Marvin Minsky, fully Marvin Lee Minsky

Marvin
Minsky, fully Marvin Lee Minsky
1927

American Cognitive Scientist in the field of Artificial Intelligence, Co-Founder of the Massachusetts Institute of Technology's AI Laboratory, Author

Author Quotes

An ethicist is someone who sees something wrong with whatever you have in mind.

Hearing music is like viewing scenery and... when we hear good music our minds react in very much the same way they do when we see things.

In today's computer science curricula... almost all their time is devoted to formal classification of syntactic language types, defeatist unsolvability theories, folklore about systems programming, and generally trivial fragments of "optimization of logic design"?the latter often in situations where the art of heuristic programming has far outreached the special-case "theories" so grimly taught and tested?and invocations about programming style almost sure to be outmoded before the student graduates.

Our culture has a universal myth in which we see emotion as more complex and obscure than intellect. Indeed, emotion might be "deeper" in some sense of prior evolution, but this need not make it harder to understand; in fact, I think today we actually know much more about emotion than about reason.

There was a failure to recognize the deep problems in AI; for instance, those captured in Blocks World. The people building physical robots learned nothing.

What is the difference between merely knowing (or remembering, or memorizing) and understanding? ...A thing or idea seems meaningful only when we have several different ways to represent it?different perspectives and different associations... Then we can turn it around in our minds, so to speak: however it seems at the moment, we can see it another way and we never come to a full stop. In other words, we can 'think' about it. If there were only one way to represent this thing or idea, we would not call this representation thinking.

Around 1967 Dan Bobrow wrote a program to do algebra problems based on symbols rather than numbers.

How do both music and vision build things in our minds? Eye motions show us real objects; phrases show us musical objects. We "learn" a room with bodily motions; large musical sections show us musical "places." Walks and climbs move us from room to room; so do transitions between musical sections. Looking back in vision is like recapitulation in music; both give us time, at certain points, to reconfirm or change our conceptions of the whole.

Innate sentic detectors could help by teaching children about their own affective states. For if distinct signals arouse specific states, the child can associate those signals with those states. Just knowing that such states exist, that is, having symbols for them, is half the battle.

Our eyes are always flashing sudden flicks of different pictures to our brains, yet none of that saccadic action leads to any sense of change or motion in the world; each thing reposes calmly in its "place"! ...What makes us such innate Copernicans?

This book... too, is a society?of many small ideas. Each by itself is only common sense, yet when we join enough of them we explain the strangest mysteries of mind.

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.

Artificial intelligence and its predecessor, cybernetics, have given us a new view of the world in general and of machines in particular. In previous times, if someone said that a human brain is just a machine, what would that have meant to the average person? It would have seemed to imply that a person must be something like a locomotive or a typewriter. This is because, in earlier days, the word machine was applied only to things that were simple and completely comprehensible. Until the past half century - starting with the work of Kurt Goedel and Alan Turing in the 1930s and of Warren McCulloch and Walter Pitts a decade later - we had never conceived of the possible ranges of computational processes. The situation is different today, not only because of those new theories, but also because we now can actually build and use machines that have thousands of millions of parts. This experience has changed our view. It is only partly that artificial intelligence has produced machines that do things that resemble thinking. It is also that we can see that our old ideas about the limitations of machines were not well founded. We have learned much more about how little we know about such matters.

How many processes are going on, to keep that teacup level in your grasp? There must be a hundred of them.

It would seem that making unusual connections is unusually difficult and, often, rather "indirect"?be it via words, images, or whatever. The bizarre structures used by mnemonists (and, presumably unknowingly, by each of us) suggests that arbitrary connections require devious pathways.

Perhaps it is no accident that one meaning of the word express is "to squeeze"?for when you try to "express yourself," your language resources will have to pick and choose among the descriptions your other resources construct?and then attempt to squeeze a few of these through your tiny channels of phrases and gestures.

This is a tricky domain because, unlike simple arithmetic, to solve a calculus problem - and in particular to perform integration - you have to be smart about which integration technique should be used: integration by partial fractions, integration by parts, and so on.

When David Marr at MIT moved into computer vision, he generated a lot of excitement, but he hit up against the problem of knowledge representation; he had no good representations for knowledge in his vision systems.

But just as astronomy succeeded astrology, following Kepler's discovery of planetary regularities, the discoveries of these many principles in empirical explorations of intellectual processes in machines should lead to a science, eventually.

I am inclined to doubt that anything very resembling formal logic could be a good model for human reasoning. In particular, I doubt that any logic that prohibits self-reference can be adequate for psychology: no mind can have enough power -- without the power to think about Thinking itself. Without Self-Reference it would seem immeasurably harder to achieve Self-Consciousness -- which, so far as I can see, requires at least some capacity to reflect on what it does. If Russell shattered our hopes for making a completely reliable version of commonsense reasoning, still we can try to find the islands of "local consistency," in which naive reasoning remains correct.

Kubrick's vision seemed to be that humans are doomed, whereas Clarke's is that humans are moving on to a better stage of evolution.

Perhaps the music that some call 'background' music can tranquilize by turning under-thoughts from bad to neutral, leaving the surface thoughts free of affect by diverting the unconscious.

Unless we can explain the mind in terms of things that have no thoughts or feelings of their own, we'll only have gone around in a circle.

When no idea seems right, the right one must seem wrong.

But there?s a big difference between impossible and hard to imagine. The first is about it; the second is about you!

Author Picture
First Name
Marvin
Last Name
Minsky, fully Marvin Lee Minsky
Birth Date
1927
Bio

American Cognitive Scientist in the field of Artificial Intelligence, Co-Founder of the Massachusetts Institute of Technology's AI Laboratory, Author