AI engineers solved the credit assignment problem for machines with a powerful algorithm called backpropagation, popularized in 1986 with the work of Geoffrey Hinton, David Rumelhart and Ronald Williams. It’s now the workhorse that powers learning in the most successful AI systems, known as deep neural networks, which have hidden layers of artificial “neurons” between their input and output layers. And now, in a paper published in Nature Neuroscience in May, scientists may finally have found an equivalent for living brains that could work in real time.
This is a really big deal. This is a storied problem, and this advance might even lead to a Nobel Prize in time.