Innovation and collaborative, synchronized program management for new programs
Aerospace & Defense
Innovation and collaborative, synchronized program management for new programs
Explore IndustryAutomotive & Transportation
Integration of mechanical, software and electronic systems technologies for vehicle systems
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Product innovation through effective management of integrated formulations, packaging and manufacturing processes
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New product development leverages data to improve quality and profitability and reduce time-to-market and costs
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Supply chain collaboration in design, construction, maintenance and retirement of mission-critical assets
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Construction, mining, and agricultural heavy equipment manufacturers striving for superior performance
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Integration of manufacturing process planning with design and engineering for today’s machine complexity
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Visibility, compliance and accountability for insurance and financial industries
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Shipbuilding innovation to sustainably reduce the cost of developing future fleets
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Siemens PLM Software, a leader in media and telecommunications software, delivers digital solutions for cutting-edge technology supporting complex products in a rapidly changing market.
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“Personalized product innovation” through digitalization to meet market demands and reduce costs
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Remove barriers and grow while maintaining your bottom line. We’re democratizing the most robust digital twins for your small and medium businesses.
Explore IndustrySiemens Digital Industries Software AI and Machine Learning
Siemens Digital Industries Software AI and Machine Learning
In recent years, advances in hardware technology and software techniques have made it possible and practical for machine learning (ML) to provide better solutions to many real-world problems, even on embedded devices.
Nevertheless, embedded ML presents a unique set of challenges, including hardware resource requirements and performance considerations, the need for integration of specialized software technologies, and not least the learning curve – including a dependency on skill sets that are often not present in existing development teams.
Siemens Embedded's platform solutions and professional services enable our customers to get started quickly and easily with ML and allow them to focus on how ML can add value to their products, without first having to solve a bewildering and time-consuming array of complex platform-level challenges.
In recent years, advances in hardware technology and software techniques have made it possible and practical for machine learning (ML) to provide better solutions to many real-world problems, even on embedded devices.
Nevertheless, embedded ML presents a unique set of challenges, including hardware resource requirements and performance considerations, the need for integration of specialized software technologies, and not least the learning curve – including a dependency on skill sets that are often not present in existing development teams.
Siemens Embedded's platform solutions and professional services enable our customers to get started quickly and easily with ML and allow them to focus on how ML can add value to their products, without first having to solve a bewildering and time-consuming array of complex platform-level challenges.
ML solutions are typically built upon open-source framework software. The Siemens Embedded Sokol™ Machine Learning Add-on solution includes an integration of the most popular ML engine for production embedded projects, TensorFlow Lite.
Other engines and frameworks can be provided on request. The framework is integrated with the Siemens Embedded Linux platforms Sokol™ Omni OS and Sokol™ Flex OS, optimized for the hardware target, rigorously tested, commercially supported, and monitored for CVEs alongside the rest of our platform software.
Customers can be assured that the ML platform software upon which their applications are built is always robust, reliable and secure, from right out of the box.
For customers that need additional help, our team of ML integration specialists offer both professional services and long-term premium support. Examples of work undertaken include integration of sensors and processing pipelines to drive ML inference, integration of alternative ML frameworks, integration of AI accelerators or other hardware devices, and performance optimization and tuning.
Sokol™ Machine Learning Add-on also benefits from integration with our other tools and frameworks.
Customers can easily build and debug platforms and applications from within the Sourcery™ Codebench™ IDE, and visualize and analyze performance of ML solutions using Sourcery™ Analyzer, allowing complex system-level performance issues to be diagnosed.
ML solutions can be monitored and managed from the cloud using Sokol™ IoT Framework, including data acquisition, analysis of system performance, and update of ML models in the field.