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Discovering the cause and effect relationships among natural events is crucial for understanding natural systems. For example, discovering the cause and effect relationships between high temperature, high humidity, low air pressure, warm ocean currents, etc. is crucial for understanding rainfall. Since natural systems are governed by complex interactions among a large number of variables, researchers have been developing artificial Intelligence-based computer algorithms to decipher them. In this talk, we will discuss one such algorithm which won the Turing Award a.k.a. the Nobel Prize of Computing in 2011. We will also reflect on what kind of causal discovery algorithms will need to be built in the future.
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