Introduction Foundations of the digital discrete revolution

Well, shall we begin? This lecture is on the – I hadn’t turned to lecture two hadn’t I? It's on the foundations of the digital discrete revolution. We are approaching the end of, or perhaps not quite the end of - the conversion from analog to digital. Analog signals are what you are used to, although if I'm careful, the world is made out of molecules, so signals do come in discrete amounts. Still we tend to think of time, your weight, density, and so on as being a continuous variable. Particularly a telephone company took the pressure on the microphone and translated electrical current regarding to varying signal and sensed the signal on the other end, moved the diaphragm and you heard the voice. We're moving to digital where we sample high frequency, very frequently at a high rate, equal space, and we converted it to digits. Now, the digits involve roundoff – I will not discuss roundoff in this course, but it's an important topic. It causes trouble in computing all the time, but I will talk about this effective sampling a good deal. Now, why are we doing this? Well, consider when the telephone company, when I arrived, they sent the voice analog across the continent.

Why are we doing this?

The gain was something like 10 to the 120. You say, “By God, how can that be?” Well, we do the back of the envelope calculation. There were amplifiers about every 50 miles, and the amplifiers had a gain of about 100, and across the continent 3000 miles you see how one gets 10 to the 120. That means that in the analog system, every bit of noise that got in early, whether it came through the wire or in the amplifier, was amplified to set on and on and on. Therefore, the amplifiers had to be made very very carefully, and maintained very carefully. Well, digitally we do something else. We send the signal. We don't amplify it; we detect it, and gait a new signal; we repeat. Repeaters copy the original signal, not with the noise, but strips it out and gives you back the nice clear pulse. So therefore, we can send a pulse across the continent with almost no distortion. Furthermore, we will take up error correcting codes, which are widely used so in case small errors do creep in. We know how to remove them if there are not too many. So the digital one is working out very well. It requires much simpler equipment, gets much higher accuracy. Now, I have to be careful and warn you that we are moving partly back to analog. We were, as you probably think most of time, signaling with pulses. We are actually now going to things called solitons, which are mysterious things. I don't want get into a theory, but they are nice features and we're beginning it analog amplify them four or five stages, then we build a repeater. So we do a sequence of analog amplifiers, then followed by a nice reshaping of a repeater, and again we get high accuracy and great reliability. That is what this revolution is about, and you've probably seen somewhere near the end of it because more and more of the experiments you do you get the stuff as numbers as soon as you can and you go ahead there and at last minute you may translate the numbers back to graphs. Well, why has it happened?

Digits work better than analog

I've given you the first reason that digits works better than analog. The second one is the transistor and the integrated circuit, particularly. You may not have thought about the trouble of building say the ENIAC with 10,000 vacuum tubes. Each vacuum tube would have quite a few terminals, which had to be soldered into the socket. There were a bunch of resistors and capacitors, and such things connected with every vacuum tube. There were hundreds of thousands of solder joints. Now solder joints require cleaning and there's some acid involved. They will in time, if the acid is left there too much, etch away and produce intermittent failures. So, solder joints were a real curse, but they, [seldom we mention it], were just something we lived with. Well, integrated circuits removed it. Fundamentally, you don't have the problem, and I note there are some figures on costs. I got an estimate from somebody else said “On a chip it costs you about a thousandth of a cent to connect one part with another. Between chips it cost you about one cent, between circuit boards that cost you about ten cents, between mainframes, it cost you maybe like a dollar.” It takes time to put a cord from one mainframe to another, and the dollar is not a bad estimated cost. These are approximations. Now, the third reason why we're going digitally is that we are going from a manufacturing society to an information society much more rapidly than most people think. If you exclude the military from government, take all other government employees, there are more of them than there are people making things in the factories. We now have more people managing than we have doing. Back in the time of the American Revolution, more than 90 percent of people were farmers. They were out there doing things. Now we have a very few farmers. We have moved, although it's Washington and other people are reluctant a minute, we have moved from a society which is dominated by making things, to manufacturing and manipulating information. That's going to go on. I would guess by the time the peak of your career which I am taking as being year 2020 – it’s a very nice convenient number most of you'll be in your peak of your career about that time and 2020 suggests 20/20 foresight. By that time I think that probably less than 25% of people who are working will be making anything. Now when you make a movie or when you make a TV program or something, you're really manipulating information. Yes, there is a film in material form. Yes, when I write a book there is a book, but the true content of a book or a film or the such things is the information it contains, and not the form in which it exists. So, in the broad sense we have moved from one to the other, so consequently, we are not dealing with material things as much.

What is really behind the digital revolution

Now these three things together, the shifting from analog to digital, integrated chip, and the fact our society has changed is what is really behind this digital revolution, which you are living through. Now, there are other ones as well. If you define a robot to be something which handles the material world – not what a child thinks robot looking like human being – robots are doing an increasing amount of our manufacturing, very much more.

Robots: what a computer can be

Now, don't think of robots necessary being run by a Von Neumann machine. It may well be run by a neural net, maybe using fuzzy logic, maybe even various other things for control. You have to take a reasonable view of what a computer could be. It doesn't have to be a [inaudible] type machine. It might be a highly parallel one. Now, we're using them in manufacturing for three reasons. First, they produce a better product with tighter control. If you think about taking some pills with a strong drug in it, I think you'd rather have a machine making those pills than human beings. The machine can operate more reliable after a moment after moment and human beings will slip up. They will get careless. They will get bored. Machines do a better job. They do it cheaper, but one more important thing. Most of the time they do a different job and I have to emphasize this to you because upon that feature depends your success in using computers. When we first started using computers in accounting, when we move the hand methods to machines, we had to change the accounting method somewhat. Mrs. Smith, who did the accounting, always knew that such and such happened. Well, it doesn't work well with machines, so we had to change the accounting slightly. When we went to numerical analysis by machines, we did it different than we did by hand. Now when we went from hand fabrication in my childhood, hand fabrication involved screws and bolts nuts. Now, you have rivets and welding. You don't make the same thing, you make an equivalent one. That change, that imaginative change which shifts it from one thing to another is what is central for successful applications of computers. It's an equivalent product. Now, it's not only material, it’s also social. When you want to build another or chose different structure, if you try and incorporate machines and keep exactly the same structure you have now, you'll have trouble. What you need to do is ask, “What are the fundamental things I'm trying to accomplish? How do I accomplish it with machines?” The attempt to do what humans always did the way humans did it has produced any number of disasters in the attempts to mechanize things. You must imagine a use- or -you must use your imagination to get the kind of results you want - a big success by using machines and equivalent product.

Effects of computers on science

Now, the effects on science of computers on science have been very very large. Somewhere in the 50s, I made a talk to the vice president and president of Bell Labs on machines, and I said “9 out of 10 experiments are now being done in the lab, 1 in 10 are on the machines, but before I leave it'll be 9 out of 10 on the machines and one in 10 in the labs.” They all knew I was a crazy irritation for the math department and he didn't believe me. As a result when they put up another building, they put a lot of labs in. You know, soapstone benches, hydrogen, oxygen, water, distilled water, frequency of any lay down. Before they got the doors on those some of the labs, we moved in programmers. They spend the enormous sum of money because I could not hear that we are moving from experiment to simulating experiments on computers. Well, by now you know there's something more like 99% of experiments are done in computers than on the lab. Now, the reason why I knew that's quite simple. I was at Los Alamos. I was stuck with computing atomic bomb designs. You can't do a field test or laboratory test other than with a critical mass. There is no small scale experiment possible. There wasn't much alternate to compute, but I realize from that laboratory work will label me to compute things you can't do in a lab. For example, in simulating traveling-wave tubes, we studied the effect of the amount of charge on the beam going down. Now, the charge, of course, makes the beam disperse. I could solve the problem with no space charge by simply taking out one term. They could not do that in the lab, but I nailed down if they made the thing finer and finer and finer, what was the element? I could get that point, they could not. Many times the simulation in a laboratory will do what you cannot do in the lab. It will also frequently get you more accurate answers, particularly in a rapidly changing experiment. It is very hard to catch what's happening on the fly, but the computers got the numbers right there. But now, let me remind you of what happened when you got your education. You were told about medieval scholastics and how they read what happened, according to Aristotle, and said that was what was going to happen, and Galileo is - died 1642 – says, “You know, you got to look at the real world. Don't look in the books, look at reality.” That is what's both of made modern science possible. Well, what I just saying a little few moments ago? We are doing the opposite. We are looking into books simulating and saying, “That is what's going to happen.” We are going back to medieval scholasticism. We will undoubtedly go too far, more than a few times and I advise you to consider that matter when you go on simulations. Are you going back to medieval scholastics? How far dare you go? It's a very serious problem because some people are going to go too far and fall back into medieval or believing whatever Aristotle said or whatever the books say. You won't find fundamentally new things that way very often. Computers are affecting engineering too. Not only are we building more complex things, but more and more engineering jobs depend upon a computer somewhere running a thing. So you look in a handbook or you look at a catalogue and you buy some chips off the shelf. You assemble them to do the job, and you write the program and you have the thing and you have your control now. Not the way they were long ago by mechanical other devices, but rather your control is very directly by the computer. It enables you to do much more, and since I told you all engineering is coming closer to research, you have the problem before you really know for sure a lot of details. As for example, the atomic bomb – it was an engineering job, but we didn't have all the constants, and so we had to do further experiments to get constants. We had to design with some flexibility in it. Well, computers give you the enormous flexibility. You can design and as the numbers become more known, you can get the appropriate formulas and write those programs instead. So, engineering is getting much more computer oriented.

Effects of society are very large #micromanagement

The effects in society are also very large, and they aren’t always good. Managers tend to believe that if they only knew what was going on, they would know what to do. It's called micromanaging, and I think most of you have more or less had to endure a certain amount of micromanaging. The bosses tell you what about, for example, in the school here, department heads have much less freedom than they did in my time. Their budgets are allocated in some detail by the deans and the Provost. Well, the effect of this is bad. In the first place, the person who knows what's going on is often the person right on the ground doing the job, and the person at headquarters doesn't really know the details, and really doesn't want to know the details, but makes decisions. Now, the evidence that this management is bad is first easily obtained by looking at the great Russian experiment of central management, which finally pretty much collapsed. You've only look at our bureaucracy which is now under serious attack for the same reason that central planning is not so good. Local planning however, has its faults. The local planner doesn't know what the whole company is trying to do, and so it's somewhat difficult, but of the two of them, it seems to me often top management micromanaging causes more trouble than local people doing things without knowing what corporate policy really is, but it's – both ways go wrong. Now the great evil of micromanagement is the following: Middle management never gets much chance to manage and make decisions because top management is always making for you. So finally when top management leaves, middle management finds themselves atop never having made a bunch of decisions and learn to live with bad decisions. Top management by micromanagement is failing to bring forward people to replace them. That is the greatest evil of micromanagement. When you're atop, remember leave the people at the bottom alone to make their mistakes to learn from those mistakes where it won't do so much harm. When they’re a top and they make mistakes it can be very very expensive. So that's one of the trends. Now there's a trend against this. It became clear to me one day when a guy had been a brokerage firm called me up and asked me to have lunch with him and I made a date to have hamburgers with him and he was forming his own brokerage company because he was tired of the big company where he'd been being told what to do, and he had found out there was a small company formed which would do bookkeeping for him and would also rent out legal talent. So he could form his investment company and pay attention to investments. He did not have to spend time on record-keeping he did not have to worry about legal aspects. Those were taken for him so that he could concentrate on the main job and not make the mistakes of top management, not knowing what's going on because top man who disturbed will of things. I was quite impressed with the fact that that was the way they were doing things, and then I realized I had invested myself in a couple of biological companies. What we do is if we can find a compound, we can develop it if we want or we can hire out some other company loosely associated with us to do it. At a later stage, we can either sell it, or we can now make more detailed markets, we can carry it all the way through approval and final marketing and take the profit, or we can sell it to various stages along the way. In short, there are a whole bunch of companies, all of them small. All of my fairly specialized, who are working together to accomplish what normally is done by a big corporation, but it's avoiding the cost of top management and all the overhead and all the micromanagement they do. I don't know how far it's going to go, but I see that that is a defense and I believe this was happening. For example, my own experience when AT&T was broken up in a bunch of small companies, there was almost universal complaint of all the wickedness and evilness that’s going to be of the government doing that.” I said, “Well, you know there's something to be said in the other side,” and I waited for some years and I think you can say that there was good and bad. The breaking up of the central management so the separate companies could their own ways has produced much more diversity and many more kinds of services than you would have had, had it remained in control of AT&T. It's got its avenue and I think that may well be what will happen, but how you want to apply that to your own business is something I don't want to get involved in.

Computers and the entertainment field

Now, computers have also invaded the entertainment field. People spend more time watching television than they do eating and other things that are needed for life. Furthermore, many of the programs you see on television and the music is computer produced. I will talk about computer music one of these days as how it's done, but a lot of cartoons a song clearly nothing but computer produce things.

How far will computers change society

Now, how far a computer will change society is a question which I would like to discuss with you but I don't dare to. We live in a litigatious society. I leave it to you individually, therefore, to think of how computers microchips connected with a few server mechanisms could operate in the areas of sex, family, sports, travel at home via virtual reality in all the comforts of home. How much the way it will change the way we live? It's obvious it can do it. The difficulties are legal and other ones in many cases. Particularly, when you come to delicate subject of sex, there are great restraints of what can happen, but if you use your imagination at all, you can easily figure out for yourself what you think are possible futures.

Computers began in the number crunching business

If you want to make a lot of money I suggest there's a lot of money in that field. Now few computers began in the number-crunching business. The atomic bomb we were crunching numbers because those are the people who could pay the bill. As the price came down we spread out into doing word processing and information retrieval and so on. When you only have 10 or 20 registers you cannot do search big databases. As we've got the ability to do so you find things like the airplane reservation system and so on which would be almost impossible without modern computers. Now we've done other things. I will talk about them somewhat later. We can do analytic integration that you learned in the calculus, cheaper and faster and more accurate than you can. Just like waves, it's all it is. [inaudible] We can do these kind of things with surprising success. Now, in the military it's easy to observe - if you want the Gulf War - the central role of information. Our failure to use information we had in our hands caused quite a few deaths. We had the information, we didn't use it fast enough. You saw there was basically tremendously a war of depriving the other person from information and you having it. Whether it's indicative huge I don't know, but it's a problem to leave to you. I can only suggest a sign I once saw around here.

The Battlefield is not a place for the human being

“Battlefield is no place for a human being.” Not a bad rule. It's got all the things. Humans are slow there are all kinds of things wrong, and furthermore they can get hurt badly and you have to do something about them. If you have robots aboard a ship and the robot gets hurt, you can kick him overboard. A human you've got to do something take care of them. It's a very different situation. The machines have got great advantages, but they got disadvantages, so we'll take them up.

Growth : Models of growth

Now, I want to talk about growth I talked about briefly last time I'll do it again. The simplest model of growth is the rate of change is proportional to how much you've got. For example, bacteria growing or human beings unrestrained they have a given rate of reproducing children. They’re going to grow exponentially unless other factors come in - this is a very simple one - and it of course gives rise to the solution you all know the exponential well, it goes out to infinity, and you don't believe infinity. The current belief is the whole universe is finite, so you haven't got any number of molecules, you haven't got anything like that you're finite, so that can't be right. So next model you pick is, well, I'm gonna put a factor which is limiting. As I get near the upper limit this is gonna bring the rate back down again. This is a reasonable model which it starts exponentially grows but then it's limited because of this factor. Now all I got to do is make some substitutions and I come down without the dimensions. The L and the K are removed then I advise you always to do this get rid of the local constants to get the down equations free of those constants, it pays off. Now, this equation all I got to do is separate variables, do partial fractions I'll come up with this solution and you can see here when X is a very large negative this is very big the quotient is 0. As I come in as X gets say to 0 I've got E to the 0 is 1, is 1 over 1 is 1 over A. I have some value at the origin. As X gets large, this gets very small, this term drops out and I have 1. So, I have a curve come up like that I'm exaggerating, and [points to white board] that's the typical growth curve. During the time I was running computers, I live basically on that piece there. It was almost a straight line doing all [inaudible] I was involved in. But we're getting into trouble now. We'll discuss some more next time, but I'll simply say why you're in trouble. Given a single computer, you believe that the world is made out of molecules. They've got to give it a size. You believe probably due to two theories of relativity. There's a maximum speed of signaling usefully from one place to another and third, although I've talked about other things you believe that heat is gonna be generated and you’ve gotta get rid of it. Those set limitations on what you can do on a single processor, and we're beginning quite definitely to see this here. That's why we're going to parallel computers. Well, instead of this model I picked here I could pick one more general I would rate [inaudible] positive quantities and if I take that 1/2 and 1/2 I get a various thing 1 which is finite in range the curve starts out here comes up the saturates got a finite range. You can play with various A's and B's you can play also with not a higher upper limit, like L, but a logarithmic growth or something and you can study growth, and you will find that these problems here have the following characteristic. This is a direction field. At every point I calculate the slope, but since T does not enter - the slopes along a given height are always the same give me the Z value and the slope is fixed, and due to the two limiting terms they flattened out here towards 0 and flattened out here towards 0 so you find the typical S-curve where you look at a solution is moved across and back but it's always the same solution, just like the exponential is the same curve. Wherever you look, it's the sa me curve cuz if I kept it up always looks locally exactly the same. So you can do those things and big studies as you want and find out quite a few things. Now sometimes, such a thing happens that a new invention comes along and you have another s-curve on top of it, but an s-curve a saturation is very common. Human population for example - for a long long while was very small hundred thousand we believe a hundred thousand humans on the earth for a long time gradually rose [inaudible] we've had one, and we sort of believe that in the long haul the population can't go on the way it has we'll be setting at each other's feet. There aren't that many molecules to make that many people let alone running our resources. So we see a future which is typically that and you've seen it in many other places computers are certain like this I will talk about again I said next lecture I'll talk about the hardware. How long a start we had, how I lived on this to how for a single computer but parallel computer is doing exactly that. It's producing another shift, [inaudible] and there's no reason why you can't have two or three but typically it requires a new technology to get there. Now, in these simple models while not great precise, give you a feeling for what has happened to you and I was well aware that I was living here and I kept worrying in the early days how close was I to that saturation point. When was it going to be that I would not be able to continue increasing computer rate doubling every 18 months or so. Now I claim as evidence in electric engineering, I said it before I'll said again, that it's going to be a matter of selecting chips to do the job you want because it's going to be information almost all the time. Gun director - the heart of it is the information you get through the radar and the information you put out to aim the gun. In all kinds of other things it's information almost always therefore electric engineering and much of other engineering is doing it but when you do this will you please for heaven's sakes think about field maintenance. The idea that I'll make the design and then I'll graph down reliability later on does not work out well. You only think about your own home the situation. How many devices do you have at home when they break you said throw it out we'll get another one.

Maintenance is too hard

Maintenance is too hard. If you've got a little small transistor radio, would you ever try have it repaired? No. Well, more valuable things must be maintained. Putting maintenance as the last thing isn’t very satisfactory, although I do think as I suggest a few moments ago with regard to robots, it comes a time when the robot is sufficiently busted due to axes, you're kicking overboard and forget start again. But maintenance of equipment will be vital, and I say again you must begin to plan in the initial stages for field maintenance. It's very very decisive. Now, I want to go to another observation. Special purpose chips - special purpose chips you have one built designed just for your job its enormously ego satisfying I mean you got a job so important we got a special chip for it. Well, I advise you against it if you possibly can avoid it. Now you can't always - sometimes you do - have to have a special chip, but a lot of times it is this ego satisfaction that controls it, because if you have a general-purpose chip as against the special program for example, you designed a pentium yourself. If you have a general-purpose chip, other people will find the bugs for you, if you don't. Other people will help write instruction manuals, other people will make upgrades. The manufacturer himself will come around say, “Hey we got a new model. It's got all these new features on it. It runs 10 times faster. You won't have to do much, you won't even have to have a big inventory. But if you have a special purpose chip, you make the production run, how many do you put in inventory?

Things will change more rapidly in the future than it did in the past

Furthermore when a change in philosophy occurs all those special purpose chips are dead and the inventory is dead too - and I'm telling you regularly things are going to change more rapidly in the future than they did in the past, and they change awful rapidly for me. They're going to change more rapidly for you. Things are not going to be stable. Then we are going to get to the point where we are on the edge of what people can stand, and I put out you several well-known things. Old people don't learn so well, and there's a very famous saying, “Children can run VCRs but old people can't.” I don't know how old your age is, I suspect most of you probably can run one, but probably some of you may already have reached a point where your children run a VCR and you don't know quite how. Well, we will get to a rate of change where the populace cannot stand more rapid change. You can't change everything every day. That's the role of habits. You get up in the morning for example I found I put my right sock on before my left sock normally, but when I put my shoes on I put the left shoe on before the right shoe. I don't think, I just put my shoes on, and when I stopped to look what I did, I thought I had habits and that's how you get fined you get up in the morning and you by and large go through a large number of things with habits you don't really think you just do it. You take a shower you don't think what you're doing, you do the things you always do in that order. That's what saves you to be able to do something else. Humans have habits in order to avoid thinking, but if I'm going to change what you could do every day, you aren't going to be able to do anything useful. You're going to be busy adjusting all the time. So the rate of change in society will be limited to a great extent by the ability of people to respond to the change. And that applies not only the material goods, it applies the organization. If you try and change the organization or corporation every six months, you'll tend to produce chaos, and if you make a change, you can't go back. That's one of the terrible things - well, many things. If you try to sell us try it out this new organization doesn't work, it isn't really possible to go back to the old one. That's why we do simulations. We say, “Well if you do that, we think this is what you will see. If you do that we think that's what you'll see.

Change is painful for human beings

We don't know, but that’s what we think.” So we try to anticipate what's going to happen, and one other thing you want to watch is that change is painful to human beings. Computers I told you of that - just put a new program in and it's changed, but humans can't learn that. You have habits, that's what makes you possible, so don't sneer at habits. They’re essential, but also they have to be changed at times.

Beware of special purpose chips

Now I want to say beware of special-purpose chips. Beware of them, they are a dead end. You may have to have them, I'm not saying you don't, but by and large, when you get a chip you are down a dead end and you are there by yourself, and to give a simple example: when I was in charge of computers and or regular other ones, I did not want to get a machine which was a dead end of a line. I wanted a machine in the mainstream. In fact I argued with a manager one time - of the two different machines I wanted one which had the most people using it. The one with the biggest sales. It might not be the best temporarily, but I've got large number of people who know how to use it, I can learn it from them. And quite a few times, several machines – the early ones - users learned how to get 10 times more other machines than the manufacturer ever thought they could do. The users did it. Well, if you've got one machine of a kind or it’s only two or three people you don't have that support. Now, I know there are things which make it difficult for corporations to cooperate, but we've done this quite successfully and I will mention one which I always find very amusing and that is the airframe company in the early days. The airframe companies as you well imagine, are competitive. What the presidents did not know was that the people in the computing groups had formed an organization in which they swapped information and traded programs. If that ever came to the attention of the lawyers, there would’ve been lawsuits every place, but we couldn't cope with the machines without cooperation. They were too big and too gigantic and even to this day a whole new chip is a big problem. It wasn't easy for anybody to find that there was an error in the Pentium chip. It wasn't a serious one but there'll be these things. If you get special-purpose chips you have no such help. If you will go out and use the general purpose chip, you might pay a little bit more, but it's more flexible, you can evolve with time. Other people will be helping you. As I said, the manufacturer come around said, “Hey, we got 10 times faster chip doing the same job only cost $2 more.” Of course you got that new one, but what the hell? You can go, the other way you cannot.

Computers at evading all of our society

Now I warn you these computers are evading all of our society. It's not only management it has to be coped with. It's everywhere else. There involving in our society are basically digital, but don't forget analog. Just today I was talking to the department head and he and I agree that analog computers are being badly neglected at times. For example, take the float in your bathroom or toilet. You flush the toilet, the water goes down, the float comes up. It's an analog device for integrating the amount of water in that tank. Goes up, now there's a digital part as it comes over the last modern ones have a snap which snaps off, so it doesn't trickle down although very slowly. It goes up and snaps off. So it's a combined analog digital and I don't expect to find a totally digital toilet system running in my near future. The analog devices are too easy. Your service that goes across until makes a contact. Turns on the furnace, and when it gets hot enough, it comes back, returns the furnace off, right? Nice simple analog device combined with yes/no/closing/contact. That combination of analog digital is very powerful. When I inherited big analog computer the first thing I did was put on some those kind of switches on. The old people who designed it and the maintenance man all screamed and hollered and I said that I'm in charge and you're putting them on. So they put them on, and they were very very useful to get a combination of digital analog. We are now far far down the digital one and you should think about the usefulness of analog at times. It works very well, but it does not work when there's deep computation many layers deep, or does not work when it requires extreme accuracy. The machine we had an old gun director parts was one part in 2,000. To get one part in 10,000, would’ve cost us fifty to a hundred times as much more money, You just can't do it. One part in 2,000 was better. We could buy commercial ones at one and 1000 for 1/10 what it costs us to build a new one. But that one binary digit viewing the problems I was having do from Bell Labs, I didn't think I'd give up one binary digit in each component and emerged with accurate answers. So we arranged get some more gun directors condemned, we took the parts, built them into a standard patch board of 1 meg/ohm, and had another computer, because the gun directors were beautifully designed. Unlike the commercial ones, they had gone through the Arctic, tropics, and they were well temperature compensated, and they had been debugged, and they were really robust. They were very nifty analog computers. Just old gun directors, and I can't dwell too much on the problem of reliability of answers. If you cannot get the right answer, you're in a bad way. You know that recently an awful lot of equipment in the military has not been functional at any one moment. In fact, there's been less functional than usually reported because people don't like to admit that the airplane there really isn't ready to fly. It's right there on line, and you could fly if you had to but really this that wasn't. Now, you may say Hamming is a nut on the subject because Hamming worried about all his life, that's why he’s better at error correcting codes, which we’ll take up one of these days. How to get reliable results out of unreliable parts. Part of his earliest talk was exactly the same thing. How we went from analog to digital to get reliable results. Pulses could be gated and repeated. Analog could only be amplified, so there's a vast difference between these.

Future class overview

Now, I'll give you a clue where we're headed for. I'm now gonna talk about machine computers, the history of them. The hardware software applications, and then I will turn to future applications, which means really the field of artificial intelligence, and will it cover two lectures of those. The next one is you. You are going to have to discuss what you think machines can and cannot do, and what they can do in your business. I will only shiver you and I will remind you what I said in the first lecture. It is not my business what you believe; it is my business that you do believe, and I put it one way. You must be responsible for your own beliefs. A quotation I like - it's in translation, obviously. The Buddha, 500 BC, said to his disciples, “I don't care where you read it. I don't care who you said it. Even if I said it, if it doesn't fit with what you believe and your common sense, then it's not so. You are responsible for what you believe.” [Inaudible] are saying professor said so and so and so and so - is not so good. You are responsible ultimately for your beliefs, and that's the one thing I've got to do. I’ve got to get you to believe these things. It's nice that I said these. You must go through the things and say to yourself, “Do I believe that guy or not? After all he's famous.” But, how many famous people were wrong? Almost all famous people were wrong sometime or another. It's bound to be. Furthermore I told you that what works in one generation does not work in the next, and of course my feet are in the past. You have got to face the future and the year 2020 is a number you can think about. What will be society like? How will you think? Make your decisions what things I'm saying will be relevant, which ones will not be relevant. You are responsible for your decisions and that's the main message I wanted in this chapter so I see you tomorrow at 3 o'clock, right? Same room.