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Sunday, April 25, 2021

FlavorGraph: Food Pairings with AI and Molecular Science

Combines a number of interests of mine.  Food science and AI, Chemistry and Graph Analytics.   At the link see some impressive graphs that look at the connections  Nicely done approach to loooking at a complex problem.  In our own food industry area, coffee blending, we looked at some aspects of this, but just barely.  Worth a look if you are in the area.

 (Update:  Hmmm ... just acted as a tester of new spice blends for McCormick. Might this act as a means of generating potential new blends for them? )

FlavorGraph Serves Up Food Pairings with AI, Molecular Science  By Isha Salian

Tags: Data Science, featured, Machine Learning & Artificial Intelligence, News

It’s not just gourmet chefs who can discover new flavor combinations— a new ingredient mapping tool by Sony AI and Korea University uses molecular science and recipe data to predict how two ingredients will pair together and suggest new mash-ups. 

Dubbed FlavorGraph, the graph embedding model was trained on a million recipes and chemical structure data from more than 1,500 flavor molecules. The researchers used PyTorch, CUDA and an NVIDIA TITAN GPU to train and test their large-scale food graph.

Researchers have previously used molecular science to explain classic flavor pairings such as garlic and ginger, cheese and tomato, or pork and apple — determining that ingredients with common dominant flavor molecules combine well. In the FlavorGraph database, flavor molecule information was grouped into profiles such as bitter, fruity, and sweet. 

But other ingredient pairings have different chemical makeups, prompting the team to incorporate recipes into the database as well, giving the model insight into ways flavors have been combined in the past. .... " 

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