Leading International Research on Artificial Intelligence and Machine Learning
Data, Knowledge, Context
Researchers at the Lamarr Institute are dedicating themselves to Machine Learning and Artificial Intelligence in order to create the AI applications of the future based on data, expert knowledge and contextual information.
Talent for the Future
Our goal is to educate the next generation of AI experts at the highest level. We promote talent in schools, universities as well as professional education and training – for a career in science or business.
Impulses for Innovation
We are shaping the future of European AI: By combining cutting-edge research and practical experience in companies, we develop powerful, trustworthy and sustainable AI solutions – for business and society.
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The Lamarr Institute for Machine Learning and Artificial Intelligence
The scientists of the Lamarr Institute are dedicated to research and development in the field of Machine Learning (ML) and Artificial Intelligence (AI).
We create the future of European AI: Combining leading research with hands-on experience in business application, we develop high-performing, trustworthy and sustainable AI solutions.
Our research activities are based on the central paradigm ‘Triangular AI’ (AI3) – a new and high-performance generation of Artificial Intelligence that is not only trained based on data, but also uses additional knowledge and contextual information.
Sustained excellence in research is only possible with sustained excellence in educating the next generation of highly qualified scientists.
Prof. Dr. Christian Bauckhage
Director Lamarr Institute
Leading International AI Research
Internationally renowned researchers work with the best young talents in AI to investigate how Machine Learning algorithms, models and applications need to be designed in order to deliver more powerful yet reliable, trustworthy results. We conduct our research and development in a way that software and hardware operate in a sustainable and resource-efficient manner.
Hybrid Machine Learning
Hybrid Machine Learning aims at an integrated treatment of empirical data, world knowledge, and application contexts.
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Resource aware ML
Resource-aware Machine Learning aims to adapt technologies to save energy, memory and computational resources
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Trustworthy AI
Trustworthy AI builds on robust, verifiable procedures and forms the basis for certifying AI applications.
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Human centered AI
Human-centered AI Systems are designed to interact with humans and deliver explainable and comprehensible results.
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Embodied AI
Embodied Artificial Intelligence refers to AI that is embedded in physical systems, such as robots, and can interact with the surroundings.
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Planning & Logistics
AI solutions help optimize transportation and mobility processes and save resources.
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Physics
Using ML methods, large data quantities are analyzed and evaluated thus providing new insights into the physical world.
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Industry & Production
AI allows the use of machine models and production data for intelligent control and increased efficiency.
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Life Sciences
AI is revolutionizing medicine, accelerating drug development, and assisting in the study of biological systems.
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Natural Language Processing
Understanding spoken and written language is the basis for many AI applications that facilitate our everyday lives.
read moreBlog on Machine Learning and Artificial Intelligence
Here, researchers have their say: The ML blog of the Lamarr Institute addresses current developments and trends and explains the scientific background. Discover the latest articles from the categories basics, research and application!
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