Artificial intelligence (AI) is first and foremost transforming our relationship with food: the food we eat, as well as the dumb kitchens we rely on to prepare food, into something smarter, safer, and more personalized. Through the combined use of optical character recognition (OCR), machine learning, and applications like Eat IQ, we are using technology to advance food intelligence to ever-increasing scales.
The Digital Lens: OCR as the Portal into Food Intelligence
Optical character recognition, or OCR, is a critical technology that allows computers to read text that appears in or on an image. Nutrition labels on packaged foods, food choices on restaurant menus, and ingredient lists on recipes are just a few common examples of OCR applications. In the past, you could track what you ate either by manually logging it in or by deciphering complicated food names. Food apps today enable products with high-end OCR to do this at the point of purchase or consumption for you: basically in real time as you scan a package or photo of a dish.
The integration of OCR technology is important not only because speed matters, but also because the reliability and accuracy of what you intend to eat, or have eaten, is captured and has become part of the systems that govern smart food systems. The data from these digital assets is more reliable, and that data will drive deeper analytics, which then will lead to machine learning.
Machine Learning: The "Intelligence" in Smart Food
In addition to actually gathering data, the next step is understanding and taking action on that data—this is where machine learning comes into play. Machine learning makes use of immense datasets—taking advantage of dietary diaries, health records, or millions of recipes—to uncover patterns and form recommendations as needed.
A few ways that machine learning could be used in the food world include:
AI systems can analyze the dietary needs of individuals, suggesting meal plans that take into account an individual's biometric data, likes, dislikes, allergies, and lifestyle.
Algorithms may be able to observe food production lines in near real time and use computer vision (assisted by OCR in many cases) to flag contaminants, improper labeling, or possible allergens, thereby enhancing food safety.
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