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     Remarks by Bill Gates, Chairman and Chief Software Architect, 
            Microsoft Corporation    Harvard University, Cambridge, 
            Massachusetts<BR>February 26, 2004    
               BILL GATES:     Thank you. It*s great to be back at Harvard. I 
            have a lot of fond memories of my time here. When I came here as a 
            student and my friend Paul Allen decided he would come out, and 
            every day say to me, hey, why don*t you leave school and start 
            Microsoft, because he*d seen the power of the microprocessor, and 
            we*d talked about wanting to be in on the ground floor, and the 
            seminal event for me was when he was in Harvard Square and picked up 
            a copy of Popular Electronics magazine that had the MITS Altair Kit 
            on the cover. And it was a clear day, I was up in my Radcliffe dorm, 
            he brought that up there and said, look, it*s going to happen 
            without us, we*ve got to do it now. And so I said, OK, you*re right. 
            Let*s get that BASIC out there, and that led to the creation of 
            Microsoft.
            Harvard has been an amazing institution, and as I talk tonight I 
            think you*ll see a lot of ways that, out into the future as computer 
            science and computer technology move forward, that Harvard can 
            contribute a lot to that, not just purely in what we think of as 
            computer science, but in a number of different areas.
            Now, Microsoft has benefited from Harvard and its excellence more 
            than just in my time here. Steve Ballmer, who is the CEO of the 
            company also was here, we met here. In fact, it was kind of a funny 
            night, we went out and saw two movies, it was "A Clockwork Orange" 
            and "Singing in the Rain." And when we came back, Steve was saying 
            to me how he thought the greatest impact you could have on the world 
            was going to work for the government, because after all the 
            government had a lot of resources, and using those effectively was 
            maybe the way to make the greatest contribution. And that started a 
            debate between Steve and I that went on for a number of years. Steve 
            graduated, Steve went to work for Procter & Gamble, came to 
            visit me a lot, and he started his first year at Stanford Business 
            School. And by then, Microsoft had about 35 people, and I really 
            needed somebody to help me. I had been signing contracts left and 
            right, and we were kind of overcommitted, in fact, the demand was so 
            amazing. So, I said to Steve, really, I need you to come help out 
            now. And so he, too, is a dropout, although he*s a dropout from 
            Stanford Business School. And so that*s how that got things 
            going.
            We have a lot of other great people who are in key roles at the 
            company who came from here, Bill Veghte, Chris Capossela, and lots 
            and lots more.
            A big message you*ll hear from me tonight is this opportunity for 
            computer science, that it is almost ironic that today people are 
            underestimating computer science more than ever before. During the 
            late 1990s, there was that hype around the startups and the 
            valuations, and people looked and ignored some of the tough problems 
            that had to be solved to get computing to be a fantastic tool. But 
            actually during that time period, some phenomenal work was going on. 
            And that*s why we can say it*s really this decade that some of the 
            seminal advances that will utterly change not just computing, but 
            how business is done, how education is done, how people communicate 
            and entertain themselves, those things will move into the 
            mainstream. And so what we have today we*ll see as quite limited 
            compared to what will happen over the next five or ten years.
            Now, the starting of this industry was very humble indeed. That 
            kit computer on the cover of that magazine had a 8080 microprocessor 
            in it, and you had to buy it and assemble it yourself, and it came 
            with 256k of memory. And you paid extra to buy the 1K memory board. 
            And, when I wrote the BASIC, I had to create a BASIC that could run 
            not only run in 4K bytes, but would leave room for the user*s 
            program and data in 4K bytes. And so, crafting this program so that 
            there was no extra bytes and was tight as can be, it was a real 
            hand-tinkering thing. " And I always said to everybody else, if you  
            can save a single byte out of this program, I*ll pay you $20. In 
            fact, nobody has yet collected on that. Still, today, I*d challenge 
            you, if you can save a byte in 4K BASIC or 8K BASIC, that would be 
            worth "something. And so memory was very scarce. The machines didn*t  
            perform well, there weren*t much in the way of peripherals, and yet 
            that got it all started.
            There were a set of machines that came after that, the TRS-80, 
            Apple II, Commodore Pet, all of which had as the software that ran 
            on those machines Microsoft BASIC. So, when you turned it on, 
            essentially the operating system for the disk, and the tape, and the 
            screen, was this language interpreter that exposed the rich sort of 
            graphics, and music capabilities of those systems.
            The next milestone we got to was a move to what many called 
            16-bit computing, and that*s where IBM came to us. It was a very 
            strange thing, they came and said, we*ve been told that because it 
            usually takes IBM five years to do something, we*re supposed to find 
            something we can do in two years. And that*s the key thing about our 
            project, and we picked doing a home computer. And so we said, wow, 
            OK, we*d love to help you with that, but we want you to do something 
            unique around 16-bit to make that something that really changes 
            things, and three of the people on that project team and our team 
            made it a very state-of-the-art machine. And what we did with that 
            machine is, we said, OK, now it*s time for the software boundary to 
            hide the hardware differences, to make it so all the applications 
            can run on the different machines whether they*re from IBM, or HP, 
            or Wang, or Digital Equipment, whatever company offers that machine. 
            And this was a radical idea, and one that just hadn*t been done 
            before, because all the software was done by the hardware companies. 
            And yet, it was a very necessary step to create the virtuous cycle 
            that we believed in.
            And that cycle is pretty simple, that you need lots of neat 
            applications that are very low cost, and to get those applications 
            to fund the development of them, you*d better be able to sell them 
            in volume. And so you need a lot of machines that are completely 
            compatible out there, and if you can get this going, the more of 
            those machines get bought, the cheaper they*ll get because the 
            components will get cheaper, so you*ll have more of them, and then 
            you*ll have more applications, and so more people want to buy the 
            machines.
            And that is something that in the early 1980s came to pass, a 
            completely different structure for the computer industry, Intel at 
            the chip level, Microsoft providing the basic software, and then 
            thousands of companies providing applications and solutions on top 
            of that. And it moved at a pace that was quite phenomenal, and now 
            we just take that for granted that that*s what computing is all 
            about.
            It*s very different than the computer from when I was high 
            school, those were really tools just of large organizations. The PC, 
            even in the 1980s, became the best tool for creativity and 
            empowerment that man had ever created. Today over 600 million people 
            are using those machines, in different and very productive ways. And 
            yet, I*m saying we*ve really just scratched the surface.
            The next milestone after the IBM PC, with MS DOS, was the arrival 
            of graphical interface, and this is an advance where some pioneering 
            work at Xerox had been seen by Apple, and Microsoft, and we both 
            said, hey, let*s go out and build machines that work that way. It*s 
            hard for people to appreciate that that was very controversial at 
            the time. People thought, this was strange, it*s hard to write 
            software for this, it*s very slow, because you have to do more up on 
            the screen, and what*s this whole icon thing anyway? I mean, do we 
            need 29 fonts in a document and all those kind of, fruit -oop little 
            icons. So it was a period of about six or seven years that we were 
            evangelizing that, getting the software developers to do work around 
            that, and eventually that got to critical mass.
            Windows was a key part of that, and the launch of Windows 95 was 
            sort of the celebration of the fact that now we had 32-bit 
            computing, and graphical interface was absolutely in the 
            mainstream.
            Soon after that came a change that started this Internet gold 
            rush, and that was the idea that you could browse, and the 
            connections were cheap. We had anticipated that e-mail, and online 
            services would take off for many years, but it never really 
            happened. 3-Com declared the Year of the Network again, and again, 
            and again, and it was all just too hard, not at critical mass. But, 
            then out of the university environment, a few dozen institutions, 
            including Harvard, got connected up, and the standards of the 
            Internet, the protocols became the basis for full connectivity. And 
            that was a phenomenal period, Netscape got started, everybody 
            thought that was an amazing thing. People thought that and it was. 
            They used to always say that they moved at Internet time, so 
            whatever that was, we must have been moving at double Internet time 
            to get something that moved ahead, and was a strongly reviewed and 
            accepted solution there.
            That got the Industry into this period where people said, well, 
            isn*t everything going to change, won*t the way people buy, do 
            banking, insurance, set up travel, won*t that all be done on the 
            Internet? And the answer is, yes, it will. It takes time, it takes 
            the software foundation relative to security and protocols, and 
            information representation that didn*t exist in those years, but is 
            now emerging. So in some ways it was just the sense that it would be 
            an overnight thing that was wrong.
            Our industry has always benefited, been driven forward by the 
            phenomenal advance in hardware. For the CPU itself, that was the 
            thing that got Paul Allen and I to say, wow, computing will be 
            cheap, the software is the missing element. And Moore*s Law says 
            you*ll double the transistors on those processors every 18 to 24 
            months, that*s held true for these last 25 years, and it appears, 
            certainly for the next 10 and probably the next 15, that will hold 
            true. Now, we need very clever software that can take that increase 
            in transistors and map that into an increase in performance. Those 
            aren*t quite as directly tied as you might hope and expect, 
            particularly because memory latency is the thing that*s holding us 
            back. Even clock speed doubling doesn*t mean a doubling in 
            performance, because we are waiting most of the time for the memory 
            hierarchy to bring data in. And you can improve clock speeds a lot 
            faster than you can improve memory latency. But, we will do the 
            software to get that performance.
            Other elements of the system are critical, too. The storage 
            people, and they*re better than the processor people, they double 
            storage capacity every 12 to 18 months. And so thinking of a disk 
            that can not only store everything you type in your whole life, or 
            everything you ever hear or see, but also the movies you watch, the 
            photos you take, it*s very realistic. Today it*s a 40-gig disk, then 
            80, 160, 320, and pretty soon you*re talking about a serious amount 
            of storage, and that*s part of the $400 personal computer. So it 
            means that scenarios that deal with rich data types become very much 
            realistic.
            A good example of this is, I*m sure many of you have experienced 
            portable media players that let you take your music wherever you 
            want to go. This fall there will be a new class of devices that we 
            call Portable Media Center that lets you take not just music, but 
            also movies and photos. So you just connect this up with a USB 
            cable, and everything that*s on your PC, the TV shows you wanted to 
            record with Media Center, anything that you*ve created, comes down 
            onto this device, and then of course you can go and play this 
            wherever you go. And so a demand to get media in digital form, to 
            have that be flexible, to have that be available, whether it*s 
            lectures that you might want to catch up on, or just fun TV shows, 
            all of that will absolutely be there.
            Screen technology is also very important. We need big screens, so 
            you have a big field of view, like opening up an entire newspaper. 
            I*ve got three big 22-inch displays on my desk, one on the left, one 
            in the center, one on the right, and that*s helping me understand 
            that with that kind of display area we need improved ways of doing 
            Windows management, and remembering how you have things set up. It*s 
            very high DPI, and so the readability is amazing, that too is 
            something that*s very important to us.
            We want to move documents from paper onto the screen, where they 
            can be searched, where they can have media, where you can take notes 
            on them, and share them with the people who would be interested in 
            that. And so all the advantage of digital will come into play once 
            we overcome our disadvantages. Disadvantages that we*ve got this 
            great Tablet device that came out a year ago, but it*s not quite as 
            thin as a Tablet, it*s not quite as light, the battery doesn*t last 
            quite as long as a Tablet, those don*t have batteries. But, the 
            progress is there.
            That*s something that we*ve been investing in for more than a 
            decade, the ink recognition software, the hardware design that can 
            get that into the mainstream, and that will come about. So screen 
            technology, including eventually even screens that you can roll up 
            or fold up, are something that we need to think, okay, what kind of 
            software will be valuable to take advantage of that.
            The next generation of video games, whether it*s PCs, or Xbox, or 
            the next generation Playstation, will be high-definition gaming. 
            They will be very realistic games. And so it*s not just the existing 
            genres that we*ll drive forward there, it*s all of these social 
            genres where people can talk and play together, and things that will 
            appeal to people of all age groups brought into that entertainment 
            scenario. The graphics processors are phenomenal in these devices. 
            That*s why we can do rendering in real time that would have taken 
            rendering farms days to do in the past. And so you don*t even think 
            about it in terms of pixels, because it*s anti-aliasing, and 
            shadows, and smoke, and fire, and all the effects that have been 
            very tough, now move to a level of realism.
            All these devices will be connected over wireless. Wireless, 
            Wi-Fi, hopefully, we don*t know if it*s in every building at 
            Harvard, but if it*s not someday it will be. Houses, corporations, 
            this is just something we*ll take for granted, you carry the device 
            anywhere you want to go, and it*s connected up. There*s new forms of 
            wireless, like ultra wide band that provides hundreds of megabits of 
            connectivity. So you don*t need to connect the computer to the 
            screen, it just connects through the wireless. You don*t need to 
            connect your disk up to the computer, the ultra wide band just 
            connects that up.
            Over long distances we have the idea of doing what we call mesh 
            networking, that*s a big software research project at Microsoft, and 
            combining the new wireless techniques like Wi-Max let you reach out 
            and connect to the rural areas, where it*s never economic to run 
            terrestrial wired infrastructure into those, and get to this goal of 
            everybody being connected up.
            Now, we see all these different devices working together, the 
            wall-sized screen, the desk-sized, the Tablet, the pocket device 
            that*s not only the phone, but your GPS locator, your 
            personal-information management. But, even glancable information on 
            your wrist, ala Dick Tracy. We took a big step towards that with the 
            shipment just a month ago of the device I*m wearing called the SPOT 
            watch. Now, what*s in here is a radio receiver, and so it*s getting 
            the weather report, stock prices, what happens is you go to a PC and 
            pick what kind of news you want, anything you care about, 
            horoscopes, daily word problems, who you want to send messages to 
            you, how you want your calendar to show up, and as soon as you do 
            that a message gets sent to the watch that tells it what information 
            to present. When I leave work I look at the traffic on here to know 
            which way to go home, because it*s completely up to date. And that 
            just means glancability is part of the hierarchy of how all these 
            devices need to work together.
            Amazingly, the microprocessor in here that we worked with 
            National Semiconductor on, and it*s based on the ARM architecture, 
            is ten times as powerful as the original PC. It*s got ten times as 
            much memory as the original PC. I could put 80 copies of BASIC into 
            this little watch. In fact, it does have an interpreter, we download 
            programs all the time. If we decide to present soccer games that are 
            happening in a better way, or baseball, or any new idea we have, we 
            just download it over this FM network that we use to connect up to 
            the device. So it*s actually the CLR .NET runtime that*s built into 
            every one of these.
            Now, where will software change things? A lot of the economy is 
            people dealing with information, we usually call those information 
            workers. That*s very broad: if you*re on the phone talking with 
            customers, if you*re purchasing things, if you*re designing new 
            products, if you*re figuring out marketing campaigns, you are an 
            information worker. And our proposition is that the way that you 
            deal with information is way, way more inefficient than it should 
            be. The way that you are able to navigate through sales information, 
            the way that you can look at quality things, the way you can find 
            out the attitudes of customers and transfer those things.
            You often get these things on a piece of paper, so you get the 
            sales data, but, say, it*s bigger than you expect, or smaller, it*s 
            just a piece of paper on the a number on a piece of paper, what are 
            you going to do, call someone up and say, I*m confused about this? 
            What you should be able to do is just click on that, and see it by 
            time, by products, by geographies, see what the currency effect was, 
            see what happened before and after you did a special, take out a 
            certain class of customer and see if that trend is different. And 
            just sit there and click and navigate at a level of semantics that 
            you understand, the way that you think, and all that information 
            coming through in a simple way.
            This doesn*t exist today. In fact, information workers that 
            should be demanding that just don*t know that that*s possible. They 
            don*t understand the visualization techniques that would be brought 
            to bear on that. Think about meetings, meetings are this huge thing 
            that clog up your schedule, and yet anyone who goes to those 
            meetings will say, no, that wasn*t a perfectly effective use of my 
            time. I didn*t need to be there for part of that meeting, some 
            things could have been sent out in advance, we could have 
            coordinated it better. Some people didn*t need to fly in, or if they 
            didn*t fly in, we were waiting, we didn*t need to meet, because 
            without their participation we couldn*t make the right decision. And 
            just taking meetings and making them 20 percent more effective with 
            software and wireless and tablets is very doable, we proved that at 
            least at that level it*s very straightforward, that alone unleashes 
            hundreds of billions of dollars of productivity into the economy, 
            where people can make better decisions, save costs, all the things 
            that really drive the economy forward.
            Take the way that you think about business applications. Today 
            you have to write lots of code to change an application for the 
            particular needs of one company, that*s a terrible way to express 
            those differences. Those differences should exist in a very visual 
            form that*s not code; it*s just a different process. The way we 
            collect cash at this company, the way we introduce products, the way 
            we review defects, all of that should simply be in business terms, 
            and as soon as you change those diagrams, the code that*s needed 
            should be automatically connected to those things.
            Take buying and selling, people don*t today have an automatic way 
            to find all sellers, check the reputation, engage in complex 
            transactions with them, the state of those things, and deal with 
            exceptions, if someone sends you defective products. Today, it*s a 
            nightmare because you negotiate with that person through e-mail and 
            the phone, and yet the software in your company and their company 
            gets completely confused about this exceptional event, and how to 
            deal with that. There*s no coordination between the pieces. There is 
            a foundation advance called XML Web services that is the 
            infrastructure to make all of that possible, and we build these 
            modeling layers on top of that. So, in the world of business, we can 
            make the jobs more interesting, make people more effective.
            Communications affects everybody, whether you*re at work, whether 
            you*re at home. Right now, you know, communications is very 
            splintered. You*re blogging, you*re IMing, you*re e-mailing, you*re 
            using your mobile phone, you*ve got your wired phone, and the whole 
            notion of when should it ring, when should things get into your 
            Inbox, the software is not working on your behalf to know your 
            context, to know exactly what*s important. Say you*re busy and 
            somebody important wants to contact you, your software should be 
            able to schedule that, get that so that you*re coordinated, and it 
            happens without any overhead at all.
            Spam is just sort of the extreme of your time not being used 
            properly. Spam is in big numbers because people have figured out 
            they can send millions, or even billions of pieces of e-mail for 
            very low cost. So, if only one out of a million people go click that 
            thing and buy a product, that*s an economically positive event for 
            those people, although it*s bad for the economy, 99,999 people had 
            some of their time taken away from them, and perhaps don*t even get 
            to the mail that is important to them.
            Some of this spam is pretty surprising and quite unusual. I*m not 
            going to show you all the spam I get, some of that might not be 
            appropriate, I don*t know why I get that. But this one is one of my 
            favorites, because what*s clear to me is that as soon as I get out 
            of debt, there are going to be a lot of nice people that are going 
            to be very friendly, and so this is definitely important for your 
            social life.
            The next one seems to be a little bit more targeted. How many 
            people need a college diploma? Not that many.
            (Laughter.)
            And then, finally is one that really appeals very directly to a 
            problem I deal with, and that is this whole legal cost thing. My 
            shareholders definitely think I should follow up on this one.
            It*s pretty interesting what comes in over the transom. How can 
            we solve that? We can solve it. This is not something that will 
            plague us in the years ahead. By authenticating who sends the 
            e-mail, like a Caller ID-type structure, by automatically passing in 
            mail from people you know, and by having mail from strangers that 
            you should pay attention to, making it trivial for them to provide 
            some sort of proof that it*s not spam, we can get e-mail back to 
            what it was. The forms of approach will include things like asking 
            their machine to do 10 seconds worth of computations. There are math 
            functions that take 10 seconds to do, and they take thousandths of a 
            second to check to see whether they were done, they*re called puzzle 
            functions.
            And so, when you receive the e-mail, you just check, was that 
            done, and so if you*re sending a modest number of messages, it*s no 
            effect at all, it*s just done in the background, but for that spam 
            generator, there*s a gigantic economic cost that undermines that 
            asymmetric model of very few people really wanting to get that 
            spam.
            We can also use human-interactive proof, where you prove there*s 
            a person on the other end willing to do a short task, or monetary 
            proof, where you show that you*re willing to put some money at risk 
            if the person who receives it says, yes, you*ve wasted my time, as 
            opposed to it being mail from a stranger who it is something that 
            you did want, your long-lost brother, somebody saying that your 
            house is on fire, that you should pay attention to.
            In the consumer realm, it*s clear things are also going to 
            change. Keeping memories about your friends, your kids, your events, 
            that*s not just photos, that*s videos, that*s the audio annotation 
            that share why it was exciting and special to you, all of that 
            should be archived and shareable and navigable in a very rich way. 
            Remembering the movies you*ve seen, and sharing recommendations with 
            other people, being able to do these things whenever you choose to 
            do them, all of that we will take or granted, because at your home 
            you will have a PC that let*s you create and organize and then 
            project through wireless that out onto any speaker or any screen 
            that*s in the house.
            One of the challenges here, though, is that you*re dealing with a 
            large number of objects. You*ve got a lot of movies, and a lot of 
            photos. And just real quickly I wanted to show you a couple of 
            prototypes that Microsoft Research has done that suggest improved 
            visualization that will make these things easy to navigate. The 
            first one we*ll bring up is about movies, and what you see is that 
            we*ve got "Blade Runner" there in the middle, and what it*s done 
            when we selected that is it took the director, Ridley Scott, and put 
            all his movies over here so we can go through and look at those, and 
            pick let*s say something here, and we bring that to the center, it 
            does the same thing of bringing the famous actress here, and so we 
            can see their movies, and select through those. We just pivot 
            through this, and of course we*d have the reviewers who we like, or 
            what our friends that we trust have said as part of this navigation 
            process as well. So, we*re making it easy and fun to go through 
            these different dimensions without making it feel like you*re 
            writing a query against a database, which actually of course it 
            is.
            The second prototype is focused on photos, and so I can see I*ve 
            got a ton of photos here that I can go through and look at. I also 
            have movie clips here, so if I take one of these movie clips, let*s 
            see, I click on it, it just plays, and that*s recorded. I have audio 
            annotations on a lot of these different photos. That*s why I*m 
            keeping that one. And so, how would you like to navigate this? Well, 
            partly you*d like to assign key words, you know, I can look at all 
            the different key words I*ve applied here, and so say I*ve picked 
            one about Thanksgiving, when I click on that, it does the selection, 
            if I double-click it, it just brings that up. But, I want the 
            software to help me with this. So, for example, the software should 
            be able to tell every photo that has faces in it. You can see it 
            goes and selects those when I go over that face thing. It should be 
            able to tell which are indoors or outdoors. It even should be able 
            to say, okay, if I take an image like that, show me anywhere that 
            I*ve got something similar. So, I can relax the similarity criteria 
            and get more. And as I make it more stringent, I get less of those. 
            I get groupings based on similarity where it*s looking at the image, 
            and it will actually use that recognition capability. In fact, every 
            one of these photos, ideally the camera records the time and the 
            location as well, and so we can group things that way.
            We*re also experimenting with where 3-D comes in. Today, most 
            computer interfaces are still very flat. And so when we get into the 
            3-D mode, we can step through things this way. Beginning to change 
            the X axis, which is based on time, and get more groupings, more 
            detail, and then we can select any set that we want, and say, okay, 
            that*s about that, let*s put a keyword on that, which is a better 
            way for me to navigate than remembering the exact time I grouped 
            together all those things that are similar. All that gives you a 
            sense that there are advances that will make the navigation of these 
            things pretty straightforward and kind of fun. We*ll have a lot of 
            different items that we*re dealing with.
            The optimism I mentioned about software breakthroughs, the best 
            way we demonstrate that at Microsoft is by our increased R&D 
            spending. We*re spending $6.8 billion a year this year. That*s 
            substantially the largest technology R&D budget, about 20 
            percent more than IBM, and more than double anyone else. And, of 
            course, IBM does a lot of hardware and physics things, they work in 
            five different operating systems, so it*s a little bit different 
            character than what we*re doing. One of the parts of this that has 
            been phenomenal for us is the pure research group called Microsoft 
            Research. And, it really has allowed us to get at the forefront of 
            these top issues, making sure that the advances we need really get 
            done. For example, we*re working with lots of universities, 
            including a good example is Harvard on this Center Network 
            Application, it*s a pretty neat thing. And that kind of 
            collaboration is very important to us. Research in the U.S. is ahead 
            because of the great symbiosis between commercial labs doing neat 
            new things, and universities.
            Now, that commercial side in some ways is not as strong as we*d 
            like it to be. Companies like Xerox and AT&T that in the *70s 
            and *80s were very big are dramatically down. So even if Microsoft 
            increased, the net amount of that activity is less, and certainly 
            that*s an issue in terms of the U.S. really having this as a unique 
            advantage.
            One of those research topics that*s vital in the top priorities 
            of the company is all the issues around security, verifying whether 
            code is correct, that involves writing it in new ways, scanning the 
            code to check for specific kinds of defects, and actually being able 
            to prove whether code works or not.
            When I left Harvard, this was a state-of-the-art problem, and 
            Professor Cheatham and others were using a thing called ECL, 
            Extensible Computer Language, and they could prove programs that 
            were about 20 lines of code. Now, Microsoft*s code is not 20 lines 
            of code. Over the last years, that*s gotten up to hundreds of lines 
            of code, but only in the last year with some work, it was 
            collaborative, but with a key breakthrough by Microsoft Research, 
            now we*re taking programs that are hundreds of thousands, even a 
            million lines of code and being able to prove things about them. And 
            if we look at, say, a device driver, and we say, does this device 
            driver ever cause a fault? And it either says, no it doesn*t, or it 
            can actually prove to you, show you exactly the set of code tabs 
            that would lead to that result. And so you immediately understand 
            what you have to do to make that better.
            Now, raising the level of abstraction, and having more modularity 
            and contracts between the pieces, these are necessary steps to get 
            security to work. The Internet was not designed with security in 
            mind, it was designed so that it over time would heal if some of the 
            nodes went down, but the time of that healing, and the fact that 
            malicious players would be on that network, were not part of the 
            original design. And so the TCP/IP-verifying the packets, SMTP 
            knowing who is sending you information, the fact that passwords are 
            used in so many of these systems, that*s an incredibly weak link. 
            And so, to get security and reliability right, we need to really do 
            a lot better. We need to make sure that it*s not easy to exploit 
            these systems. A combination of firewalling things and updating 
            systems will make a huge impact, and those will be being used in a 
            very widespread way even in the next year.
            More profound is watching systems to see when their behavior is 
            unusual. For example, if you look at the whole Internet and say that 
            the level of traffic is way up, what are the types of traffic errors 
            that have risen up as a percentage of the profile, and can we drop 
            those and let the other traffic have higher priority? If you look at 
            a computer and look at a program that normally doesn*t, say, update 
            files is all of a sudden updating files, isn*t that an unusual event 
            that should be examined, and thought about. So this whole active 
            protection is one of the paths forward, and one that there*s a lot 
            of good invention taking place around.
            Other inventions we need are things that have been thought about 
            for a long time, but only now can we say that these will be solved 
            in the not-too-distant future. Ink recognition I mentioned, this is 
            one where we now have hundreds of thousands of devices out there, 
            and we got it good enough that we have those users, and we take any 
            time one of them is frustrated by the recognition, and they send it 
            back to us, and we make it better. We understand by that 
            information. A lot of our approaches are very data driven. We look 
            at all the handwriting people do, and build rich Bayesian models, 
            neural models around that. That*s the underlying technology that*s 
            used.
            Ink is moving into the mainstream, a little bit before speech. 
            Part of the reason for that is that with ink you see your mistakes, 
            you too can read it and say, OK, I wouldn*t have recognized that 
            either, it*s OK. Whereas with speech, it*s all subconscious, and so 
            you never say to yourself that you misspoke or anything, because you 
            have no idea what the correction function looks like, and it*s very 
            frustrating, it appears random. With ink, people actually change, if 
            they are taking a C and closing the loop to open, and we think it*s 
            an E, and over time you get better at that. Even subconsciously they 
            get way better at it, and so the recognition rates improve quite a 
            bit. In speech, that doesn*t happen, you don*t have conscious 
            plasticity. And so we have to get an error rate that*s pretty 
            unbelievable.
            Just take speech and take random words, so there*s no context, 
            take a perfect microphone, and eliminate all noise, the difference 
            between human and computer recognition is quite small, it*s only as 
            you relax those constraints that we see that humans are unbelievably 
            good at using context, eliminating noise, and really getting a 
            strong signal that gives them that huge advantage. And that*s really 
            informative, because now we*re matching those things, we*re matching 
            through signal processing techniques the noise elimination, we use 
            what are called array microphones to do that, with some very deep 
            algorithms. We*re using our natural language work to say, OK, how is 
            this context done in a very deep way and make that work well.
            Another input modality we believe in is vision. We*re already 
            seeing on video games little cameras where you can sit there and 
            swing the bat, and do various things. The cost of these cameras is 
            way down. So in meeting rooms, on your PC, in your video game we*ll 
            have very high-resolution cameras that take information, and the 
            computer will be able to understand that. The computer will know, 
            are you looking at the screen, maybe it should notify you of 
            something, or are you looking at something else, is there someone 
            else in the room talking if the voice is different. And it will use 
            that to build a richer model of interaction.
            The holy grail of computer science is artificial intelligence, 
            and this is the idea of learned behavior. And people today, there*s 
            actually, if you take the field, there*s less working on it now than 
            20 years ago. We at Microsoft have a large group because we actually 
            feel some real advances have taken place, and will take place around 
            Bayesian systems, or statistical verifier approaches that are very 
            strong. We*re applying this in many different ways. One is that we 
            watch how games are played up on Xbox Live, and we have our AI 
            engine learn all the playing techniques. So you can take any level 
            of difficulty and the machine will play like an idiot, or it will 
            beat you hands down the same way that human players would beat you, 
            because it has that learning base that it*s been designed around. 
            Machine translation is another one that we believe is really ready 
            for prime time, to take and have lots of documents be made available 
            in different languages.
            Now, computer science, I mentioned, will also be the set of tools 
            that advance and really change the other sciences. Jim Gray, who 
            works for us, got together with astronomers and said, look, each of 
            these observatories has their own database, a database at different 
            resolution, frequencies, from different parts of the earth, and 
            they*re not normalized in any way so that somebody who wants to 
            propose something in astronomy, they can just test out that idea and 
            see, are there any pulsars like this, anywhere near anything else 
            like this, and boom, get that answer back. There*s so much data that 
            it*s not about just staring into a telescope late at night and 
            hoping you*re there when some supernova blows up, it*s about mining 
            that rich data. So the frontiers of that science only can be 
            advanced by having tools that are good at that. And already there*s 
            some amazing things that have come out of the work of taking that 
            data, connecting it up through Web services.
            The same thing can be said for most of the hard sciences, biology 
            is a particularly interesting one, and a tough one. The complexity 
            of the data, the breadth of the data -- but the value of 
            understanding that data makes that a very, very exciting area.
            If you look at Harvard, this trend of computer science working 
            with the other sciences is a very interesting opportunity, because 
            Harvard, of course, is a leader in so many areas, health and 
            medicine, you*ve got an incredible group of people to work with. The 
            Government school, the Business school, all of the other hard 
            sciences. And so there should be more opportunities really for 
            Harvard really to stitch those things together than almost any other 
            university.
            Now, as we charge forward in making these great tools, and having 
            them work fro everyone, we need to continue to look at the issue 
            that these are so important that we want everyone to have access. 
            This is often talked about as the Digital Divide, and it*s a 
            challenge. One of the things Microsoft does, of course, is make sure 
            that high-volume computing, software and hardware are more 
            available, less expensive. The broadband communications costs are 
            the most expensive piece, but here wireless and our mesh software we 
            think will come in and even solve that piece so that it won*t be as 
            much of a barrier as it is today.
            We did a program, that was actually my foundation working with 
            Microsoft, to say, let*s try and put computers in libraries. And we 
            started this six years ago. It was something we were worried about, 
            in terms of would the librarians like it, would kids come in and do 
            things that weren*t considered all that educational, using the 
            machines? Would the machines break down, would people still go for 
            the books? How would this be accepted? And by providing a lot of 
            training, and really reaching out to librarians, this thing has been 
            a phenomenal success. It*s raised the traffic in the libraries, it*s 
            raised the number of books being checked out. It means that anybody 
            who can reach a library has the latest software and is connected up 
            to the Internet.
            The demands that came out of this were fascinating. We had to 
            make Windows so you could just push a button and switch from Spanish 
            to English, boom, all the software would be switched. We have to 
            have a button so you could push and all the fonts would get bigger, 
            so that older people coming in would find it easy to navigate and 
            read the information. We had to make systems more robust, so in case 
            somebody was a little bit messing around the system state could be 
            restored very easily and be exactly right.
            So now in a sense the U.S. project is complete. We*ve got 18,000 
            libraries who now have these 50,000 machines, and those are being 
            used very heavily. There*s more to do in the U.S., schools and 
            community centers, and then the final frontier, the tough one, is 
            making sure this happens on a global basis.
            Computing is making the world a smaller place. I*m always 
            fascinated when I go to hospitals in Africa or high schools in 
            India, and see that PCs are there, and people are connecting up to 
            the Internet, they*re getting that wealth of material, some of it is 
            only in English, but the wealth of material that is as good as what 
            all of us here have access to.
            Some people are worried about this globalization, because it 
            means that jobs can be done anywhere in the world. It means that if 
            you have an education you can compete for jobs that other educated 
            people are looking at as well. And what this means is for global 
            productivity, for raising the level of wealth of these countries, 
            for having better goods and services, it*s a fantastic thing. It 
            does mean that in the same way the U.S. during the 1980s had to 
            think, OK, what is our edge, what makes us better, we need to do 
            that now, and renew our commitment to those things.
            In the 1980s it was a concern about Japan, and it was 
            overwhelming, people wrote books about that their industrial system 
            was just better, and that the consumer electronics industry was 
            gone, the car industry was going, the computer industry was next, 
            people were kind of depressed. And along with that, there was this 
            humility of saying, no, we*re not just going to do it the way we do 
            it, we*re going to keep our university research system, we*re going 
            to let it pursue lots of different paths, we*re going to have this 
            capital formation, and companies taking risks, and rewards for 
            intellectual property that defines our approach. And all those 
            productivity benefits that came out of the *90s were based on work 
            that was done during the 1980s.
            So it really is something where you can have lots of winners as 
            this moves forward, including the U.S. staying in that strong 
            position. In order to do that we need great people working on the 
            important areas. And computer sciences, the sciences at large, all 
            of that is very important. We*re falling short a little bit, in 
            terms of getting diversity, lots of women and minorities, into these 
            fields. I*ve done a little bit to help with that with a Foundation 
            program that*s called the Gates Millennium Scholars, and here at 
            Harvard there*s about 60 of these Gates Millennium Scholars that I 
            hope will do well themselves and set a role model that will really 
            drive forward and make a change in this.
            So we need diversity and we need the excitement, we need people 
            to understand these are jobs that are very interesting, most of 
            these jobs are very sociable. If you want to just write code, 
            actually that will be fine, too, but most of them are demanding a 
            broad range of skills. And the excitement of the kind of impact you 
            can have doing this work rivals anything else, because the change is 
            there, the breakthrough is there, so every day is fun and then when 
            you look back on the change that you drove, that*s fun as well.
            And so I*m very excited to see this move forward at full speed, 
            I*m very excited to see how each of you can contribute to it.
            Thank you.<!--START RIGHT NAVBAR--></TD>