Remodelling machine learning: An AI that thinks like a scientist

Modern machine learning is great for helping scientists sort through huge, complex datasets. But it’s less useful for explanation and understanding cause and effect. This video illustrates a new approach to find the underlying algorithmic models that interact and generate data, to help scientists uncover the dynamics of cause and effect. This could aid researchers across a huge range of scientific fields, such as cell biology and genetics, answering the kind of questions that typical machine learning is not designed for.