Sponsored Content by NVIDIA

How AI helps Domino’s predict when 3 billion pizzas are ready to go

by Zachary Fragoso, Manager, Data Science and AI, Domino’s

Zachary Fragoso is a manager of data science and AI at Domino’s in Ann Arbor, Michigan.

AI is ready for the enterprise. I know because I’m part of a team at Domino’s that’s delivering business results with the technology today.

I won’t claim it’s easy, but I do know success is out there for people ready to do the work needed to master this emerging approach to computing. I hope our experiences can inspire others to experiment with AI in their business, and figure out what works best for them.

Leveraging Docker and our NVIDIA DGX-1 cluster, Domino’s data science team has aligned on a standard way of building AI models and deploying APIs inside well-packaged virtual environments. Having a system to manage a model’s lifecycle greatly eased the transition from development to integration with our production platforms managed by our business partners. 

As a result of that work, Domino’s has been able to boost productivity. We train and iterate on AI models faster and get them deployed to inference systems at lightning speed, accelerating time to positive business outcomes.

The big challenge for us was integrating our AI-enabled microservices into our e-commerce and in-store platforms. The teams running these platforms have been keeping one of the largest global e-commerce sites running for decades.

Our data science team, while quite mature, is relatively new. So we had to learn about software development at scale. Our internal partners had to learn about model development cycles. With a little flexibility, both sides succeeded.

Scoring with AI at the Super Bowl

We have a diverse team at Domino’s, but we’re all united on the mission to make the customer experience and store operations better.

AI has helped us achieve this mission: by rewarding customers for ordering pizza, by giving them a better estimate of when their order will be ready, and by improving their phone ordering experience. Routing orders more efficiently even helps our drivers get more tips!

Points for Pie, Domino’s highest profile AI project to date, launched around last year’s Super Bowl. The concept allowed customers to snap a picture of the pizza eating, and in exchange we gave them loyalty points toward a free pizza from Dominos.

Part of the Domino’s data science team with one of its NVIDIA DGX-1 servers. (Photos courtesy of Domino’s)

The idea generated a lot of excitement within the organization early on, but no one was sure how to effectively recognize purchases and award points.

The data science team joined the conversation because we knew this could be a great AI application. We built a model using a deep learning neural network that classified pizza images.

We trained our model on an NVIDIA DGX system using more than 5,000 images of pizzas. A customer survey sent in response to the pictures helped automate some of the job of labeling the unique dataset. The system was even able to recognize unexpected images of plastic, dog toy pizzas.

The response to this campaign was overwhelmingly positive. We got a lot of press and massive redemptions of coupons, so we knew our customers were embracing the campaign.

Serving up a superior AI system

We acquired two NVIDIA DGX-1 systems to accommodate our growing team. Our server-based approach provides an affordable way to train large, complex models and share knowledge across the team. 

Our team started training models on Windows desktops with single NVIDIA GPUs, but we knew that wouldn’t scale. We quickly realized local development can be more expensive than a server-based approach for large data science teams. What’s more, developing AI models across desktops with different configurations makes collaboration very difficult.

Using a DGX-1, we’ve seen training time for a single model drop from multiple days to multiple hours. The ability to quickly iterate and train multiple models simultaneously is like going from an Easy-Bake Oven to a Domino’s industrial pizza oven!

We adopted a strategy of training and deploying models on-premises for two reasons. We feel it gives us tighter control over both security and how we dynamically scale our services.

Baking algorithms for better predictions

Making quick decisions is important when you need to deliver more than 3 billion pizzas a year — fast. So, Domino’s is exploring the use of AI for a host of applications, including more accurately predicting when an order will be ready.

We recently boosted accuracy from 75% to 95% for predictions of an order’s readiness. We used what we call a load-time model that factors in labor variables, order complexity and other operational factors.

The improvement has been well received and could be the basis for future ways to advance operator efficiencies and customer experiences, thanks in part to NVIDIA GPUs.

Domino’s does a very good job cataloging data in its stores. But until recently, we lacked the hardware to build a model large enough to handle all the load-time factors. At first, it took three days to train the load-time model, too long to make its use practical.

Once we had our DGX server, we could train an even more complicated model in less than an hour, thanks to a 72x speed-up. That let us iterate our model’s design very quickly, adding new data and improving the model, which is now in production in a version 3.0.

Accelerating predictions and queries

One of the next big steps for our team is tapping a bank of  to accelerate AI inferencing for all Domino’s tasks that involve real-time predictions.

Model latency is extremely important, so we’re building out an inference stack using T4 GPUs to host our AI models in production. We’ve already seen pretty extreme improvements, with latency down from 50 milliseconds to sub-10 ms.

Separately, we recently adopted BlazingSQL, open-source software to run data-science queries on GPUs. Migrating your work to a new platform takes some doing, but software eased the transition, supporting the APIs from a prior CPU-based tool while delivering better performance.

This new GPU-accelerated data science platform is delivering an average 10x speed-up across all use cases in the part of the AI process that involves building datasets. In the past, some of the data-cleaning and feature-engineering operations might have taken 24 hours. Now we do them in less than an hour.

Here at Domino’s we’re just getting started with AI. We’re having impact translating analytics insights into actionable items for our stores that are meaningful for our business. 

The most vital element in this work is collaboration. AI reaches its full potential when data science teams form a user group that shares Docker file specs, data connectors, and GPU management code. All of these things help the team put out quality products faster.

Collaboration should extend outside your company. From my experience, the experts at NVIDIA keep up with cutting-edge tools and methods and have a very good grasp of how companies are using their products. 

Hungry for more?

If I’ve managed to whet your appetite and you’d like to learn more, I encourage you to check out the presentation I’ll be giving about Domino’s experience with AI during NVIDIA’s GTC Digital conference. Registration for NVIDIA’s GTC Digital conference is FREE and will allow you to explore dozens of live webinars and libraries of on-demand content detailing the experiences of those on the front lines implementing AI and other cutting-edge technologies. 

As you see, I’m not alone. There’s a growing community of data scientists who know AI is ready to deliver real business successes. If you’re ready to join us, I’m confident AI can deliver results for your business.

 

More TechCrunch

After Apple loosened its App Store guidelines to permit game emulators, the retro game emulator Delta — an app 10 years in the making — hit the top of the…

Adobe comes after indie game emulator Delta for copying its logo

Meta is once again taking on its competitors by developing a feature that borrows concepts from others — in this case, BeReal and Snapchat. The company is developing a feature…

Meta’s latest experiment borrows from BeReal’s and Snapchat’s core ideas

Welcome to Startups Weekly! We’ve been drowning in AI news this week, with Google’s I/O setting the pace. And Elon Musk rages against the machine.

Startups Weekly: It’s the dawning of the age of AI — plus,  Musk is raging against the machine

IndieBio’s Bay Area incubator is about to debut its 15th cohort of biotech startups. We took special note of a few, which were making some major, bordering on ludicrous, claims…

IndieBio’s SF incubator lineup is making some wild biotech promises

YouTube TV has announced that its multiview feature for watching four streams at once is now available on Android phones and tablets. The Android launch comes two months after YouTube…

YouTube TV’s ‘multiview’ feature is now available on Android phones and tablets

CSC ServiceWorks provides laundry machines to thousands of residential homes and universities, but the company ignored requests to fix a security bug.

Two Santa Cruz students uncover security bug that could let millions do their laundry for free

OpenAI’s Superalignment team, responsible for developing ways to govern and steer “superintelligent” AI systems, was promised 20% of the company’s compute resources, according to a person from that team. But…

OpenAI created a team to control ‘superintelligent’ AI — then let it wither, source says

TechCrunch Disrupt 2024 is just around the corner, and the buzz is palpable. But what if we told you there’s a chance for you to not just attend, but also…

Harness the TechCrunch Effect: Host a Side Event at Disrupt 2024

Decks are all about telling a compelling story and Goodcarbon does a good job on that front. But there’s important information missing too.

Pitch Deck Teardown: Goodcarbon’s $5.5M seed deck

Slack is making it difficult for its customers if they want the company to stop using its data for model training.

Slack under attack over sneaky AI training policy

A Texas-based company that provides health insurance and benefit plans disclosed a data breach affecting almost 2.5 million people, some of whom had their Social Security number stolen. WebTPA said…

Healthcare company WebTPA discloses breach affecting 2.5 million people

Microsoft won’t be facing antitrust scrutiny in the U.K. over its recent investment into French AI startup Mistral AI.

Microsoft dodges UK antitrust scrutiny over its Mistral AI stake

Ember has partnered with HSBC in the U.K. so that the bank’s business customers can access Ember’s services from their online accounts.

Embedded finance is still trendy as accounting automation startup Ember partners with HSBC UK

Kudos uses AI to figure out consumer spending habits so it can then provide more personalized financial advice, like maximizing rewards and utilizing credit effectively.

Kudos lands $10M for an AI smart wallet that picks the best credit card for purchases

The EU’s warning comes after Microsoft failed to respond to a legally binding request for information that focused on its generative AI tools.

EU warns Microsoft it could be fined billions over missing GenAI risk info

The prospects for troubled banking-as-a-service startup Synapse have gone from bad to worse this week after a United States Trustee filed an emergency motion on Wednesday.  The trustee is asking…

A US Trustee wants troubled fintech Synapse to be liquidated via Chapter 7 bankruptcy, cites ‘gross mismanagement’

U.K.-based Seraphim Space is spinning up its 13th accelerator program, with nine participating companies working on a range of tech from propulsion to in-space manufacturing and space situational awareness. The…

Seraphim’s latest space accelerator welcomes nine companies

OpenAI has reached a deal with Reddit to use the social news site’s data for training AI models. In a blog post on OpenAI’s press relations site, the company said…

OpenAI inks deal to train AI on Reddit data

X users will now be able to discover posts from new Communities that are trending directly from an Explore tab within the section.

X pushes more users to Communities

For Mark Zuckerberg’s 40th birthday, his wife got him a photoshoot. Zuckerberg gives the camera a sly smile as he sits amid a carefully crafted re-creation of his childhood bedroom.…

Mark Zuckerberg’s makeover: Midlife crisis or carefully crafted rebrand?

Strava announced a slew of features, including AI to weed out leaderboard cheats, a new ‘family’ subscription plan, dark mode and more.

Strava taps AI to weed out leaderboard cheats, unveils ‘family’ plan, dark mode and more

We all fall down sometimes. Astronauts are no exception. You need to be in peak physical condition for space travel, but bulky space suits and lower gravity levels can be…

Astronauts fall over. Robotic limbs can help them back up.

Microsoft will launch its custom Cobalt 100 chips to customers as a public preview at its Build conference next week, TechCrunch has learned. In an analyst briefing ahead of Build,…

Microsoft’s custom Cobalt chips will come to Azure next week

What a wild week for transportation news! It was a smorgasbord of news that seemed to touch every sector and theme in transportation.

Tesla keeps cutting jobs and the feds probe Waymo

Sony Music Group has sent letters to more than 700 tech companies and music streaming services to warn them not to use its music to train AI without explicit permission.…

Sony Music warns tech companies over ‘unauthorized’ use of its content to train AI

Winston Chi, Butter’s founder and CEO, told TechCrunch that “most parties, including our investors and us, are making money” from the exit.

GrubMarket buys Butter to give its food distribution tech an AI boost

The investor lawsuit is related to Bolt securing a $30 million personal loan to Ryan Breslow, which was later defaulted on.

Bolt founder Ryan Breslow wants to settle an investor lawsuit by returning $37 million worth of shares

Meta, the parent company of Facebook, launched an enterprise version of the prominent social network in 2015. It always seemed like a stretch for a company built on a consumer…

With the end of Workplace, it’s fair to wonder if Meta was ever serious about the enterprise

X, formerly Twitter, turned TweetDeck into X Pro and pushed it behind a paywall. But there is a new column-based social media tool in town, and it’s from Instagram Threads.…

Meta Threads is testing pinned columns on the web, similar to the old TweetDeck

As part of 2024’s Accessibility Awareness Day, Google is showing off some updates to Android that should be useful to folks with mobility or vision impairments. Project Gameface allows gamers…

Google expands hands-free and eyes-free interfaces on Android