Several companies from Silicon Valley are taking advantage of AI's ability to accurately recognize images in order to benefit consumer's health decisions. For instance, Habit, founded by Nail Grimmer, uses a combination of genetics and machine learning to help personalize the user's diet, the startup Passio uses AI to give nutritional advice, and the New York based company Edamam implements Recipe Analysis API to provide nutritional information to the user.
Not only will artificial intelligence assist consumers, but they will also bring advantages to producers. In the future, AI could be able to help recognize agricultural diseases (researchers at Cornell already trained their own AI to identify brown leaf spot disease on cassava leaves with a 98% accuracy). Other applications of AI in the food industry include reducing the use of herbicides and other harmful chemicals through precision weeding or simply aiding in the harvest of crops.
But why is AI so good at decision making? A study done by Stanford reported on by FoodTanks concluded that the artificial neural networks (analogous to the brain's neural networks) are trained with "huge data sets and large-scale computing (deep learning), boosting data-driven solutions for improving decision making." To learn more about the difference in deep learning and machine learning, feel free to check out this article by Forbes.