You are currently viewing How BMW Group has embraced AI for positive use cases and to improve sustainability | AWS re:Invent

How BMW Group has embraced AI for positive use cases and to improve sustainability | AWS re:Invent

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Synthetic intelligence (AI) helps many varied industries and is having an especially steady impact within the automobile industry. Amongst the most delightful use cases is for fully self reliant vehicles, nonetheless that’s no longer the single condominium the build AI is having an impact. For instance, Microsoft and Mercedes-Benz are working together to enhance car manufacturing effectivity. 

On the AWS re:Assign cloud convention this week, BMW Crew outlined the impact that AI has had on its organization and detailed rising use cases the build AI will yield future sure industry outcomes.

In a session, Marco Görgmaier, GM, recordsdata transformation and synthetic intelligence, BMW Crew, said that his personnel had constructed up a library of thousands of recordsdata resources across the company that may presumably perchance also furthermore be reused for analysis and AI. Since 2019, he said his personnel has been ready to direct extra than 800 use cases which relish yielded over $1 billion in U.S. dollar price. The use cases span analysis and vogue, logistics, gross sales, quality and seller community.

“The vision and the mission of our personnel is to pressure and scale industry price advent throughout the utilization of AI across our price chain,” Görgmaier said.


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BMW riding toward a sustainable future with some abet from AI

An rising condominium the build BMW is now investing sources is in serving to to enhance sustainability. 

Görgmaier commented that 60% of the realm’s inhabitants lives in cities and concrete areas and that’s furthermore the build 70% of greenhouse gasoline emissions are generated. What BMW is now searching out for to perform is abet metropolis planners in solving complications to abet sever emissions.

BMW is already serving to with machine finding out units that are ready to foretell how website online traffic laws can doubtlessly abet to sever each and every website online traffic and gasoline emissions. ML units are furthermore old-fashioned to abet name the build there isn’t but ample electrical car charging infrastructure. Görgmaier said that an absence of charging infrastructure prevents of us from switching to an electrical car, which in flip has an impact on sustainability.

There is furthermore a BMW ML effort to abet predict the impact of parking condominium availability and pricing on riding patterns. Those patterns consist of commuting routes and website online traffic, which furthermore can relish an impact on emissions.

Using geospatial recordsdata with Amazon SageMaker

Görgmaier said that quite loads of the urban sustainability complications that BMW is making an are attempting to abet resolve can procure pleasure from geospatial recordsdata. That’s the build BMW is initiating to style use of unique geospatial capabilities within the Amazon SageMaker ML tool suite that were steady publicly published this week.

One condominium the build BMW is taking a look to procure pleasure from geospatial ML is for serving to to foretell when a company with a shortly of vehicles may be ready to transition to electrical vehicles.

“We role up the unbiased to recount machine finding out units to learn correlations between engine style and riding profiles,” he said. “The rationale on the abet of that used to be if this kind of correlation would exist, then the mannequin may presumably presumably learn to foretell the affinity of decided drivers for an electrical car primarily based totally on their profiles.”

As BMW used to be working with fully anonymized recordsdata at a shortly stage, it needed to use GPS traces and geospatial recordsdata to style the correlations.

“On the stop of the coaching, the mannequin used to be in a position to predicting how likely it used to be for explicit fleets to rework to EV with an accuracy of additional than 80%,” Görgmaier said.

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