Early in his career, IEEE fellow and retired National Science Foundation program director Paul Werbos developed the neural network training algorithm known as error backpropagation, which has been foundational to the vast majority of today’s advances in artificial intelligence. Listen in as he discusses his work in this area and other topics, including his tenure with the National Science Foundation, Read More ›
In today’s episode, Dr. Robert J. Marks continues his conversation with Dr. Paul Werbos, the inventor of the most commonly used technique to train artificial neural networks. Listen in as they turn to the National Science Foundation, its role in steering research in artificial intelligence, and the major turning points in machine intelligence that Dr. Werbos witnessed as a program Read More ›
Dr. Paul Werbos calls it “a soap opera you wouldn’t believe”: the story of how a young Werbos was inspired by the pioneering computer scientist to pursue the development of artificial neural networks, and how Minsky later could not support the effort for disbelief that there was a solution to its many problems. In this week’s podcast, Dr. Robert J. Marks interviewed Dr. Paul Werbos, famous for his 1974 dissertation which proposed training artificial neural networks through the use of a backpropagation of errors. The two discuss Werbos’s journey in the development of artificial neural networks and the role Marvin Minsky played throughout. This portion begins at 04:25. A partial transcript, Show Notes, and Additional Resources follow. Robert J. Marks: Read More ›
The applications of artificial neural networks are legion. Today, Robert J. Marks talks with Dr. Paul Werbos, the man who invented the method used for over four decades to train artificial neural networks. The two discuss Werbos’s mathematical journey, the error backpropagation algorithm, and the slog of “making it” in scientific academic research. Show Notes Additional Resources