Marvin Minsky? Seymour Papert? Apocryphal?

Question for Quote Investigator: The remarkable breakthroughs in artificial intelligence in the twenty-first century are based on digital neural networks. This area of machine learning was pioneered by Warren McCulloch and Walter Pitts who created an artificial neuron model. Also, researcher Frank Rosenblatt moved the field forward with his work on perceptrons.
The field suffered a massive blow when influential researchers proved that a simple perceptron network was incapable of learning an XOR function. Frank Rosenblatt attempted to extend his research to multilayer perceptrons which were more capable. Sadly, Rosenblatt died in an accident in 1971 when he was 43 years old.
Ultimately, multilayer perceptron networks became the foundation of deep learning and modern advances in artificial intelligence. Would you please explore what early critics and respondents said about multilayer networks?
Reply from Quote Investigator: In 1969 by Marvin L. Minsky and Seymour A. Papert published “Perceptrons: An Introduction to Computational Geometry”. A second printing with corrections was published in 1972. These authors highlighted the limitations of simple perceptron networks. They also mentioned with skepticism a “many-layered” version. Now, these systems are called “multilayer neural networks”. Boldface added to excerpts by QI:1
The problem of extension is not merely technical. It is also strategic. The perceptron has shown itself worthy of study despite (and even because of!) its severe limitations. It has many features to attract attention: its linearity; its intriguing learning theorem; its clear paradigmatic simplicity as a kind of parallel computation.
There is no reason to suppose that any of these virtues carry over to the many-layered version. Nevertheless, we consider it to be an important research problem to elucidate (or reject) our intuitive judgment that the extension is sterile. Perhaps some powerful convergence theorem will be discovered, or some profound reason for the failure to produce an interesting “learning theorem” for the multilayered machine will be found.
Below are additional selected citations in chronological order.
Continue reading “Quote Origin: (Multilayer Perceptrons) Our Intuitive Judgment That the Extension Is Sterile”







