Which event marked a setback for neural network theory in the late 1950s?

Which event marked a setback for neural network theory in the late 1950s?

• A. The Perceptrons book by Minsky and Papert
• B. The introduction of backpropagation
• C. The rise of modern deep learning
• D. The LISP programming language

Answer: (A)

The event that marked a setback for neural network theory is the publication of the Perceptrons book by Minsky and Papert. This work analyzed the capabilities of simple, single-layer perceptrons and proved they cannot solve certain problems that require nonlinear decision boundaries, such as the XOR problem. By clearly outlining these limitations, it tempered widespread optimism about neural networks and led to reduced funding and interest in neural network research for years. This slow period gave way later to renewed progress with ideas like backpropagation and deeper architectures, but the Perceptrons critique is what is recognized as the major setback. The other options don’t fit this turning point: backpropagation later sparked revival, deep learning is much newer, and the LISP language, while important in AI history, wasn’t the cause of a setback in neural network theory.

The event that marked a setback for neural network theory is the publication of the Perceptrons book by Minsky and Papert. This work analyzed the capabilities of simple, single-layer perceptrons and proved they cannot solve certain problems that require nonlinear decision boundaries, such as the XOR problem. By clearly outlining these limitations, it tempered widespread optimism about neural networks and led to reduced funding and interest in neural network research for years. This slow period gave way later to renewed progress with ideas like backpropagation and deeper architectures, but the Perceptrons critique is what is recognized as the major setback. The other options don’t fit this turning point: backpropagation later sparked revival, deep learning is much newer, and the LISP language, while important in AI history, wasn’t the cause of a setback in neural network theory.