[We] became involved with a somewhat therapeutic compulsion: to dispel what we feared to be the first shadows of a “holistic” or “Gestalt” misconcept… - Marvin Minsky

For generations, scientists and philosophers have tried to explain ordinary reasoning in terms of logical principles — with virtually no success. I suspect this enterprise failed because it was looking in the wrong direction: common sense works so well not because it is an approximation of logic; logic is only a small part of our great accumulation of different, useful ways to chain things together.

All intelligent persons also possess some larger-scale frame-systems whose members seemed at first impossibly different — like water with electricity, or poetry with music. Yet many such analogies — along with the knowledge of how to apply them — are among our most powerful tools of thought. They explain our ability sometimes to see one thing — or idea — as though it were another, and thus to apply knowledge and experience gathered in one domain to solve problems in another. It is thus that we transfer knowledge via the paradigms of Science. We learn to see gases and fluids as particles, particles as waves, and waves as envelopes of growing spheres.

More concretely, we would call the student's atten­tion to the following considerations: 1. Multilayer machines with loops clearly open all the questions of the general theory of automata. 2. A system with no loops but with an order restriction at each layer can compute only predicates of finite order. 3. On the other hand, if there is no restriction except for the absence of loops, the monster of vacuous generality once more raises its head. 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.