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 Before I introduce him, I would like to remind you that computing 
            is deeply embedded in the culture of this campus, and we are proud 
            to say we have maintained our edge. Our students, faculty and staff 
            enjoy more than 47,000 network connections by which we connect to 
            the world, and people connect to us. More than 1 million times a 
            week, people log on to the online catalogue of the University of 
            Illinois Library, which is the third, only to Harvard and Yale, in 
            size of its collection. And this campus is a giant in research and 
            development in science and engineering. We have more than 80 
            centers, labs, and institutes where important, life-altering work is 
            underway. Among them is the widely known National Center for 
            Supercomputing Applications, which is helping to build the future of 
            high performance cyber infrastructure. And this new office here at 
            the far edge of the campus is the Beckman Institute for Science and 
            Technology where 600 researchers collaborate, and finally I would be 
            remiss not to mention the investments in R&D brought to the 
            happy place of having two of our faculty members win Nobel 
            Prizes.
            (Applause.)
            As you know, they are Paul Lauterbur, who was awarded the Nobel 
            Prize in Medicine for his ground breaking work on the MRI, and Tony 
            Leggett, Nobel Prize winner for pioneering theoretical work in 
            understanding super fluid.
            But that*s enough about us, it*s time that we move on to our 
            guests this evening. You are here to see Bill Gates, the Chairman 
            and Chief Software Architect of Microsoft Corporation. As you know, 
            Microsoft is the worldwide leader in software, services, and 
            Internet technology for personal and business computing. Last year*s 
            revenues topped $32 billion, and the company employed 55,000 people 
            in 85 countries. And Mr. Gates is an iconic figure in contemporary 
            computing.
            While attending Harvard, Bill Gates and his childhood friend Paul 
            Allen started Microsoft, and launched a revolution. The fledgling 
            company was more interesting than the classroom for Bill Gates, so 
            he dropped out in his junior year. In his case, it was clearly a 
            great decision. He not only built a company, but more importantly he 
            built a vision. Both were built on the idea that the computer would 
            be a valuable tool on every office desk, in every home, and that 
            software was key. The penetration of personal computing in our 
            businesses, our offices, our public libraries, on the train or on 
            the plane, and in our home is astonishing, and truly reflects the 
            Bill Gates* view that if the software is right, they will come.
            Bill Gates also is an author of two books. One of them, Business 
            at the Speed of Thought, is available in 60 nations and 25 
            languages. It shows how computer technology can solve business 
            problems in fundamentally new ways. By the way, the proceeds of both 
            books are donated to nonprofits that support the use of technology 
            in education and skill development.
            Since he is a man on the edge, it makes sense that Bill Gates 
            also has invested in biotechnology, one of the most exciting 
            frontiers in science, and you probably have heard that he and his 
            wife Melinda have endowed a foundation with $24 billion. Their 
            generosity extends to global health, technology for public libraries 
            that serve low income neighborhoods in the U.S. and Canada, and a 
            variety of other community and special projects. He*s an avid 
            reader, a golfer, and a bridge player. He is a household name, a 
            visionary, a philanthropist, and tonight he is our guest. So please 
            join me in giving an Illinois welcome to William H. "Bill" 
Gates.
            (Applause.)
            <B>BILL GATES:</B> Thank you. It*s great to be here this evening. 
            They told me I couldn*t come too early in the morning or the 
            computer science students wouldn*t be up to hear what I had to 
            say.
            I want to share some of the exciting things that are going to 
            happen in computer science, and how that*s going to change the world 
            in a pretty profound way. Computer science has done a lot over these 
            last 25 years, but I would say that the most exciting years are the 
            years ahead, and there*s amazing opportunities for all of you in 
            contributing to that.
            It*s great to be here in this particular location. The University 
            of Illinois has a great history of contributing to engineering and 
            the sciences, and actually this is the university that Microsoft 
            hires the most computer science graduates from of any university in 
            the entire world.
            (Applause.)
            I*m always a tiny bit embarrassed speaking in university groups, 
            because I, myself, am a dropout, but I*m not here to spread the word 
            about becoming a dropout. In fact, quite the opposite. I*m going to 
            talk a little bit about how computing got to where we are today. The 
            early days of computing were very big machines, and although they 
            were visionaries like Vannevar Bush, who as long ago as 1945 wrote 
            about the Memex machine. Most people thought of them as tools of 
            large organizations, and certainly when I was in high school the 
            computer was a very daunting thing, people talked about taking those 
            punch cards you get in the mail and putting staples in them so you 
            could defeat that evil machine that was always sending you bills 
            that didn*t seem to be correct. And nobody thought of it as a tool 
            of empowerment.
            It really took an amazing breakthrough in chip technology, the 
            idea of putting at first thousands, and eventually millions, and in 
            the future billions, of transistors on a single chip to get this 
            idea that computers could become a tool for the individual. I think 
            it*s fair to say that personal computers have become the most 
            empowering tool we*ve ever created. They*re tools of communication, 
            they*re tools of creativity, and they can be shaped by their user. 
            New applications are coming out all the time. Now there*s a few key 
            elements that allowed that to happen. From a software point of view, 
            one of the problems in computing was that the machines from every 
            different manufacturer were incompatible. IBM made different 
            machines than Digital Equipment, which were different than NCR or 
            Wang, or UNIVAC, or all the big computer companies of the 1960s and 
            1970s.
            One of the unique things that Microsoft, myself and Paul Allen, 
            had in mind was that we wanted to have a software layer that would 
            hide the hardware differences, and allowed people to invest in 
            software applications, knowing that they could be used across all 
            those machines. In fact, the goal was to create this virtuous cycle 
            that, as more applications became available, people would be these 
            machines, and, as more people bought them, the economies of scale 
            would allow the prices to come down, creating a thriving personal 
            computer and software business. That was our dream, and that was the 
            thing that got me to leave university and start the company. And 
            it*s a dream that to some degree came true. Today 600 million people 
            get up every day and have personal computers that they use in a very 
            rich way.
            There are still a lot of milestones in that progression. The very 
            first machine, the Altair, was a kid computer that could only light 
            up the lights, it was a miracle if you could even program it to do 
            that much. Then there was a generation of computers like the 
            Commodore 64, the Apple II, the TRS-80, and Microsoft wrote the 
            software which was inside those machines. It was actually a 
            programming language called Basic that let you get in and play 
            around a little bit with the graphics, and write applications.
            A major step took place as we moved to larger memory machines in 
            the early *80s, the so-called IBM personal computers with MS-DOS. 
            That machine by today*s standards is unbelievably primitive, slow, 
            very limited storage, but it really created the path for this 
            virtuous cycle to take place. It was in the early 1990s that we 
            moved up to graphical machines. This was an approach, of course, 
            that was pioneered at Xerox*s Palo Alto Research Center. And then 
            Apple, with both their Lisa and Macintosh got behind it. We got 
            behind it, putting Windows software on top of the PC hardware. It*s 
            hard to remember now, but when that was done it was considered a 
            crazy thing. People thought graphics interface was slow, it was hard 
            to program to. And of course, today we take that completely for 
            granted.
            The late 1990s were another step change in how we think of these 
            machines, because that*s when they all began to be connected 
            together. The standards of the Internet, the pioneering work done 
            here on the browser as a way of visualizing the information across 
            the entire Internet. Those things created a phenomenon that was 
            quite unbelievable, and a phenomenon that created almost a Gold Rush 
            atmosphere. The number of start ups, as we look back on it, was 
            pretty wild. The valuations of companies that had no business model 
            was pretty wild. But, in a sense that hyper-investment, and that 
            attention all accelerated the installations of the connections, and 
            getting people aware that there was something pretty phenomenal 
            going on here.
            Today I think we very much take it for granted. Certainly when I 
            want to look up what*s new in some area of science, medicine, I want 
            to look up something about history, I just take it for granted that 
            I can go and type in a few simple search terms, and immediately be 
            connected up with the information that comes from the very best 
            experts in the world. So we*ve come along way.
            In fact, the original Microsoft vision of a personal computer in 
            every home, and on every desk, we*ve gotten a trajectory that*s 
            going to get us there. The systems we have today are not the 
            ultimate device. They*re not as reliable as we need. They*re not as 
            secure as we need. They*re not as easy to use as we need. In fact, 
            we have a technology that we call Watson that lets us monitor, if 
            people are willing to send us the reports, when you get error 
            conditions on PCs. Maybe some of you have seen that dialogue that 
            comes up and says, do you want to send this report in, and that 
            gives us a very statistical view of what drivers, what applications, 
            what*s going on in terms of that user experience. So it*s one source 
            of data that says to us that we have a long way to go to achieve the 
            vision of the personal computer that*s as easy as it should be.
            At the same time, people are far more ambitious about what 
            they*re doing with these machines. We have a whole new area called 
            social computing, the idea of being able to reach out, connect with 
            friends, meet new people, and ways that*s taking place. We have new 
            forms of communication, so-called blogging, and Wikis that are 
            drawing people in to participate in new ways. In the area of 
            entertainment this idea that you can play games with your friends, 
            have massive multiplayer games, not just play but also talk to them, 
            in some cases see them, those things are bootstrapped now, and 
            eventually we*ll just take those for granted.
            One of the things that helps us drive forward is that hardware 
            advance. The chip advance, as predicted by Moore*s Law that says 
            you*ll have a doubling in power every two years. And that has held 
            true for these last 25 years. And it looks like it will hold true 
            for the next 10 to 15 years. Actually mapping that increase in 
            transistors into computer performance turns out to be a very tough 
            problem. As we get more transistors and very high bandwidth, we*re 
            still limited by the actual delay in these systems that*s at every 
            level of the hierarchy. It is very much a limiting factor, and 
            there*s a lot of clever things we*re going to have to do on this. 
            But, certainly we*ll have a lot of transistors.
            The graphics processing units, the CPUs, all of these things are 
            becoming phenomenally effective. We have 64-bit computing that will 
            give us an address space that will last us quite a long time, moving 
            up from the 32-bit address space.
            And when we think of storage, the limitations of the past where 
            you could literally type and fill up a hard disk, that simply can*t 
            be done now. In fact, the hard disks that you*ll have by the end of 
            this decade, you*ll be able to store thousands of movies, tens of 
            thousands of photos, and everything you create in terms of typing 
            your entire lifetime on that single storage device.
            That third path is going up even faster than chip performance. 
            Those double every 14 months or so, and they*re literally coming to 
            software companies and saying, what are we going to do with all this 
            storage? What kind of applications, what things can you create that 
            would take advantage of that?
            Screen technology is another very key factor. We eventually need 
            screens that have unbelievably high resolution. There*s no reason 
            that things like magazines and newspapers should be delivered in 
            paper form. The cost, the inability to search, to annotate, the fact 
            that it*s not completely up to date, all those things are much 
            superior in digital form. But, our systems still require batteries, 
            and they*re still fairly heavy, the resolution is still improving. 
            But where we*ll be in a few years at a crossover point where most 
            consumption of media will move to that pure digital form, partly 
            because of these low-cost LCD screens. A 20-inch LCD, which used to 
            be a $2,000 thing, is coming down, will be down to $400 or $500 
            price point within three to four years.
            And so, we have to think about how we take all that display space 
            and resolution and use it on behalf of the user. And so you have to 
            be fairly adaptive because the display space you*ll have at your 
            desktop will be much greater than you*ll have as you*re moving 
            around. The tablet type machine that you carry simply won*t have 
            that same display surface, although at some point we may get screens 
            that literally go back to the papyrus where you can unroll them, and 
            then we can get back to having really big screens anywhere that we 
            go.
            And then to graphics processors, those are achieving a level of 
            performance that will let us provide high definition realism as part 
            of a serious software activity, or just as part of the 
            communications or game playing. The next generation of video games 
            will be thought of as the high definition devices, including 
            realistic scene that are already pretty good on today*s Playstation 
            2 or Xbox. There*s more than an order-of-magnitude improvement that 
            comes in that generation, and is therefore at a level of reality 
            that will draw people in, and allow for game genres that really 
            haven*t made sense to this point.
            All of these things will be connected with very high performance 
            wireless networks, you*re experimenting with this in the Siebel 
            Center, I know, but things like ultra wideband will provide hundreds 
            of megabits of connection. And so the idea that you have to connect 
            the computer up to the display, that will be very antiquated, you 
            will connect up to the display simply over that wireless 
            connection.
            And various new approaches like Wi-Max will let us deliver 
            wireless data in a very low-cost way without building a lot of 
            infrastructure. That*s fundamentally important to get computing out 
            into all countries, where you can*t afford to run fiber optics, or 
            DSL, or cable-modem type infrastructure into all the residences, but 
            these wireless technologies, taking advantage of semiconductor 
            advance in the spectrum will give us essentially infinite spectrum 
            to those homes at very, very low cost. And so that*s a breakthrough 
            that we*re just taking for granted in designing in to the 
            assumptions we have about the software.
            There will be devices of all sizes. The screen that*s up on the 
            wall in a meeting room or in the living room in the house, that*s 
            your largest way of interacting. You do that at a distance. I 
            mentioned the desktop, I mentioned the Tablet. Of course, the 
            pocket-sized devices are getting far more powerful as well and the 
            idea that your digital wallet, GPS locator and games and personal 
            information will be there, together with your communications 
            functionality, we*ll just take that absolutely for granted.
            We*ve even moved to a device size somewhat smaller than that. 
            We*ve come out with actually a watch that I have on here. This is 
            called the SPOT watch. And what this does is it receives a data 
            signal over the FM network. It*s a data-sideband approach. And so as 
            I just look at my watch, not only do I see the time, but I see my 
            calendar that*s kept up to date, I see news, I see weather, stock 
            prices. I get instant messages from people that I*ve authorized to 
            send me information right there on my wrist. Sports games, you can 
            see while they*re in progress who*s on base, what*s going on, and 
            then get the report on anything that you*re interested in.
            And the chip that*s in here, which is an ARM microprocessor, has 
            10 times the performance and 10 times the memory of the original IBM 
            personal computer. And so we can literally download programs into 
            this device over the FM channel, we take what are called CLR 
            programs and send them to this thing and so we can always create new 
            channels, new ways of gathering information and it*s ubiquitous and 
            secure.
            And so scaling on to all these devices and getting them to work 
            together, so your information shows up where you want and you don*t 
            have to manually synch these things or think about the information 
            mismatches, those are big challenges and those are software 
            challenges.
            In fact, software is where the action is. I admit to some bias in 
            this, but I think even objectively the hardware people are doing 
            their jobs, they are going to give us the miracle opportunities, but 
            will it be usable, will it be secure, will it be fun and exciting 
            and approachable? That is purely something that the software 
            industry needs to deliver on.
            Let*s look at different domains where software can help us be 
            more effective. First, let*s take people at work. People at work 
            overwhelmingly are what we call information workers, designing new 
            products, dealing with customer service, forecasting demand, buying 
            and selling. Those are the kinds of jobs that overwhelmingly in 
            developed economies are the vast majority of people.
            And competition exists in terms of how effectively you do those 
            jobs. Do you design a new model properly? Do you anticipate the 
            demand? Do you understand the least cost way of getting something 
            done? Do you see where your quality problems are? And the insights 
            into those things can be provided through software.
            The lack of visibility of what*s going on and all the information 
            about a business that people have today is really quite unbelievable 
            and they don*t have the expectation that they should be able to look 
            at all those transactions and data mine the transactions and 
            navigate the latest information.
            But software can change that. Visualization techniques, modeling 
            techniques, even things that you might think of mundane, saying 
            that, hey, when you have a meeting let*s make that meeting 20 
            percent more efficient, let*s allow people who aren*t physically 
            present to participate in a very rich way. When you have a phone 
            call, why can*t you just connect your screen up to their screen so 
            instead of talking about a budget or a plan or whatever the 
            information is, you can sit there and edit that together?
            The very mechanism of capitalism, finding buyers and sellers, 
            there was a lot of hype in the late 1990s about how that would 
            change and become friction free, but, in fact, the software 
            infrastructure was not present. The idea of having software anywhere 
            on the planet being able to find other relevant software and 
            exchange very complex information, we didn*t have the protocols, 
            standards and tools to make that work.
            So as we connected up things to the Internet, we connected them 
            up with a presentation standard, HTML, but the idea of arbitrary 
            software, no matter what the application is, but take buying and 
            selling as a good example of it, we don*t have that today. And with 
            the challenges of security and things, that*s not an easy thing but 
            it is being built. 
            These are called the Web services standards, and they*re 
            fundamental to letting information be exchanged in a rich way. They 
            fulfill a dream of computer science that existed for a long time, 
            dreams about heterogeneous information, that the advances in XML are 
            finally solving those very tough problems.
            And so within the next year, as that foundation gets into place, 
            a lot of those dreams of the late 1990s will become a reality. The 
            cost of a transaction, the cost of finding who can well you the 
            product that is absolutely the most suitable and check their 
            reputation and check the state of that transaction, all of those 
            things will move to be digital, and that hasn*t happened yet but 
            with the software advance that will absolutely take place.
            People waste a lot of time on various communications modalities. 
            Today software doesn*t know which calls or e-mails are important to 
            you. We*ve all been in meetings where peoples* cell phones ring. 
            We*ve all gone to our e-mail and found lots of unusual, unwanted 
            e-mail that wastes our time. I have been offered many university 
            degrees in that spam e-mail. (Laughter.) I don*t know if they*re 
            targeting me or if other people are being offered those as well. The 
            most interesting ones, they said that for dollars a month they would 
            pay all my legal bills. (Laughter, applause.) That one, I know they 
            didn*t mean it to come to me probably. (Laughter.)
            Another good story about that is just this weekend my wife and I 
            were sleeping in a little bit. Our 7-year old came in and woke us up 
            and said, "You*ve got to come, you*ve got to come." And we said, 
            "No, no, no, it*s still 7 o*clock, why don*t you go back and keep  
            doing what you were doing?" And she said, "Well, I was using the 
            computer and it*s "amazing. And I said, "Well, keep using "it.  
            (Laughter.) And she said, "No, no, no, we won, we won money, dad." 
            (Laughter.) And I didn*t want to say something flip, like, "Hey, we  
            don*t need more "money. (Laughter, applause.) So I got up and, of  
            course, it was one of those come-on type things, and there*s my 
            7-year old who thinks she*s won some amazing contest, and I*m trying 
            to explain to her about it*s just somebody trying to get her to go 
            to that website and all that.
            So we have a lot of work to have the computer model our 
            interests, what is worth interrupting us for at various contexts 
            we*re in during the day, what kind of e-mails should we see no 
            matter what*s going on, what should only be brought to our attention 
            as we go home. 
            How do we organize our tasks? Think about all the different 
            things you want to get done; the computer is not very good at 
            helping to organize those things, notifying us about deadlines.
            Literally take phone calls today. If you call somebody and 
            they*re not available, if you can prove who you are through some 
            caller-ID-type mechanism, if you*re a person who works with that 
            other person, their software ought to negotiate with you, looking at 
            your schedule, to find exactly the best time for you to meet or be 
            in touch with each other, and the idea of phone tag or busy signals 
            and those things should really become a thing of the past. But we 
            need a software model. We need something that*s adaptive, that 
            learns, that has the right authentication built underneath.
            And we have far too many communications things: e-mail, phone 
            and, even phones, we have our phone at home, we have the portable 
            phone. The fact that we have to remember phone numbers and update 
            those things, the instant messaging is a world of its own; all of 
            those things really have to come together and help people and make 
            people far more productive.
            In terms of things that people do at home, we are at the 
            beginning of a revolution in terms of people being in control, 
            control of when they want to watch a TV show that the digital video 
            recorder is now getting people addicted to this idea that it*s up to 
            them to decide when they want to do it. People are getting addicted 
            to the idea that, in terms of their music, they can organize their 
            collection and have different play lists, that they can have a 
            portable device that they take with them that lets them play that 
            music.
            We*re even getting to the point now where we can take videos and 
            put those on a portable device.
            This is a little device called the Portable Media Center. You can 
            see the basic size of it and that shows what comes up on the screen. 
            You connect this to your PC over a wireless or a USB cable and you 
            can take whatever TV shows you recorded, your movies, your pictures 
            and all of those things can be downloaded onto this hard disk. It*s 
            a 40-gig hard disk, which, of course, is becoming unbelievably 
            inexpensive, and then relative to a music player the only extra 
            expense is just having this LCD screen, where that too is becoming 
            quite inexpensive.
            And so this is a different way of thinking about consuming media, 
            putting the person in control, having it wherever you want it, 
            having your lifetime collection easy for you to get at and work 
            with.
            And as people have all this different media, we need to make it 
            easy for them to navigate around in this information.
            I*ve just got two little quick demos that are ideas coming out of 
            Microsoft Research that give a sense of how we think visualization 
            can be made a lot better than it is today. The first screen I*ve got 
            here is to help you look at a set of movies or a movie collection. 
            And so at the center we have a particular movie, "Blade Runner," and 
            you can see that off on the side here it takes things that are 
            related in some way, like everything that*s directed by Ridley 
            Scott, it shows and I can go in and cycle through at any speed, see 
            those different things, and I can pick one of those and say, OK, put 
            that at the center and then go look up in the database, get me the 
            information and tell me who are the actors. So here are all the 
            Anthony Hopkins movies, here are all the Julianne Moore movies. I 
            can pivot there. And so this idea of going back and forth between 
            these different things becomes a fairly straightforward thing.
            Another example is dealing with lots of photos. This is a case 
            where it*s going to be so easy to take photos, you*re going to have 
            thousands and thousands. And, in fact, one of the researchers at 
            Microsoft Research goes around with what she calls a little photo 
            button, and it*s noticing transitions during the day and it*s taking 
            a few hundred photos. And so she doesn*t even have to think about 
            actually clicking a camera; she just gets at the end of the day all 
            these interesting photos that she can decide if she wants to share 
            with people or in terms of having memories about her activities or 
            things she*s doing with kids or friends or things like that, it*s 
            there at no effort at all.
            Well, you*re going to get a lot of these photos and what do you 
            do with them? Well, this is a research project called Media Frame to 
            start to suggest that we can have user interfaces that make this 
            practical. 
            So you see we have a bunch of images here, hundreds, we can hover 
            over different ones of these. And some of these actually aren*t 
            photos, they*re actually movies. It*s our belief that you*ll more 
            and more not think of photos by themselves and movies by themselves, 
            but rather you*ll think of still images, motion video and all of the 
            audio that you capture either at that time or that you can easily 
            add later on, we*ll think about these things as wanting to organize 
            them together.
            Now, sometimes what you want to do is put various keywords on 
            these things and you can see here we*ve done that a little bit. So 
            let*s take one, let*s go in and look at the thing that relates to 
            Thanksgiving.
            I still have a fair number of photos here, so I can go in and use 
            a software algorithm that shows me which are the ones that have 
            faces in it and those get highlighted, or which are the ones that 
            are indoors and you can see it*s automatically able to tell which 
            those are and highlight those.
            And so we have recognition software that actually did the 
            orientation. It found and notified me of all the slides that were 
            coming in mis-rotated; it did that without my having to spend time 
            scanning through those things and it can see these different 
            photos.
            And, in fact, if I take the photos of those faces and I tell it 
            who somebody is, if I make an association with my contact list, then 
            in the future it will be able to do that recognition and do that 
            categorization in a very automatic way.
            We have the idea of finding similar images. Actually, let me go 
            back into that and try the similarities. If images are similar, it*s 
            actually looking at what*s inside here. And so if I can take this 
            image and say, okay, what else is similar to that, if I relax the 
            constraint, eventually everything is similar, but at this rating 
            it*s just these particular images. And so actually intelligent 
            analysis is part of how we*ll be able to deal with these things.
            If we go back and see the whole set again, we can also try out a 
            different view where we*re using 3D. And here what it does is it 
            takes and organizes them by time. Of course, the camera is storing 
            lots of metadata with these photos. It has a clock in it. It is able 
            to know when that photo is taken and I can just switch and change 
            that X-axis and break it down into different groups. And as I select 
            a group of photos, I can use these tags, add tags, change tags on a 
            whole set, all at once.
            And so this is just an idea that we ought to be able to make it 
            reasonable to play around with lots of different photos and media 
            clips and make navigating through those things a very, very simple 
            activity.
            Well, the wellspring that really drives software forward is 
            research and research is done both at universities and in commercial 
            organizations. And, in fact, the United States is dramatically the 
            leader in both aspects of this. The best universities are 
            overwhelmingly here in the United States doing this work and there*s 
            a real symbiosis of the relationship between the companies trying to 
            build these things into products, whether they*re startups or larger 
            companies and the universities; very much a virtuous cycle of 
            sharing ideas, helping research get funded, creating jobs for people 
            and it*s worked in a really fantastic way.
            Microsoft is a big believer in investing in R&D. Our R&D 
            budget at $6.8 billion is substantially the largest of any 
            technology company. And it*s kind of amazing to me, when I grew up, 
            I always thought IBM was the big company and actually in terms of 
            employees they are the biggest. They still have 330,000 -- I 
            shouldn*t say still -- employees, because they*ve taken an approach 
            that*s more based on services and doing different things than we do. 
            We*re very focused on building software products, but to do that 
            it*s got to be about R&D, and R&D that looks well out into 
            the future and takes on the very toughest problems.
            There are some good examples of collaborations here at the 
            University of Illinois. The Gaia.Net distributed OS was something 
            that some of our devices and software components can come in there, 
            and I*m sure we*ll learn a lot from what*s going on there.
            The experimentation of the Siebel Center, built on a lot of 
            different kinds of software, including some of the Conference XP 
            things we*ve done there, we*re very excited to see what can come out 
            of that.
            Some of these research problems are very tough problems. A good 
            example of that is what we call Trustworthy Computing. In fact, when 
            I met with the faculty earlier, I was very pleased to hear this is 
            going to be a major focus of bringing together a lot of research 
            ideas about security and reliability into an institute that looks at 
            it in a very broad way.
            When the Internet was first designed, it was designed assuming 
            that different parts of the network could be malfunctioning, that 
            they might be broken or literally that they might be bombed, but 
            there was not an assumption that there would be malicious actors on 
            the network, and so there*s no authentication of the From and To 
            addresses. SMTP mail, there*s no authentication of who that mail is 
            coming from. Many of the software systems are built around passwords 
            that are truly a weak link in terms of being written down or used on 
            less secure systems or being very guessable.
            And so what we*ve ended up with is a situation that*s very 
            fragile. Any software bug can result in what*s called an escalation 
            of privilege, and then hijacking a system to either flood the 
            network with traffic or to send lots of e-mail out that appears to 
            come from that person or various kinds of attack methods that are 
            taking place.
            There is no doubt that for computer science to fulfill its role 
            in helping business, helping entertainment, that we*ve got to make 
            this network secure and reliable, that we have to be able to make 
            privacy guarantees to people in terms of how information is dealt 
            with on this network. 
            And there*s a lot of invention taking place here. This has been 
            our biggest area of R&D investment for many years now. It was 
            about three years ago that we really pushed this up to the top of 
            the list and really brought in a lot of additional expertise.
            Some of the issues are very simple to solve: Moving to smart 
            cards instead of the password, having software be kept up to date so 
            that when there are problems they don*t sit there so people can do 
            exploits, having firewalls so you partition the systems off and you 
            don*t just look at what type of remote call is being made but you 
            also look at who*s making it, the transition to IPSec and IPv6 will 
            help us with this.
            There are new programming methodologies around interpretive 
            systems, like our Compact Language Runtime, the CLR, that helps you 
            define the privileges of a piece of software so you*re not just 
            doing exactly what that user is privileged to do but rather saying 
            what*s appropriate for that software.
            Some of the newer techniques have biological inspirations of 
            monitoring systems and having a way of looking at them and seeing 
            when their behavior becomes abnormal, both at a system level and at 
            a network level. So that*s a very exciting area.
            Another big area of investment is what you might broadly call 
            natural interface. The keyboard is okay, the keyboard is going to be 
            around for a long time, but it would be far more natural if we could 
            use ink and speech as a way of getting information into these 
            systems.
            These are tough problems. They*ve been worked on for a long time. 
            Ink is somewhat easier than speech, partly because users have a very 
            explicit model of what readable handwriting is and what it*s not. 
            And so even as people start to use our Tablet PC that*s got ink 
            built-in, they find themselves taking an E versus a C, being a 
            little more careful after they*ve had recognition errors, to loop 
            the E and not loop the C and so you get more and more accuracy.
            And so these handwriting systems are really coming into the 
            mainstream. The cost of the digitizer is extremely low and the way 
            that software is adapting to it, we*ll take this for granted that 
            every portable PC is a Tablet-type PC within the next two to four 
            years.
            Speech has been a little tougher. It*s one that we are investing 
            in very, very heavily, but users have no explicit model of speech. 
            In fact, when the speech systems start to make errors, their 
            tendency is to not only get irritated but talk louder. And whatever 
            the model is of their speech becomes less and less capable as 
            they*re getting slightly more irritated at the system. And the fact 
            that there*s no predictability and the system makes errors that 
            every other thing you*ve ever spoken to, which are humans, would 
            never make those errors, is kind of frustrating.
            And so we have to get the accuracy levels to be extremely high. 
            There are great advances here, not just driven by the extra power we 
            have, but modeling, going through, for example, all of the user*s 
            e-mail and understanding the corpus of words that are typical in 
            their discourse, we*re using that both in mail and in speech 
            capability, having deeper language models, having better microphone 
            type systems.
            One thing that*s fascinating is that the difference between human 
            and computers, in a noise-free environment -- well, if you take the 
            best case, a noise-free, context-free environment where you*re just 
            doing random words for a human and a computer, the computer is not 
            that bad, the difference is very modest. Where the human gets the 
            wild advantage is that the human has context, they have a sense of 
            what the speaker might say next, based on what*s going on and what 
            they know about the subject. And humans are dramatically better at 
            doing noise elimination and this is a case where the signal people 
            and the speech people are coming together now to get a sense of, 
            okay, how does the human audio system do this.
            Like most things related to human capabilities, our appreciation 
            for how good the human system is just gets higher and higher as we 
            try and create the equivalent on a digital basis.
            The ultimate natural capability is the idea of artificial 
            intelligence, and there is less research on this today than when I 
            left school 25 years ago, but there is some very good research going 
            on. Bayesian systems are a type of system that attempt to model 
            non-linear activities, and there are many similar approaches that 
            are becoming ripe and can be applied in interesting ways.
            We*re starting out with some very simple things. The only AI 
            product that actually sells today is this vacuum cleaner that goes 
            around, so that gives you a sense that we*re really at the low level 
            there, down on the rug trying to find our way around.
            The next generation will be using AI algorithms in games. If you 
            play a computer opponent today, after you*ve done that for two or 
            three days, that computer opponent becomes somewhat predictable and 
            the range of skills is either too high or too low. And with an AI 
            machine built in there, we*ll be able to make that richer and 
            richer, in fact, learn from users how they play, gather that 
            information centrally and reprogram the AI machines down on those 
            different systems.
            One fascinating trend is that all of the sciences are becoming 
            very data driven. Take a science like astronomy. Jim Gray, who*s one 
            of our researchers, realized that if you want to propose a theory 
            about astronomy, you need to look into all the different databases 
            that are out there, and yet these databases were not connected in a 
            way that you could perform these very rich queries and try and see 
            what*s the density of a start system like this or are there any 
            cases of something where these two things are near to each 
other.
            And so he led a project taking very advanced software technology, 
            Web services, and built, together with a lot of collaborators, 
            what*s called the National Virtual Observatory. And so no longer is 
            astronomy just sort of being at 3 in the morning with your eyes to 
            the lens when a supernova explodes, but rather it*s doing 
            sophisticated data mining and looking and forming theorems about the 
            information that*s been recorded over all time in this very large 
            virtual database that*s been created there.
            That same sort of thing is necessary across all the different 
            sciences, biology being probably one of the most interesting and 
            challenging. And so the interplay between people who have computer 
            science backgrounds, and data mining and modeling and networking and 
            what they*ll be able to bring to advancing biology in these next 
            several decades, will be quite phenomenal.
            I think it*s really biology and computer science that are 
            changing the world in a dramatic way. Other fields, they*re great, 
            but they are not changing the world. They*re not empowering people. 
            They*re not making the advances like these are. And it*s actually at 
            the intersection of these two fields where perhaps some of the most 
            interesting activity is taking place.
            Certainly nature has come up with a learning algorithm that we 
            have no understanding of, and as we, through various techniques, are 
            approaching that kind of capability, implementing that in software 
            will be a profound contribution.
            While all this computer activity is so neat as a tool, one of the 
            big problems we get is the so-called digital divide, that is that 
            you have a lot of people who have access in richer countries but 
            even there, not everyone, and yet the tool, you*d like it to be 
            everywhere. What*s the solution to that? Well, you can drive the 
            cost down on the hardware side, the software side; that*s happening 
            very effectively. You can make sure there*s lots of philanthropy and 
            donations around it; some good activity there. It*s actually the 
            communications costs, the broadband connections that are the most 
            expensive part of this, but even there the advances in wireless can 
            solve the problem.
            One of the projects I have the most fun with that Microsoft and 
            my foundation did over the last six years is go out to 18,000 
            different libraries and put in a total of 50,000 computers that are 
            just sitting there so that anyone who can reach a library can get 
            in, get out on the Internet, get that information and use the latest 
            software. And it*s amazing to see how people come in and use that. 
            
            There*s a lot more to be done there in terms of the schools in 
            terms of looking at that on a global basis, but it*s a very 
            important goal, particularly if you see this as almost like 
            literacy, like reading literacy in the same imperative for everyone 
            to have access.
            Now, the tools of technology are changing global competition and 
            there is a lot of concern about this. The tools of technology are 
            making it possible for not only manufacturing type jobs to be done 
            anywhere on the globe but actual services type jobs, not just 
            programming, not just call center but design, architecture, any type 
            of work, if you have these rich collaborative interfaces that the 
            Internet and the rich software on top of it make possible, that will 
            let people compete for that work anywhere around the world.
            And so we*re going to go from a world where the thing that would 
            predict your opportunity best historically was, were you lucky 
            enough to be in one of a very few countries, to, in the future, the 
            best predictor will be what*s your level of education. If you have a 
            college education, no matter what country you*re in, there will be 
            substantial opportunity because of the way these things connect 
            together.
            Now, this is an interesting challenge for the United States. The 
            United States actually did its best work during the 1970s and 1980s, 
            and that was actually a period of great humility, of concern about 
            international trends. In fact, the great concern of that era was 
            that Japan had a better model, Japan was ahead of us, Japan was 
            going to own industry after industry, and just wipe out the United 
            States -- including computing was going to move there. And although 
            that was completely overblown, completely wrong, it underestimated 
            the vitality of both the commercial and research side in this 
            country, it allowed us to really step back and examine what our 
            strengths were in driving forward, and that*s why such amazing work 
            I think was done during that period.
            Here we*re going to have that same type of questioning as we*re 
            seeing more global trade and all these different activities, as we 
            see particularly India and China stepping onto the world stage with 
            their university output and the energy and the innovation in those 
            countries, a lot taking place, that will challenge the U.S. to say, 
            are we really able to keep our edge, are we really able to keep 
            ahead? And it*s the investment in research, the value of 
            intellectual property, it*s a lot of things that the U.S. is 
            actually pretty good at, that we just have to renew our commitment 
            to.
            So my view is that in the next 10 to 15 years computer science 
            really will be magical, that the impact, whether you think what it*s 
            going to do for medicine, what it*s going to do for education, what 
            it*s going to do for worker productivity, the impact is really hard 
            to exaggerate. 
            And I*m not saying this is going to happen in the next year or 
            two. Every year there will be some neat things as speech and ink and 
            all these things come along. But it*s really the accretion of those 
            things where people are used to the tool and the tool is super 
            secure that creates this shift in how things are done. How will 
            education be done, how will that change? Well, that*s one of those 
            great open questions.
            The key element in doing this is having great people, and 
            Microsoft succeeds by having great people, universities succeed by 
            having great people and making sure that the re-investment in those 
            people takes place.
            There*s a little bit of concern that the peak enrollments in 
            computer science are off from the years past, and looking at that, 
            particularly on a national basis, it says, OK, what aren*t we doing 
            to show the opportunities that are here?
            Another challenge, of course, is the lack of diversity; both 
            women and minorities in computer science are not nearly at the 
            levels that we*d like. Obviously we*d like those numbers to be 50 
            percent, purely diverse, and yet the numbers are much more at the 
            10, 15 percent level, and a lot that needs to be done about 
that.
            I*m sure that this is a very multifaceted thing in terms of 
            showing the opportunity, giving people an opportunity at a young age 
            to see that it*s very interesting and pointing out that these jobs 
            aren*t all just hard-core coding type jobs. There are plenty of 
            those, those are neat, I like that, but a lot of them are much more 
            in terms of having skill sets where you need to know computer 
            science but also understanding usability and social factors and 
            marketing and business and bringing those things together. Those are 
            a lot of the really great jobs that are there.
            On the minority opportunity front, I*m very pleased that I*ve 
            been able to sponsor what*s called the Millennium Scholarship 
            Program. (Applause.) Here at this university there are 25 Millennium 
            Scholars, including some here tonight. It*s a neat thing and I hope 
            all of you will serve as role models and really encourage other 
            people to do the things you*re doing, because I think that*s a key 
            part of the path forward.
            So the tough problems just take great people. We will have any 
            type of simple user interface, secure type systems, and the 
            direction this is going to head in, there*s a lot of unknowns that 
            are going to make this, in my view, by far the most interesting 
            place to be involved.
            And so I*m excited that many of you will go through a computer 
            science program and join a variety of companies, perhaps Microsoft, 
            perhaps some of the startups, and really make this a reality, 
            because this is the important stuff and the great stuff is all ahead 
            of us.
            Thank you. (Applause.)