How AI helped Domino’s improve pizza delivery

When the words artificial intelligence (AI) and machine learning (ML) are used, people often think of advanced industries such as space exploration and biomedicine that rely heavily on research and development. The fact is, AI and ML should be something all industries are looking at, including retail. We are now in the customer service era and small differences in service can make a big difference in market share.

This past week Nvidia held a virtual version of its annual GPU Technology Conference (GTC), which has become a showcase for real life AI/ML use cases. Historically, the show has been a highly technical one, but over the years, it has evolved into an event where companies showcase how they use advanced technologies to transform their businesses.

Domino’s is using AI and ML to improve store and online operations

Domino’s is an example of a familiar retail business that presented how it’s using AI and ML. The company has come up with a successful recipe to change the way it operates. The secret ingredient is Nvidia’s technology, which the leading pizza chain is using to improve store and online operations, provide a better customer experience, and route orders more efficiently.

As a result, Domino’s is seeing happier customers and more tips for its drivers. But that’s only a small piece of the multifaceted pie. So, what does it take to get pizza from a Domino’s store to someone’s house? The answer is quite complex.

Nvidia DGX-1 server enabled Domino’s to accelerate its AI and ML initiatives

The data science team at Domino’s tested the company’s speed and efficiency by leveraging Nvidia’s DGX-1 server, an integrated software and hardware system for deep learning research. For those not familiar with the DGX server line, Nvidia has created a series of turnkey appliances businesses can drop in and start using immediately. The alternative is to cobble together hardware, software, and AI platforms and tune the entire system correctly. This can take weeks to do.

The Domino’s team created a delivery prediction model that forecasts when an order would be ready, using attributes of the order and what is happening in a Domino’s store, such as the number of employees, managers, and customers present at that moment. The model was based on a large dataset of five million orders, which isn’t massive but large enough to create accurate models. All future orders are fed back into the system to further increase model accuracy.

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