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Our Fields Of Expertise

Deep Learning

What Motivates Us

Deep learning refers to a modern class of machine learning systems that rely on multi-stage processing of data in neural networks. As a field, it has produced some of the most exciting advances in AI in recent years: breakthroughs in computer vision, language understanding and speech recognition have all had their roots in deep learning. This makes deep learning the key enabler for Bosch applications in fields like automated driving, robotics, or embedded AI. However, despite this promise, modern deep learning systems also have some deficiencies that make them ill-suited to tasks relevant to Bosch: the systems are compute and data-hungry, often brittle in real-world deployments, and typically unexplainable. Addressing these challenges motivates our team to create robust, safe, and efficient deep learning systems as part of continuously learning AIoT products.​

Our Approach

At Bosch, we are pushing forward the boundaries of deep learning to make these systems fully realizable within products. We create new methods of explainable and robust deep learning models that are ready to be validated and safely used in real-world environments. We develop novel training methods and tools to scale deep learning systems towards working efficiently on various types of embedded hardware. This way, we extend deep learning concepts from computer vision to the entire range of Bosch sensors. Data-efficient learning and generative models allow us to augment data sets with realistic variations of scenes, thereby reducing the efforts for data collection and labelling.​


The broad product portfolio of Bosch offers countless application fields for modern deep learning systems. Some of our core domains include perception for driving assistants and automated driving, robotics, health care, smart cameras, and many other applications of Bosch AIoT devices.​