Who invented backpropagation (BP)? Its modern version (also called the reverse mode of automatic differentiation) was first published in 1970 by Finnish master student Seppo Linnainmaa. A precursor of BP was published by Henry J. Kelley in 1960. The first NN-specific application of BP was described by Paul Werbos in 1982 (but not yet in his 1974 thesis, as is sometimes claimed). Some ask: "Isn't backpropagation just the chain rule of Leibniz (1676)?" No, it is the efficient way of applying the chain rule to big networks with differentiable nodes. (There are also many inefficient ways of doing this.) It was not published until 1970. See the backpropagation overview web page with more details: See also the "Annotated History of Modern AI and Deep Learning" (2022):