How the Food Industry Incorporates with AI?
Back in the past days, the food industry faces a dilemma, which is time-consuming, high volume but low-margin. However, the advent of AI implements new energy to run this industry in another useful way. Below, the article unveils three applications of AI in food-processing.
- Sorting products
On the sides of manufacturing, the challenge is to sort out each plant based on the quality, color, shape, and size. Facing to tons of plants, it heavily weights on the manual labor and consumes more times with inefficiency. Fortunately, a significant breakthrough in AI overturns the industry. And data is an integral part of the process. For example, in a Japanese company, Kewpie, it deploys Google’s TensorFlow to teach machine learning to detect anomalies automatically. The sample data of acceptable plants is implemented in the machine. Thus it can only identify those who match with the data input and throw out the defectives. Below is the visualized version of the mechanism.
2. Improving the customer experience.
Customization is becoming prevailing in the current days. Customers embrace brands that take care of their needs and thoughts. The same thing occurs in the food industry. Flavors, level of spices, and ingredients are all essential variables that affect the performance of recipes. To meet customers’ expectations, using AI might be a witty choice. In Coca-Cola, the installment of self-service that allows individuals to customize their drink is an intelligent use of AI. By collecting the data from customers, the food-processor can predict the taste trends regarding what customers chase now, and they will want in the future, offering rationality outside-of-box suggestions.
3. Speeding up the creativity with accuracy
Creativity is essential in food-making since none of the customers can accept immutable recipes in restaurants. However, changing methods is risky. Therefore, human invites AI as a consulting role to determine the matching formula. For example, in the system powered by IBM’s Chef Watson, it is capable of analyzing thousands of ingredient pairs. The AI can come out the result of what ingredients to add to t to new cuisine and what if a particular component is like to taste food together or not. In this case, it cuts down unnecessary times to do the experiment and encourage more creativity running.
To sum up, it is inevitably hat data becomes powerful while meeting the AI. The automatic system can now, in seconds, collects a variety of data from real customer experiences, make an assessment, and output the result, which complies with each individual. However, the concern is evident as well. “Subjectivity” is a vital human element that trips up AI. People’s tastes change in an unexpected way that AI overlooks. Therefore, in views of technology that can’t determine the human mind, companies need to invest in artificial intelligence wisely and cautiously.
