How Machine Learning Fuels The Industrialisation Of Information Processing

 
Progress in autonomous vehicles and digital assistants shows that today’s machines can perform certain human tasks with remarkable accuracy. But they lack versatility and only work within limited domains for which large sets of training data are available. Transfer of knowledge, common sense, and an understanding of causality are open problems. As machine learning systems become pervasive, their role in our society is scrutinised and fascinating research areas open up, including accountability and fairness of automatic systems.

Bernhard Schölkopf is director at the Max Planck Institute for Intelligent Systems in Tübingen. With his foundational research, Bernhard has become one of the most important voices in international machine learning. His work includes methods of artificial intelligence that distinguish coincidental correlation from actual causation, as well as machine learning applications in fields ranging from medicine to astronomy. His research has won him several prestigious awards and he recently helped to start an AI lab funded by Amazon. At Falling Walls, Bernhard will show the essential role his research has in shaping the intelligent systems that are increasingly becoming part of our daily lives.

Bernhard Schölkopf

Max Planck Institute for Intelligent Systems

Bernhard Schölkopf is the director of the Max Planck Institute for Intelligent Systems in Tübingen. With his foundational research, Bernhard was able to become one of the most important voices in machine learning and specifically the area of causality. His work includes “common sense”-based artificial intelligence, which smartly separates coincidental correlation from actual causation. His research has won him several prestigious awards and he is currently co-heading an AI research lab funded by Amazon. Bernhard’s research is essential in shaping the intelligent systems we will increasingly interact with on a daily basis.

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