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            Remarks by Bill Gates, Chairman and Chief Software Architect, 
            Microsoft Corporation Massachusetts Institute of Technology, 
            Cambridge, Massachusetts February 26, 2004
            BILL GATES:  Thank you. Well, it*s great to be here at MIT. 
            MIT has invented so many things and played such a key role in the 
            advance in computer science I won*t have time to name them all. But 
            Microsoft has been very privileged to be associated with MIT and 
            helping collaborate on a number of projects here.
            Microsoft also has some great employees who came from MIT, most 
            notably people like Gordon Bell, who*s some still very creative 
            after making so many contributions, and also Butler Lampson, who*s 
            actually back here teaching courses, as well as continuing to help 
            Microsoft.
            The main thing I want to present today is how I see the next 10 
            years of computer science as doing some really amazing things, 
            solving some problems that have been out there for many decades and 
            transforming most things of interest, transforming the way people 
            work in businesses, the way they deal with information and meet and 
            communicate, transforming the way that people at home find 
            information, the way that they create things and connect up with 
            other people, and transform even the sciences, bringing the 
            methodologies of machine learning and modeling and rich data mining 
            into all of the hard sciences and allowing those sciences to move to 
            the next level.
            It*s a paradox to me that computer science today is poised to do 
            all these amazing things, and yet in some ways people*s expectation 
            and even the excitement level about computer science is not as high 
            today as it was, say, five years ago when we were in the midst of 
            what we can now look back and say was the Internet bubble.
            Many of the challenges, the problems, the things that were hard 
            to deliver on during that period are exactly the kinds of things 
            that a combination of great academic work and great commercial 
            working coming together has solved and will make sure that the 
            productivity advances that we see in the economy will be 
            dramatically higher, more than double what we received in the 1990s. 
            And that*s very profound for innovation, employment, many things on 
            a global basis.
            The computer industry started by making very big, expensive 
            machines and, in fact, when I was young people thought of computers 
            as kind of these daunting things in the back room that would often 
            print out bills that would be wrong and you could never get 
            corrected. People talked about taking the punch card in your billing 
            envelope and putting staples in it or mutilating it to somehow 
            defeat the big machines.
            And I was lucky enough to be young at a time when that changed. 
            My friend Paul Allen saw the very first microprocessor, the 8008, 
            not very capable but better than a PDP8 was, and he challenged me, 
            he said, "Hey, Bill, could you write software for this, could you do  
            a "BASIC, and that really got us going, saying that we wanted to be  
            in on the ground floor of building the kind of software that 
            computing would need as it moved from that back room onto the 
            desktop, as it became a tool of empowerment, a tool for creativity 
            and communications.
            Now, it started in a very humble way. The kit computer that Paul 
            saw on the cover of Popular Electronics magazine, a freezing cold 
            day in Harvard Square, and brought back to me and said, "You*ve got  
            to drop out; it*s happening without "us, -- (laughter) -- that  
            machine was laughable. It at most had 8k of memory, had no 
            peripherals, so the software we wrote would flash lights and do 
            funny things. It was a major discovery that because of the noisiness 
            of the electronics in it that we could actually put a radio nearby 
            and if we did certain instruction patterns cause predictable music 
            to come out of that radio. And it was kind of limited what we could 
            do, but that was the beginning and the kind of excitement around 
            that, thinking where could this go, that got our industry off to a 
            great start.
            There was a generation of machines that came after that, 
            so-called 9-bit machines, TRS-80, Commodore 64, Apple II, all of 
            which included Microsoft BASIC in as their fundamental software. It 
            was the equivalent of not only the language but the operating 
            system, everything, and you could type in BASIC statements to do 
            graphics and games and business software. And we even got disks 
            connected up to these things, we moved away from cassette tapes and 
            paper tapes to these ridiculous eight-inch disks that hardly held 
            any information at all, but constant improvements.
            A big milestone in 1981 was the entry of IBM with the PC into 
            this business, and that had been a joint project with Microsoft 
            where we*d convinced them to use the 8086, created the DOS operating 
            system, very limited system but very appropriate for that machine, 
            and we kicked off an era that was fairly different, because starting 
            with that machine, we had a vision that we wanted all the machines 
            to be compatible, that is to use a software layer to make it so that 
            whenever you wrote an application it would run on machines from IBM 
            or HP or Digital Equipment or any of the other computers at the 
            time. And that hadn*t been the case and, in fact, that prevented the 
            virtuous cycle that we wanted to have happened, it prevented it from 
            getting going. And that cycle was that as more people saw 
            applications that were meaningful to them, they would buy machines, 
            the more machines that were bought, the more volume of components 
            would happen, the lower the cost those components would be and the 
            more people would invest in buying applications so it would make 
            sense to really build the software industry.
            There essentially was no software industry before the PC. There 
            were about 20 different companies and the highest award in the 
            industry was one that you got for selling a thousand copies of a 
            piece of software; it was called the ITP award. And I filled out the 
            application after we*d sold 2 million copies of BASIC, I sent it in 
            and they said, "Well, we*d love to give you this award but there  
            must be some scientific notation error here, you*ve got too many 
            "zeroes. And I said, "No, I*m not kidding, we sold 2 million 
            "copies. And they said, "Well, geez, how come we haven*t heard of 
            you?" And we said, "Well, I don*t know where you*ve been, but we do 
            have this very high-volume, low-price model, so we*re not like on 
            the New York stock exchange or anything but we have sold two million 
            "copies."
            And so personal computing gained in momentum, it gained in 
            excitement. One of the great issues was to move from character-mode 
            interface to graphics interface. It may seem strange today, everyone 
            takes that for granted, but the cycles required, the difficulty of 
            writing these programs made a lot of people say, "Hey, we don*t need  
            this, that*s just really too many icons, too many fonts, let*s stick 
            to the serious stuff, we love these mono space characters up there 
            on the "screen. And there were about six or seven years where taking  
            some of the pioneering work from Xerox, Apple, and Microsoft really 
            pushed forward with this idea of graphics interface and that became 
            Microsoft Windows, it was integrated in the operating system.
            And then we got to the next frontier. That frontier was 
            connecting all the machines together. And year after year we*d 
            always say e-mail is coming, connectivity is coming, online services 
            are coming, and, in fact, it didn*t happen and didn*t happen, and 
            then all of a sudden, coming out of the university environment, the 
            standards of the Internet exploded, along with the decrease in cost 
            of optic fiber and the increase of the speed of the network and a 
            critical mass was achieved. And that was a period where things 
            definitely went a little crazy but the gold rush atmosphere actually 
            accelerated the investments people were making and raised the 
            awareness that people had of what a revolution this was.
            Now, some of the things that are hard about e-commerce or 
            workflow or modeling or making sure these systems are 
            ultra-reliable, ultra-secure, some of those were revealed as 
            shortcomings that needed software breakthroughs, needed software 
            advances. And so as we look forward, it*s kind of a bias I have, but 
            the thing that*s really going to make a difference is software. It 
            is the new generations of software that let us interact in natural 
            ways, that connect these devices up in new ways and problems that I 
            see being solved in the near future.
            Now, the hardware guys, I have to give them credit. They*ve 
            always provided a more powerful platform for us to exercise our 
            software creativity against. And that*s why Paul Allen and I could 
            say back in 1975, personal computers will be mainstream. The slogan 
            we had was, "A computer on every desk and in every home," and in 
            some small part in some countries we*ve come a long ways towards 
            that. It*s not yet the machine that we envisioned in terms of the 
            ease of use or breadth of things that can be done, but it*s 
            certainly a good rough draft that*s on its way.
            The hardware people have given us Moore*s Law that predicts a 
            doubling in chip performance every 18 to 24 months. That*s held true 
            these last 25 years. And something like the next 10 to 15 years it*s 
            very likely to continue to hold true.
            Now, that increase in transistors, there are some very 
            interesting software techniques related to parallelization that are 
            needed to take transistor count and map it into performance. It*s 
            not automatic that just because you have twice as many transistors 
            that you get that performance. And so finally some of these issues 
            of automatic parallelization and understanding the algorithms that 
            let you do that, we*re making progress on those.
            The storage people do an even better job than the chip people. 
            Their doubling rate is something like 12 to 18 months. And this is 
            very important, because when storage was expensive, the idea that 
            you could deal with photos and videos and audio annotation and 
            replicate information around so it would be immediately available, 
            even if the system is not connected up to the network, that just 
            wasn*t possible. People didn*t think in those terms. 
            And, in fact, storage is so available now we have to be creative 
            in thinking about what we*re going to do with it. We*re getting lots 
            and lots of that. In fact, a good example of how cheap storage is, 
            is that we have this device that comes out this fall called the 
            Portable Media Center. It*s a 40-gig disk, beautiful LCD display, 
            and you can just connect it to a PC that*s recording TV shows or has 
            your movies or whatever is there and it automatically downloads the 
            movies, videos, photos onto this device that you can, of course, 
            carry around and use anywhere you want.
            And these devices will come out fairly inexpensive in the $400 
            range, and the price will just come down and down and down because 
            this is the magic of that hardware innovation. Eventually we*ll just 
            take it for granted that kids who want to watch movies or people who 
            want to watch shows have this available, and so it won*t just be 
            portable music players but devices that deal with the video as 
            well.
            The screen is another place where innovation is critical for us. 
            If we think about how we can move reading from paper to the screen 
            so that we get the rich searching, updating, annotating, sharing 
            that the digital world allows, that requires screens with very high 
            resolution. It requires screens that we*re comfortable holding in 
            our lap and just sitting there paging through the information. It 
            requires a thin, light device, long battery life; big challenges but 
            certainly what*s gone on with LCDs and other screen technologies 
            says that in the future we can assume a 30-inch LCD on a knowledge 
            worker*s desktop or three 22-inch displays, which is the 
            configuration I*m using right now and lets me work with information 
            in a much better way. And the same way that a newspaper gives you a 
            big, wide field of vision, this does that and there are certainly 
            some advances in window management use of the screen area that have 
            to take place as we get to extremely high DPI on big screen areas 
            that come with it.
            We believe that reading will move onto the digital platform, that 
            the superiority of the cost structure, all these things argue for 
            that as we get devices that are based on this new screen 
            technology.
            A nice milestone in that is the arrival of the Tablet PC. That 
            got kicked off about a year ago. It*s based on the miniaturization 
            of hardware, the ink software, ink-recognition technology that we*ve 
            been working on for over 10 years is now bootstrapping in terms of 
            the quality of the hardware, learning from that software, doing that 
            better and better and making that mainstream. And so all the 
            portable devices will become Tablet devices, and they really will be 
            like Tablets, which they*re a little bit heavier than a Tablet 
            today.
            The graphics processors, there the improvements are you can get 
            higher transistor counts there because of the number of duplicated 
            components and actually if we look to the future of CPU 
            architecture, we can see that more predicted by what*s happened in 
            the JPU level, because they*ve thought about parallelization. Now, 
            they do it in a domain specific way that we need to open up, but 
            it*s really the blending of those that is the next stage there.
            A big element, of course, is wireless. As we get things like 
            ultra-wideband wireless, which is hundreds of megabits, the idea 
            that you connect a computer to the screen will become obsolete. The 
            computer will find the screen that*s nearby and take advantage of 
            it. The idea that the computer and the storage have to be associated 
            with each other, there*s no reason for that. You can carry your 
            storage with you and whatever PC is around, in a very secure way 
            your storage can be made available to it and you can be given 
            guarantees that that information isn*t left on that machine after 
            you log out from that machine. So we*ll see the dis-aggregation of 
            the PC that way. 
            We*ll see the arrival of rich new peripherals. Digital cameras 
            are now the most popular way to take photos and that*s happening in 
            the motion video space. Well, those devices will have ultra wideband 
            and so they*ll mark not only the time but the location of that 
            information and deliver that to your storage system.
            Your storage system will be a combination of data stored in the 
            cloud and sort of a far-sight ocean store type way where you don*t 
            have to worry about whether you*ve backed it up, because there are 
            many copies that are stored in encrypted ways that mean that only 
            you have control of that information. Or you*ll have the storage 
            that you carry with you physically that will give you total control 
            over it, and making those two things work well together is very 
            important.
            Now, in the area of wireless, one of the tough challenges has 
            been the cost of broadband. When you would think about what*s 
            expensive, getting a PC, say, into rural India, the hardware is $300 
            or $400, the software is less than $50; it*s that broadband cost, a 
            monthly cost of paying again and again and getting that 
            infrastructure out there that*s really the prohibitive factor. 
            And we believe through some software techniques around mesh 
            networks and some advances in the wireless hardware, particularly 
            the Wi-Max-type approaches, bringing in not just omni-directional 
            approaches but directional antennas as well, that we will get the 
            kind of connectivity that can make sure that connecting everyone on 
            the planet becomes very feasible.
            So you*ll have a range of devices, wall-sized screen devices, 
            desktop Tablets, pocket-sized. We even believe in a wrist-sized 
            device. In fact, I*m wearing my SPOT watch, which just came out in 
            the last month, and this -- I don*t know if you*ve seen it -- it 
            lets you see sports activities, stock prices, your schedule, you get 
            messages on it and a lot of different things that are being 
            transmitted to this watch.
            It was actually when I was at MIT over 10 years ago that I first 
            saw a demonstration of FM sideband data networking and this watch is 
            based on that approach. Of course, the modulation techniques are 
            several generations later.
            There*s a microprocessor in here that we paid National 
            Semiconductor to create that*s based on the ARM architecture. This 
            microprocessor just on my wrist has 10 times the power of the 
            original IBM PC. It*s got 10 times the memory of the original IBM 
            PC. This thing is powerful. And, of course, the battery life is on 
            the order of many, many days because these things are low power.
            We can download arbitrary programs to this device, so as we get 
            new ideas about sports presentation, information presentation, as 
            people have neat things they want to do, it can come down in an 
            automatic way.
            Today, the watch is in receive-only mode, but we actually have 
            the capability to send data as well in a local area, and so you can 
            find people with common interests, a lot of applications that the 
            glanceable information platform will be particularly appropriate for 
            working with the other devices.
            We have to think in terms of the scenarios. The photo scenario 
            that you use all the different devices, the scheduling scenario 
            using all those devices, and it*s way too hard today to get those 
            things to work together.
            One of the big places that software advances will change things 
            is change things in the way business is done. The information 
            visibility that a typical information worker has is extremely low. 
            They*re used to it in a way so they don*t know to complain, but 
            their ability, say somebody gives them a sales printout. They look 
            at these numbers and they must think, "Wow, that one*s really big.  
            Wow, what did we do? That one is kind of small. Geez, are we in 
            "trouble. Well, their ability to just dive into that data and see it  
            by time period, product, cost structure, they don*t have it. It*s 
            not there. The schematization and model approach to bring that down 
            to every employee to just naturally expect that they can see those 
            things and understand those things, that*s not there. The world of 
            business intelligence hasn*t delivered on that.
            The XML foundation that*s advanced so fantastically over these 
            last six years is the foundation to make that happen, to build XML 
            into the spreadsheet, to build a knowledge of business processes so 
            you can visually see what*s the state of this activity.
            Businesses today do all these custom modifications to the 
            application programs they run, the enterprise applications. And 
            that*s very strange because the differences between those 
            businesses, you ought to be able to express it in some other way 
            than code. Code is complex. When people update the applications, you 
            don*t know how to combine that new code with the other code because 
            it*s not orthogonal. There shouldn*t be code in that process; there 
            should just be visual business processes that you*re connecting up 
            to and explaining how this business is different than this business. 
            How does the order process work, how does the collection process 
            work, how does the analysis process work and that*s the kind of 
            thing we*re really on the verge of, because XML gets our semantic 
            level up and lets us finally address making this information really 
            available.
            If we look at meetings, meetings are a source of a lot of 
            inefficiency, as any information worker will tell you. Things that 
            they didn*t need to be there for, meetings they had to fly in to 
            that they would have preferred to be able to do at a distance, 
            things that didn*t get followed up on, things that somebody who 
            wasn*t there you wanted to explain to them that you couldn*t just 
            link in and see the transcript or see the video of what went on 
            there. 
            Well, storage is almost free and cameras and software to scan and 
            understand this stuff will be almost free, and so we can take the 
            meeting and have that be something that we bring a lot of efficiency 
            to. If you make meetings in general 10 percent more efficient, 
            that*s tens of billions of dollars of extra productivity every year, 
            and that can be used just as cost savings, it can be used to make 
            better decisions, to drive quality into processes and it will do 
            every one of those things.
            Even the basic process of buying and selling hasn*t been made as 
            efficient as it should be. Can you find all the sellers of a 
            particular type of product? Can you check their reputation? Can you, 
            if you engage in a transaction, see the state of that transaction in 
            a very rich way? If your computer is talking to their computer and 
            their computer is somehow malicious, are you protected from that 
            kind of behavior?
            If the software is talking to the other software, what about the 
            workers? Say that there*s a delivery that*s defective, how do you 
            coordinate the negotiation on e-mail in an ad hoc way with these 
            back-end systems so they can understand things and check the state 
            of things? These things are incredibly inefficient today, so basic 
            workflow is not built-in.
            E-commerce has not happened. E-commerce only really happens where 
            every seller can find every buyer, every buyer can find every 
            seller, independent of location or previous knowledge of each other, 
            and that rich transaction is done in a pure digital way.
            In communications, what we*ve got today is kind of a hodgepodge 
            of different things. The latest thing is blogging. That comes after 
            instant messaging, which comes after e-mail. You*ve got your 
            wireless phone and your wired phone. Lots of times you*re 
            interrupted, the phone rings when you don*t want it, things come 
            into your Inbox that you don*t want and your time is a scarce 
            resource. And so these activities are wasting your time, causing a 
            lack of productivity, even in some cases you have enough spam that 
            you filter out or don*t have time to read e-mail that would have 
            been of value.
            Now, for me spam is this awful thing, but sometimes when I look 
            at the spam I get I have to just step back and laugh about them. 
            I*ve got a few examples here. This is one of my first ones. 
            (Laughter, applause.) And it*s clear once I get out of debt I*m 
            going to be meeting a lot of nice people who are going to be 
            friendly to me. (Laughter.)
            The next one looks like it might be more targeted. (Laughter.) 
            And this is not one that any of you need worry about, since I hope 
            you won*t drop out.
            And finally there was one that really related to a serious cost 
            problem I*ve got. (Laughter.) The shareholders really want me to dig 
            into this one and understand what*s going on there.
            So it*s a serious problem but it*s amazing the things that are 
            out there.
            Letting people send billions of pieces of mail very, very cheaply 
            devalues the time of the person on the other end. And this is a very 
            solvable problem. We need mail that comes from people we communicate 
            with regularly to be authenticatable, and we announced on Tuesday a 
            way of doing that, leveraging off the DNS that we think can be 
            applied and uses a standard literally within months. Mail that comes 
            in from a stranger, some type of proof is necessary. If the filter 
            thinks that looks like spam, then you need some type of proof to 
            distinguish it from the other e-mail. And there are several forms of 
            proof that will be used and they all work in parallel; any one of 
            them is kind of an "or" condition. 
            Proof that*s computational, where you solve one of these problems 
            that asymmetric in the opposite way that cryptographic functions 
            are, that is it*s asymmetric in the sense that checking the answer 
            is easy but actually doing the computation is hard, and so for 
            somebody sending a modest amount of mail it will just happen in 
            background, they won*t notice it, but if you were sending millions 
            of e-mails it would be a significant computation cost to do that, so 
            you screen out.
            Human interactive proof where you bounce back and make somebody 
            solve something that software alone can*t do is another approach, or 
            if there*s connection into a payment system, making somebody put a 
            little bit of money at risk, not that gets charged to them and this 
            is only e-mail to strangers, but that it*s at risk so that if it 
            really is junk, the person who receives it and spends time reading 
            it, at least they get the benefit that whatever the threshold they 
            set for their time, their Inbox rate, that gets credited to them, 
            but if it*s their long lost brother or somebody saying their house 
            is on fire, hopefully they won*t debit that, they*ll say, okay, that 
            was just at risk and I*m glad that person connected up to me.
            In the home environment, when we think about media and memory, 
            there is so much that can be done and yet we*re going to have to 
            deal with a lot of volume. All the music you like, all the movies 
            that you*re interested in, all those photos that you take, it*s kind 
            of amazing. 
            We have a researcher at Microsoft Research who wears as she goes 
            around in the day something that*s just a camera, and it notices 
            when there*s a big scene change or when there are people laughing or 
            anything loud or something, and it takes photos. And so at the end 
            of the day that researcher has over a hundred photos that might be 
            interesting to put in her journal and save and even annotate with 
            some voice or something. But software has got to help select which 
            one of those things are interesting and to navigate amongst those 
            things. And so there is a lot that has to be done on that.
            We want to put users in control in the home. This idea of 
            watching TV shows only on a schedule, slowly but surely that*s going 
            away. People who use that, whether it*s built into what we call the 
            Media Center PC or a TiVo or the satellite receiver, get very 
            addicted to it. It*s kind of like e-mail where you know it*s not 
            perfect, but you don*t want to give it up; you just want it to get 
            better. 
            And so as we think about that, we think about what kind of 
            interfaces would deliver on that. In fact, I*ve got just real 
            quickly a couple prototypes from Microsoft Research I wanted to give 
            you just a sense of this. In fact, these were both done by an MIT 
            graduate.
            The first one here is pretty straightforward. Let*s say you*re 
            looking at movies, you*re looking at "Blade Runner" here and what it 
            shows is, okay, the director is Ridley Scott. Well, then I can go 
            over here and see other movies directed by Ridley Scott and I can 
            just select one of those, "Alien," that*s brought to the center and, 
            of course, then all the things related to that come out and I can 
            see, okay, these actors and see the different things they were in 
            and see if one of those might be interesting and just pivot through 
            these sets of movies in a simple digital way.
            Of course, this will be annotated with the reviews that you 
            trust, comments from friends, if you*ve seen the movie what you 
            thought about it, and so very navigable to get around the movies of 
            interest.
            The other one I wanted to show has to do with photos. In photos 
            we*re dealing with lots and lots of photos, literally, if you take 
            your lifetime, tens of thousands of photos that you and your friends 
            are sharing and you*d like to be able to get back to in a rich 
            way.
            And so here we see them as miniatures. I can just hover over 
            these things, lots of photos. We*ve even mixed in video clips as 
            well. Here is Gordon Bell at the computer museum. Because we don*t 
            think the boundary between stills and motion will hold up. In fact, 
            these audio comments that we call Photo Stories bring a lot more 
            emotional connection to that experience.
            And so when it*s just like this it*s hard to find exactly what 
            you want. And so people will tag these things with keywords. Here 
            are things that relate to Thanksgiving. We can do software analysis 
            and so if we want the photos with faces, we just select those. If we 
            want the photos that are indoors, the software can select those. If 
            we want the outdoor photos, we can select those. If we want to see 
            photos that are similar, let*s select this bridge photo and say, OK, 
            I can relax the constraint and say what*s similar to that. OK, 
            that*s a lot like it, that*s a little bit more like it and I can 
            select groups of things to be used.
            This software automatically when it brought the photos in helped 
            orient the photo by being able to recognize the cases where things 
            were kind of, at least to the software looked like they might be 
            misoriented.
            We can also start to use a 3-D way of looking at these things, to 
            group these things, and what that means is now this by timeline so I 
            can select this set and tag these, I can change the timeline and get 
            to finer groups in terms of when they were taken or where they were 
            taken, and this makes it very easy to just step through these but 
            also deal with groups that I want to organize and tag in different 
            ways.
            So in a general sense we can say, well, that*s just a database 
            but we need much better ways of interacting with the database than 
            just the common query processor. People won*t be writing SQL 
            statements to navigate through their photos.
            Now, this optimism I have about computer science and its impact, 
            a little bit the proof of how serious we are about that is the 
            R&D spending that has been increasing at Microsoft. Today, it*s 
            $6.8 billion a year, kind of an intimidating number, at least to me 
            since 10 years from now people will say to me whether that was wise 
            or not, but I*m quite confident that it is. That*s the largest 
            technology R&D budget that there is. IBM is about 20-percent 
            less than that, but, of course, it*s not all focused on software, 
            and then other commercial entities you*d have a big drop down, 
            particularly if you take the long-term components, the equivalent of 
            Microsoft Research.
            We actually do our research work in three different locations, in 
            Cambridge and in our headquarters, and in Beijing. We have smaller 
            groups in some other areas but those are the primary areas.
            We*ve had, as I mentioned earlier, a strong collaboration on a 
            number of things with MIT. For example, the iCampus project, we*re a 
            key partner in that. I*m thrilled at the things that are coming out 
            of that. Some involve learning at a distance, some involve the 
            Tablet PC. The idea that we can make learning better there*s no 
            doubt and I think that*s a great pioneering project.
            Natural interfaces for learning, that*s this magic paper idea. 
            That*s a fantastic thing.
            We*ve gotten involved in things that think. We*ve got a lot of 
            people on the faculty here that are helping drive our agenda. For 
            example, Victor Hsu is on the technical advisory board for our group 
            over in Beijing.
            So it*s been a good, strong relationship and the progress being 
            made in the combination of academia and commercial research labs is 
            really fascinating. It*s phenomenal and it*s not getting that much 
            visibility, and yet these advances are extremely relevant to 
            problems that we have, the problems that are of critical 
            importance.
            Take, for example, security. Of course, MIT has a strong program 
            on that. Of course, you*ve got Professor Rivest, who just got the 
            Turing Award, which is a fantastic thing. Security is something that 
            if we*re going to achieve the potential of these systems has to get 
            a lot better. And that*s a tough thing, because code reliability 
            gets into that, how you configure up these systems, how you watch 
            behavior as part of that, so it*s going to take some 
            breakthroughs.
            Over 25 years ago, when I was leaving Harvard, this idea of 
            proving program correctness was sort of in vogue. And unfortunately 
            for many years, although there was some progress, that scale of the 
            program it could be applied against didn*t get very large, hundreds 
            of lines of code.
            Now, working with universities, people in Microsoft Research are 
            taking literally things that are a million lines of code and being 
            able to go in and prove very important things about those programs. 
            Or if they can*t prove them, they*re able to show the counter 
            example that says, yes, this can touch memory that it shouldn*t 
            touch or it can acquire the lock and never release a lock. And so 
            you see exactly what the pattern is and how to fix that.
            Now, all this proving technology is having a wonderful effect on 
            innovation in programming languages, because we want to take 
            everything that the programmer knows about the data types and the 
            constraints and express those in as high a level, as strong a 
            fashion as we can through contracts. And this idea of contracts very 
            easily, having languages that are very explicit about those things, 
            that takes all the theory of language innovation and brings it into 
            the mainstream and says we really need those capabilities.
            Keeping systems up to date, being able to look at a system and 
            say is this behavior normal, we need this both at the single 
            computer level and looking at the network, is there a type of 
            traffic that*s exploded in terms of usage at a time where the 
            overall traffic is starting to be too heavy for the network to deal 
            with. There should be automatic tools out there that are doing that. 
            And, in fact, machine learning techniques that build the model of 
            typical behavior and then see these things that are unusual will be 
            used at every level of the system, at the memory management level, 
            at the API level, at the network level and at the wide networking 
            monitoring level. We call that behavior blocking and that will be a 
            critical component in solving those security issues.
            Another set of areas that I think are making wonderful progress 
            are getting a more natural interface between users and the computer. 
            Victor Hsu here has been a big advocate of that, building some 
            wonderful systems that take speech all the way up into particular 
            domains and lets people interact with those. And making it so that 
            it*s not a huge technical exercise to build one of those systems, 
            that you just have a general runtime for that, I think is something 
            that will be solved in the years ahead.
            The progress in speech recognition is very good. If you take an 
            isolated, simplistic case where there*s no context and no noise and 
            a perfect microphone, three great simplifications, the difference 
            between a human and a computer is not very drastic. It*s as we relax 
            those constraints and bring in context, crummy microphones and noise 
            that then the divergence between the computer and the human is quite 
            substantial.
            And, of course, human users of these things are very demanding. 
            Because speech doesn*t operate at a conscious level, as it makes 
            mistakes you just get irritated and talk louder. And, of course, 
            it*s been trained, it*s learned you*re speaking in normal tones, so 
            it just gets worse and worse and so it just degenerates while you*re 
            yelling at the system.
            Now, ink is not quite the same. It*s a little easier because you 
            process ink at a conscious level. And so although it*s irritating 
            when it doesn*t work, you can look and say, well, hmm, could I have 
            recognized that, is that E looped so closely that it looks like a C, 
            and, in fact, as we monitor people using our handwriting system, the 
            plasticity is partly in our subsystem but a lot of it is in the 
            user, that the user consciously or subconsciously is actually 
            writing more explicitly the features that have caused the problem in 
            the past. So that*s partly why ink is coming into the mainstream, 
            say, a few years in terms of general input, the equivalent of 
            dictation a little bit faster.
            The place where we*re seeing our speech work really catch on is a 
            combination of people where the keyboard is unattractive for them 
            for any reason, including repetitive stress injury, or people in 
            China, Japan or Korea where the keyboard is relatively less 
            effective as an input technique. We can already beat the fastest 
            typist of Chinese with a Chinese speech recognition system. And so 
            that*s a milestone along the way that is pretty exciting.
            General artificial intelligence, this is the Holy Grail, and when 
            I was talking to the faculty today I was impressed that MIT has kept 
            its commitment to this area throughout all the years. It is one 
            where some very interesting approaches, statistical approaches, 
            Bayesian approaches all are now starting to be used in different 
            fashions.
            The actual product on the market that apparently is a spin-off 
            related to a professor here is the thing that goes around and 
            vacuums the rug, and that*s pretty low level, better than nothing 
            but we want to move up in terms of the things that go on.
            For gaming, one place we*re using our machine-learning technology 
            a lot is we on Xbox Live can watch player behavior in different 
            strategies and the machine can learn. And so if you want to pick an 
            opponent, typically if you play the computer historically it*s an 
            algorithm that isn*t that much fun to play because eventually you 
            see that as being very predictable. We can take all the play styles 
            that we*re seeing across this network and create any sort of level 
            of difficulty or different fashion of play and make it as 
            interesting and as varied as playing with human opponents, including 
            letting you win every once in a while, which on videogames for me 
            that is pretty tough. You pick these things up and they are geared 
            to, well, to you and not to people who haven*t used them nearly as 
            much. And so we*ll make these things appeal and even if you start to 
            beat the system, boy, we*ll crank that up to a level that will keep 
            it challenging.
            So AI is going to be applied in a lot of different ways, modeling 
            things in the other sciences, helping with dynamic behavior in 
            systems, very, very important.
            All the natural interface techniques -- vision, speech -- we*ll 
            come to take those for granted in a very strong way.
            Now, the boundary between computer science and the other sciences 
            historically was a fairly hard boundary, and that is breaking down. 
            One great example of that is the research we have of Jim Gray, who 
            looked at astronomy and said, boy, there*s a lot of data there and a 
            lot of the advances come in proposing something that you can either 
            validate by looking at that data or invalidate. And so we really 
            need to get all these databases connected together.
            And the semantics are very high level. It*s again not just a 
            relational problem. But collaborating with a lot of astronomers who 
            know the domain, he*s been hooking up those databases and now 
            navigating through this logically connected database is a very 
            important tool in astronomy. And many of the sciences are going to 
            where those rich data collections are necessary for everyone to have 
            access to in a high level way.
            Biology, of course, is perhaps one of the most challenging 
            because of the breadth and the differences in the data, but even 
            there this is starting to happen and I had a great discussion with 
            some of the faculty who are pushing off in that direction and really 
            seeing that the boundary of computer science and biology are very 
            much coming together and we need people who understand both of those 
            things to make advances in solving diseases. And I*m very optimistic 
            about how fast that will move forward.
            Now, this tool that we*ve got, the PC connected to the Internet, 
            all this great empowerment, it*s such an important thing that we do 
            have to worry that there are people who are benefiting from this and 
            people who are not, and people talk about that as the Digital 
            Divide. It*s something that I think people in computer science 
            should care a lot about and in various ways contribute to trying to 
            minimize that difference.
            One of the projects that Microsoft got involved with, together 
            with my foundation, was saying, well, what about libraries, would it 
            be appropriate to have computers there. And we were a little worried 
            about this because would the librarian like it, would it be at 
            expense of the books, would kids come in and just hack up the 
            machines, would they be doing enriching things as they were using 
            those computers; it was unclear. But six years ago we kicked it off, 
            we did pilot projects and over six years in all 50 states in 18,000 
            libraries, rural, everywhere in the country, we put in over 50,000 
            computers. And the response of librarians was just phenomenal of 
            wanting to be trained, wanting to reinforce the role of that 
            library, and traffic to the library increased, not just to come use 
            the computer but also the number of books that were being lent out. 
            And we were able to monitor and support all these things in a very 
            efficient way that made it work very well.
            Throughout the project we learned things. We came up with a 
            version of the software you can just hit a button to switch from 
            Spanish to English for a lot of these libraries. We had a button you 
            can just hit to switch to big print so if you don*t like reading the 
            font that we typically use, boom, all of a sudden it*s a lot better. 
            We came up with things to help people with the common scenarios. 

            And so it*s great to see if you give people those tools they*ll 
            use them and it really makes a big difference for them.
            Getting these tools out to schools, getting them out to all 
            different countries, a lot of challenges remain there that need to 
            be addressed.
            When we think about computer science, one thing computer science 
            has done through the Internet, through software has made the world a 
            smaller place. In fact, people now worry that this is going to 
            create a new level of global competition. And the answer is it is. 
            People*s opportunity to have great jobs in the future will be far 
            more determined by their level of education than by what country 
            they happen to be in. Historically, your educational level didn*t 
            matter that much. If you were in a rich country you made a lot of 
            money, and if you were in a poor country you made very little money. 
            Now the opportunity for educated people worldwide to help out, to 
            contribute to products, not just software products but anything you 
            can imagine, architecture, law, answering the phone, it will be done 
            where people have those skills.
            And as people look at that, they go, wow, what does that mean? 
            Well, it means the U.S. has to keep its edge in terms of doing the 
            best work and that means research, it means intellectual property, 
            it means improving the education system, rededication.
            It*s very similar to what happened in the 1980s when there was a 
            lot of angst about Japan. Japan at the time appeared to have a model 
            where they would just pick an industry, the car industry, the 
            computer industry, the consumer electronics industry and boom they 
            would do it better. 
            And the great thing that happened in the *80s was there was a lot 
            of humility, a lot of thinking, well, do we just match what they do 
            exactly that way or do we just push forward on our strengths, our 
            approach to things.
            During the *80s they did this AI project and it really because of 
            the way it was done it wasn*t done with a diverse academic approach 
            that we use here, it really ended up not generating much.
            So we rededicated ourselves and it was actually the work done 
            during that period that led to that productivity increase that 
            benefited all countries but the U.S. in particular during the 1990s. 
            I see that same thing repeating itself as we question our unique 
            role and reinforce what needs to be done.
            One challenge that we have in the field, in all science fields 
            but particularly in computer science is the issue of diversity. To 
            do the best work we want to draw on everybody*s talent and give 
            everybody a deep involvement. The variety of jobs, the need for 
            great people is pretty phenomenal. And the diversity numbers in some 
            professions like law and medicine have been going pretty strongly in 
            the favorable direction.
            One thing I personally have gotten involved with to try and help 
            push this forward is a scholarship program that*s called the Gates 
            Millennium Scholarship. And here at MIT, out of actually a thousand 
            people who get those scholarships, 60 people are here at MIT, so 
            it*s a great thing and a real endorsement of MIT that there are more 
            Gates scholars at this school than at any other school.
            These science problems are tough but they*re fun to work on. The 
            jobs that are involved with them, you can have an impact, you can 
            work with other people, it*s not just somebody isolated off coding 
            all night, although if you want to do that, that*s fine, we still 
            have lots of jobs that are like that.
            And so the sense of reward of being involved in changing 
            business, changing entertainment, changing education, giving tools 
            to those new sciences, including to help with disease, I think 
            that*s a phenomenal opportunity. So that*s why I*m more excited 
            about computer science than ever and I*m very excited to see what 
            some of you here can do, taking that to the next level.
            Thank you. (Applause.)

Instituto de Tecnología de Massachusetts (en inglés, Massachusetts Institute of Technology, MIT), una de las principales universidades de investigación del mundo, situada en Cambridge (Massachusetts, Estados Unidos). El MIT fue inaugurado en Boston en 1865 por el geólogo William Barton Rogers, que se convertiría en su primer presidente. En un principio sólo se estudiaban las ciencias industriales, pero el MIT ha pasado a convertirse en un conjunto de cinco centros que ofrecen estudios tanto de licenciatura como de posgrado. En ciencias se ofrecen carreras de Biología, Química, Matemáticas y Física, así como Ciencias planetarias, atmosféricas y de la tierra. Igualmente ofrece carreras en todos los campos de la ingeniería, además de aeronáutica y astronáutica. La Escuela de Arquitectura ofrece, además de los estudios propios del Centro, programas de artes y ciencias de la comunicación, así como planificación y estudios urbanísticos. La Facultad de Empresariales Alfred P. Sloan se ha especializado en ciencias empresariales, combinando disciplinas fundamentales con estudios cuantitativos. La Facultad de Humanidades y Ciencias Sociales ofrece carreras de Economía, Humanidades, Lingüística, Filosofía, Ciencias políticas, Tecnología y Sociología. El MIT y la Institución Oceanográfica de Woods Hole ofrecen de forma conjunta programas de posgrado en Oceanografía e Ingeniería oceánica. Durante toda su historia, el MIT ha mantenido su fama mundial por la calidad de la enseñanza y la investigación. Fue uno de los primeros centros que aplicaron el método de enseñanza por medio del laboratorio, que desarrollaron la moderna profesión de ingeniería química y que ofrecieron estudios en ingeniería aeronáutica y eléctrica, y en física aplicada. En la actualidad, sus instalaciones especiales incluyen cinco aceleradores de partículas, un reactor nuclear, y más de 70 programas y laboratorios interdisciplinarios, incluidos el Centro para la Investigación del Cáncer, el Laboratorio de Informática, el Centro de Estudios Internacionales, el Laboratorio de Medios de Comunicación, el Laboratorio para la Investigación de la Electrónica, el Centro para la Ciencia Cognitiva y el Centro de Investigación de Servicios Financieros Internacionales. La editorial del MIT lleva a cabo un activo programa de publicaciones y es conocida sobre todo por sus libros de teoría lingüística, ciencias, arquitectura y estudios urbanísticos.