Siemens develops AI models faster with Microsoft Azure-based platform

Siemens develops AI models faster with Microsoft Azure-based platform


Technology company is able to create production estimates and provide support to departments more efficiently  

Alice Chambers |

Technology company Siemens has used Microsoft Azure to create a platform that enables it to develop and deploy artificial intelligence models more efficiently.

The platform, now being used by more than 500 Siemens employees, builds AI models to create production estimates and provide targeted support for different departments such as manufacturing, infrastructure, transport and healthcare. It has enabled Siemens to create a variety of models without needing to write new code for each one, which was previously time consuming for data analysts.

Siemens is using Azure Cognitive Services to provide the components for the platform, the Azure Machine Learning Studio to help analysts monitor the development of model workflows, and Computer Vision, which uses AI models to identify damaged devices in images. 

“Since the platform has introduced a standardised language across Siemens, the departments and the data analysts can collaborate much more closely and productively,” said Dr Ioannis Petrakis, IT principal of key expert data analytics and AI at Siemens, in a recent Microsoft customer story. “Now our focus is on creating real added value while the platform itself manages the models and infrastructures.

“The automated training of machine learning models in Azure was particularly important to us: this makes it possible to create AI models automatically. As a result, we are a lot faster and have cut our development time down from several months to a few weeks.”

Siemens first began using AI to streamline operations when it introduced the ‘ai:attack’ initiative in 2021 and has continued to expand its use of the technology  ever since. For example, it is using automated image analysis to detect any product damage and implementing AI to make returns management easier and automatically extract relevant data from incoming invoices to expedite finance processing.

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