After Google’s AI confronts the winner of the Great British Bake Off competition, Sony has developed An in-depth education system FlavorGraph is called to bind ingredients like garlic, olives, and milk.
Artificial intelligence has entered games, autonomous driving, and other fields with mixed success, and is now entering the field of cooking.
Overall, FlavorGraph predicts the pairing compatibility of two components by combining information about the molecules in a specific ingredient with the way people have used that ingredient in the past.
These suggestions can be used to predict relationships between compounds and foods, and the goal is to develop a smart deep learning model that recommends pairing complementary and new ingredients to help chefs with new creations.
Sony and the University of Korea researchers note that chefs have discovered how to incorporate ingredients through intuition, which led to the gradual development of ingredients such as cheese, tomatoes, apples, garlic and ginger.
Many of these classic combinations were later explained by science, as researchers realized that ingredients that shared dominant flavor molecules often worked well together.
At the same time, other components that combine well may have completely different chemical formulations.
To find out why, the team examined both the molecular information about the ingredients and how they were historically used in recipes.
Hence they created a FlavorGraph database with flavor profiles, such as: bitter and sweet based on 1561 flavor molecules.
The team examined nearly a million recipes to see how the ingredients had been incorporated in the past.
The resulting data show the chemical compounds shared between foods and how they affect their overall taste, showing which foods can match specific types of fruits.
There are some obvious examples of associated foods, such as cookies and ice cream, but others are less.
The researchers haven’t discovered anything unusual yet, but FlavorGraph is just the starting point.
The team writes: As science develops and food representations are better, we must discover more and more interesting associated ingredients, as well as new alternatives to ingredients that are either unhealthy or unsustainable.