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Better Service at Restaurants — With AI and Deep Learning

AI is found in most industries these days.

AI is actively changing health care and finance every day. However, AI is still a baby in the foodservice industry. In 2016, the U.S. Foodservice accounts for 2.1 percent of GDP. Although it is not large, the U.S. is the second-largest owner of restaurants, and people interact with restaurants every day. That means the AI services ​​will soon be entering your eating experience.

Here’s how:

AI in restaurants

Robots don’t take your order at a fine dining establishment across the street. AI’s initial foray into food service is simple: online ordering.

Chatbots are already working here, helping when you order online for pizza. Chatbots and AI-based online ordering systems can fully automate restaurant takeout and delivery. That means fewer human defects in your diet.

Here’s how AI can help with food service:

Recommendations.

Netflix, Spotify, and Amazon are already telling you what you want. The natural next step is to find our food preferences, allergies, or dietary restrictions. Food ordering apps can remind you of that recipe (or something you hated) the last time you liked it, and recommend trying similar items if you’re worried about new things.

Assessing food quality.

Video Intelligence can determine the quality of food to ensure that things are up to date and in good shape.

Kiosks

Self-ordering kiosks are already showing up at some counter-service and fast-food restaurants, including Panera and McDonald’s. These kiosks reduce flaws because people put their own order first instead of telling someone else. Kiosks can save money on maintenance and smooth the entire customer experience, so you can expect most of them to be found in casual dining areas.

Robots

Robots are assisting in the foodservice while not looking big. The more common use is with food preparation or delivery and optimization in warehouses and distribution centers. However, “Flippy” helps cook burgers at Caliberger and the original robot waiter.

“Pepper” takes your order to other locations in Asia, including MasterCard Cafe and Pizza Hut.

AI in Restaurant Management

One of the most valuable uses of AI is data analysis. There has not been much mention of companies using AI to predict food orders, revenue, inventory or customer traffic, but some companies have begun delivering that data to restaurant groups.

One such program, Ingest.AI, takes data about food distribution, shift hours, staffing, reservations, vendors and bill payments. Most restaurants use a variety of software programs to perform related tasks, but none interact or produce a big picture, resulting in food waste and wasting time and money.

According to Wired Magazine, the AI ​​program “uses all of the data bits to bundle all the data bits together and give the restaurant a 360-degree view of its operations”.

Data helps restaurants to automate scheduling.

An indication of more busy or slower nights than scheduled. Design menus based on popular items, maintain inventory and track good or on-track staff in over-selling.

The restaurant can also know your preferences, make it easy for your server to serve your favorite dish and store your credit card on file for a hassle-free experience.

Deep learning in the food industry

There may also be a place in our diet for deep learning. Deep learning is a subset of AI. Deep learning uses artificial neural networks (ANN), a computing path that simulates the human brain — unless we have billions of neurons, and large ANN can hold thousands of neurons.

These neurons function in many layers, from which we get the “deep” part of deep learning. Each layer can add and count new information.

Deep Learning Project

A team of Harvard students used deep learning in a project for TripAdvisor to help those searching for restaurants. The event took pictures of restaurants and visitors uploaded and categorized them into five categories: Food, Beverages, Interior, Exterior and Menu. The results are, on average, 87 percent accurate.

Photos

A similar project aimed at evaluating restaurant properties by analyzing user photos using 200,00 images on Yelp.

The future of AI and eating

The costs associated with AI and deep learning are too high for single-owner restaurants to manage. But as AI becomes less expensive and begins to save people money and time, you can bet it’ll be serving you up a plate of food in one way or another very soon.

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