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4. DISCUSSION- QUESTIONS AND ANSWERS

(A. G. Chynoweth):

Well that was 50 minutes of concentrated wisdom and observations accumulated over a fantastic career; I lost track of all the observations that were striking home. Some of them are very very timely. One was the plea for more computer capacity; I was hearing nothing but that this morning from several people, over and over again. So that was right on the mark today even though here we are 20 ­ 30 years after when you were making similar remarks, Dick. I can think of all sorts of lessons that all of us can draw from your talk. And for one, as I walk around the halls in the future I hope I won't see as many closed doors in Bellcore. That was one observation I thought was very intriguing.

Thank you very, very much indeed Dick; that was a wonderful recollection. I'll now open it up for questions. I'm sure there are many people who would like to take up on some of the points that Dick was making.

(Hamming):

First let me respond to Alan Chynoweth about computing. I had computing in research and for 10 years I kept telling my management, "Get that !&@#% machine out of research. We are being forced to run problems all the time. We can't do research because were too busy operating and running the computing machines." Finally the message got through. They were going to move computing out of research to someplace else. I was persona non grata to say the least and I was surprised that people didn't kick my shins because everybody was having their toy taken away from them. I went in to Ed David's office and said, "Look Ed, you've got to give your researchers a machine. If you give them a great big machine, we'll be back in the same trouble we were before, so busy keeping it going we can't think. Give them the smallest machine you can because they are very able people. They will learn how to do things on a small machine instead of mass computing." As far as I'm concerned, that's how UNIX arose. We gave them a moderately small machine and they decided to make it do great things. They had to come up with a system to do it on. It is called UNIX!

(A. G. Chynoweth):

I just have to pick up on that one. In our present environment, Dick, while we wrestle with some of the red tape attributed to, or required by, the regulators, there is one quote that one exasperated AVP came up with and I've used it over and over again. He growled that, "UNIX was never a deliverable!"

Question: What about personal stress? Does that seem to make a difference?

Answer: Yes, it does. If you don't get emotionally involved, it doesn't. I had incipient ulcers most of the years that I was at Bell Labs. I have since gone off to the Naval Postgraduate School and laid back somewhat, and now my health is much better. But if you want to be a great scientist you're going to have to put up with stress. You can lead a nice life; you can be a nice guy or you can be a great scientist. But nice guys end last, is what Leo Durocher said. If you want to lead a nice happy life with a lot of recreation and everything else, you'll lead a nice life.

Question: The remarks about having courage, no one could argue with; but those of us who have gray hairs or who are well established don't have to worry too much. But what I sense among the young people these days is a real concern over the risk taking in a highly competitive environment. Do you have any words of wisdom on this?

Answer: I'll quote Ed David more. Ed David was concerned about the general loss of nerve in our society. It does seem to me that we've gone through various periods. Coming out of the war, coming out of Los Alamos where we built the bomb, coming out of building the radars and so on, there came into the mathematics department, and the research area, a group of people with a lot of guts. They've just seen things done; they've just won a war which was fantastic. We had reasons for having courage and therefore we did a great deal. I can't arrange that situation to do it again. I cannot blame the present generation for not having it, but I agree with what you say; I just cannot attach blame to it. It doesn't seem to me they have the desire for greatness; they lack the courage to do it. But we had, because we were in a favorable circumstance to have it; we just came through a tremendously successful war. In the war we were looking very, very bad for a long while; it was a very desperate struggle as you well know. And our success, I think, gave us courage and self confidence; that's why you see, beginning in the late forties through the fifties, a tremendous productivity at the labs which was stimulated from the earlier times. Because many of us were earlier forced to learn other things ­ we were forced to learn the things we didn't want to learn, we were forced to have an open door ­ and then we could exploit those things we learned. It is true, and I can't do anything about it; I cannot blame the present generation either. It's just a fact.

Question: Is there something management could or should do?

Answer: Management can do very little. If you want to talk about managing research, that's a totally different talk. I'd take another hour doing that. This talk is about how the individual gets very successful research done in spite of anything the management does or in spite of any other opposition. And how do you do it? Just as I observe people doing it. It's just that simple and that hard!

Question: Is brainstorming a daily process?

Answer: Once that was a very popular thing, but it seems not to have paid off. For myself I find it desirable to talk to other people; but a session of brainstorming is seldom worthwhile. I do go in to strictly talk to somebody and say, "Look, I think there has to be something here. Here's what I think I see .~.~." and then begin talking back and forth. But you want to pick capable people. To use another analogy, you know the idea called the "critical mass". If you have enough stuff you have critical mass. There is also the idea I used to call `sound absorbers'. When you get too many sound absorbers, you give out an idea and they merely say, "Yes, yes, yes." What you want to do is get that critical mass in action; "Yes, that reminds me of so and so," or, "Have you thought about that or this?" When you talk to other people, you want to get rid of those sound absorbers who are nice people but merely say, "Oh yes," and to find those who will stimulate you right back.

For example, you couldn't talk to John Pierce without being stimulated very quickly. There were a group of other people I used to talk with. For example there was Ed Gilbert; I used to go down to his office regularly and ask him questions and listen and come back stimulated. I picked my people carefully with whom I did or whom I didn't brainstorm because the sound absorbers are a curse. They are just nice guys; they fill the whole space and they contribute nothing except they absorb ideas and the new ideas just die away instead of echoing on. Yes, I find it necessary to talk to people. I think people with closed doors fail to do this so they fail to get their ideas sharpened, such as "Did you ever notice something over here?" I never knew anything about it ­ I can go over and look. Somebody points the way. On my visit here, I have already found several books that I must read when I get home. I talk to people and ask questions when I think they can answer me and give me clues that I do not know about. I go out and look!

Question: What kind of tradeoffs did you make in allocating your time for reading and writing and actually doing research?

Answer: I believed, in my early days, that you should spend at least as much time in the polish and presentation as you did in the original research. Now at least 50% of the time must go for the presentation. It's a big, big number.

Question: (How much effort should go into library work?)

Answer: It depends upon the field. I will say this about it. There was a fellow at Bell Labs, a very, very, smart guy. He was always in the library; he read everything. If you wanted references, you went to him and he gave you all kinds of references. But in the middle of forming these theories, I formed a proposition: there would be no effect named after him in the long run. He is now retired from Bell Labs and is an Adjunct Professor. He was very valuable; I'm not questioning that. He wrote some very good Physical Review articles; but there's no effect named after him because he read too much. If you read all the time what other people have done you will think the way they thought. If you want to think new thoughts that are different, then do what a lot of creative people do ­ get the problem reasonably clear and then refuse to look at any answers until you've thought the problem through carefully how you would do it, how you could slightly change the problem to be the correct one. So yes, you need to keep up. You need to keep up more to find out what the problems are than to read to find the solutions. The reading is necessary to know what is going on and what is possible. But reading to get the solutions does not seem to be the way to do great research. So I'll give you two answers. You read; but it is not the amount, it is the way you read that counts.

Question: How do you get your name attached to things?

Answer: By doing great work. I'll tell you the hamming window one. I had given Tukey a hard time, quite a few times, and I got a phone call from him from Princeton to me at Murray Hill. I knew that he was writing up power spectra and he asked me if I would mind if he called a certain window a "Hamming window." And I said to him, "Come on, John; you know perfectly well I did only a small part of the work but you also did a lot." He said, "Yes, Hamming, but you contributed a lot of small things; you're entitled to some credit." So he called it the hamming window. Now, let me go on. I had twitted John frequently about true greatness. I said true greatness is when your name is like ampere, watt, and fourier ­ when it's spelled with a lower case letter. That's how the hamming window came about.

Question: Dick, would you care to comment on the relative effectiveness between giving talks, writing papers, and writing books?

Answer: In the short-haul, papers are very important if you want to stimulate someone tomorrow. If you want to get recognition long-haul, it seems to me writing books is more contribution because most of us need orientation. In this day of practically infinite knowledge, we need orientation to find our way. Let me tell you what infinite knowledge is. Since from the time of Newton to now, we have come close to doubling knowledge every 17 years, more or less. And we cope with that, essentially, by specialization. In the next 340 years at that rate, there will be 20 doublings, i.e. a million, and there will be a million fields of specialty for every one field now. It isn't going to happen. The present growth of knowledge will choke itself off until we get different tools. I believe that books which try to digest, coordinate, get rid of the duplication, get rid of the less fruitful methods and present the underlying ideas clearly of what we know now, will be the things the future generations will value. Public talks are necessary; private talks are necessary; written papers are necessary. But I am inclined to believe that, in the long-haul, books which leave out what's not essential are more important than books which tell you everything because you don't want to know everything. I don't want to know that much about penguins is the usual reply. You just want to know the essence.

Question: You mentioned the problem of the Nobel Prize and the subsequent notoriety of what was done to some of the careers. Isn't that kind of a much more broad problem of fame? What can one do?

Answer: Some things you could do are the following. Somewhere around every seven years make a significant, if not complete, shift in your field. Thus, I shifted from numerical analysis, to hardware, to software, and so on, periodically, because you tend to use up your ideas. When you go to a new field, you have to start over as a baby. You are no longer the big mukity muk and you can start back there and you can start planting those acorns which will become the giant oaks. Shannon, I believe, ruined himself. In fact when he left Bell Labs, I said, "That's the end of Shannon's scientific career." I received a lot of flak from my friends who said that Shannon was just as smart as ever. I said, "Yes, he'll be just as smart, but that's the end of his scientific career," and I truly believe it was.

You have to change. You get tired after a while; you use up your originality in one field. You need to get something nearby. I'm not saying that you shift from music to theoretical physics to English literature; I mean within your field you should shift areas so that you don't go stale. You couldn't get away with forcing a change every seven years, but if you could, I would require a condition for doing research, being that you will change your field of research every seven years with a reasonable definition of what it means, or at the end of 10 years, management has the right to compel you to change. I would insist on a change because I'm serious. What happens to the old fellows is that they get a technique going; they keep on using it. They were marching in that direction which was right then, but the world changes. There's the new direction; but the old fellows are still marching in their former direction.

You need to get into a new field to get new viewpoints, and before you use up all the old ones. You can do something about this, but it takes effort and energy. It takes courage to say, "Yes, I will give up my great reputation." For example, when error correcting codes were well launched, having these theories, I said, "Hamming, you are going to quit reading papers in the field; you are going to ignore it completely; you are going to try and do something else other than coast on that." I deliberately refused to go on in that field. I wouldn't even read papers to try to force myself to have a chance to do something else. I managed myself, which is what I'm preaching in this whole talk. Knowing many of my own faults, I manage myself. I have a lot of faults, so I've got a lot of problems, i.e. a lot of possibilities of management.

Question: (Would you compare research and management?)

Answer: If you want to be a great researcher, you won't make it being president of the company. If you want to be president of the company, that's another thing. I'm not against being president of the company. I just don't want to be. I think Ian Ross does a good job as President of Bell Labs. I'm not against it; but you have to be clear on what you want. Furthermore, when you're young, you may have picked wanting to be a great scientist, but as you live longer, you may change your mind. For instance, I went to my boss, Bode, one day and said, "Why did you ever become department head? Why didn't you just be a good scientist?" He said, "Hamming, I had a vision of what mathematics should be in Bell Laboratories. And I saw if that vision was going to be realized, I had to make it happen; I had to be department head." When your vision of what you want to do is what you can do single-handedly, then you should pursue it. The day your vision, what you think needs to be done, is bigger than what you can do single-handedly, then you have to move toward management. And the bigger the vision is, the farther in management you have to go. If you have a vision of what the whole laboratory should be, or the whole Bell System, you have to get there to make it happen. You can't make it happen from the bottom very easily. It depends upon what goals and what desires you have. And as they change in life, you have to be prepared to change. I chose to avoid management because I preferred to do what I could do single-handedly. But that's the choice that I made, and it is biased. Each person is entitled to their choice. Keep an open mind. But when you do choose a path, for heaven's sake be aware of what you have done and the choice you have made. Don't try to do both sides.

Question: How important is one's own expectation or how important is it to be in a group or surrounded by people who expect great work from you?

Answer: At Bell Labs everyone expected good work from me ­ it was a big help. Everybody expects you to do a good job, so you do, if you've got pride. I think it's very valuable to have first-class people around. I sought out the best people. The moment that physics table lost the best people, I left. The moment I saw that the same was true of the chemistry table, I left. I tried to go with people who had great ability so I could learn from them and who would expect great results out of me. By deliberately managing myself, I think I did much better than laissez faire.

Question: You, at the outset of your talk, minimized or played down luck; but you seemed also to gloss over the circumstances that got you to Los Alamos, that got you to Chicago, that got you to Bell Laboratories.

Answer: There was some luck. On the other hand I don't know the alternate branches. Until you can say that the other branches would not have been equally or more successful, I can't say. Is it luck the particular thing you do? For example, when I met Feynman at Los Alamos, I knew he was going to get a Nobel Prize. I didn't know what for. But I knew darn well he was going to do great work. No matter what directions came up in the future, this man would do great work. And sure enough, he did do great work. It isn't that you only do a little great work at this circumstance and that was luck, there are many opportunities sooner or later. There are a whole pail full of opportunities, of which, if you're in this situation, you seize one and you're great over there instead of over here. There is an element of luck, yes and no. Luck favors a prepared mind; luck favors a prepared person. It is not guaranteed; I don't guarantee success as being absolutely certain. I'd say luck changes the odds, but there is some definite control on the part of the individual.

Go forth, then, and do great work!

End of the General Research Colloquium Talk
5. BIOGRAPHIC SKETCH OF RICHARD HAMMING

Richard W. Hamming was born February 11, 1915, in Chicago, Illinois. His formal education was marked by the following degrees: B.S. 1937, University of Chicago; M.A. 1939, University of Nebraska; and Ph.D. 1942, University of Illinois. His early experience was obtained at Los Alamos 1945­1946, i.e. at the close of World War II. From there he went directly to Bell Laboratories where he spent thirty years in various aspects of computing, numerical analysis, and management of computing, i.e. 1946­1976. On July 23, 1976 he `moved his office' to the Naval Postgraduate School in Monterey, California where he teaches, supervises research, and writes books. He continues an active schedule of lecturing in seminars and short courses.

While at Bell Laboratories, he took time to teach in Universities, sometimes locally and sometimes on a full sabbatical leave; these activities included visiting professorships at New York University, Princeton University (Statistics), City College of New York, Stanford University, 1960­61, Stevens Institute of Technology (Mathematics), and the University of California, Irvine, 1970­71.

Richard Hamming has received a number of awards which include: Fellow, IEEE, 1968; the ACM Turing Prize, 1968; the IEEE Emanuel R. Piore Award, 1979; Member, National Academy of Engineering, 1980; and the Harold Pender Award, U. Penn., 1981. In 1987 a major IEEE award was named after him, namely the Richard W. Hamming Medal, ``For exceptional contributions to information sciences and systems''; fittingly, he was also the first recipient of this award, 1988. He was both a Founder and Past President of ACM, and a Vice Pres. of the AAAS Mathematics Section.

He is probably best known for his pioneering work on error-correcting codes, his work on integrating differential equations, and the spectral window which bears his name. His extensive writing has included a number of important, pioneering, and highly regarded books. These are:

1. Numerical Methods for Scientists and Engineers, McGraw-Hill, 1962; Second edition 1973; Reprinted by Dover 1985; translated into Russian also.
2. Calculus and the Computer Revolution, Houghton-Mifflin, 1968.
3. Introduction to Applied Numerical Analysis, McGraw-Hill, 1971.
4. Computers and Society, McGraw-Hill, 1972.
5. Digital Filters, Prentice-Hall, 1977; Second edition 1983; Third edition 1989; translated into several European languages.
6. Coding and Information Theory, Prentice-Hall, 1980; Second edition 1986.
7. Methods of Mathematics Applied to Calculus, Probability and Statistics, Prentice-Hall, 856 pp., 1985.
8. The Art of Probability for Scientists and Engineers, Addison-Wesley, 344 pp., 1991.
9. The Art of Doing Science and Engineering: Learning to Learn, Gordon and Breach, 1997.

He continued a very active life as Adjunct Professor, teaching and writing in the Mathematics and Computer Science Departments at the Naval Postgraduate School, Monterey, California for another twenty-one years before he retired to become Professor Emeritus in 1997. He was still teaching a course in the fall of 1997. Richard Wesley Hamming passed away unexpectedly on January 7th, 1998. An extensive biography appeared in The New York Times on January 11th, 1998.

Possibly his best-known quotation:

"The purpose of computing is insight, not numbers."
6. ACKNOWLEDGEMENT

I would like to acknowledge the professional efforts of Donna Paradise of the Word Processing Center who did the initial transcription of the talk from the tape recording. She made my job of editing much easier. The errors of sentence parsing and punctuation are those of mine and mine alone. Finally I would like to express my sincere appreciation to Richard Hamming and Alan Chynoweth for all of their help in bringing this transcription to its present readable state.

(signed)
J. F. Kaiser

You and Your Research
Dr. Richard W. Hamming

Transcription of the Bell Communications Research
Colloquium Seminar - 'You and Your Research' given by
Richard W. Hamming at MRE on March 7, 1986.

J. F. Kaiser
Bell Communications Research
435 South Street, Room 2E-354
Morristown, NJ 07980

ABSTRACT
As a seminar in the Bell Communications Research Colloquia Series, Dr. Richard W. Hamming, a Professor at the Naval Postgraduate School in Monterey, California and a former Bell Labs scientist, gave an interesting and stimulating talk, `You and Your Research' to an overflow audience of some 200 Bellcore staff members and visitors at the Morris Research and Engineering Center on March 7, 1986. This talk centered on Hamming's observations and research on the question "Why do so few scientists make significant contributions and so many are forgotten in the long run?" From his more than forty years of experience, thirty of which were at Bell Laboratories, he has made a number of direct observations, asked very pointed questions of scientists about what, how, and why they did things, studied the lives of great scientists and great contributions, and has done introspection and studied theories of creativity. The talk is about what he has learned in terms of the properties of the individual scientists, their abilities, traits, working habits, attitudes, and philosophy.

This paper is a transcription of that talk along with the discussions from the question and answer period.

1. INTRODUCTION

As a seminar in the Bell Communications Research Colloquia Series, Dr. Richard W. Hamming, a Professor at the Naval Postgraduate School in Monterey, California and a retired Bell Labs scientist, gave a very interesting and stimulating talk, `You and Your Research' to an overflow audience of some 200 Bellcore staff members and visitors at the Morris Research and Engineering Center on March 7, 1986. This talk centered on Hamming's observations and research on the question "Why do so few scientists make significant contributions and so many are forgotten in the long run?" From his more than forty years of experience, thirty of which were at Bell Laboratories, he has made a number of direct observations, asked very pointed questions of scientists about what, how, and why they did things, studied the lives of great scientists and great contributions, and has done introspection and studied theories of creativity. The talk is about what he has learned in terms of the properties of the individual scientists, their abilities, traits, working habits, attitudes, and philosophy.

In order to make the information in the talk more widely available, the tape recording that was made of that talk was carefully transcribed. This transcription includes the discussions which followed in the question and answer period. As with any talk, the transcribed version suffers from translation as all the inflections of voice and the gestures of the speaker are lost; one must listen to the tape recording to recapture that part of the presentation. While the recording of Richard Hamming's talk was completely intelligible, that of some of the questioner's remarks were not. Where the tape recording was not intelligible I have added in parentheses my impression of the questioner's remarks. Where there was a question and I could identify the questioner, I have checked with each to ensure the accuracy of my interpretation of their remarks.
2. INTRODUCTION OF DR. RICHARD W. HAMMING

As a speaker in the Bell Communications Research Colloquium Series, Dr. Richard W. Hamming of the Naval Postgraduate School in Monterey, California, was introduced by Alan G. Chynoweth, Vice President, Applied Research, Bell Communications Research.

Introduction of Richard W. Hamming
Alan G. Chynoweth

Greetings colleagues, and also to many of our former colleagues from Bell Labs who, I understand, are here to be with us today on what I regard as a particularly felicitous occasion. It gives me very great pleasure indeed to introduce to you my old friend and colleague from many many years back, Richard Hamming, or Dick Hamming as he has always been know to all of us.

Dick is one of the all time greats in the mathematics and computer science arenas, as I'm sure the audience here does not need reminding. He received his early education at the Universities of Chicago and Nebraska, and got his Ph.D. at Illinois; he then joined the Los Alamos project during the war. Afterwards, in 1946, he joined Bell Labs. And that is, of course, where I met Dick ­ when I joined Bell Labs in their physics research organization. In those days, we were in the habit of lunching together as a physics group, and for some reason this strange fellow from mathematics was always pleased to join us. We were always happy to have him with us because he brought so many unorthodox ideas and views. Those lunches were stimulating, I can assure you.

While our professional paths have not been very close over the years, nevertheless I've always recognized Dick in the halls of Bell Labs and have always had tremendous admiration for what he was doing. I think the record speaks for itself. It is too long to go through all the details, but let me point out, for example, that he has written seven books and of those seven books which tell of various areas of mathematics and computers and coding and information theory, three are already well into their second edition. That is testimony indeed to the prolific output and the stature of Dick Hamming.

I think I last met him ­ it must have been about ten years ago ­ at a rather curious little conference in Dublin, Ireland where we were both speakers. As always, he was tremendously entertaining. Just one more example of the provocative thoughts that he comes up with: I remember him saying, "There are wavelengths that people cannot see, there are sounds that people cannot hear, and maybe computers have thoughts that people cannot think." Well, with Dick Hamming around, we don't need a computer. I think that we are in for an extremely entertaining talk.
3. THE TALK

"You and Your Research"
Dr. Richard W. Hamming

It's a pleasure to be here. I doubt if I can live up to the Introduction. The title of my talk is, "You and Your Research." It is not about managing research, it is about how you individually do your research. I could give a talk on the other subject ­ but it's not, it's about you. I'm not talking about ordinary run-of-the-mill research; I'm talking about great research. And for the sake of describing great research I'll occasionally say Nobel-Prize type of work. It doesn't have to gain the Nobel Prize, but I mean those kinds of things which we perceive are significant things. Relativity, if you want, Shannon's information theory, any number of outstanding theories ­ that's the kind of thing I'm talking about.

Now, how did I come to do this study? At Los Alamos I was brought in to run the computing machines which other people had got going, so those scientists and physicists could get back to business. I saw I was a stooge. I saw that although physically I was the same, they were different. And to put the thing bluntly, I was envious. I wanted to know why they were so different from me. I saw Feynman up close. I saw Fermi and Teller. I saw Oppenheimer. I saw Hans Bethe: he was my boss. I saw quite a few very capable people. I became very interested in the difference between those who do and those who might have done.

When I came to Bell Labs, I came into a very productive department. Bode was the department head at the time; Shannon was there, and there were other people. I continued examining the questions, "Why?" and "What is the difference?" I continued subsequently by reading biographies, autobiographies, asking people questions such as: "How did you come to do this?" I tried to find out what are the differences. And that's what this talk is about.

Now, why is this talk important? I think it is important because, as far as I know, each of you has one life to live. Even if you believe in reincarnation it doesn't do you any good from one life to the next! Why shouldn't you do significant things in this one life, however you define significant? I'm not going to define it ­ you know what I mean. I will talk mainly about science because that is what I have studied. But so far as I know, and I've been told by others, much of what I say applies to many fields. Outstanding work is characterized very much the same way in most fields, but I will confine myself to science.

In order to get at you individually, I must talk in the first person. I have to get you to drop modesty and say to yourself, "Yes, I would like to do first-class work." Our society frowns on people who set out to do really good work. You're not supposed to; luck is supposed to descend on you and you do great things by chance. Well, that's a kind of dumb thing to say. I say, why shouldn't you set out to do something significant. You don't have to tell other people, but shouldn't you say to yourself, "Yes, I would like to do something significant."

In order to get to the second stage, I have to drop modesty and talk in the first person about what I've seen, what I've done, and what I've heard. I'm going to talk about people, some of whom you know, and I trust that when we leave, you won't quote me as saying some of the things I said.

Let me start not logically, but psychologically. I find that the major objection is that people think great science is done by luck. It's all a matter of luck. Well, consider Einstein. Note how many different things he did that were good. Was it all luck? Wasn't it a little too repetitive? Consider Shannon. He didn't do just information theory. Several years before, he did some other good things and some which are still locked up in the security of cryptography. He did many good things.

You see again and again, that it is more than one thing from a good person. Once in a while a person does only one thing in his whole life, and we'll talk about that later, but a lot of times there is repetition. I claim that luck will not cover everything. And I will cite Pasteur who said, "Luck favors the prepared mind." And I think that says it the way I believe it. There is indeed an element of luck, and no, there isn't. The prepared mind sooner or later finds something important and does it. So yes, it is luck. The particular thing you do is luck, but that you do something is not.

For example, when I came to Bell Labs, I shared an office for a while with Shannon. At the same time he was doing information theory, I was doing coding theory. It is suspicious that the two of us did it at the same place and at the same time ­ it was in the atmosphere. And you can say, "Yes, it was luck". On the other hand you can say, "But why of all the people in Bell Labs then were those the two who did it?" Yes, it is partly luck, and partly it is the prepared mind; but `partly' is the other thing I'm going to talk about. So, although I'll come back several more times to luck, I want to dispose of this matter of luck as being the sole criterion whether you do great work or not. I claim you have some, but not total, control over it. And I will quote, finally, Newton on the matter. Newton said, "If others would think as hard as I did, then they would get similar results."

One of the characteristics you see, and many people have it including great scientists, is that usually when they were young they had independent thoughts and had the courage to pursue them. For example, Einstein, somewhere around 12 or 14, asked himself the question, "What would a light wave look like if I went with the velocity of light to look at it?" Now he knew that electromagnetic theory says you cannot have a stationary local maximum. But if he moved along with the velocity of light, he would see a local maximum. He could see a contradiction at the age of 12, 14, or somewhere around there, that everything was not right and that the velocity of light had something peculiar. Is it luck that he finally created special relativity? Early on, he had laid down some of the pieces by thinking of the fragments. Now that's the necessary but not sufficient condition. All of these items I will talk about are both luck and not luck.

How about having lots of `brains'? It sounds good. Most of you in this room probably have more than enough brains to do first-class work. But great work is something else than mere brains. Brains are measured in various ways. In mathematics, theoretical physics, astrophysics, typically brains correlates to a great extent with the ability to manipulate symbols. And so the typical IQ test is apt to score them fairly high. On the other hand, in other fields it is something different. For example, Bill Pfann, the fellow who did zone melting, came into my office one day. He had this idea dimly in his mind about what he wanted and he had some equations. It was pretty clear to me that this man didn't know much mathematics and he wasn't really articulate. His problem seemed interesting so I took it home and did a little work. I finally showed him how to run computers so he could compute his own answers. I gave him the power to compute. He went ahead, with negligible recognition from his own department, but ultimately he has collected all the prizes in the field. Once he got well started, his shyness, his awkwardness, his inarticulateness, fell away and he became much more productive in many other ways. Certainly he became much more articulate.

And I can cite another person in the same way. I trust he isn't in the audience, i.e. a fellow named Clogston. I met him when I was working on a problem with John Pierce's group and I didn't think he had much. I asked my friends who had been with him at school, "Was he like that in graduate school?" "Yes", they replied. Well I would have fired the fellow, but J. R. Pierce was smart and kept him on. Clogston finally did the Clogston cable. After that there was a steady stream of good ideas. One success brought him confidence and courage.

One of the characteristics of successful scientists is having courage. Once you get your courage up and believe that you can do important problems, then you can. If you think you can't, almost surely you are not going to. Courage is one of the things that Shannon had supremely. You have only to think of his major theorem. He wants to create a method of coding, but he doesn't know what to do so he makes a random code. Then he is stuck. And then he asks the impossible question, "What would the average random code do?" He then proves that the average code is arbitrarily good, and that therefore there must be at least one good code. Who but a man of infinite courage could have dared to think those thoughts? That is the characteristic of great scientists; they have courage. They will go forward under incredible circumstances; they think and continue to think.

Age is another factor which the physicists particularly worry about. They always are saying that you have got to do it when you are young or you will never do it. Einstein did things very early, and all the quantum mechanic fellows were disgustingly young when they did their best work. Most mathematicians, theoretical physicists, and astrophysicists do what we consider their best work when they are young. It is not that they don't do good work in their old age but what we value most is often what they did early. On the other hand, in music, politics and literature, often what we consider their best work was done late. I don't know how whatever field you are in fits this scale, but age has some effect.

But let me say why age seems to have the effect it does. In the first place if you do some good work you will find yourself on all kinds of committees and unable to do any more work. You may find yourself as I saw Brattain when he got a Nobel Prize. The day the prize was announced we all assembled in Arnold Auditorium; all three winners got up and made speeches. The third one, Brattain, practically with tears in his eyes, said, "I know about this Nobel-Prize effect and I am not going to let it affect me; I am going to remain good old Walter Brattain." Well I said to myself, "That is nice." But in a few weeks I saw it was affecting him. Now he could only work on great problems.

When you are famous it is hard to work on small problems. This is what did Shannon in. After information theory, what do you do for an encore? The great scientists often make this error. They fail to continue to plant the little acorns from which the mighty oak trees grow. They try to get the big thing right off. And that isn't the way things go. So that is another reason why you find that when you get early recognition it seems to sterilize you. In fact I will give you my favorite quotation of many years. The Institute for Advanced Study in Princeton, in my opinion, has ruined more good scientists than any institution has created, judged by what they did before they came and judged by what they did after. Not that they weren't good afterwards, but they were superb before they got there and were only good afterwards.

This brings up the subject, out of order perhaps, of working conditions. What most people think are the best working conditions, are not. Very clearly they are not because people are often most productive when working conditions are bad. One of the better times of the Cambridge Physical Laboratories was when they had practically shacks ­ they did some of the best physics ever.

I give you a story from my own private life. Early on it became evident to me that Bell Laboratories was not going to give me the conventional acre of programming people to program computing machines in absolute binary. It was clear they weren't going to. But that was the way everybody did it. I could go to the West Coast and get a job with the airplane companies without any trouble, but the exciting people were at Bell Labs and the fellows out there in the airplane companies were not. I thought for a long while about, "Did I want to go or not?" and I wondered how I could get the best of two possible worlds. I finally said to myself, "Hamming, you think the machines can do practically everything. Why can't you make them write programs?" What appeared at first to me as a defect forced me into automatic programming very early. What appears to be a fault, often, by a change of viewpoint, turns out to be one of the greatest assets you can have. But you are not likely to think that when you first look the thing and say, "Gee, I'm never going to get enough programmers, so how can I ever do any great programming?"

And there are many other stories of the same kind; Grace Hopper has similar ones. I think that if you look carefully you will see that often the great scientists, by turning the problem around a bit, changed a defect to an asset. For example, many scientists when they found they couldn't do a problem finally began to study why not. They then turned it around the other way and said, "But of course, this is what it is" and got an important result. So ideal working conditions are very strange. The ones you want aren't always the best ones for you.

Now for the matter of drive. You observe that most great scientists have tremendous drive. I worked for ten years with John Tukey at Bell Labs. He had tremendous drive. One day about three or four years after I joined, I discovered that John Tukey was slightly younger than I was. John was a genius and I clearly was not. Well I went storming into Bode's office and said, "How can anybody my age know as much as John Tukey does?" He leaned back in his chair, put his hands behind his head, grinned slightly, and said, "You would be surprised Hamming, how much you would know if you worked as hard as he did that many years." I simply slunk out of the office!

What Bode was saying was this: "Knowledge and productivity are like compound interest." Given two people of approximately the same ability and one person who works ten percent more than the other, the latter will more than twice outproduce the former. The more you know, the more you learn; the more you learn, the more you can do; the more you can do, the more the opportunity ­ it is very much like compound interest. I don't want to give you a rate, but it is a very high rate. Given two people with exactly the same ability, the one person who manages day in and day out to get in one more hour of thinking will be tremendously more productive over a lifetime. I took Bode's remark to heart; I spent a good deal more of my time for some years trying to work a bit harder and I found, in fact, I could get more work done. I don't like to say it in front of my wife, but I did sort of neglect her sometimes; I needed to study. You have to neglect things if you intend to get what you want done. There's no question about this.

On this matter of drive Edison says, "Genius is 99% perspiration and 1% inspiration." He may have been exaggerating, but the idea is that solid work, steadily applied, gets you surprisingly far. The steady application of effort with a little bit more work, intelligently applied is what does it. That's the trouble; drive, misapplied, doesn't get you anywhere. I've often wondered why so many of my good friends at Bell Labs who worked as hard or harder than I did, didn't have so much to show for it. The misapplication of effort is a very serious matter. Just hard work is not enough ­ it must be applied sensibly.

There's another trait on the side which I want to talk about; that trait is ambiguity. It took me a while to discover its importance. Most people like to believe something is or is not true. Great scientists tolerate ambiguity very well. They believe the theory enough to go ahead; they doubt it enough to notice the errors and faults so they can step forward and create the new replacement theory. If you believe too much you'll never notice the flaws; if you doubt too much you won't get started. It requires a lovely balance. But most great scientists are well aware of why their theories are true and they are also well aware of some slight misfits which don't quite fit and they don't forget it. Darwin writes in his autobiography that he found it necessary to write down every piece of evidence which appeared to contradict his beliefs because otherwise they would disappear from his mind. When you find apparent flaws you've got to be sensitive and keep track of those things, and keep an eye out for how they can be explained or how the theory can be changed to fit them. Those are often the great contributions. Great contributions are rarely done by adding another decimal place. It comes down to an emotional commitment. Most great scientists are completely committed to their problem. Those who don't become committed seldom produce outstanding, first-class work.

Now again, emotional commitment is not enough. It is a necessary condition apparently. And I think I can tell you the reason why. Everybody who has studied creativity is driven finally to saying, "creativity comes out of your subconscious." Somehow, suddenly, there it is. It just appears. Well, we know very little about the subconscious; but one thing you are pretty well aware of is that your dreams also come out of your subconscious. And you're aware your dreams are, to a fair extent, a reworking of the experiences of the day. If you are deeply immersed and committed to a topic, day after day after day, your subconscious has nothing to do but work on your problem. And so you wake up one morning, or on some afternoon, and there's the answer. For those who don't get committed to their current problem, the subconscious goofs off on other things and doesn't produce the big result. So the way to manage yourself is that when you have a real important problem you don't let anything else get the center of your attention ­ you keep your thoughts on the problem. Keep your subconscious starved so it has to work on your problem, so you can sleep peacefully and get the answer in the morning, free.

Now Alan Chynoweth mentioned that I used to eat at the physics table. I had been eating with the mathematicians and I found out that I already knew a fair amount of mathematics; in fact, I wasn't learning much. The physics table was, as he said, an exciting place, but I think he exaggerated on how much I contributed. It was very interesting to listen to Shockley, Brattain, Bardeen, J. B. Johnson, Ken McKay and other people, and I was learning a lot. But unfortunately a Nobel Prize came, and a promotion came, and what was left was the dregs. Nobody wanted what was left. Well, there was no use eating with them!

Over on the other side of the dining hall was a chemistry table. I had worked with one of the fellows, Dave McCall; furthermore he was courting our secretary at the time. I went over and said, "Do you mind if I join you?" They can't say no, so I started eating with them for a while. And I started asking, "What are the important problems of your field?" And after a week or so, "What important problems are you working on?" And after some more time I came in one day and said, "If what you are doing is not important, and if you don't think it is going to lead to something important, why are you at Bell Labs working on it?" I wasn't welcomed after that; I had to find somebody else to eat with! That was in the spring.

In the fall, Dave McCall stopped me in the hall and said, "Hamming, that remark of yours got underneath my skin. I thought about it all summer, i.e. what were the important problems in my field. I haven't changed my research," he says, "but I think it was well worthwhile." And I said, "Thank you Dave," and went on. I noticed a couple of months later he was made the head of the department. I noticed the other day he was a Member of the National Academy of Engineering. I noticed he has succeeded. I have never heard the names of any of the other fellows at that table mentioned in science and scientific circles. They were unable to ask themselves, "What are the important problems in my field?"

If you do not work on an important problem, it's unlikely you'll do important work. It's perfectly obvious. Great scientists have thought through, in a careful way, a number of important problems in their field, and they keep an eye on wondering how to attack them. Let me warn you, `important problem' must be phrased carefully. The three outstanding problems in physics, in a certain sense, were never worked on while I was at Bell Labs. By important I mean guaranteed a Nobel Prize and any sum of money you want to mention. We didn't work on (1) time travel, (2) teleportation, and (3) antigravity. They are not important problems because we do not have an attack. It's not the consequence that makes a problem important, it is that you have a reasonable attack. That is what makes a problem important. When I say that most scientists don't work on important problems, I mean it in that sense. The average scientist, so far as I can make out, spends almost all his time working on problems which he believes will not be important and he also doesn't believe that they will lead to important problems.

I spoke earlier about planting acorns so that oaks will grow. You can't always know exactly where to be, but you can keep active in places where something might happen. And even if you believe that great science is a matter of luck, you can stand on a mountain top where lightning strikes; you don't have to hide in the valley where you're safe. But the average scientist does routine safe work almost all the time and so he (or she) doesn't produce much. It's that simple. If you want to do great work, you clearly must work on important problems, and you should have an idea.

Along those lines at some urging from John Tukey and others, I finally adopted what I called "Great Thoughts Time." When I went to lunch Friday noon, I would only discuss great thoughts after that. By great thoughts I mean ones like, "What will be the role of computers in all of AT&T?", "How will computers change science?". For example, I came up with the observation at that time that nine out of ten experiments were done in the lab and one in ten on the computer. I made a remark to the vice presidents one time, that it would be reversed, i.e. nine out of ten experiments would be done on the computer and one in ten in the lab. They knew I was a crazy mathematician and had no sense of reality. I knew they were wrong and they've been proved wrong while I have been proved right. They built laboratories when they didn't need them. I saw that computers were transforming science because I spent a lot of time asking "What will be the impact of computers on science and how can I change it?" I asked myself, "How is it going to change Bell Labs?" I remarked one time, in the same address, that more than one-half of the people at Bell Labs will be interacting closely with computing machines before I leave. Well, you all have terminals now. I thought hard about where was my field going, where were the opportunities, and what were the important things to do. Let me go there so there is a chance I can do important things.

Most great scientists know many important problems. They have something between 10 and 20 important problems for which they are looking for an attack. And when they see a new idea come up, one hears them say "Well that bears on this problem." They drop all the other things and get after it. Now I can tell you a horror story that was told to me but I can't vouch for the truth of it. I was sitting in an airport talking to a friend of mine from Los Alamos about how it was lucky that the fission experiment occurred over in Europe when it did because that got us working on the atomic bomb here in the US. He said "No; at Berkeley we had gathered a bunch of data; we didn't get around to reducing it because we were building some more equipment, but if we had reduced that data we would have found fission." They had it in their hands and they didn't pursue it. They came in second!

The great scientists, when an opportunity opens up, get after it and they pursue it. They drop all other things. They get rid of other things and they get after an idea because they had already thought the thing through. Their minds are prepared; they see the opportunity and they go after it. Now of course lots of times it doesn't work out, but you don't have to hit many of them to do some great science. It's kind of easy. One of the chief tricks is to live a long time!

Another trait, it took me a while to notice. I noticed the following facts about people who work with the door open or the door closed. I notice that if you have the door to your office closed, you get more work done today and tomorrow, and you are more productive than most. But 10 years later somehow you don't quite know what problems are worth working on; all the hard work you do is sort of tangential in importance. He who works with the door open gets all kinds of interruptions, but he also occasionally gets clues as to what the world is and what might be important. Now I cannot prove the cause and effect sequence because you might say, "The closed door is symbolic of a closed mind." I don't know. But I can say there is a pretty good correlation between those who work with the doors open and those who ultimately do important things, although people who work with doors closed often work harder. Somehow they seem to work on slightly the wrong thing ­ not much, but enough that they miss fame.

I want to talk on another topic. It is based on the song which I think many of you know, "It ain't what you do, it's the way that you do it." I'll start with an example of my own. I was conned into doing on a digital computer, in the absolute binary days, a problem which the best analog computers couldn't do. And I was getting an answer. When I thought carefully and said to myself, "You know, Hamming, you're going to have to file a report on this military job; after you spend a lot of money you're going to have to account for it and every analog installation is going to want the report to see if they can't find flaws in it." I was doing the required integration by a rather crummy method, to say the least, but I was getting the answer. And I realized that in truth the problem was not just to get the answer; it was to demonstrate for the first time, and beyond question, that I could beat the analog computer on its own ground with a digital machine. I reworked the method of solution, created a theory which was nice and elegant, and changed the way we computed the answer; the results were no different. The published report had an elegant method which was later known for years as "Hamming's Method of Integrating Differential Equations." It is somewhat obsolete now, but for a while it was a very good method. By changing the problem slightly, I did important work rather than trivial work.

In the same way, when using the machine up in the attic in the early days, I was solving one problem after another after another; a fair number were successful and there were a few failures. I went home one Friday after finishing a problem, and curiously enough I wasn't happy; I was depressed. I could see life being a long sequence of one problem after another after another. After quite a while of thinking I decided, "No, I should be in the mass production of a variable product. I should be concerned with all of next year's problems, not just the one in front of my face." By changing the question I still got the same kind of results or better, but I changed things and did important work. I attacked the major problem ­ How do I conquer machines and do all of next year's problems when I don't know what they are going to be? How do I prepare for it? How do I do this one so I'll be on top of it? How do I obey Newton's rule? He said, "If I have seen further than others, it is because I've stood on the shoulders of giants." These days we stand on each other's feet!

You should do your job in such a fashion that others can build on top of it, so they will indeed say, "Yes, I've stood on so and so's shoulders and I saw further." The essence of science is cumulative. By changing a problem slightly you can often do great work rather than merely good work. Instead of attacking isolated problems, I made the resolution that I would never again solve an isolated problem except as characteristic of a class.

Now if you are much of a mathematician you know that the effort to generalize often means that the solution is simple. Often by stopping and saying, "This is the problem he wants but this is characteristic of so and so. Yes, I can attack the whole class with a far superior method than the particular one because I was earlier embedded in needless detail." The business of abstraction frequently makes things simple. Furthermore, I filed away the methods and prepared for the future problems.

To end this part, I'll remind you, "It is a poor workman who blames his tools ­ the good man gets on with the job, given what he's got, and gets the best answer he can." And I suggest that by altering the problem, by looking at the thing differently, you can make a great deal of difference in your final productivity because you can either do it in such a fashion that people can indeed build on what you've done, or you can do it in such a fashion that the next person has to essentially duplicate again what you've done. It isn't just a matter of the job, it's the way you write the report, the way you write the paper, the whole attitude. It's just as easy to do a broad, general job as one very special case. And it's much more satisfying and rewarding!

I have now come down to a topic which is very distasteful; it is not sufficient to do a job, you have to sell it. `Selling' to a scientist is an awkward thing to do. It's very ugly; you shouldn't have to do it. The world is supposed to be waiting, and when you do something great, they should rush out and welcome it. But the fact is everyone is busy with their own work. You must present it so well that they will set aside what they are doing, look at what you've done, read it, and come back and say, "Yes, that was good." I suggest that when you open a journal, as you turn the pages, you ask why you read some articles and not others. You had better write your report so when it is published in the Physical Review, or wherever else you want it, as the readers are turning the pages they won't just turn your pages but they will stop and read yours. If they don't stop and read it, you won't get credit.

There are three things you have to do in selling. You have to learn to write clearly and well so that people will read it, you must learn to give reasonably formal talks, and you also must learn to give informal talks. We had a lot of so-called "back room scientists". In a conference, they would keep quiet. Three weeks later after a decision was made they filed a report saying why you should do so and so. Well, it was too late. They would not stand up right in the middle of a hot conference, in the middle of activity, and say, "We should do this for these reasons." You need to master that form of communication as well as prepared speeches.

When I first started, I got practically physically ill while giving a speech, and I was very, very nervous. I realized I either had to learn to give speeches smoothly or I would essentially partially cripple my whole career. The first time IBM asked me to give a speech in New York one evening, I decided I was going to give a really good speech, a speech that was wanted, not a technical one but a broad one, and at the end if they liked it, I'd quietly say, "Any time you want one I'll come in and give you one." As a result, I got a great deal of practice giving speeches to a limited audience and I got over being afraid. Furthermore, I could also then study what methods were effective and what were ineffective.

While going to meetings I had already been studying why some papers are remembered and most are not. The technical person wants to give a highly limited technical talk. Most of the time the audience wants a broad general talk and wants much more survey and background than the speaker is willing to give. As a result, many talks are ineffective. The speaker names a topic and suddenly plunges into the details he's solved. Few people in the audience may follow. You should paint a general picture to say why it's important, and then slowly give a sketch of what was done. Then a larger number of people will say, "Yes, Joe has done that," or "Mary has done that; I really see where it is; yes, Mary really gave a good talk; I understand what Mary has done." The tendency is to give a highly restricted, safe talk; this is usually ineffective. Furthermore, many talks are filled with far too much information. So I say this idea of selling is obvious.

Let me summarize. You've got to work on important problems. I deny that it is all luck, but I admit there is a fair element of luck. I subscribe to Pasteur's "Luck favors the prepared mind." I favor heavily what I did. Friday afternoons for years ­ great thoughts only ­ means that I committed 10% of my time trying to understand the bigger problems in the field, i.e. what was and what was not important. I found in the early days I had believed `this' and yet had spent all week marching in `that' direction. It was kind of foolish. If I really believe the action is over there, why do I march in this direction? I either had to change my goal or change what I did. So I changed something I did and I marched in the direction I thought was important. It's that easy.

Now you might tell me you haven't got control over what you have to work on. Well, when you first begin, you may not. But once you're moderately successful, there are more people asking for results than you can deliver and you have some power of choice, but not completely. I'll tell you a story about that, and it bears on the subject of educating your boss. I had a boss named Schelkunoff; he was, and still is, a very good friend of mine. Some military person came to me and demanded some answers by Friday. Well, I had already dedicated my computing resources to reducing data on the fly for a group of scientists; I was knee deep in short, small, important problems. This military person wanted me to solve his problem by the end of the day on Friday. I said, "No, I'll give it to you Monday. I can work on it over the weekend. I'm not going to do it now." He goes down to my boss, Schelkunoff, and Schelkunoff says, "You must run this for him; he's got to have it by Friday." I tell him, "Why do I?"; he says, "You have to." I said, "Fine, Sergei, but you're sitting in your office Friday afternoon catching the late bus home to watch as this fellow walks out that door." I gave the military person the answers late Friday afternoon. I then went to Schelkunoff's office and sat down; as the man goes out I say, "You see Schelkunoff, this fellow has nothing under his arm; but I gave him the answers." On Monday morning Schelkunoff called him up and said, "Did you come in to work over the weekend?" I could hear, as it were, a pause as the fellow ran through his mind of what was going to happen; but he knew he would have had to sign in, and he'd better not say he had when he hadn't, so he said he hadn't. Ever after that Schelkunoff said, "You set your deadlines; you can change them."

One lesson was sufficient to educate my boss as to why I didn't want to do big jobs that displaced exploratory research and why I was justified in not doing crash jobs which absorb all the research computing facilities. I wanted instead to use the facilities to compute a large number of small problems. Again, in the early days, I was limited in computing capacity and it was clear, in my area, that a "mathematician had no use for machines." But I needed more machine capacity. Every time I had to tell some scientist in some other area, "No I can't; I haven't the machine capacity," he complained. I said "Go tell your Vice President that Hamming needs more computing capacity." After a while I could see what was happening up there at the top; many people said to my Vice President, "Your man needs more computing capacity." I got it!

I also did a second thing. When I loaned what little programming power we had to help in the early days of computing, I said, "We are not getting the recognition for our programmers that they deserve. When you publish a paper you will thank that programmer or you aren't getting any more help from me. That programmer is going to be thanked by name; she's worked hard." I waited a couple of years. I then went through a year of BSTJ articles and counted what fraction thanked some programmer. I took it into the boss and said, "That's the central role computing is playing in Bell Labs; if the BSTJ is important, that's how important computing is." He had to give in. You can educate your bosses. It's a hard job. In this talk I'm only viewing from the bottom up; I'm not viewing from the top down. But I am telling you how you can get what you want in spite of top management. You have to sell your ideas there also.

Well I now come down to the topic, "Is the effort to be a great scientist worth it?" To answer this, you must ask people. When you get beyond their modesty, most people will say, "Yes, doing really first-class work, and knowing it, is as good as wine, women and song put together," or if it's a woman she says, "It is as good as wine, men and song put together." And if you look at the bosses, they tend to come back or ask for reports, trying to participate in those moments of discovery. They're always in the way. So evidently those who have done it, want to do it again. But it is a limited survey. I have never dared to go out and ask those who didn't do great work how they felt about the matter. It's a biased sample, but I still think it is worth the struggle. I think it is very definitely worth the struggle to try and do first-class work because the truth is, the value is in the struggle more than it is in the result. The struggle to make something of yourself seems to be worthwhile in itself. The success and fame are sort of dividends, in my opinion.

I've told you how to do it. It is so easy, so why do so many people, with all their talents, fail? For example, my opinion, to this day, is that there are in the mathematics department at Bell Labs quite a few people far more able and far better endowed than I, but they didn't produce as much. Some of them did produce more than I did; Shannon produced more than I did, and some others produced a lot, but I was highly productive against a lot of other fellows who were better equipped. Why is it so? What happened to them? Why do so many of the people who have great promise, fail?

Well, one of the reasons is drive and commitment. The people who do great work with less ability but who are committed to it, get more done that those who have great skill and dabble in it, who work during the day and go home and do other things and come back and work the next day. They don't have the deep commitment that is apparently necessary for really first-class work. They turn out lots of good work, but we were talking, remember, about first-class work. There is a difference. Good people, very talented people, almost always turn out good work. We're talking about the outstanding work, the type of work that gets the Nobel Prize and gets recognition.

The second thing is, I think, the problem of personality defects. Now I'll cite a fellow whom I met out in Irvine. He had been the head of a computing center and he was temporarily on assignment as a special assistant to the president of the university. It was obvious he had a job with a great future. He took me into his office one time and showed me his method of getting letters done and how he took care of his correspondence. He pointed out how inefficient the secretary was. He kept all his letters stacked around there; he knew where everything was. And he would, on his word processor, get the letter out. He was bragging how marvelous it was and how he could get so much more work done without the secretary's interference. Well, behind his back, I talked to the secretary. The secretary said, "Of course I can't help him; I don't get his mail. He won't give me the stuff to log in; I don't know where he puts it on the floor. Of course I can't help him." So I went to him and said, "Look, if you adopt the present method and do what you can do single-handedly, you can go just that far and no farther than you can do single-handedly. If you will learn to work with the system, you can go as far as the system will support you." And, he never went any further. He had his personality defect of wanting total control and was not willing to recognize that you need the support of the system.

You find this happening again and again; good scientists will fight the system rather than learn to work with the system and take advantage of all the system has to offer. It has a lot, if you learn how to use it. It takes patience, but you can learn how to use the system pretty well, and you can learn how to get around it. After all, if you want a decision `No', you just go to your boss and get a `No' easy. If you want to do something, don't ask, do it. Present him with an accomplished fact. Don't give him a chance to tell you `No'. But if you want a `No', it's easy to get a `No'.

Another personality defect is ego assertion and I'll speak in this case of my own experience. I came from Los Alamos and in the early days I was using a machine in New York at 590 Madison Avenue where we merely rented time. I was still dressing in western clothes, big slash pockets, a bolo and all those things. I vaguely noticed that I was not getting as good service as other people. So I set out to measure. You came in and you waited for your turn; I felt I was not getting a fair deal. I said to myself, "Why? No Vice President at IBM said, `Give Hamming a bad time'. It is the secretaries at the bottom who are doing this. When a slot appears, they'll rush to find someone to slip in, but they go out and find somebody else. Now, why? I haven't mistreated them." Answer, I wasn't dressing the way they felt somebody in that situation should. It came down to just that ­ I wasn't dressing properly. I had to make the decision ­ was I going to assert my ego and dress the way I wanted to and have it steadily drain my effort from my professional life, or was I going to appear to conform better? I decided I would make an effort to appear to conform properly. The moment I did, I got much better service. And now, as an old colorful character, I get better service than other people.

You should dress according to the expectations of the audience spoken to. If I am going to give an address at the MIT computer center, I dress with a bolo and an old corduroy jacket or something else. I know enough not to let my clothes, my appearance, my manners get in the way of what I care about. An enormous number of scientists feel they must assert their ego and do their thing their way. They have got to be able to do this, that, or the other thing, and they pay a steady price.

John Tukey almost always dressed very casually. He would go into an important office and it would take a long time before the other fellow realized that this is a first-class man and he had better listen. For a long time John has had to overcome this kind of hostility. It's wasted effort! I didn't say you should conform; I said "The appearance of conforming gets you a long way." If you chose to assert your ego in any number of ways, "I am going to do it my way," you pay a small steady price throughout the whole of your professional career. And this, over a whole lifetime, adds up to an enormous amount of needless trouble.

By taking the trouble to tell jokes to the secretaries and being a little friendly, I got superb secretarial help. For instance, one time for some idiot reason all the reproducing services at Murray Hill were tied up. Don't ask me how, but they were. I wanted something done. My secretary called up somebody at Holmdel, hopped the company car, made the hour-long trip down and got it reproduced, and then came back. It was a payoff for the times I had made an effort to cheer her up, tell her jokes and be friendly; it was that little extra work that later paid off for me. By realizing you have to use the system and studying how to get the system to do your work, you learn how to adapt the system to your desires. Or you can fight it steadily, as a small undeclared war, for the whole of your life.

And I think John Tukey paid a terrible price needlessly. He was a genius anyhow, but I think it would have been far better, and far simpler, had he been willing to conform a little bit instead of ego asserting. He is going to dress the way he wants all of the time. It applies not only to dress but to a thousand other things; people will continue to fight the system. Not that you shouldn't occasionally!

When they moved the library from the middle of Murray Hill to the far end, a friend of mine put in a request for a bicycle. Well, the organization was not dumb. They waited awhile and sent back a map of the grounds saying, "Will you please indicate on this map what paths you are going to take so we can get an insurance policy covering you." A few more weeks went by. They then asked, "Where are you going to store the bicycle and how will it be locked so we can do so and so." He finally realized that of course he was going to be red-taped to death so he gave in. He rose to be the President of Bell Laboratories.

Barney Oliver was a good man. He wrote a letter one time to the IEEE. At that time the official shelf space at Bell Labs was so much and the height of the IEEE Proceedings at that time was larger; and since you couldn't change the size of the official shelf space he wrote this letter to the IEEE Publication person saying, "Since so many IEEE members were at Bell Labs and since the official space was so high the journal size should be changed." He sent it for his boss's signature. Back came a carbon with his signature, but he still doesn't know whether the original was sent or not. I am not saying you shouldn't make gestures of reform. I am saying that my study of able people is that they don't get themselves committed to that kind of warfare. They play it a little bit and drop it and get on with their work.

Many a second-rate fellow gets caught up in some little twitting of the system, and carries it through to warfare. He expends his energy in a foolish project. Now you are going to tell me that somebody has to change the system. I agree; somebody's has to. Which do you want to be? The person who changes the system or the person who does first-class science? Which person is it that you want to be? Be clear, when you fight the system and struggle with it, what you are doing, how far to go out of amusement, and how much to waste your effort fighting the system. My advice is to let somebody else do it and you get on with becoming a first-class scientist. Very few of you have the ability to both reform the system and become a first-class scientist.

On the other hand, we can't always give in. There are times when a certain amount of rebellion is sensible. I have observed almost all scientists enjoy a certain amount of twitting the system for the sheer love of it. What it comes down to basically is that you cannot be original in one area without having originality in others. Originality is being different. You can't be an original scientist without having some other original characteristics. But many a scientist has let his quirks in other places make him pay a far higher price than is necessary for the ego satisfaction he or she gets. I'm not against all ego assertion; I'm against some.

Another fault is anger. Often a scientist becomes angry, and this is no way to handle things. Amusement, yes, anger, no. Anger is misdirected. You should follow and cooperate rather than struggle against the system all the time.

Another thing you should look for is the positive side of things instead of the negative. I have already given you several examples, and there are many, many more; how, given the situation, by changing the way I looked at it, I converted what was apparently a defect to an asset. I'll give you another example. I am an egotistical person; there is no doubt about it. I knew that most people who took a sabbatical to write a book, didn't finish it on time. So before I left, I told all my friends that when I come back, that book was going to be done! Yes, I would have it done ­ I'd have been ashamed to come back without it! I used my ego to make myself behave the way I wanted to. I bragged about something so I'd have to perform. I found out many times, like a cornered rat in a real trap, I was surprisingly capable. I have found that it paid to say, "Oh yes, I'll get the answer for you Tuesday," not having any idea how to do it. By Sunday night I was really hard thinking on how I was going to deliver by Tuesday. I often put my pride on the line and sometimes I failed, but as I said, like a cornered rat I'm surprised how often I did a good job. I think you need to learn to use yourself. I think you need to know how to convert a situation from one view to another which would increase the chance of success.

Now self-delusion in humans is very, very common. There are enumerable ways of you changing a thing and kidding yourself and making it look some other way. When you ask, "Why didn't you do such and such," the person has a thousand alibis. If you look at the history of science, usually these days there are 10 people right there ready, and we pay off for the person who is there first. The other nine fellows say, "Well, I had the idea but I didn't do it and so on and so on." There are so many alibis. Why weren't you first? Why didn't you do it right? Don't try an alibi. Don't try and kid yourself. You can tell other people all the alibis you want. I don't mind. But to yourself try to be honest.

If you really want to be a first-class scientist you need to know yourself, your weaknesses, your strengths, and your bad faults, like my egotism. How can you convert a fault to an asset? How can you convert a situation where you haven't got enough manpower to move into a direction when that's exactly what you need to do? I say again that I have seen, as I studied the history, the successful scientist changed the viewpoint and what was a defect became an asset.

In summary, I claim that some of the reasons why so many people who have greatness within their grasp don't succeed are: they don't work on important problems, they don't become emotionally involved, they don't try and change what is difficult to some other situation which is easily done but is still important, and they keep giving themselves alibis why they don't. They keep saying that it is a matter of luck. I've told you how easy it is; furthermore I've told you how to reform. Therefore, go forth and become great scientists!

(End of the formal part of the talk.)

Kai-Fu Lee gave a lecture "Wisdom of Choice" at the auditorium this morning.
And I found his another speech online, "Talent needed in 21 Century".
excerpt as follows,

李开复：21世纪最需要的7种人才

我们都知道21世纪最有价值的是人才，是什么人才呢，就是我今天要演讲的题目。我想我这个演讲有一个很大的假设就是21世纪需要的人才与20世纪、19世纪有着很大的差别，因为21世纪有几个很重大的革命发生。在21世纪我们更多的工作是靠我们脑力的创造，是靠平等的竞争，已经没有国界的差别，世界被铲为平地，任何一个国家的人都可以和另外一个国家的人合作或者竞争，而他们都可以接触到、使用到、共享到同样的信息。不像过去，谁能独占信息他就能对另一个人或者对那个公司发挥相当大的价值。

今天的信息是因为共享才能发挥它真正的潜力。所以在这样的情况下，每个人都可以自由地选择，平等地竞争，他们会积极地去获取自己的信息，追求自己的兴趣。他们期望自己工作的公司采取的不再是控制式的管理，而是放权式的管理。因为在21世纪，一个人他是靠自己的脑力创造财富，他很聪明很有创意，他跟全世界每一个人平等地竞争，然后每一个人都有同样的信息，没有一个人会愿意在一个不公平的控制下做一个公司的齿轮。每个人都会希望发挥自己的潜能，他希望自己到一个公司工作，这个公司能够放权地让每一个员工做自己的事情。还有呢，21世纪什么都改变得非常快。你才认为说某某一个技术或者某某一个公司是很火热的，忽然一个新的技术或者一个新的公司已经出来了。这都是因为互联网，每个国家，每个领域之间的边界因此在不断地消除，世界各地的人们可以一起工作，竞争和合作。所以在这样的一个环境之下，21世纪需要的不再是19、20世纪听话，没有自己意见，努力有毅力的所谓的蓝领或者白领工人，更需要的是我的演讲要谈到的7种人。

创新实践者——What matters is not innovation , but useful innovation。

这7种人中的第1种是创新实践者。在今天谈到的所有人时，我都会引用一句我认为很好的话。那么第一句话是谁说得呢，是我说的。这句话跟创新有关，待会还会谈到。我想说的是在21世纪真正有价值的人是能够创新的人。他不是一个只会使用别人的方法做事情的人，他不是那种只会听话做事情的一颗棋子，一个齿轮。因为，在如今的竞争之下，一个公司唯一可以延续的竞争优势就是它的创新。任何东西都可以很容易地被模仿，只有创新很难被模仿。而创新一旦被模仿，你唯一的办法就是继续地创新。所以一批有生命力的能够持续创新的员工是唯一能够带给企业持续竞争力的财富。

你们可能会说，李开复是不是要讲Google，讲其他科技公司要学计算机科学，要做最高深的研究这才是创新呢？其实不是的。在每一个领域都可以创新，也就是这些每一个不同领域的创新，让每一个工作变得多彩多姿。我可以举个例子。如果你在美国加州101公路硅谷段上开车，你可能会看到一个广告牌。整个广告牌上面没有公司名也没有任何广告词，只简简单单刷着“(在‘e’的数列中所能找到的第一个十位数质数).com”。很多在硅谷工作的聪明人开车看到了这个广告，他们回家就会去算，有些用计算机来算，有些用数学方法来推算，算出来答案以后登陆这个网站一看，发现另外有一个更难的题目。然后他们再做了这道题目，又会到达另外一个网站，就着样做了一个题目又一个题目，最后他们发现自己到了一个很特殊的网站，这个网站就是Google的招聘网站。我们可以从这个例子看到，在Google这样一个创新的公司，它的创新其实远远不止在于一个工程部门。你可以看到招聘，市场都是充满了创意的。

关于创新还有一点要注意的，21世纪的创新必须实时、实践。因为我们有了互联网的存在，每个公司的步伐都非常快。如果你花很多的时候去做一些验证，一些用户调查，再花一两年的时间才把一个东西编出来再做测试，一个产品四五年做出来以后很可能已经过时了。所以在这21世纪，光做一个创新者是不够的，要做一个创新实践者。这就回答了我上面那句话：What matters is not innovation, but useful innovation。只是为了创新而创新是没有意义的，要做有用的创新才是有意义的。

记得我在SCI公司的时候，曾经犯过的一个最大的错误就是只想到创新，没有想到实践。我们做了一个非常酷的三维浏览器，今天可能都还没有人在使用。当时，我们每次演示的时候，观众的下巴都会掉下来，说：哇，怎么会做这么酷的一个东西！但是我们忘记了这么酷的东西却是没有市场的。最后结果是相当的失败，让我也有了一个很惨痛的经验，尤其是当我看到一百多名员工失去他们工作的时候，让我下了一个决心，就是上面这句话。

我们虽然要创新，但是不是为了创新而创新，而是为了做有用的事情而创新。我们如果回顾历史，可以看到许多成功的人才，他们有些创新，有些实践，有些左脑发达，有些右脑发达。但是那些真正对世界有重大贡献的人，我想他们不仅是创新者，也是实践者，比如说爱迪生，比尔盖茨，Larry 和Sergey，都是很好的例子。一个真正的创新实践者每一次在创新的时候都忘不了实践，在实践的时候也忘不了创新，这样的人，我想是21世纪不可缺少的人才。

跨领域合成者——What matters is not analysis but synthesis。

第2点呢，我想非常需要的是跨领域合成者。刚才听到了竺可桢学院，它本身是多学科的，强化班也是由来自不同专业的同学组成的。这点确实也是非常符合了所谓的合成者。相信在中国的未来，在全世界的未来，我们更需要的人才不只是那些把一个学科学得非常非常深的，而是那些把自己学科学好，同时能够与其他领域做一个跨领域结合的人才。原因其实非常简单，如果是世界上有1000种知识，这个知识本身你可以学得很深，但是两个人的知识通过交叉碰撞又可以产生新的知识，三个人的碰撞就能产生十亿个组合。

以计算机为例，如果你是学计算机的，又对心理学感兴趣，这样一个跨学科的合成，你可能对用户界面或者可用度测试会有一些贡献。所以，很多新的领域的产生，都是靠过去的两种学科所交叉碰撞出来的，这是一个很好的机会。如果把一门学科学得太深了，可能会去钻牛角尖，反而失去创新实践的机会。真正重要的不是analysis，不是要分析得很深，而是synthesis，怎么样有合成的机会。

所以，对各位同学我的建议就是，当然读好你的专业是有必要的，但是同时要考虑下是否还有别的什么专业是你有兴趣的。这两个专业最新的思想能不能结合起来，做一些即有创意又可以实践的东西，这可能是最有成长空间的一些机会。

高情商合作者——EQ is 9 times more important than IQ。

第3种最需要的人是高情商合作者。EQ is 9 times more important than IQ，这句话来自Daniel Goleman的《EQ》这本书。《EQ》这本书谈到情商和智商的一些差别，还有哪个比较重要。他做了一个研究，找了几千个企业的领导者。他研究是什么因素让这些非常优秀的领导者和普通的领导者有所区别。他研究的结论最重要的差别不在于IQ，而是比IQ要更重要9倍的EQ，即情商。

情商包括了怎样与人合作，包括了对自己的一种自觉，包括了对自己的一种管理，也包括了和别人团结合作以及社交的一些能力。EQ的重要性在21世纪是非常显著的，因为在21世纪，我们需要全球的合作，需要跨领域的合成。比如说你学的是心理学，你要跟学计算机的人合作才能做得出用户界面。跨领域的合作，跨国度的合作，跨语言的合作，这些都是必须要的。所以，过去也许在很多的环境里面，你作为一个孤僻自傲的天才会得到很大的重视，但是这个情况现在已经在大大地改变了。

过去，我曾在我的人才观里提到，在这个信息社会里，与过去的工业社会很大的一个差别就是信息社会最好的一个人才，一个程序员、一个科学家，可能比普通人生产力好个3倍、5倍、10倍或者20倍甚至更多。但是我想在这里补充的一句话就是说，即使他在技术方面好个多少倍，如果他是一个孤僻自傲、不能合作，甚至引起团队无法工作的人，那么他对这个团队，反而是一个负面的效果。

当我们做管理的时候，我们也必须考虑到，如果你要建立一个非常健康的团队，不管是在Google工作还是未来的Google Camp，一定要在每个人很客观高情商地愿意与他人合作，尊敬别人的前提之下，才可能有很好的结果，尤其是在21世纪这样一个情商和合作是那么重要的世纪里面。所以，我对各位同学的建议是，在你可以抓住的每一个机会里，多参与社团工作，多建立一些与人合作的基础，无论是在上课，还是参与社团项目，或是暑期工作的机会。让自己除了读书之外，多做一个能够与人团结、合作、客观、尊敬别人、聆听别人的一个高情商的学生。

高效能沟通者——The man who can think and does not know how to express what he thinks is at the level of him who cannot think。

第4种人是高效能的沟通者。一个人如果有思想但是不能表达自己，他其实就是一个没有思想的人，这句话其实相当的有道理。我想在座很多理工科的同学以前可能认为只要有思想就够了，不过这句话告诉我们你只有思想不能沟通，其实你是没有思想的。这句话其实并没有夸张，在21世纪全世界都是信息的前提下，很好的信息传播渠道还是经过人。人怎么传播信息的，靠沟通。一个人他的沟通能力很好，他可以把一个很难懂的信息很好地传播给别人。一个人沟通能力很差，他就无法传播信息，因此别人可能看不起他，认为他没有思想。所以沟通能力是非常需要学习的。

这种沟通的能力怎么得到呢，我可以给同学们几个很好的建议。你沟通的时候一定要理解你的听众，你要知道你的听众在想什么，听众从你的讲话中能得到什么好处，即What’s in it for you。还有要注意说话的方式，不要用说教，而应该采取引导的方式。当你与别人沟通的时候，你要先想好你主要要传达的Message是什么，用听众能够接受的方式表达出来。

热爱工作者——If you find a job you love , you will never work a day in your life。

第5种非常需要的人才是热爱工作者。因为在全球被铲平之后，每一个人都是平等的。如果你能够做一个工作是你非常热爱的，那么你可能在睡觉、洗澡、吃饭时都在想你的工作。你可能就会更有热情去做你的工作。你不认为你的工作是一个枯燥的事情，而是可以享受的事情。所有就有这么一句话，有一天有个美国朋友到我的办公室来说你们的孔夫子实在是太聪明了。我说怎么回事呢。他说你看他讲的这句话多有道理啊：If you find a job you love， you will never work a day in your life。我就跟他说谢谢你夸奖我们的孔夫子，不过我实在想不起来孔夫子说了这句话。

后来当天开车回家的时候我才想到可能是“知之者不如好之者，好之者不如乐之者”这句话。但是今天看起来，我认为可能这句英文的翻译还更贴切一些，在21世纪更能够被更多的人理解。因为如果你真的很爱你的工作，你就不是在工作了，你是在享受了。如果你是在享受的话，你一定会有更多的热情投入，更多的时间投入，更乐意去做更多的工作。到了星期五可能不想回家，到了星期天可能就想来上班了。那么你想比别人做得差可能都很困难。

我们能看到的是，如果你能找到你的最爱，你的一生都会过得比较快乐。所以各位同学，如果你们还没找到你们的最爱，我的建议是保持一颗好奇的心，多去尝试不同的事情。然后要理解你的专业和你的工作不见得是完全一样的。要多做咨询，了解有什么样的公司，什么样的环境，什么样的工作你毕业后可以从中选择。如果你在一个你喜欢的专业里面呢，珍惜它，好好地去找一份未来相应的工作。如果是在一个可以选择的十字路口，比如说考研，出国等等，这个时候你要好好地去选一个你真正喜欢的专业，而且也许把刚才谈到的跨领域合作的概念借鉴过来。并不是说我过去学的是一个不喜欢的专业，我就要从文科转到理科。也许你可以找到一个更好的跨越的台阶。如果你不喜欢你的专业呢，你也可以在这个专业里面尽量找一个大专业里面的小专业，也许是你比较喜欢的；或者你可以在一个你认为你比较喜欢的专业和你现在不喜欢的专业之间的交叉学科找一些机会。所以不管怎么样，最后能够找到你爱的事情，你就能发挥你的潜力，成为21世纪需要的热爱工作者。

积极主动者——In a few hundred years , the most important event those historians will see is that for the first time , people will have a choice. They will have to manage themselves。

第6种是积极主动者。这句话是Peter Drucker所说的。他说几百年之后，历史学家回顾今天，他们会说这个世纪里最重要的事情，不是互联网，而是人有了选择。有了选择就要积极主动，然后需要管理自己。这是最重要的一点，这也就是我们从工业社会转变到现在的信息社会所发生的最重要的事情。一个积极主动者他对自己的一切一定要负责，因为如果你自己不在乎，没有别人会比你更在乎，没有人会比你更知道你想做什么。在来到大学之前，一切都是消极，由父母来决定的。进入大学之后，要开始对自己的一切负责。不去解决也是一种解决，不做决定其实也是一种决定，这个决定就是让自己走入一个消极而不是积极的方向。

在我出书的时候许多人喜欢让我把他们的座右铭写在书上，当我有时间的时候我也会尽量配合，但是有一句话我绝对是不写的，这句话就是沉默是金。因为在今天的环境里面，每个人需要合适地推销自己，让别人知道你的成果。因为如果你不表达，那其实别人就会认为你没有思想。当然，在适当的环境里，你才能做适当的表达，并不是要你抢别人的机会，也不是要你过分地做一个出头鸟。但是，如果你有一些想法有一些思想一定要表达出来。

在这个21世纪里，每个人都有想法，都有信息。那些最有信息或者最有想法的人可能会得到很多或者更多的注意。比如说在这次成立Google Camp的时候，工作人员有一天来找我说我们这个Google Camp有一些想法你觉得怎么样？当时我记得非常清楚的就是我在全国20多个高校做巡回演讲的时候在那些学校见到了一些非常积极主动的同学。我就跟他说，你去下面四个学校见见曾经主持我办的活动的同学吧，因为我认为他们是积极主动的，是符合Google Camp的精神的。我认为他们会给你很多想法，也许他们会成为我们的Google Camp的骨干。所以，如果你们在想，怎么挑到这四个学校的呢，很大的原因就是当时我做巡回演讲的时候这是四个让我感触最深最积极主动的学校，最优秀的同学。所以这是一个活生生的今天在Google Camp成立的时候发生的例子。

我们可以看到正是因为当时有这么一批积极主动的同学让我们今天有机会在浙大成立这个Google Camp。积极主动者，他并不只是积极地等待机会，他还需要积极地把握机会，为自己创造机会。这点可能是中国的学生，中国的员工最需要常常提醒自己的地方。前一阵我们在中国差不多招了三十多个员工，工作了三四个月。有一天我们在聚会，他们就问我说：开复，你对我们这三十个刚开始的关门弟子有什么建议没有。我的回答是：从技术方面，从对公司的理想、价值观认同以及努力方面，我都非常非常的满意。但是，如果要讲一点我希望你们未来可以做的更好的，我希望你们未来能够更加积极主动，要提出你们的想法。

乐观向上者——The glass is half full or half empty depending on whether you’re pouring in or out

最后我想讲的是乐观向上者。这句话来自美国的一个喜剧演员Bill Cosby，他是这么说的，我们常说一杯水是一半满的还是一半空的，其实要看你是继续把水注进杯子里，还是把水从杯子里面倒出去。如果你在继续注水的话，你会期望着水位上升；如果你在倒水的话，你会想到很快杯子就会空掉了。其实这告诉我们的是一个人的思想，是一个乐观的人，还是一个悲观的人。如果你是一个乐观向上的人，你会总告诉自己未来会更好。台湾有位企业家叫做张忠谋，他是台基电的董事长，他最近写了一篇文章，我觉得里面有些很有哲理的话。他有个朋友请他提几个字挂在墙上。然后张忠谋就跟他说，我的字写得不好，但是我随便帮你写几个字，然后他就写了“常想一二”这四个字。他朋友说什么叫“常想一二” 呢。然后张忠谋就告诉他说，你没有听过吗？我们都说人生不如意之事十有八九，我要告诉你常想那剩下那一二比较如意的事情。他说他从小就看了很多大人物的传记，他发现了一个规律，凡是成功者都是受苦受难的。然后他们的生命几乎就是人生不如意事十有八九的真实写照。但是他发现这些人之所以能够成功，就是因为他们保持了正面的思考，通过“常想一二”，他们能够超越苦难。苦难对他们来说反而成了生命中最好的养料，为他们未来的成功做了良好的铺垫。

所以这些成功者在面对苦难时的坚持、乐观和勇气是最重要的。人生的如意或不如意，更重要的不是取决于人生的际遇而是思想的瞬间。所以，人生的真正品质取决于你有没有“常想一二”这种乐观的思维方式，观点反而比这个事实更重要。这是他很有哲理的一篇文章，我想你用Google可以搜索得到。

其实在21世纪，还有很多其他的理由要做一个乐观向上的人。因为21世纪是一个更实时善变的环境，我们尝试的事情会碰到很多很多的失败。我们都听到说Google很酷，有一个20％的Project，每一个人都有20％的时间做自己想做的事情。但是，如果我们做一个统计，我想一定会发现，这个 20％自己想做的Project绝大多数一定是失败的。如果你没有一个良好的心态，不能客观地说我学到了一个Lesson有助于我做下一个项目时，那你很快就会处于一个非常沮丧的心态。所以Google公司不但不惩罚失败，还鼓励每个人客观地从失败中爬起来。我们要有一种心态，要认为挫折不是一种惩罚，而是一个学习的机会。

当我回顾我一生的职业生涯，我想我学到最多的绝对不是来源于我的成功。反而是我在读博士的时候被评为最坏的老师，在一个公司做了一个很酷的技术却没有用，导致公司被卖掉、员工失业等等失败的经历让我学到了很多，超过了我在语音识别或者其他领域所取得的成就。所以一定要把握每一个失败的时候，让自己过渡好每一个痛苦的时期。然后要能有正面的思想，要站起来，要正视自己的错误，能够从错误中学习。

最后我做一个总结：在21世纪里面，我们需要认真读书的同学，但是我们更需要创新实践的人才。我们需要每一科的专才，但是我们更需要跨领域合成者。我们需要高智商的人，但是更需要高情商的人。我们需要每一个学生能够高效能地理解，但是未来你们更需要高效能地沟通。

毕业后，当然要找一个热门的工作，但是更重要的是你要热爱你的工作。不要再继续做一个只会被动听话的学生，而要做一个积极主动的学生。不要只是做一个小心翼翼的人，而要做一个乐观向上的人。

Adi Shamir will give an invited talk "Random Graphs in Cryptography", and Ivan Damgard will give an IACR distinguished lecture "The Past, Present and Future of Multiparty Computation".

The program (draft) is here.

New York Times profile on Yau. (丘成桐)

Yau's homepage at CUHK.

佛经上讲的181条做人道理

一、人之所以痛苦，在于追求错误的东西。
　　二、与其说是别人让你痛苦，不如说自己的修养不够。
　　三、如果你不给自己烦恼，别人也永远不可能给你烦恼。因为你自己的内心，你放不下。
　　四、好好的管教你自己，不要管别人。
　　五、不宽恕众生，不原谅众生，是苦了你自己。
　　六、别说别人可怜，自己更可怜，自己修行又如何？自己又懂得人生多少？
　　七、学佛是对自己的良心交待，不是做给别人看的。
　　八、福报不够的人，就会常常听到是非；福报够的人，从来就没听到过是非。
　　九、修行是点滴的工夫。 　　
十、在顺境中修行，永远不能成佛。
　　十一、你永远要感谢给你逆境的众生。
　　十二、你随时要认命，因为你是人。
　　十三、你永远要宽恕众生，不论他有多坏，甚至他伤害过你，你一定要放下，才能得到真正的快乐。
　　十四、这个世界本来就是痛苦的，没有例外的。
　　十五、当你快乐时，你要想，这快乐不是永恒的。当你痛苦时你要想这痛苦也不是永愕摹?
　　十六、认识自己，降伏自己，改变自己，才能改变别人。
　　十七、今日的执著，会造成明日的后悔。
　十八、你可以拥有爱，但不要执著，因为分离是必然的。
　　十九、不要浪费你的生命在你一定会后悔的地方上。
　　二十、你什么时候放下，什么时候就没有烦恼。
　　二一、内心没有分别心，就是真正的苦行。
　　二二、学佛第一个观念，永远不去看众生的过错。你看众生的过错，你永远污染你自己，你根本不可能修行。
　　二三、你每天若看见众生的过失和是非，你就要赶快去忏悔，这就是修行二四、业障深重的人，一天到晚都在看别人的过失与缺点，
真正修行的人，从不会去看别人的过失与缺点。
　　二五、每一种创伤，都是一种成熟。
　　二六、当你知道迷惑时，并不可怜，当你不知道迷惑时，才是最可怜的。
　　二七、狂妄的人有救，自卑的人没有救。
　　二八、你不要一直不满人家，你应该一直检讨自己才对。不满人家，是苦了你自己。
　　二九、一切恶法，本是虚妄的，你不要太自卑你自己。一切善法，也是虚妄的，你也不要太狂妄你自己。
　　三十、当你烦恼的时候，你就要告诉你自己，这一切都是假的，你烦恼什么？
　　三一、当你未学佛的时候，你看什么都不顺。当你学佛以后，你要看什么都很顺。
　　三二、你要包容那些意见跟你不同的人，这样子日子比较好过。你要是一直想改变他，那样子你会很痛苦。要学学怎样忍受他才是。你要学学怎样包容他才是。
　　三三、承认自己的伟大，就是认同自己的愚疑。
　　三四、修行就是修正自己错误的观念。
　　三五、医生难医命终之人，佛陀难渡无缘的众生。
　　三六、一个人如果不能从内心去原谅别人，那他就永远不会心安理得。
　　三七、心中装满着自己的看法与想法的人，永远听不见别人的心声。
　　三八、毁灭人只要一句话，培植一个人却要千句话，请你多口下留情。
　　三九、当你劝告别人时，若不顾及别人的自尊心，那么再好的言语都没有用的。
　　四十、不要在你的智慧中夹杂着傲慢。不要使你的谦虚心缺乏智慧。
　　四一、根本不必回头去看咒骂你的人是谁？如果有一条疯狗咬你一口，难道你也要趴下去反咬他一口吗？
　　四二、忌妒别人，不会给自己增加任何的好处。忌妒别人，也不可能减少别人的成就。
　　四三、永远不要浪费你的一分一秒，去想任何你不喜欢的人。
　　四四、多少人要离开这个世间时，都会说出同一句话，这世界真是无奈与凄凉啊！
　　四五、恋爱不是慈善事业，不能随便施舍的。感情是没有公式，没有原则，没有道理可循的。可是人们至死都还在执著与追求。
　　四六、请你用慈悲心和温和的态度，把你的不满与委屈说出来，别人就容易接受。
　　四七、创造机会的人是勇者。等待机会的人是愚者。
　　四八、能说不能行，不是真智慧。
　　四九、多用心去倾听别人怎么说，不要急着表达你自己的看法。
　　五十、同样的瓶子，你为什么要装毒药呢？同样的心理，你为什么要充满着烦恼呢？
　　五一、得不到的东西，我们会一直以为他是美好的，那是因为你对他了解太少，没有时间与他相处在一起。当有一天，你深入了解后，你会发现原不是你想像中的那么美好。
　　五二、这个世间只有爱猫扑.爱生活的。
　　五三、修行要有耐性，要能甘于淡泊，乐于寂寞。
　　五四、活着一天，就是有福气，就该珍惜。当我哭泣我没有鞋子穿的时候，我发现有人却没有脚。
　五五、多一分心力去注意别人，就少一分心力反省自己，你懂吗？
　　五六、眼睛不要老是睁得那么大，我且问你，百年以后，那一样是你的。
　　五七、欲知世上刀兵劫，但听屠门夜半声。不要光埋怨自己多病，灾祸横生，多看看横死在你刀下的众生又有多少？
　　五八、憎恨别人对自己是一种很大的损失。
　　五九、每一个人都拥有生命，但并非每个人都懂得生命，乃至于珍惜生命。不了解生命的人，生命对他来说，是一种惩罚。
　　六十、自以为拥有财富的人，其实是被财富所拥有。
　　六一、情执是苦恼的原因，放下情执，你才能得到自在。
　　六二、随缘不是得过且过，因循苟且，而是尽人事听天命。
　　六三、不要太肯定自己的看法，这样子比较少后悔。
　　六十四、当你对自己诚实的时候，世界上没有人能够欺骗得了你。
　　六五、用伤害别人的手段来掩饰自己缺点的人，是可耻的。
　　六六、世间的人要对法律负责任。修行的人要对因果负责任。
　　六七、在你贫穷的时候，那你就用身体去布施，譬如说扫地、洒水、搬东西等，这也是一种布施。
　　六八、内心充满忌妒，心中不坦白，言语不正的人，不能算是一位五官端正的人。
　　六九、默默的关怀与祝福别人，那是一种无形的布施。
　　七十、多讲点笑话，以幽默的态度处事，这样子日子会好过一点。
　　七一、与人相处之道，在于无限的容忍。
　　七二、不要刻意去猜测他人的想法，如果你没有智慧与经验的正确判断，通常都会有错误的。
　　七三、要了解一个人，只需要看他的出发点与目的地是否相同，就可以知道他是否真心的。
　　七四、人生的真理，只是藏在平淡无味之中。
　　七五、不洗澡的人，硬擦香水是不会香的。名声与尊贵，是来自于真才实学的。有德自然香。
　　七六、与其你去排斥它已成的事实，你不如去接受它，这个叫做认命。
　　七七、佛菩萨只保佑那些肯帮助自己的人。
　　七八、逆境是成长必经的过程，能勇于接受逆境的人，生命就会日渐的茁壮。
　　七九、你要感谢告诉你缺点的人。
　　八十、能为别人设想的人，永远不寂寞。
　　八一、如果你能像看别人缺点一样，如此准确般的发现自己的缺点，那么你的生命将会不平凡。
　　八二、原谅别人，就是给自己心中留下空间，以便回旋。
　　八三、时间总会过去的，让时间流走你的烦恼吧！
　　八四、你硬要把单纯的事情看得很严重，那样子你会很痛苦。
　　八五、永远扭曲别人善意的人，无药可救。
　　八六、人不是坏的，只是习气罢了，每个人都有习气，只是深浅不同罢了。只要他有向道的心，能原谅的就原谅他，不要把他看做是坏人。
　　八七、说一句谎话，要编造十句谎话来弥补，何苦呢？
　　八八、其实爱美的人，只是与自己谈恋爱罢了。
　八九、世界上没有一个永远不被毁谤的人，也没有一个永远被赞叹的人。当你话多的时候，别人要批评你，当你话少的时候，别人要批评你，当你沈默的时候，别人还是要批评你。在这个世界上，没有一个不被批评的。
　　九十、夸奖我们，赞叹我们的，这都不是名师。会讲我们，指示我们的，这才是善知识，有了他们我们才会进步。
　　九一、你目前所拥有的都将随着你的死亡而成为他人的，那为何不现在就布施给真正需要的人呢？
　　九二、为了赞美而去修行，有如被践踏的香花美草。
　　九三、白白的过一天，无所事事，就像犯了窃盗罪一样。
　　九四、能够把自己压得低低的，那才是真正的尊贵。
　　九五、广结众缘，就是不要去伤害任何一个人。
　　九六、沈默是毁谤最好的答覆。
　　九七、对人恭敬，就是在庄严你自己。
　九八、拥有一颗无私的爱心，便拥有了一切。
　　九九、仇恨永远不能化解仇恨，只有慈悲才能化解仇恨，这是永恒的至理。
　　一００、你认命比抱怨还要好，对于不可改变的事实，你除了认命以外，没有更好的办法了。
　　一０一、不要因为众生的愚疑，而带来了自己的烦恼。不要因为众生的无知，而痛苦了你自己。
　　一０二、别人讲我们不好，不用生气、难过。说我们好也不用高兴，这不好中有好，好中有坏，就看你会不会用？
　　一０三、如果你自己明明对，别人硬说你不对，你也要向人忏悔，修行就是修这些。你什么事都能忍下来，才会进步。就是明明是你对，你也要向他人求忏悔，那就是修行了。
　　一０四、当你的错误显露时，可不要发脾气，别以为任性或吵闹，可以隐藏或克服你的缺点。
　　一０五、不要常常觉得自己很不幸，世界上比我们痛苦的人还要多。
　　一０六、愚痴的人，一直想要别人了解他。有智慧的人，却努力的了解自己。
　　一０七、别人永远对，我永远错，这样子比较没烦恼。
　　一０八、来是偶然的，走是必然的。所以你必须，随缘不变，不变随缘。
　　一０九、慈悲是你最好的武器。
　　一一０、只要面对现实，你才能超越现实。
　　一一一、良心是每一个人最公正的审判官，你骗得了别人，却永远骗不了你自己的良心。
　　一一二、不懂得自爱的人，是没有能力去爱别人的。
　　一一三、学佛就是在学做人而已。
　　一一四、正人行邪法，邪法亦正，邪人行正法，正法亦邪，一切唯心造。
　　一一五、有时候我们要冷静问问自已，我们在追求什么？我们活着为了什么？
　　一一六、不要因为小小的争执，远离了你至亲的好友，也不要因为小小的怨恨，忘记了别人的大恩。
　　一一七、勇于接受别人的批评，正好可以调整自己的缺点。
　　一一八、感谢上苍我所拥有的，感谢上苍我所没有的。
　　一一九、凡是能站在别人的角度为他人着想，这个就是慈悲。
　　一二０、学佛不是对死亡的一种寄托，而是当下就活得自在和超越。
　　一二一、佛陀从不勉强别人去做他不喜欢的事情，佛陀只是告诉众生，何者是善？何者是恶？善恶还是要自己去选择，生命还是要自己去掌握。
　　一二二、所谓的放下，就是去除你的分别心、是非心、得失心、执著心。
　　一二三、说话不要有攻击性，不要有杀伤力，不夸已能，不扬人恶，自然能化敌为友。
　　一二四、一个常常看别人缺点的人，自己本身就不够好，因为他没有时间检讨他自己。
　　一二五、是非天天有，不听自然无，是非天天有，不听还是有，是非天天有，看你怎么办？
　　一二六、真正的布施，就是把你的烦恼、忧虑、分别和执著心通通放下。
　　一二七、如果你真的爱他，那么你必须容忍他部份的缺点。
　　一二八、要克服对死亡的恐惧，你必须要接受世上所有的人，都会死去的观念。
　　一二九、所有的病患，医生最难治，所有的众生，自以为是的人最难渡。
　　一三０、一匹驴，吃再好的草，也不会成为一匹俊马。用执著和分别心去修行，再大的精进，也不会成佛。
　　一三一、了解永恒真理的人，就不会为任何的生离死别而哀伤悲泣，因为生离死别是必然的。
　　一三二、虽然你讨厌一个人，但却又能发觉他的优点好处，像这样子有修养的人，天下真是太少了。
　　一三三、若能一切随他去，便是世间自在人。
　　一三四、希望你常对自己说，闻到了佛法，我是最幸福的人，除了这幸福外，再没有别的了。
　　一三五、如果你能每天呐喊二十一遍「我用不着为这一点小事而烦恼」，你会发现，你心里有一种不可思议的力量，试试看，很管用的。
　　一三六、诚实的面对你内心的矛盾和污点，不要欺骗你自己。
　　一三七、因果不曾亏欠过我们什么，所以请不要抱怨。
　　一三八、我们确实有如是的优点，但也要隐藏几分，这个叫做涵养。
　　一三九、无事莫把闲话聊，是非往往闲话生。
　　一四０、大多数的人一辈子只做了三件事；自欺、欺人、被人欺。
　　一四一、太过于欣赏自己的人，不会去欣赏别人的优点。
　　一四二、活在别人的掌声中，是禁不起考验的人。
　　一四三、心是最大的骗子，别人能骗你一时，而它却会骗你一辈子。
　　一四四、坏孩子，父母总是比较操心。所以对于罪业愈深重的众生，我们更应该特别宽恕他怜愍他，而不应该远离他舍弃他。
　　一四五、只要自觉心安，东西南北都好。如有一人未度，切莫自己逃了。
　　一四六、用平常心来生活，用惭愧心来待人，心来处事，用菩提心契佛心。
　　一四七、当你手中抓住一件东西不放时，你只能拥有这件东西，如果你肯放手，你就有机会选择别的。人的心若死执自己的观念，不肯放下，那么他的智慧也只能达到某种程度而已。
　　一四八、人家怕你，并不是一种福，人家欺你，并不是一种辱。
　　一四九、不是某人使我烦恼，而是我拿某人的言行来烦恼自己。
　　一五０、不要刻意去曲解别人的善意，你应当往好的地方想。
　　一五一、世上的事，不如己意者，那是当然的。
　　一五二、我的财富并不是因为我拥有很多，而是我要求的很少。
　　一五三、吃了就一定要拉，人一定要学会随缘放下，否则就会？便秘。
　　一五四、常以为别人在注意你，或希望别人注意你的人，会生活的比较烦恼。
　　一五五、我能为你煮东西，但我不能为你吃东西。各人吃饭是各人饱，各人生死是个人了。
　　一五六、看轻别人很容易，要摆平自己却很困难。
　　一五七、人类最大的错误，在于不敢承担圣人的心。
　　一五八、你只管活你自己的，不必去介意别人的扭曲与是非。
　　一五九、如果你准备结婚的话，告诉你一句非常重要的哲学名言「你一定要忍耐包容对方的缺点，世界上没有绝对幸福爱猫扑.爱生活的婚姻，幸福只是来自于无限的容忍与互相尊重。」
　　一六０、如果你能够平平安安的渡过一天，那就是一种福气了。多少人在今天已经见不到明天的太阳，多少人在今天已经成了残废，多少人在今天已经失去了自由，多少人在今天已经家破人亡。
　　一六一、是非和得失，要到最后的结果，才能评定。
　　一六二、你不必和因果争吵，因果从来就不会误人。你也不必和命运争吵，命运它是最公平的审判官。
　　一六三、你有你的生命观，我有我的生命观，我不干涉你。只要我能，我就感化你。如果不能，那我就认命。
　　一六十四、你希望掌握永恒，那你必须控制现在。
　　一六五、恶口永远不要出自于我们的口中，不管他有多坏，有多恶。你愈骂他，你的心就被污染了，你要想，他就是你的善知识。
　　一六六、当你明天开始生活的时候，有人跟你争执，你就让他赢，这个赢跟输，都只是文字的观念罢了。当你让对方赢，你并没有损失什么。所谓的赢，他有赢到什么？得到什么？所谓的输，你又输到什么？失去什么？
　　一六七、我们大部份的生命都浪费在文字语言的捉摸上。
　　一六八、你不要常常觉得自己很委曲，你应该要想，他对我这样已经很好了，这就是修行的功夫。
　　一六九、别人可以违背因果，别人可以害我们，打我们，毁谤我们。可是我们不能因此而憎恨别人，为什么？我们一定要保有一颗完整的本性和一颗清净的心。
　　一七０、与任何人接触时，要常常问自己，我有什么对他有用？使他得益。如果我不能以个人的道德、学问和修持的力量，来使人受益，就等于欠了一份债。
　　一七一、出家是一生一世的事，修行是多生多劫的事。
　　一七二、信佛，学佛，不是为自己，乃是为一切苦海中的众生。
　　一七三、佛不渡无缘的人，不能渡的人，我们就把他当做菩萨来看。
　　一七四、如果一个人没有苦难的感受，就不容易对他人给予同情。你要学救苦救难的精神，就得先受苦受难。
　　一七五、一般人在遇到对方的权势大，财富大，气力大，在无可奈何的情形之下而忍，这算什么忍耐呢？真正的忍是，就算他欺负了你，对不住你，但他什么都不及你，你有足够的力量对付他，而你却能容忍他，认为他的本性和我一样，只是一时糊涂，或在恶劣的环境中受到熏染罢了，你不必与他计较，能在这样的情况及心境之下容忍那才是真正的忍耐。
　　一七六、如果我们放眼从累生历劫去看，那么一切的众生，谁不曾做过我的父母、兄弟姊妹、亲戚眷属？谁不曾做过我的仇敌冤家？如果说有恩，个个与我有恩；如果说有冤，个个与我有冤。这样子我们还有什么恩怨亲疏之别呢？再就智慧愚笨来说，人人有聪明的时候，也有愚痴的时候，聪明的人可能变愚痴，愚痴的人也可能变聪明。最坏的人，也曾做过许多好事，而且不会永远坏；好人也曾做过许多坏事，将来也不一定会好。如此我们反覆思索，所谓的冤亲、贤愚，这许多差别的概念，自然就会渐渐淡了。这绝对不是混沌，也不是不知好坏，而是要将我们无始以来的偏私差别之见，以一视同仁的平等观念罢了！
　　一七七、世界原本就不是属于你，因此你用不着抛弃，要抛弃的是一切的执著。万物皆为我所用，但非我所属。
　　一七八、宁可自己去原谅别人，莫让别人来原谅你。
　　一七九、当你用烦恼心来面对事物时，你会觉得一切都是业障，世界也会变得丑陋可恨。
　　一八０、欲为诸佛龙象，先做众生马牛。
　　一八一、虽然我们不能改变周遭的世界，我们就只好改变自己，用慈悲心和智慧心来面对这一切。

Prof. Guang Gong will visit our lab and deliver a talk on efficient key managements in mobile ad hoc networks (MANETs). The official news is here.

related events: International Conference on SEQUENCES AND THEIR APPLICATIONS 2006 (SETA06).

农历五月初五为端午节，又称端阳节、午日节、五月节、艾节、端五、重午、午日、夏节。虽然名称不同，但各地人民过节的习俗是相同的。端午节是我国二千多年的旧习俗，每到这一天，家家户户都悬钟馗像，挂艾叶菖蒲，赛龙舟，吃粽子，饮雄黄酒，游百病，佩香囊，备牲醴。

端午节的第一个意义就是纪念历史上伟大的民族诗人屈原。屈原，名平，是战国时代的楚国人，生于楚威王五年夏历正月初七，或谓生于楚宣王二十七年，卒于楚襄王九年。

端 午节的第二个意义是伍子胥的忌辰。伍子胥名员，楚国人，父兄均为楚王所杀，后来子胥弃暗投明，奔向吴国，助吴伐楚，五战而入楚都郢城。当时楚平王已死，子 胥掘墓鞭尸三百，以报杀父兄之仇。吴王阖庐死后，其子夫差继位，吴军士气高昂，百战百胜，越国大败，越王勾践请和，夫差许之。子胥建议，应彻底消灭越国， 夫差不听，吴国大宰，受越国贿赂，谗言陷害子胥，夫差信之，赐子胥宝剑，子胥以此死。子胥本为忠良，视死如归，在死前对邻舍人说："我死后，将我眼睛挖出 悬挂在吴京之东门上，以看越国军队入城灭吴。"便自刎而死，夫差闻言大怒，令取子胥之尸体装在皮革里于五月五日投入大江，因此相传端午节亦为纪念伍子胥之 日。

端 午节第三个意义是为纪念东汉孝女曹娥救父投江而死。曹娥是东汉上虞人，父亲溺于江中，数日不见尸体，当时孝女曹娥年仅十四岁，昼夜沿江号哭。过了十七天， 在五月五日也投江，五日后抱出父尸。就此传为神话，继而相传至县府知事，令度尚为之立碑，让他的弟子邯郸淳作诔辞颂扬。孝女曹娥之墓，在今浙江绍兴，后传 曹娥碑为晋王义所书。后人为纪念曹娥的孝节，在曹娥投江之处兴建曹娥庙，她所居住的村镇改名为曹娥镇，曹娥殉父之处定名为曹娥江。

端 午节第四个意义是纪念现代革命女诗人秋瑾。秋瑾是六月五日殉国，后人为敬仰其诗，复哀其忠勇事迹，乃与诗人节合并举行纪念，而诗人节亦因纪念爱国诗人屈原 而定为端午节。秋瑾字睿卿竞雄，号鉴湖女侠，小字玉姑，浙江绍兴人，幼年擅长诗、词、歌、赋，且喜骑马击剑，有花木兰、秦良玉在世之称。28岁时参加革 命，影响极大，预谋起义，开会时为清兵所捕，不屈，于光绪三十三年六月五日在绍兴轩亨口英勇就义。

悬钟馗像：钟 馗捉鬼，是端午节习俗。在江淮地区，家家都悬钟馗像，用以镇宅驱邪。唐明皇开元，自骊山讲武回宫，疟疾大发，梦见二鬼，一大一小，小鬼穿大红无裆裤，偷杨 贵妃之香囊和明皇的玉笛，绕殿而跑。大鬼则穿蓝袍戴帽，捉住小鬼，挖掉其眼睛，一口吞下。明皇喝问，大鬼奏曰：臣姓钟馗，即武举不第，愿为陛下除妖魔，明 皇醒后，疟疾痊愈，于是令画工吴道子，照梦中所见画成钟馗捉鬼之画像，通令天下于端午时，一律张贴，以驱邪魔。

挂艾叶菖蒲：在端午节，家家都以菖蒲、艾叶、榴花、蒜头、龙船花，制成人形称为艾人。将艾叶悬于堂中，剪为虎形或剪彩为小虎，贴以艾叶，妇人争相佩戴，以僻邪驱瘴。用菖蒲作剑，插于门楣，有驱魔祛鬼之神效。

赛龙舟：当 时楚人因舍不得贤臣屈原死去，于是有许多人划船追赶拯救。他们争先恐后，追至洞庭湖时不见踪迹，是为龙舟竞渡之起源，后每年五月五日划龙舟以纪念之。借划 龙舟驱散江中之鱼，以免鱼吃掉屈原的尸体。竞渡之习，盛行于吴、越、楚。清乾隆二十九年台湾开始有龙舟竞渡，当时台湾知府蒋元君曾在台南市法华寺半月池主 持友谊赛。现在台湾每年五月五日都举行龙舟竞赛。香港有竞渡，近来英国人也有仿效我国人作法，组织鬼佬队，进行竞赛活动。

吃粽子：荆楚之人，在五月五日煮糯米饭或蒸粽糕投入江中，以祭祀屈原，为恐鱼吃掉，故用竹筒盛装糯米饭掷下，以后渐用粽叶包米代替竹筒。

饮雄黄酒：此种习俗，在长江流域地区的人家很盛行。

游百病：此种习俗，盛行于贵州地区的端午习俗。

佩香囊：端午节小孩佩香囊，不但有避邪驱瘟之意，而且有襟头点缀之风。香囊内有朱砂、雄黄、香药，外包以丝布，清香四溢，再以五色丝线弦扣成索，作各种不同形状，结成一串，形形色色，玲珑夺目。

                               裴定一：从数论到密码学 理论与应用的完美结合
                                                                       —记裴定一教授的科研之路
                                                      科学中国人 （2005年第2期）

模形式理论是现代数论的一个重要分支，它与其它数学分支有广泛的联系，因而也有着广泛的应用。二十世纪七十年代，世界著名的美国普林斯顿大学数学系 的K.Iwasawa和G.Shimura（志村五郎）是当时数论方面的大师。在上世纪九十年代出现的轰动国际数学界的费马大定理的证明中，就利用了志村 教授在模形式理论方面的重要结果。

模形式是定义在上半平面的一类特殊的复变函数，它有一个参数，称为权。权可以是一个正整数1，2，3……也可以是一个正的半整数1/2，3/2， 5/2……在上世纪三十年代，人们证明了任一权为正整数或大于2的半整数的模形式一定可以表成一个尖形式和一个爱森斯坦级数之和，从而把一般模形式的研究 归结为对这两类特殊模形式的研究。这是模形式理论中的一个基本定理。但对权为1/2和5/2两种情况，还不知道上述同样情况是否也成立，成为一个长期未能 解决的遗留问题。上世纪七十年代，法国两位著名数学家J.P.Serre和H.M.Stark证明了权为1/2时，上述性质成立。与此同时，一位中国的学 者证明了权为3/2时，上述性质也同样成立，从而使模形式基本定理中的遗留问题全部解决。这个结果分为两篇论文先后发表在“美国数学会论丛”上。他就是师 从世界顶尖级数论大师、美国普林斯顿大学志村教授的中国学者裴定一。

裴定一，教授、博士生导师。1959年考入中国科学技术大学应用数学系。1964年考入该系研究生，师从华罗庚教授。1968年至1977年在大庆油田当 采油工及大庆油田开发研究院技术员，期间参加了华罗庚推广优选法和统筹法小分队。1977年底调入中国科学院。1978年12月作为改革开放后教育部派往 美国的第一批访问学者中的一员，赴美国普林斯顿大学数学系进修两年。回国后先后担任中国科学院应用数学研究所副研究员，中国科学院研究生院教授，广州大学 教授，信息安全国家重点实验室（中国科学院研究生院）学术委员会主任、副主任，广州大学信息安全研究所所长等职务。

裴定一从中学时代开始就对数学产生了浓厚的兴趣，经常利用课余时间钻研数学。1959年高中毕业前夕，当他知道我国著名数学家华罗庚教授在中国科技大学应 用数学系担任系主任，便选择第一志愿报考该系。大学四年级分配专业时进入数论代数专业，华老给该专业开设“典型群”课程，讲授华老和万哲先院士在这个领域 所提出的独特的研究方法，以及所取得的成果，在学习这门课程时，裴定一发现其中一个未解决的问题，并给出了一个技巧性很高的解决方法，写出论文“长方阵射 影几何基本定理的证明”，刊登在“中国科学技术大学建校五周年纪念论文集”上。裴定一在数学方面的能力崭露头角，受到老师们的好评。

1964年，裴定一大学毕业后考取本系研究生，导师为华罗庚教授。在参加推广双法小分队期间，他与华老朝夕相处，一起到工厂推广双法，一起研讨数学，耳濡 目染，他从华老那里学到很多研究数学的高招。华老把积累知识进入科学研究的过程形容为“从薄到厚，从厚到薄”，他说，当我们进入一个新的知识领域，开始知 之甚少，通过不断的学习，后来积累的知识就越来越多，但这时必须消化这些知识，深入思考分析，一层一层地“拆架子”，抓住其中的一些关键，在我们的脑子中 就会觉得这些知识并不很多了，也只有在这时就有可能进入科学研究阶段了。华老的很多研究问题的方法，对裴定一日后的研究生涯产生很大的影响。

1978年12月25日，裴定一作为改革开放后由教育部派出的第一批赴美访问学者五十人中的一员，经华罗庚教授写信推荐，进入世界著名的美国普林斯顿大学 数学系进修两年，跟数论大师志村教授研究模形式，于是他在志村教授的指导下重新开始了数论研究。并且在模形式基本定理的研究中取得了非凡的成就。志村教授 和裴定一开始接触时，对这位中国大陆去的学者毫无了解，后来就刮目相看、赞不绝口了。裴定一回国后，志村教授在关于裴定一的成果的一个评价材料中说，这个 成果“是近十五年来模形式理论上最重要的成果之一”。1989年这项成果还获得了国家自然科学三等奖。

1981年，裴定一从普林斯顿回国后，他的研究领域就从数论逐步转向密码学。

人类历史上很早就开始使用加密技术，古希腊人在战场上传递信件时，就知道将信的内容加密，这样即使一旦被敌人俘获，敌人也很难得到信件中所包含的军事机 密，尽管他们的加密方法较简单，遇到聪明的敌人，有可能被破译。人们使用的加密方法不断改进，越来越不容易被敌人破译。但直到上世纪二十年代，密码技术仍 停留在“一张纸一支笔”的状态，之后出现了电子密码，使密码技术进入一个新阶段，数学工具在其中开始发挥越来越重要的作用。在第二次世界大战中，密码的应 用与侦破成为影响战争胜负的一个重要因素。第二次世界大战后，密码研究出现一个高潮。Shannon利用信息论方法研究加密问题，提出了完善加密的概念， 他在1948年发表的论文“秘密体制的通讯理论”为密码学奠定了理论基础，使密码学成为一门科学。Shannon的工作是近代密码学发展的一个里程碑。

随着现代计算机网络通信的广泛使用，传统密码受到很大挑战，它们已经不能完全适应网络环境下使用密码的需求。于是在上世纪七十年代，提出了公钥密码的概 念，并且利用数论方法设计了第一个公钥密码体制（RSA公钥密码），经过二十多年的研究，RSA已得到了广泛的应用。在RSA密码体制中，使用了一个大整 数（目前通常取这个数有1024比特长），它是两个素数的乘积，这个大整数是公开的，而它的两个素因子是保密的。如果有人能将这个大整数分解因子而得到它 的两个素因子，就能破译这个密码体制，所以RSA的安全性是建立在大整数因子分解问题的基础之上的。这是一个经典的数论问题，RSA的提出大大推动了大整 数因子分解算法的研究。在上世纪八十年代，人们又提出了椭圆曲线公钥密码，它应用了更深刻的数论知识，它的安全性也得到了密码界的公认，现在也正逐步推向 应用。公钥密码的出现，使数学在密码研究中发挥了更加核心的作用。

除了信息的保密之外，信息的认证是网络通信中信息安全的另一个重要方面。当人们从网络上收到一个信息时，在有些情况下（例如网络银行），收信方十分关心信 息发送方的真实身份，十分关心信息内容在传输过程中是否被他人非法篡改，信息的认证技术就是要保证信息的来源方是真实的（不是假冒的），保证收到的信息的 可靠的（没有被非法篡改）。Shannon利用信息论方法研究加密问题，Simmons在上世纪八十年代利用信息论方法研究了信息认证问题，提出了完善认 证码的概念。他研究的认证模型中包括三方：信息的发方、收方以及敌方，发方要向收方发送信息，而敌方想假冒发方，或篡改发方的信息，用以欺骗收方，达到他 的某种目的，在三方认证模型中，假定发方和收方是互相信任的，我们仅考虑敌方的欺骗攻击，但在有些实际情况中，发方和收方也可能会互相欺骗，例如，发方不 承认他已发出的信息，收方捏造他收到的信息，因而Simmons后来又提出了包括仲裁方的四方认证模型，在这个模型中要同时考虑来自发方、收方和敌方的欺 骗攻击。裴定一发展和完善了 Simmons的认证信息理论，他首先找到了各类欺骗攻击成功概率的信息论下界，在此基础上找到了密钥个数的下界。他把密钥个数达到这个下界的认证码称为 完善的，并证明了完善认证码的各类欺骗攻击成功概率同时也达到下界，使各类欺骗攻击成功概率尽可能小正是我们设计认证码时所追求的目标，所以完善认证码是 一类最重要的认证码。裴定一发现一个认证码是完善的必要充分条件是它的组合结构具有某一类特殊的性质，他称具有这类性质的组合结构为强部分平衡设计。因而 只要构造强部分平衡设计，就能构造得到完善认证码，这样就完全解决了完善认证码的构造问题。如何构造强部分平衡设计，这也成为组合设计（它是组合数学的一 个分支）的一个新的研究课题。进而，裴定一利用有限域上射影空间中的有理正规曲线，构造了一类新的强部分平衡设计，从而也就构造了一类新的完善认证码，这 是第一个完善的非Cartesian认证码，即可带保密功能的认证码，而在此之前已知的完善认证码都是Cartesian码，即不带保密功能的码。裴定一 在认证码方面的研究成果在国际上权威的密码学杂志和密码学会议上发表，关于这一成果的专著将于2005年由CRC出版社在国外出版。

现代密码技术的应用已不再局限于军事、外交等传统密码的应用部门，它已进入金融、商业、政务等很多社会领域，与老百姓的日常生活发生密切关系。裴定一在从 事密码学理论研究的同时，也积极投入密码技术的开发应用。1996年美国RSA数据安全公司与我国信息安全国家重点实验室（中国科学院研究生院）合作开发 椭圆曲线公钥密码软件，他是该项目的中方负责人，该项目完成的软件作为RSA公司开发的信息安全软件包BSEF 4.0的一部分上市。近年来，他领导广州大学信息安全研究所积极开发椭圆曲线公钥密码的软件和硬件，部分成果已被实用部门采用。

裴定一在密码方面的研究成果先后获得国家科技进步一等奖和二等奖（集体奖）。

裴定一从1990年开始参与筹建中国密码学会，担任副理事长兼秘书长，积极推动国内密码学的学术交流活动。1991年部分亚洲国家发起召开亚洲密码年会 （Asiacrypt），随后组建了亚洲密码年会管理委员会（ASC），从1996年开始裴定一担任该委员会中国方的委员，直到现在。1998年信息安全 国家重点实验室承办了Asiacrypt98，他担任这次会议的程序委员会（共）主席。现在亚洲密码年会已与美洲密码年会、欧洲密码年会一起成为国际密码 研究会（IACR）负责的三个最高水平的国际密码学术会议。IACR现已决定，信息安全国家重点实验室和上海交通大学密码和信息安全实验室联合于2006 年在上海承办亚洲密码年会Asiacrypt2006，裴定一将担任这次会议的总主席，同时也将担任IACR的理事（2005-2006）。

Invited by Prof. Jiwu Jing, Prof. Peng Liu from Penn State University is visiting our lab. He delivered a talk focus on overview of Cyber security in this morning. In particular, he briefly introduced the main problems and attack and defense techniques in DDoS, Worm, and survivable systems. The official news is here (in Chinese).

ps. Peng Liu's  Cyber Security Lab   and his research interests (quoted from his page)

* Survivable Systems, Network Security, Database Security, Privacy, Distributed Systems Security, Wireless Security, Forensics
* Electronic Health Care, Identity Theft, E-Commerce, Cyber Infrastructures, Telecommunications

Just spent six days vacation (Labour Day) with my family. The trip plan was absolutely depended on the interest of my son. Wonderful time!

The main arrangement was,

1, May.  Beijing Amusement Park

Accompanied with my son to participate in some exciting and challenging amusements. Some breathtaking games was speedy even before my son was afraid and cried. ;-) , such as terrifying waves.

2, May.  Beijing Shijing Shan Amusement Park

With my brother's family, my wife&son, my niece, and Xingwu. Most amusement equipments are similar to those in Beijing Amusement Park, but the former are newer than the latter. My son spent a lot of time to play toy (tank) , a present  his sister gave him.

I'm expecting the Beijing Happy Valley to be opened in this summer.

3, May.  See the night scene at Tian'an Men Square.

4, May.  Rest.

5, May.  Children's Science Paradise in  China Science and Technology Museum.

6, May.  Beijing Zoo and Beijing Aquarium

Some pics. will be uploaded soon.

Current Mood: amused

from Oded Goldreich's page.

莫绍揆


丁德成

　　莫绍揆 1917年8月13日诞生于广西桂平县．南京大学教授．数理逻辑、数学教育． 　　


　　莫绍揆，1917年8月13日生于广西桂平．1939年7月毕业于中央大学理学院数学系．在
中央大学任两年助教以后，他先后担任过中央大学和中山大学数学系讲师．从1947年起，
赴瑞士洛桑大学、国立高等工业学校和巴黎大学留学，师从国际著名的数理逻辑大师贝尔
奈斯(P．Bernays)，研究数理逻辑和数学基础．1950年4月回国后，任南京大学副教授、教
授，创建数理逻辑专业，并长期担任数理逻辑教研室主任．他在数学研究和数学教育的园
地上辛勤耕耘了50余年，艰苦创业，成绩卓著，是我国数理逻辑教育和研究的开拓者之一
．

　　莫绍揆已发表学术论文60多篇，学术专著20多本，科普论文20余篇．其中，《数理逻
辑导论》、《递归函数论》两本专著获1978年全国科技大会奖，《数理逻辑教程》获全国
优秀教材奖，《质点几何学》获全国城市出版社优秀图书一等奖；学术论文“高级函词与
约束词本质”获江苏省科技成果二等奖．莫绍揆的卓越成就为他赢得了很高的荣誉．他的
多项研究成果被载入一些国际著名的逻辑史专著中，他的许多论文受到了国内外同行的重
视与好评．他是我国第一批博士生导师，曾任中国数学会理事，中国逻辑学会副理事长，
江苏省逻辑学会会长、名誉会长，《数学年刊》编委，《数学研究与评论》副主编，“现
代数学丛书”编委．他还是美国“Associa－tion for symbolic logic”的成员，美国“
Mathematical reviews”和德国“Zentralblattfr Mathematik”等杂志的评论员．

　　1920年，英国数学家罗素(Russell)应邀来华讲学一年，这时数理逻辑开始传入中国；
1922年，傅种孙等将罗素的《罗素算理哲学》翻译出版．其后，汤璪真、朱言钧(公谨)等
对数理逻辑和数学基础作过介绍；1926年金岳霖在清华大学开设逻辑学课，1927年汪奠基
的《逻辑和数学逻辑论》出版；1937年，金岳霖的《逻辑》出版，其中有专门章节论及数
理逻辑；同年，汪奠基的又一著作《现代逻辑》出版．30年代后期40年代初，沈有鼎、王
宪钧、胡世华先后从国外学成回国，数理逻辑开始在中国发展．

　　1947年，莫绍揆赴瑞士留学，开始在洛桑大学攻读数学．第二年，转入瑞士国立高等
工业学校，攻读数理逻辑．该校曾是著名科学家爱因斯坦工作过的地方；当时，一代数理
逻辑宗师希尔伯特(Hilbert)的继承人贝尔奈斯正在任教．莫的导师就是贝尔奈斯．

　　初到该校，莫绍揆认真听课，提问较少，没有受到人们的注意．不久，有一件事情，
引起了贝尔奈斯的极大注意．

　　在一个命题演算系统中，有一些公式，它是永真的，但与生活中的逻辑不甚相符，使
人们觉得有点“怪”，被称为“蕴含怪论”．许多数理逻辑学家在证明公式时都尽量避免
使用“蕴含怪论”，除非迫不得已.论”．但莫绍揆却避开“蕴含怪论”巧妙地证明了该公
式．贝尔奈斯对此大加赞赏，称之为“莫的漂亮证明”．波兰的莫斯托夫斯基(A．Mostow
ski)也是一代数理逻辑宗师．有一次，贝尔奈斯要莫绍揆对莫斯托夫斯基的一篇关于各种
选择公理的独立性的论文谈谈看法时，莫不仅正确地评价了该文，而且指出了其中的瑕疵
．尤其令贝尔奈斯惊讶的是，这个年轻人还有完整的修改意见．贝尔奈斯对莫绍揆十分青
睐，经常与之一起研究问题，对莫的论文，还帮助解决了其中一个难解决的问题．那时贝
尔奈斯已到晚年，在国际上久负盛名，他的这一切行动对于一个年轻的中国学者是一种崇
高的荣誉．后来莫绍揆回国了，贝尔奈斯对这位中国弟子却久久不能忘怀．据德国Heidel
berg大学数学系前系主任谬勒(H．Müller)教授后来回忆，莫离开后，贝尔奈斯经常在课
上情不自禁地问：莫先生对此问题如何看？当其他学生告诉他，莫先生已经回中国去了，
贝尔奈斯当即神情黯然．

　　悖论在数理逻辑中有着重要的地位．可以说，公理集合论就是为解决悖论而发展起来
的．从近代数理逻辑诞生之日起(近代数理逻辑的诞生以弗雷格[Frege]的逻辑系统为标志
)，直到50年代，对悖论的研究一直是数理逻辑研究的主流方向之一．莫绍揆在悖论研究方
面的贡献为世人所瞩目．悖论被发现以后，人们曾经尝试以各种不同的方法解决它，用多
值逻辑来解决集合论中的悖论就是方法之一．以波兰学派为领袖的许多数理逻辑学家构造
了数以百计的多值逻辑系统．正当许多数理逻辑学家对用多值逻辑解决集合论中的悖论寄
予厚望时，莫绍揆发表了他的著名论文“多值系统的逻辑悖论”．在这篇论文中，他石破
天惊地指出，即使引入多值逻辑也不能无条件地使用概括原理，否则在多值逻辑系统中仍
能构造出类似二值逻辑悖论的悖论．这结论无疑宣告了试图用多值逻辑来解决集合论中悖
论的幻想破灭．

　　自从数理逻辑诞生以来，数理逻辑学家们为了各种不同的目的和用途构造了数以百计
的逻辑系统，但是其中绝大多数已经被淘汰了，仅有少数真正具有重要价值的逻辑系统被
载入逻辑史册．在罗马尼亚学者杜密特里乌(Dumitriu)的四卷巨著“逻辑史”中列有一些
最著名的逻辑系统．莫绍揆的三种逻辑系统赫然在列．享受此殊荣的除他之外，仅有少数
几位逻辑巨匠．他在1950年发表的论文中，构造了两个新的逻辑系统．这两系统不仅简炼
，分别只含10个和5个公理(类似的Hilbert－Bernays系统含有15个公理)，而且有效地避免
了“蕴含怪论”．这些系统被公认为相干逻辑的奠基性论文．由于相干逻辑的实用性正日
益受到人们的重视，一些国内外学者正在致力于将它应用于计算机科学．在“关于数理逻
辑的一些研究”一文中，莫绍揆作出了一个各组公理相对于联结词C自足的古典逻辑公理系
统M，一个古典构造主义逻辑系统G，极小演算逻辑系统J，直觉主义逻辑系统H．在整个系
统中，G是M的共否系统，且G可由J加两条公理而得到，或可由把H、M中一条公理换成相应
的两条较弱的公理而得到．这种对各种不同学派的逻辑系统的彻底研究是不多见的．

　　约束词的引入是数理逻辑发展史上的里程碑，高级函词的使用标志着逻辑开始超出狭
义谓词演算向更高一级发展．在“高级函词与约束词的本质”一文中，莫绍揆深入地讨论
了高级函词与约束词的关系，澄清了一些错误观念，促进了逻辑学的进一步发展．在论文
[41]中，他研究了推理式的推理规则的本质，深刻地指出了推理式之对于数理逻辑恰似代
数式之对于代数学，本文受到了国际数理逻辑界的重视．在数理逻辑的语义学研究中，人
们几乎毫无例外地要么只研究永真性，要么只研究永假性．而在“永真假性的研究”一文
中，莫提出了一种崭新的研究方法，即同时研究永真性和永假性，并首次提出了特征数的
概念，这不仅简化了传统上使用的“永真性谱”，而且深刻地刻画了一阶逻辑公式的永真
性和永假性的本质和特征．

　　众所周知，一股“五代机”热正在计算机界方兴未艾．许多计算机科学家和逻辑学家
共同认识到要制造出新的一代计算机，必须突破冯·诺意曼(Von Neumann)为计算机创立的
逻辑理论．许多学者认为模态逻辑是一种有用的逻辑理论，它将有助于“五代机”的研制
．早在50年代，莫绍揆系统地研究了模态逻辑，他的“具有有穷个模态词的模态系统”和
“有穷模态系统的基本系统”等论文是对有穷模态词的模态系统的深入和彻底的研究，并
把这方面的研究工作大大向前推进了一步．1959年，他发表了“模态系统与蕴涵系统”一
文，对当时已有的各种模态系统作了系统的归纳和总结，首先提出了基本模态系统的概念
．当时已有的各种模态系统，包括最著名的刘易斯(C．I．Lewis)的五个模态系统S1—S5，
都概莫能外地不能避免蕴涵怪论，因而不足以表达蕴涵词的真相．在该文中，莫绍揆提出
了两个新的模态系统，在这两个系统中蕴涵怪论已绝迹，蕴涵词及模态词均与直觉相符，
这样的系统受到国内外学者的高度赞赏是可以想象的．

　　递归论是数理逻辑的一个重要分支，由于它与计算机科学关系密切正越来越受到人们
的重视．莫绍揆在递归论方面作过许多重要的工作．50年代，他系统地研究了原始递归函
数定义的简化，一般递归函数的构造，尤其是对归宿步骤式作了精辟的研究．他独树一帜
地提出了初基函数和五则函数等新概念，这些概念不仅使得一般递归函数的构成大大简化
，而且也具有一定的实用意义．正是在这些新概念的基础上，他在1986年解决了Scholz问
题，即一个一阶谓词演算公式的可满足集是什么样的集的问题．这个问题是1952年出版的
“Journal of Symbolic Logic”第17卷第二期上刊登的四个悬而未决的问题中的第一个．


　　递归数论由于不用量词，彻底贯彻能行性而受到许多数理逻辑大师的重视，斯科列姆
(Th．Skolem)、希尔伯特、贝尔奈斯、切尔奇(A．Church)、古特斯坦(R．L．Goodstein)
均在此方面作出不少工作．自60年代起，莫绍揆与他的学生们系统地研究了递归数论系统
的构造、性质以及各种系统之间的关系，他还提出了递归数论的各式各样系统，从而将这
方面的研究向前推进了一大步，这些研究工作当时在国际上是领先的．

　　莫绍揆在公理集合论的研究方面也有出色的工作．他研究了集合论的公理系统的简化
，把ZFC系统中的九条公理简化为四条，这可算归约到最简了．基数的方幂问题是集合论中
一个基本且重要的问题，各国学者曾对此问题作过许多研究工作，但是这些研究基本上都
是建立在共尾数理论之上，从而未能得出完整的结果，而且不够系统．莫绍揆在1987年发
表的“集合论公理的简约与基数方幂”一文，撇开了共尾数理论，用一种新方法讨论了基
数方幂，从而完美地解决了这个问题．在“概括原理及其消除”一文中，他指出函词的作
用功能可以用代入运算来表示，从而函词、函元、量词、函元约束词、概括原理等均可删
除不用，一阶谓词逻辑即是功能完全的逻辑演算，以代入运算代替抽象运算更能深刻揭示
逻辑本质，并可避免λ演算与集合论所导致的悖论．

　　莫绍揆的研究工作不仅涉及到数理逻辑的各个分支，而且在数理逻辑以外的其他一些
学科也有深厚的造诣．他十分重视计算机科学，特别重视将数理逻辑应用于计算机科学．
在60年代初，莫绍揆亲自参加过一些计算机的研究工作．在80年代，他参加过由计算机科
学家徐家福、孙钟秀主持的“五代机”讨论班，试图为“五代机”的研制找到新的逻辑理
论．他在国内较早地介绍了布尔代数在逻辑设计中的应用，论述了递归函数与循环、约束
变元与局部量的密切关系．他还探讨过软件理论中组合逻辑与λ演算的重要作用．前面已
说过，由他奠基的相干逻辑正日益受到计算机科学家的重视，国内外均有人致力于将此理
论应用于计算机．

　　莫绍揆也很注意数学史，认为要熟悉一门科学，如能知其过去的发展历史，将更能进
一步深入了解．他对中国数学史尤其注意，发表了多篇论文，并多次参加数学史的会议，
与同行交流．1982年，他在“假如没有素数概念该怎么办”一文中指出：中国古代算术的
一个特征是没有素数概念，但是仍能完善地处理分数运算及求最大公约数、最小公倍数的
运算．一般人认为，《九章算术》中给出了一些勾股弦数，但没有解决求一切正整数的勾
股弦数问题，而莫绍揆指出，中国古代数学利用等数(最大公约数)能够很完善地发展有理
数论乃至给出勾股弦数的通解．他对秦九韶的生平和《数书九章》也颇有研究，对秦九韶
的“大衍求一术”提出了独到的见解．他还指出，李冶的《测圆海镜》是一本很完善的讨
论公理系统的书，以前人们只知该书讨论“天元术”，这是出于误解．对中国古历尤其是
太初改历经过，提出一套新的看法．

　　莫绍揆教授不仅是一位优秀的数学家，而且也是教育家．50多年来，他在教育领域辛
勤耕耘，为国家培养出了许多优秀人才．在他开始研究数理逻辑时，国内从事此项研究的
仅数人而已，而现在国内已有一支数百人的数理逻辑研究队伍．中国数理逻辑研究水平正
在不断提高，日益受到国际数理逻辑界的重视．这些成果里就有莫绍揆教授一生的心血．
值得一提的是，莫绍揆在培养计算机科学的人才方面亦有重要贡献，现在活跃在计算机科
学界的许多颇有建树的学者曾是他的学生．莫绍揆教授培养人才的特点是“博”和“严”
．所谓“博”，是指他传授给学生广博的知识，不拘一格地培养人才，能根据各个学生不
同的特点，指导他们向不同的方向发展．莫指导学生，不要求他们急于出一两篇论文，而
要他们先打下广博而扎实的基础．他认为只有打下坚实的基础，才能有科研“后劲”．他
给研究生亲自开设数理逻辑基础、递归论、集合论、模型论、证明论等课程，这在国内是
不多见的．由于他本人具有扎实而广博的基础，能根据不同学生的不同特点，指导他们在
不同的方向上开展研究工作．70年代末80年代初，莫绍揆同时指导8个研究生论文，这8篇
论文涉及到五个不同的方向．所谓“严”，就是严格要求．他向来以考试严格，对论文质
量要求严格而闻名．他曾有一个研究生的论文已被答辩委员会通过，但是在系里学术委员
会讨论时，他认为该生论文没有达到硕士水平而赞同暂不授予该生硕士学位．正因为他的
“博”和“严”，他才培养出了许多优秀的人才．

　　莫绍揆除发表过不少学术论著外，在科普方面也做了不少工作．他发表了20多种科普
论著．有些作品向广大中学生和一般读者生动地介绍了数理逻辑的基础知识、发展过程，
以及与计算机的关系．有些作品深刻地讨论了初等数学中许多有趣的问题，给广大中学生
以启迪；有些作品深入浅出地剖析了数学中某些有争议的问题．这些作品都有力地推动了
数学和数理逻辑的普及工作．不少数学工作者说，正是这些作品引导他们走上了研究数学
的道路，特别是数理逻辑的道路．

　　“熟读一本书”是莫绍揆的一条治学格言，也是他治学经验的总结．他认为，要掌握
某一方面或某一学科的知识，进而开展研究工作，必须首先选一本这方面的优秀作品熟读
之．这就是熟知它的内容，了解这些内容的来龙去脉，并且能熟练应用它．然后以这本书
为基础，通过比较，用这部书的内容吸收、消化你在这个领域内新获得的知识，不断地向
“精”、“深”方面发展．只有这样才能做出出色的研究工作．他曾回忆说：“在我青少
年时代，当时条件艰苦，得到一本书不容易，要得到一本好书更不容易．每得到一本好书
，我就反复研读，直到对这本书内容完全熟悉，完全掌握．以后，若遇到这方面的问题，
我就将它与那本书联系起来，通过对比、分析，一般能很快地解决问题，并且能将新获得
的知识融化进去．”

　　莫绍揆业余爱好桥牌，围棋．桥牌技艺很精，曾多次代表校、系参加比赛，常得胜而
归．

　　莫绍揆教授一生，经历了这个时期的中国知识分子所经历的各种曲折道路．不管身处
逆境还是顺境，他都热爱祖国，热爱教育，热爱科学．现在他年事已高，却仍在继续开展
研究工作，为祖国建设贡献自己的力量．

　　作者简介 丁德成 男，汉族，皖籍，1943年5月出生．1978—1981年为莫绍揆教授研究
生，1991年获德国Heidelbeng大学博士学位，现为南京大学数学系教授．

Prof. Bimal delivered 2 talks in the last week at SKLOIS.
The topics are,

1 A Key Pre-distribution Scheme for Wireless Sensor Networks: Merging Blocks in Combinatorial Design

2 Black and White Visual Cryptographic Schemes

Invited by Prof. Dingyi Pei, Prof. Bimal Roy will visit SKLOIS at the end of this month (from 26,Mar. to 30 Mar.)and he will deliver two talks at our lab.


P.S. Bimal Roy's Bio.

obtained Bechelor's and master's degree in Statistics from Indian Statistical
Institute, Calcutta, India, Ph.D. degree in Mathematics from University of
Waterloo, Canada. Currently professor of Indian Statistical Institute, calcutta.
General Secretary of CRSI.

Program chairs for Indocrypt 2000, FSE 2004, Asiacrypt 2005.
Held visiting position at State University of Newyork, USA,
University of Ottawa, Canada, Carleton University, Canada,
Lund University, Sweden, INRIA, France etc

Research interest: Cryptology, Combinatorics, Optimization, statistical Method.

Some news will be published on My Blog.

No duplication in the two blogs.

The CISC 2005 photos were posted online now.

Current Mood: happy

http://www.51766.com/www/detailhtml/1100014951.html
http://news.xinhuanet.com/collection/2003-06/04/content_903477.htm

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Most recently, two crypto&security conferences were hold on Beijing, ICICS 2005 and CISC 2005. And I met many interesting people in crypto community during the conferences. Maybe I will write some memorable and interesting things later.

Current Mood: amused

    I established a list of Chinese crypto. researchers today. Main crypto & security labs in Chinese Mainland, Hong Kong, Taiwan were included in the list too.

    It's just begin.

Current Mood: amused