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.
