AI in Food Processing – An Application Overview From Farm to Fork

Artificial intelligence has enormous applications in various fields, including the food industry.

- Dr. Kaushik Ramakrishnan, Chief Research Manager, F1RST

The application of AI starts right at the farm and ends at the consumer level with varying degrees of sophistication and utilization. It must be remembered at the outset that Al is simply a powerful means of organizing existing data collection and decision-making processes. It is important to separate the hype from existing solutions that have been around for a long time, to get a feel for the real and practical applications of AI-based technologies in food processing.

A quick primer on AI

At the heart of Al lies machine learning, deep learning, and neural networks. Machine learning, at its core, is simply the science of teaching computers to learn patterns from data. Inside machine learning, supervised learning is the most widely used approach across industries — because it mirrors human teaching so naturally. Unsupervised learning groups things based on similarities without any labels, without any instruction. Reinforcement learning embodies trial-and-error improvement. As you can see, each of these learning models has its own unique advantages:

• Supervised learning gives us accuracy, precision, and consistency.

• Unsupervised learning gives us discovery, insight, and structure.

• Reinforcement learning gives us optimization, adaptability, and skill.