Will AI inspire a new M&M? How artificial intelligence is reshaping Mars


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Could AI text-to-image generators like DALL-E inspire new designs for iconic candies like M&Ms or Skittles?

As a candy-filled Halloween approaches, it seemed an obvious question to ask the head of AI and machine learning at Mars Inc. — a company that has over the past century created a range of popular candy brands from M&Ms to Milky Way and Snickers has overseen; grown into a CPG giant, owning brands like Dove, Pedigree and Whiskas; and now claims to care for half of the world’s pets through nutrition, health and service companies like Banfield Pet Hospitals and Anicura.

While Shubham Mehrish, global vice president of digital strategy at Mars Inc., wouldn’t say if an AI-designed M&M is on the horizon, he did sound bullish on DALL-E and other AI art tools for idea generation at Mars.

DALL-E will increase creativity

“The DALL-E team was stingy in granting access, but some of our AI scientists are already playing with it,” he told VentureBeat. “I think DALL-E will not replace the creative endeavor, it will expand it – we will use DALL-E as inspiration and have started to at least play with his abilities on Mars.”

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Mehrish, who leads Mars’ global digital, data and analytics teams, including in AI and machine learning, says the effort with DALL-E is just a tiny part of the massive AI-focused digital transformation journey Mars is embarking on has undertaken in the past five years.

“We’re about halfway there, so we’re still on that path,” said Mehrish, who joined Mars in 2018 after a two-decade career in banking, technology, consulting, strategy and data science. The efforts behind AI and digital transformation at Mars, he explained, came from outgoing CEO Grant Reid with a focus on agile development, speed and scale.

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“It’s a heart project that our new CEO, Poul Weihrauch, will continue and build on, so it’s really a top-down mandate and it’s always been a very high priority for the company,” said Mehrish.

At this point, there is no question of when Mars will use AI, he added: “It’s about finding a process of where we are Not with AI and machine learning today.”

Artificial intelligence improves animal care

An example of Mars Inc.’s strong AI focus is the company’s pet business.

“We are now the largest veterinary hospital chain in the US and the largest pet care company in the world,” said Mehrish, who explained that Mars uses AI in its pet food business to forecast commodity prices, track inflation and optimize pricing decisions. Promotions and assortments.

In 2016, Mars spent $117 million to acquire Whistle, a smart collar startup known as “Fitbit for dogs.” Last May, Whistle launched Whistle Health, an AI-enabled, data-driven smart device for canines for prevention that, according to a press release, “can convert each dog’s movements into a personalized, holistic wellness index,” including health behaviors like eating, Drinking, Scratching, Licking, Sleeping and Fitness.

“These are based on huge training sets with built-in machine learning and AI that give you a score that you can use to track your dog’s health and also connect with a vet,” Mehrish said.

A sweet use of AI for products and supply chains

At Mars’ candy store, AI is combined with sensors on the production line to increase speed and accuracy while reducing costs. In 2021, the company announced a digital twin initiative with Microsoft to develop virtual clones of its physical supply chain operations to simulate scenarios that would be too difficult to test with physical assets.

“We can now perform preventative maintenance using AI methods to see where problems are occurring on the line so we can improve capacity and slowly automate certain components of this process,” he explained, adding that AI can even be used to determine candy bugs is used.

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“Imagine an M&M running on a conveyor where we can see shape deformations through image recognition and extend human workers doing quality assurance to look at M&Ms and decide if they are good enough to pack or not not,” said Mehrish.

In addition, the company also uses AI in its upstream supply chain. “We can look at weather patterns and see how our crops are doing and actually predict cases of fungi affecting our raw material in India and Africa,” he said. The Mars Advanced Research Institute (MARI) and the University of Tennessee’s National Institute for Computational Sciences recently established the Mars Advanced Research Virtual Environment Lab (MARVEL) to perform next-generation data analytics and make the science behind Mars products and services better to understand.

For example, aflatoxin is a toxic but little-known natural product made by certain fungi. Specialists from the University of Cambridge and Mars Digital Technologies use MARVEL to predict the likelihood of aflatoxin in corn by analyzing data on things like humidity, temperature and precipitation, all of which affect whether aflatoxin can grow.

MARI also recently announced a multi-year agreement with AI company PIPA to accelerate the discovery of new herbal ingredients. LEAP, PIPA’s AI platform, combines AI, knowledge graphs and bioinformatics to highlight connections between food, compounds, microbes and health conditions.

Development of data science teams at Mars

Explaining the evolution of Mars’ AI teams, Mehrish said the company quickly realized that multiple small peaks wouldn’t work. Instead, a centrally controlled route was needed for the first wave of transformation.

“We hired data scientists and data engineers at the heart of the business — the marketing center, the corporate center,” he said.

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In the past two years, the company has shifted into what it calls a “federated growth center,” where the lines of business added their own data scientists and engineers.

“This is the second wave, where we’re digging deeper into the organization and educating our people from a bottom-up perspective,” said Mehrish.

This move will continue over time, he added, moving to local markets with dedicated AI teams with centralized oversight and governance around best practices, knowledge, sharing and artifacts.

Increasingly, Mars has also reconfigured teams into products and platforms.

“For example, I oversee the entire data lake platform for the business and the infrastructure – we decide the tools that the businesses work with, decide the governance, and then let them work within that framework that incorporates privacy and security,” he said. “And then every company has product teams that focus on specific use cases, like B. strategic revenue management.”

Mars goes from AI laggard to leader

Mars has been a bit of a latecomer when it comes to AI in consumer packaged goods (CPG), admits Mehrish. Now the company is a CPG leader according to its external benchmarking.

“But my intention is not to compare us to CPG companies, but to the Googles and Amazons of the world,” he said. “That’s really the inspiration I try to encourage in our teams.”

Today, Mehrish, who comes from financial services rather than CPG, finds consumer staples a satisfying industry — and not just in terms of candy.

“They’re dealing with products that consumers touch and feel and interact with every day, and in our case they consume,” he said. “The fact that people’s eyes light up when you say where you work is just another level of satisfaction.”

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