Marvin Minsky Quotations

You don't understand anything until you learn it more than one way.

In general we are least aware of what our minds do best.

The basic idea in case-based, or CBR, is that the program has stored problems and solutions. Then, when a new problem comes up, the program tries to find a similar problem in its database by finding analogous aspects between the problems.

We wanted to solve robot problems and needed some vision, action, reasoning, planning, and so forth. We even used some structural learning, such as was being explored by Patrick Winston.

I believed in realism, as summarized by John McCarthy's comment to the effect that if we worked really hard, we'd have an intelligent system in from four to four hundred years.

Societies need rules that make no sense for individuals. For example, it makes no difference whether a single car drives on the left or on the right. But it makes all the difference when there are many cars!

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.

I heard that the same thing occurred in a scene in Alien, where the creature pops out of the chest of a crewman. The other actors didn't know what was to happen; the director wanted to get true surprise.

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.

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

Stanley Kubrick knew we had good graphics around MIT and came to my lab to find out how to do it. We had some really good stuff. I was very impressed with Kubrick; he knew all the graphics work I had ever heard of, and probably more.

No computer has ever been designed that is ever aware of what it's doing; but most of the time, we aren't either.

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.

There are three basic approaches to AI: Case-based, rule-based, and connectionist reasoning.

By the way, it was his simulations that helped out in Jurassic Park - without them, there would have been only a few dinosaurs. Based on his techniques, Industrial Light and Magic could make whole herds of dinosaurs race across the screen.

If you just have a single problem to solve, then fine, go ahead and use a neural network. But if you want to do science and understand how to choose architectures, or how to go to a new problem, you have to understand what different architectures can and cannot do.

I think Lenat is headed in the right direction, but someone needs to include a knowledge base about learning.

Once when I was standing at the base, they started rotating the set and a big, heavy wrench fell down from the 12 o'clock position of the set, and got buried in the ground a few feet from me. I could have been killed!

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.

For the real systems, you never knew if it worked or if it didn't work because a cloud went over the window and changed the lighting.

Well, we were trying to make intelligent machines. There were lots of good students working on interesting and important problems.

A major problem with AI research then was that Ph.D. dissertations were huge programs, and only the writer knew how they worked.

The nature of mind: much of its power seems to stem from just the messy ways its agents cross-connect. ...it's only what we must expect from evolution's countless tricks.

Our present culture may be largely shaped by this strange idea of isolating children's thought from adult thought. Perhaps the way our culture educates 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.

Everything is similar if you're willing to look far out of focus.

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.

You don't understand anything unless you understand there are at least 3 ways.

Common sense is not a simple thing. Instead, it is an immense society of hard-earned practical ideas - of multitudes of life-learned rules and exceptions, dispositions and tendencies, balances and checks.

Once the computers got control, we might never get it back. We would survive at their sufferance. If we're lucky, they might decide to keep us as pets.

Computer languages of the future will be more concerned with goals and less with procedures specified by the programmer.

Eventually, robots will make everything.

In science, one learns the most by studying what seems to be the least.

Each part of the mind sees only a little of what happens in some others, and that little is swiftly refined, reformulated and "represented." We like to believe that these fragments have meanings in themselves-apart from the great webs of structure from which they emerge-and indeed this illusion is valuable to us qua thinkers-but not to us as psychologists-because it leads us to think that expressible knowledge is the first thing to study.

Experience has shown that science frequently develops most fruitfully once we learn to examine the things that seem the simplest, instead of those that seem the most mysterious.

To say that the universe exists is silly, because it says that the universe is one of the things in the universe. So there's something wrong with questions like, "What caused the Universe to exist?"

What would a Martian visitor think to see a human being laugh? It must look truly horrible: the sight of furious gestures, flailing limbs, and thorax heaving in frenzied contortions...

How hard is it to build an intelligent machine? I don't think it's so hard, but that's my opinion, and I've written two books on how I think one should do it. The basic idea I promote is that you mustn't look for a magic bullet. You mustn't look for one wonderful way to solve all problems. Instead you want to look for 20 or 30 ways to solve different kinds of problems. And to build some kind of higher administrative device that figures out what kind of problem you have and what method to use.

Theorems often tell us complex truths about the simple things, but only rarely tell us simple truths about the complex ones. To believe otherwise is wishful thinking or "mathematics envy.

A couple of hundred years from now, maybe [science fiction writers] Isaac Asimov and Fred Pohl will be considered the important philosophers of the twentieth century, and the professional philosophers will almost all be forgotten, because they're just shallow and wrong, and their ideas aren't very powerful.

We turn to quantities when we can't compare the qualities of things.

It makes no sense to seek a single best way to represent knowledge-because each particular form of expression also brings its particular limitations. For example, logic-based systems are very precise, but they make it hard to do reasoning with analogies. Similarly, statistical systems are useful for making predictions, but do not serve well to represent the reasons why those predictions are sometimes correct.

We must see that music theory is not only about music, but about how people process it. To understand any art, we must look below its surface into the psychological details of its creation and absorption.

It would be as useless to perceive how things 'actually look' as it would be to watch the random dots on untuned television screens.

But the big feature of human-level intelligence is not what it does what it is works but what it does when it's stuck.

Imagine what it would be like if TV actually were good. It would be the end of everything we know.

All intelligent problem solvers are subject to the same ultimate constraints - limitations on space, time, and materials.

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.

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

Will robots inherit the earth? Yes, but they will be our children.

Logic doesn't apply to the real world.

Speed is what distinguishes intelligence. No bird discovers how to fly: evolution used a trillion bird-years to 'discover' that–where merely hundreds of person-years sufficed.

General fiction is pretty much about ways that people get into problems and screw their lives up. Science fiction is about everything else.

If we understood something just one way, we would not understand it at all.

Minds are simply what brains do.

In general, we’re least aware of what our minds do best.

Each practitioner thinks there's one magic way to get a machine to be smart, and so they're all wasting their time in a sense. On the other hand, each of them is improving some particular method, so maybe someday in the near future, or maybe it's two generations away, someone else will come around and say, "Let's put all these together," and then it will be smart.

One can acquire certainty only by amputating inquiry.

Good theories of the mind must span at least three different scales of time: slow, for the billions of years in which our brains have survivied; fast, for the fleeting weeks and months of childhood; and in between, the centuries of growth of our ideas through history.

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

It's ridiculous to live 100 years and only be able to remember 30 million bytes. You know, less than a compact disc. The human condition is really becoming more obsolete every minute.

The principal activities of brains are making changes in themselves.

Logic doesn't apply to the real world. D. R. Hofstadter and D. C. Dennett (eds.) The Mind's I, 1981.

Everything, including that which happens in our brains, depends on these and only on these: A set of fixed, deterministic laws.

The brain happens to be a meat machine.

Listening to music engages the previously acquired personal knowledge of the listener.

I cannot articulate enough to express my dislike to people who think that understanding spoils your experience... How would they know?

We'll show you that you can build a mind from many little parts, each mindless by itself.

What is intelligence, anyway It is only a word that people use to name those unknown processes with which our brains solve problems we call hard. But whenever you learn a skill yourself, you're less impressed or mystified when other people do the same. This is why the meaning of 'intelligence' seems so elusive: It describes not some definite thing but only the momentary horizon of our ignorance about how minds might work.

I bet the human brain is a kludge

We rarely recognize how wonderful it is that a person can traverse an entire lifetime without making a single really serious mistake — like putting a fork in one's eye or using a window instead of a door.

A computer is like a violin. You can imagine a novice trying first a phonograph and then a violin. The latter, he says, sounds terrible. That is the argument we have heard from our humanists and most of our computer scientists. Computer programs are good, they say, for particular purposes, but they aren’t flexible. Neither is a violin, or a typewriter, until you learn how to use it.

Within 10 years computers won't even keep us as pets.

Daniel Dennett is our best current philosopher. He is the next Bertrand Russell. Unlike traditional philosophers, Dan is a student of neuroscience, linguistics, artificial intelligence, computer science, and psychology. He's redefining and reforming the role of the philosopher.

Anyone could learn Lisp in one day, except that if they already knew Fortran, it would take three days.

The secret of what anything means to us depends on how we've connected it to all the other things we know. That's why it's almost always wrong to seek the "real meaning" of anything. A thing with just one meaning has scarcely any meaning at all.

Artificial intelligence is the science of making machines do things that would require intelligence if done by men.

If you understand something in only one way, then you don't really understand it at all. The secret of what anything means to us depends on how we've connected it to all other things we know. Well-connected representations let you turn ideas around in your mind, to envision things from many perspectives until you find one that works for you. And that's what we mean by thinking!