chicory’s grocery integrations.

“We were able to teach Dolores to implement the same subjective reasoning about food that humans make,” said Yuni Sameshima, Chicory CEO and Co-Founder. “For example, Dolores sees that the recipe requires pepper and can deduce whether that is black pepper or a bell pepper based on the context, which allows us to better provide users with their desired ingredients.”

A startup out of Sweden has a roughly similar AI-driven concept that begins with personalized recipe recommendations, then transforms the information pertaining to the recipes into a shopping list.

AI researchers are joining in, too. A team from MIT has trained an artificial intelligence system called Pic2Recipe to scrutinize a photo of food and then predict the ingredients and suggest similar recipes.  You can watch a video of how it works here:

The same team at MIT has created Recipe1M, a large-scale, structured “corpus” of over one million  recipes and 800,000 food images. According to the team: “As the largest publicly available collection of recipe data, Recipe1M affords the ability to train high-capacity models on aligned, multi-modal data. Using these data, we train a neural network to find a joint embedding of recipes and images that yields impressive results on an image-recipe retrieval task. Additionally, we demonstrate that regularization via the addition of a high-level classification objective both improves retrieval performance to rival that of humans and enables semantic vector arithmetic.”

In addition to winning Jeopardy!, IBM’s famed Watson supercomputer-driven AI engine is also getting smart about recipes and food pairings. According to a Quartz post: “Watson scanned publicly available data sources to build up a vast library of information on recipes, the chemical compounds in food, and common pairings. Knowledge that might’ve taken a lifetime for a Michelin-starred chef to attain can now be accessed instantly from your tablet.”

Yale University researchers have recently conducted a series of experiments showing that enhancing personal skillsets with AI is much more promising than entirely substituting human skillsets with AI. That concept is giving rise to many AI-driven chatbots that can suggest recipes intelligently.

For example, Microsoft has launched “Heston Bot,” its first ever food-inspired bot, exclusively for the Skype platform. It lets you get up close and personal with superstar chef Heston Blumenthal, and provides several ways for you to benefit from his fluency with food.

Heston Bot appears to have very strong natural language and AI smarts. I asked it about cooking techniques and more, and it understood me and also directed me to where I can find all of Heston’s recipes. It’s definitely smarter than your average bot.

For more on AI and cooking, see our recent stories on the Forksy conversational foodbot, a chatbot-powered sommelier, and our interview with Michael Gyarmathy, the creator of an Alexa Skill called Cooking Competition.

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