First model for General Causality: Artificial Intelligence Breakthrough

Real-world problems in economics and public health can be very hard to analyse. Often, multiple causes are suspected but large datasets with time-sequenced data are not available. Previous models could not reliably analyse these challenges.

Now researchers have tested the first Artificial Intelligence model to identify and rank many causes in real-world problems, built on the concepts of Causal Independence and Causal Influence. The model significantly outperforms previous models using simulated real-world datasets.

See more at https://www.uj.ac.za/newandevents/Pag...
with researchers Prof Tshilidzi Marwala and Dr Pramod Kumar Parida from the University of Johannesburg. The research is published in the journal Neural Networks.

First model for General Causality: Artificial Intelligence Breakthrough johannesburg paris
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