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Marvin L. Minsky

Marvin Minsky has made many contributions to AI, cognitive psychology, mathematics, computational linguistics, robotics, and optics. In recent years he has worked chiefly on imparting to machines the human capacity for commonsense reasoning. His conception of human intellectual structure and function is presented in The Society of Mind, which is also the title of the course he teaches at MIT. He received the BA and PhD in mathematics at Harvard and Princeton. In 1951 he built the SNARC, the first neural network simulator. His other inventions include mechanical hands and other robotic devices, the confocal scanning microscope, the "Muse" synthesizer for musical variations (with E. Fredkin), and the first LOGO "turtle" (with S. Papert). A member of the NAS, NAE and Argentine NAS, he has received the ACM Turing Award, the MIT Killian Award, the Japan Prize, the IJCAI Research Excellence Award, the Rank Prize and the Robert Wood Prize for Optoelectronics, and the Benjamin Franklin Medal. Minsky's current work in progress is titled The Emotion Machine: Commonsense Thinking, Artificial Intelligence, and the Future of Human Kind (due September, 2006). A pre-release, draft version of this book is available on Minsky's website.

Related Links

Marvin Minsky's home page
Marvin Minsky's Wikipedia page
Brief Academic Biography of Marvin Minsky
MIT Press interview with Marvin Minsky
NICSI video interview with Marvin Minsky
Marvin Minsky's Usenet posts
Conscious Machines, by Marvin Minsky
A Framework for Representing Knowledge, by Marvin Minsky
Review of Marvin Minsky's book, Society of Mind

Marvin Minsky Quotes

What magical trick makes us intelligent? The trick is that there is no trick. The power of intelligence stems from our vast diversity, not from any single, perfect principle. Our species has evolved many effective although imperfect methods, and each of us individually develops more on our own. Eventually, very few of our actions and decisions come to depend on any single mechanism. Instead, they emerge from conflicts and negotiations among societies of processes that constantly challenge one another.

Our present culture may be largely shaped by this strange idea of isolating children's thought from adult thought. Perhaps the way our culture educated its children better explains why most of us come out as dumb as they do, than it explains how some of us come out as smart as they do.

Eventually, robots will make everything.

Even the most technically, sophisticated people maintain that whatever consciousness might be, it has a quality that categorically places it outside the realm of science, namely, a subjective character that is makes it utterly private and unobservable. Why do so many people feel that consciousness cannot be explained in terms of anything science can presently do?

We humans do not possess much consciousness. That is, we have very little natural ability to sense what happens within and outside ourselves.

It seems entirely clear to me that consciousness has usefulness.

It seems to me that the ingredients of most theories both in Artificial Intelligence and in Psychology have been on the whole too minute, local, and unstructured to account – either practically or phenomenologically – for the effectiveness of common-sense thought. The "chunks" of reasoning, language, memory, and "perception" ought to be larger and more structured; their factual and procedural contents must be more intimately connected in order to explain the apparent power and speed of mental activities.

I draw no boundary between a theory of human thinking and a scheme for making an intelligent machine; no purpose would be served by separating these today since neither domain has theories good enough to explain – or to produce – enough mental capacity. There is, however, a difference in professional attitudes. Workers from psychology inherit stronger desires to minimize the variety of assumed mechanisms. I believe this leads to attempts to extract more performance from fewer "basic mechanisms" than is reasonable. Such theories especially neglect mechanisms of procedure control and explicit representations of processes. On the other side, workers in Artificial Intelligence have perhaps focused too sharply on just such questions. Neither have they given enough attention to the structure of knowledge, especially procedural knowledge.