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            Remarks by Bill Gates, Chairman and Chief Software Architect, 
            Microsoft Corporation    Carnegie Mellon University, Pittsburgh, 
            Pennsylvania    February 25, 2004    
               BILL GATES:     Thank you. Well, good morning. It*s good to 
            know that computer science students are willing to get up this early 
            in the morning. (Laughter.) That wasn*t my practice when I was an 
            undergraduate.
            Well, I want to talk today about some of the incredible things 
            that will be happening in the next decade as hardware and software 
            move forward, we*ll clearly realize some of the dreams that people 
            have had for many decades, turning the personal computer into far 
            more than it is today and connecting it up in new ways so that it*s 
            a natural tool that is really the change agent that*s going to make 
            business far more effective, and education far more effective, and 
            just plain old having fun and communicating, a lot better than it is 
            today.
            I*m very pleased to be here at Carnegie Mellon. This institution 
            has made phenomenal contributions in engineering and computer 
            science. People like U.S. News and World Report have recognized this 
            institution as probably the premier institution in those areas. And 
            certainly Microsoft has benefited phenomenally from the relationship 
            we*ve had with CMU. The joint research that*s gone on and some of 
            the great people who have joined Microsoft, including people like 
            Rick Rashid who runs our research group, Anoop Gupta, who*s running 
            our communications work, Kai-Fu Lee, who runs our speech effort, 
            Gordon Bell, one of our top researchers, and many, many other people 
            who are continuing their relationship with Carnegie Mellon as they 
            help Microsoft define new software.
            As I*m talking about how great it is to be in computer science, 
            and get not only undergraduate and graduate degrees, I*m a little 
            bit embarrassed because, of course, I myself am a dropout -- kind of 
            a paradox, but certainly what Microsoft looks for are people who 
            have been through the undergraduate and graduate programs, and these 
            are the people who are going to have an incredible impact on 
            society.
            Computing has gone through a big transition over these last 30 
            years. When I was young and using that computer at age 13, computers 
            were big and expensive and only the tools of governments and large 
            corporations. In fact, people had a very negative reaction to the 
            fact that the computer would have data about them, and probably 
            print out bills that didn*t make sense, and some people talked about 
            putting staples into those punch cards that would come in the mail 
            so that maybe the big machine would be defeated by that little 
            staple.
            The very first personal computers were quite modest. The Altair 
            computer, the kit that became available in 1975 that got me to found 
            Microsoft and leave school, was powered by an 8008 microprocessor, 
            and that was less than a millionth as powerful as a $300 personal 
            computer is today. And it really couldn*t do much at all. One of the 
            big breakthroughs that Paul Allen and I made was coming up with 
            software that would flash the lights and make it appear that there 
            was some intelligence inside the machine. (Laughter.) 
            One of the great discoveries was that the bus was so noisy that 
            if you put a radio nearby we could actually make sound because of 
            the electrical leakage, and if you programmed it the right way you 
            could actually generate a little bit of music with that very, very 
            limited machine.
            That was in an era of eight-bit personal computers: the TRS-80, 
            Commodore 64, Apple II. You only find those in museums today, but 
            they did have one thing in common, which was that they all ran 
            Microsoft BASIC; that is, they came with a piece of software that we 
            created to let you sit down and program those machines, write games, 
            write business applications. We started to get disks connected to 
            these systems, we started to get a decent amount of graphics 
            capability, but we were really limited, the 64K limitation of those 
            systems held us back.
            And so actually the arrival in 1981 of the IBM PC was a 
            milestone. This was a machine that Microsoft helped design. That*s 
            where MS-DOS first showed up. And it ushered in an increase in 
            volume, and really started a virtuous cycle that had been part of 
            the vision of the company. And that cycle was that as we got more 
            software, computers would become relevant to more people, and that 
            volume would lead to more scale of making the parts, which would 
            bring the prices down and therefore draw more people in.
            And in fact, in 1981, that cycle started so that now, in a 
            country like the United States, we think of the personal computer as 
            a tool that a very high percentage of people have access to. 
            Two-thirds of homes have access to personal computers, and it*s a 
            tool that in many business settings we simply take for granted.
            Now, there was a business model change there to say that all of 
            the hardware should be compatible. That hadn*t been the case before; 
            that is, machines from each company -- IBM, Univac, NCR, Digital 
            Equipment -- all of them ran completely different software. And so 
            there was really a focus on hardware advances and no ability to 
            share software across machines or moving forward.
            And what Microsoft did was say, okay, we will be neutral to these 
            hardware companies and make those systems absolutely compatible. And 
            that was key, because volume is the secret of the software industry. 
            If you want to be able to sell software for very, very low prices, 
            you*ve got to sell tens of millions of copies, and that came into 
            play. It was phenomenal to see that really come together.
            The next big transition point was moving away from the character 
            mode interface to a graphical interface. And I*m sure probably you 
            appreciate today that that was a very controversial thing. The 
            complexity of the code, the number of cycles it took just to put 
            text up on the screen; we bet our company on that and we had the 
            pioneering work at Xerox, we had the work that Apple was doing in 
            parallel where we were doing applications for Mac as well as 
            building Windows. And it took, well, at least six or seven years 
            before that became broadly accepted. That led to a whole new 
            generation of applications, a whole new layer of richness, pretty 
            phenomenal advance.
            And then the next big milestone was the arrival of the Internet. 
            In a sense, it was interesting, people had been talking about e-mail 
            and connectivity and information sharing, but it was those standards 
            that came out of the university environment that really defined the 
            seed that it all got built around.
            And, of course, that became by the late *90s a fairly crazy 
            period, the idea that things were going to change overnight and 
            startups that had no profit models would run the world. Today we can 
            look back on it and say that it was fairly extreme in some ways, and 
            yet the increased levels of investment and attention were 
            phenomenal. That gold rush atmosphere, although it had its excesses, 
            really drove things forward.
            Now we*re stepping back and saying as an industry we*ve got some 
            big challenges. The ability to really do e-commerce, the 
            infrastructure is not there, whether it*s the protocols, the data 
            schemas, the security elements, the simple development tools, and we 
            have to get those in place for some of those dreams to actually be 
            realized.
            So as we move forward, it*s really software that*s going to be 
            the key element. And yet software is boosted by these rapid advances 
            in the hardware performance.
            At the microprocessor level, Moore*s Law that was sort of a 
            prediction that every 18 to 24 months we*d have double the 
            transistors on those processors, that has held true for these last 
            25 years and will hold true for the next 10 to 15 years.
            Now, actually translating those transistors into true computer 
            performance is a very tough problem. You*d think by this time we*d 
            be able to execute things in parallel and sort of have the sum of 
            the performance add up on behalf of a wide range of applications, 
            but that*s really not the case. That*s a very tough problem, and one 
            that with these new architectures we*ll have to really solve.
            Storage systems, whether it*s RAM or a magnetic disk, has 
            improved faster than the processor. And so although 10 years ago it 
            was very tough to even store the documents you would create on your 
            local disk, today you can type your entire lifetime and not come 
            anywhere near that capacity. In fact, by the end of the decade 
            you*ll be able to store basically all the movies you*ve ever 
            watched, the photos you*ve ever taken, the documents you*ve created, 
            sort of your life*s history will fit on that disk and it*s up to 
            software to make it accessible, navigable, fun to use, private, 
            appropriate so that that will be a real benefit.
            The screen is changing. Getting bigger screens with high 
            resolution, portable screens, it really changes how we think about 
            computing. Today there is a big divide between the world of paper 
            and the world of the screen. And most people, if you get a very long 
            document, at some point will go and read off of paper. That really 
            needs to be changed, because the ability to navigate and annotate 
            and share and be up to date is far superior in that digital 
            realm.
            You know, there*s no reason why that weekly magazine or daily 
            newspaper shouldn*t have this superior experience up on the screen. 
            And yet the usability and the layout, the feel, the vision, these 
            are all things that we need to make sure we catch up and do as well 
            as we provide the advantages of that digital environment.
            Part of this is having a mobile screen, a screen you can hold in 
            your hand. When we did our reading research, it turns out that 
            anything that*s in a fixed position, you get fatigue, you don*t get 
            the immersion in the content because it*s very tiring to look at 
            that fixed viewpoint. So when you*re reading off of paper or a book, 
            you*re shifting that around subconsciously so that you*re not 
            distracted by that fatigue. And so getting things like the Tablet PC 
            and these new screen form factors are very important. 
            The size of the screen area you*ll be dealing with will be much 
            larger, and there are a lot of user interface techniques to be 
            invented there.
            The graphics capabilities of these systems will be phenomenal. 
            The kinds of things we see that are only done on a non-real time 
            basis, we*ll be able to do on a real time basis. And so the PCs and 
            videogames, the successor to today*s PCs, the successor to Xbox will 
            provide high-definition, realistic scene generation. And the 
            question of whether those user interfaces now can move into things 
            like browsing to find a book or browsing to find a file or being in 
            a social environment with a set of friends talking about things, do 
            those 3D interfaces come in, I think that*s very right that it*s 
            time that we found a way to apply that, because the quality of 
            graphics is so unbelievable.
            In connecting these systems, of course, network speeds go up even 
            faster than storage capacity, and the wireless element of this has 
            come in to make a huge difference. Ultra wideband wireless will let 
            us disaggregate the PC, so that the screen, the storage, the 
            computation are all thought of as different pieces and you can 
            dynamically assemble those pieces on behalf of the user, control 
            multiple screens, use different screens at different times. 
            And wireless is going to take what is today the most expensive 
            part of computing -- broadband expense -- that really makes it 
            prohibitive to get this out pervasively in developing countries, 
            particularly in rural areas, and solve that problem.
            So advances in wi-fi with direction antennas, peer-to-peer 
            networks that self organize using mesh techniques, so-called Wi-Max, 
            802.16, that*s going to come in and provide more distance, that 
            should bring the broadband costs down the same way that the cost of 
            the hardware and software have advanced.
            Now, all these devices are going to have to work together. The 
            single system centric point of view is very much obsolete. It*s 
            tough to make systems work together today: moving files between PCs, 
            upgrading a PC, synching your schedule or your mail onto the 
            different devices. So this holistic approach of learning what the 
            user is interested in and applying across those devices, there*s 
            definitely work to be done in that area of ubiquitous computing.
            We see that devices from wall-sized screens to the huge 
            desk-sized monitor to the tablet to the pocket device, which is the 
            evolution of the phone, all the way down to the wrist-sized device 
            will need to work together.
            The watch I*m wearing here is actually a so-called SPOT watch 
            that has a microprocessor in it. This is an ARM microprocessor. It*s 
            running at 10 times the speed of the original IBM PC. It*s got 10 
            times the memory of the original IBM PC. In fact, if you take this 
            watch onto a U.S. nuclear submarine, there*s more processing power 
            in here than is on the submarine, because they use older systems 
            that they chose a long time ago.
            So the power is quite phenomenal, and we can deliver in a secure 
            way, code down to this watch using a byte code CLR approach. And so 
            whether it*s watching baseball updates or stock updates or any 
            information you care about, you just go to your PC and choose what 
            you*re interested in -- news, sports, weather, your calendar, 
            messages -- and those messages are sent to the device so that it*s 
            working on your behalf, showing information that you care about.
            It actually uses a wireless network that piggybacks FM 
            transmission, the so-called FM sideband, and so we didn*t have to 
            build out a new network infrastructure; we just inject the data into 
            the transmission of the FM radio stations and then anybody who*s in 
            range gets connected up.
            So the hardware will not be holding us back. The hardware will 
            give us the speed, the storage, the connections, the screens, the 
            graphics to let the software work on behalf of the user.
            It*s interesting to think what scenarios can we advance, what 
            kind of change can we bring forward.
            The economy is largely made up of people dealing with 
            information. If you have somebody who*s designing a new product or 
            providing customer service or working with a customer on a 
            purchasing situation, their ability to do their job is based on 
            navigating to information, knowing what*s going on, communicating 
            with people at a distance.
            And even the modest advance we made in the late *90s at giving 
            people better tools, electronic mail, browsers, a little bit of 
            electronic exchange, that caused a big change in the economy. 
            Advancing productivity is the magic thing; it creates jobs, it makes 
            the products and goods available far better. And yet the 
            productivity we gave in that time period is a very small percentage 
            of what we*ll be able to give in the next decade. 
            As software tackles these very tough problems, we can make those 
            information workers far better. The information they have today is 
            limited, the way they visualize that information is limited, the way 
            that meetings are organized and followed up on, the way that you 
            record the notes and the video, the way you draw in somebody who*s 
            not in that location; the way we think about workflow, what is it 
            that people should get done and the boundary between software 
            systems and people. Just take a simple incident where you get an 
            invoice that you disagree with; today, the inefficiency of pointing 
            out what*s wrong, trying to get their software system and your 
            software system to deal with the phone calls and the e-mails that 
            are an ad hoc way of coming up with a solution to that problem, it*s 
            10 times more complex than it should be and it doesn*t lead to the 
            record that would let you monitor those things and understand those 
            things.
            So-called business intelligence where you try and see where are 
            your quality challenges, where are your sales problems and where are 
            your sales opportunities is very, very poor today.
            Even the basic process of buying and selling, finding a seller 
            that you don*t know, checking their reputation, checking your 
            transaction, we don*t have the XML standards and the protocols to 
            solve that, and yet every one of those things is being put 
            together.
            The idea of visually looking at workflow processes, so that if 
            you*re customizing software, you don*t go in and write thousands of 
            lines of code, you simply look at that visual process and make those 
            changes, today companies that are 99 percent identical end up with 
            vastly different application software that they have a hard time 
            upgrading and connecting up to others, because the way we*re 
            expressing these business process differences are way, way too low 
            level. We*re writing too much code, the code is not abstract the way 
            that it should be.
            In communications the inefficiencies are something we can all 
            relate to. We have multiple phone numbers that our ability to 
            control when somebody gets a hold of us or puts mail in our Inbox is 
            very limited today, our time is being wasted and even things that we 
            should be notified of, it*s hard to say, "let me know if this  
            schedule "changes or "this account is "overdrawn or if this person  
            is unhappy about something. You should have exactly the information 
            you care about and not be forced to deal with things that are not 
            important to you.
            An extreme example of this is spam. Spam is a major problem 
            wasting lots of people*s time. I have to say sometimes I actually 
            get a kick out of the spam that shows up in my inbox. Here*s one 
            that I got and it looks like if I get out of debt I*ll get to meet 
            new interesting people, so that could be a lot of fun. (Laughter.) 
            Then I got one that offers to solve my problems of not having a 
            university degree, that I thought that would be pretty good, 24 
            hours a day I could call those people up. And then finally there was 
            one that really spoke directly to me. (Laughter.) Being able to get 
            legal help for just pennies a day would be a significant 
            productivity advance for me. So it*s interesting what comes in there 
            and yet clearly spam is something we*ve got to get rid of so that 
            people aren*t wasting time and so they don*t miss e-mails that are 
            of importance.
            And there is a lot of technology we can bring to this in terms of 
            what we pass through, authenticating the mail, that spam is actually 
            even a security problem because the original mail protocol, SMTP, 
            doesn*t authenticate who it*s from and so you can pretend to be 
            something that you*re not and cause people to do all sorts of things 
            they shouldn*t do because of that. And it*s also a spreading 
            function for malicious code, so making sure that we change that is 
            important.
            We also have to take all these variety of communication 
            techniques and bring them together. We*ve got blogs, weekies, we*ve 
            got instant messaging. We*ve got still the PBX systems and the voice 
            calls, both wireless and wired. And being essentially able to create 
            a software agent that as people are trying to get a hold of you or 
            trying to schedule things with you, understanding your sense of 
            priorities and the context that you*re in, what device you*re with, 
            what the cost of interruption in terms of your present activity is, 
            that*s got to come. And there*s a lot of very sophisticated software 
            that can work on your behalf to do those things.
            If we just think about the consumer, there*s clearly a revolution 
            taking place in how we consume music, how we deal with photos. And 
            it won*t just be photos; it will be movies and photos and audio 
            annotation, simple presentations you make around those things. 
            Dealing with cherished memories and making them accessible, that*s a 
            scenario that every personal computer basically ought to just come 
            with that capability and as you take pictures they should 
            automatically be filed, they should be backed up in the network in a 
            way that makes sure you can never lose them and yet where you retain 
            total control over who has access to those things; a lot that needs 
            to be done to take advantage of this revolution towards digital 
            media.
            Now, coming up with interfaces that make it natural to deal with 
            those thousands and thousands of things is fairly difficult. One 
            thing we*re seeing in terms of devices is that people want their 
            media with them wherever they go. So inside the house you*ll have 
            high-speed wireless networks and the PC will be able to project onto 
            any screen or send the audio out to any speaker, and so you don*t 
            have to try and have it in many different places.
            The device I*m holding is called a Portable Media Center and what 
            this is, it*s a 40-gig disk that you can just connect up either 
            wirelessly or through USB and download movies, download photos, 
            songs, and so it*s an evolution beyond just the pure audio player 
            because there*s a nice color LCD here. So whether it*s kids in the 
            back of the van or sitting on the airplane, your video is 
            available.
            And this whole idea of digital video recording, that you get to 
            control what you watch and when you watch, is very addictive. I 
            mean, there*s no doubt most video will be consumed on some sort of 
            time delayed basis as things move forward. And as we get devices 
            like this, this will come out this fall from a variety of 
            manufacturers but with a very consistent user interface, driven by 
            our software, these will come out at $300 or $400 and the price will 
            simply come down from there. And so we really do need to solve the 
            issues of making it easy to get the information there and navigating 
            that information.
            I just want to quickly show you a few prototypes that have been 
            done in Microsoft Research that suggest the kind of visualization 
            that*s possible as we*re dealing with lots and lots of media.
            This is a movie application here. We can see there*s a movie at 
            the center there. So what happens is, it*s taking the movie and 
            putting it at the center and then finding things that are related 
            like the director and the various actors. So if we go over here, we 
            can see all the movies by Ridley Scott, we can just select one of 
            those and that goes to the center. And then I see it goes into the 
            database and it calls up all the things that you might want to pivot 
            on related to that. And then over here it has all the different 
            movies in the genre.
            Of course, you*d like to have this annotated by professional 
            reviews that you trust, friends who have made comments on it, things 
            that when you might have seen the movie, what you thought about it. 
            But this type of visual interface starts to deal with the variety of 
            information that you*re going to have.
            One other prototype I*d like to show you -- look at the photo 
            realm in particular, or actually, photos and movie clips, and this 
            is called Media Frame. And this is the idea that when you have all 
            these different photos it*s a little bit tricky to organize them. In 
            fact, there*s one person at Microsoft Research who actually carries 
            around a little camera, sort of a lapel camera, and it automatically 
            during the course of their day will take photos sort of noticing 
            there*s a scene change or that people are talking loudly or 
            somebody*s laughing and so over the course of the day there might be 
            a hundred photos taken and then those, of course, are automatically 
            sent to a computer system, but kind of taking those, selecting the 
            ones that are interesting, we need a lot of help from software to do 
            that.
            So here we can see a lot of photos and I can just go look at any 
            one of these. Actually, this one I*ll click on is a movie clip 
            that*s stored there, and so just quite a variety of different 
            things.
            Now, I can put keywords on all of these things, so I can say, 
            okay, which of these are related to Thanksgiving? When they come in 
            from the camera, they are time marked because most cameras now will 
            have time information, and more and more they*ll have GPS 
            information. So the idea of seeing a map, seeing the timeline 
            definitely makes sense.
            Here you can see all the things tagged about Thanksgiving. I 
            might want to say, okay, which of these, if I pick one of these, I 
            might want to say what*s similar to that photo and I can relax the 
            condition of how similar things are and various things get selected 
            because of that.
            I can say, okay, which of these photos have a face in them and so 
            this is recognition software that goes in, and to some high degree 
            of accuracy, is able to see where the faces are. I can say, okay, 
            which ones are indoors, which ones are outdoors and software is 
            helping out.
            In fact, this whole database as it came in, the software 
            automatically tried to figure out the orientation and proposed the 
            ones that should be rotated so that it was in there in a very strong 
            way.
            If we go back and select all, we can say, okay, what would it be 
            like if we see this in a 3D fashion? So here we*re organized by 
            date. I can take that X axis and go to finer grain groupings of 
            these things. I can take a set of photos, select them and say, okay, 
            those all relate to a certain event, so I can apply the keyword 
            there, so then I get that very rich navigation.
            And obviously this is a database, but it*s a very different 
            interface than sitting with a typical forms entry, select an item at 
            a time type interface, and we think this is the kind of thing that 
            you*ll need to be fully empowered to deal with all your rich 
            personal media.
            Well, let*s talk now about R&D. The software field, the 
            economics of it are fascinating. All the costs are up front and once 
            the software is created, the actual marginal costs of making copies 
            is almost zero. Certainly there are support costs and upgrade costs, 
            but it*s a very different equation than many parts of the 
            economy.
            Microsoft is showing its optimism about these software advances 
            by, as your president said, driving our budget upward to about 6.8 
            billion a year that we spend. And that is substantially the largest 
            technology R&D budget in the world. So that either means we*re 
            crazy or there*s going to be a lot of software breakthroughs coming 
            out of that.
            A very important part of that is the Microsoft Research function. 
            That got started now about 12 years ago when Nathan Myhrvold at 
            Microsoft recruited Rick Rashid, who was a professor here, to come 
            and be the founder of that activity. And it started fairly small, it 
            started on things like linguistics and graphics and now has expanded 
            to the point where we cover a lot of different areas, and, in fact, 
            I*d say the vast majority of the areas that we have counterparts 
            here at Carnegie Mellon who are working on very similar problems. 
            The idea of mobile and wireless computing, the ubiquitous thing, 
            they*re doing of lot of interesting things there. The language area, 
            speech recognition linguists, actually our whole group there, the 
            majority of them are people who had some of their academic 
            experience here at CMU. CMU was one of very few places that believed 
            in that and did before it was fashionable. Then it was fashionable, 
            now it*s not fashionable again, but it will be fashionable in the 
            next five years.
            Speech recognition is one of those things where as we*ve gotten 
            into it, our appreciation for how good human recognition is just 
            goes up and up. If we take a fairly isolated case of it and say 
            let*s take words where there*s no context, that is randomly selected 
            words in an environment where there*s no background noise at all, 
            the perfect audio environment. The difference between computer 
            recognition and human recognition is not very dramatic. But as you 
            give the human the advantage of context and as you put noise into 
            the environment, there*s more and more of a divergence of the human 
            ability versus the computer ability.
            And so although even at the basic acoustic level there are still 
            advances, it*s really that noise elimination and understanding of 
            context are the things that are going to close the gap in the most 
            dramatic way.
            We believe that speech over the next several years will be ready 
            for primetime. In fact, it was kind of a fun thing in China just 
            last year where XD Huang, the head of this group, was there saying 
            how great it was and somebody in the audience challenged him to say 
            that they could type faster than he could enter things completely 
            accurate with text. And, in fact, they had this runoff and speech 
            won by a huge amount.
            Now, in the case of Chinese, that*s a little bit easier than it 
            is in English because the keyboard isn*t nearly as good when your 
            alphabet has literally thousands of characters, but it*s a milestone 
            and we are starting to see that bootstrap of acceptance in China and 
            Japan, which you*d expect. But as we talk about ubiquitous 
            computing, the keyboard will be less and less available and speech 
            has got to come in.
            It turns out that ink recognition is actually an easier problem 
            than speech recognition. Part of the reason is that you not only 
            have the processing of the software, in the case of handwriting it*s 
            done at a very conscious level. So if you enter something in a 
            Tablet PC and there*s about 400,000 of those out today, and we*re 
            gathering the database of what people put in and what the mistakes 
            are and using our learning machine technology to get better and 
            better at this. In fact, there will be a major release this summer 
            that will raise the accuracy very, very dramatically.
            But in any case, you can see that if you do an E where the loop 
            is really small, sometimes it will think it*s a C. And so you can 
            even subconsciously collaborate with us and say when you*re going to 
            make Es in the future you*ll actually make them sort of unnaturally 
            large and the system just gets better.
            Speech doesn*t work like that. You have no conscious model. And 
            so it*s very upsetting and it appears to be completely random when 
            the system gets something wrong. And, of course, the thing it picks, 
            because it doesn*t have context, is beyond irritating because 
            there*s no logic that the choice it*s made should show up within 
            that corpus of material. And so it*s these contextual things that 
            are one of the important advances.
            In fact, by the summer release of the ink recognizer, one thing 
            we do is we just look through your documents and your e-mail 
            addresses and your URLs and we bring our dictionary to understand 
            what you personally are likely to be dealing with, and that alone 
            makes a huge difference in terms of how well that system works.
            This morning I had a chance to meet with the faculty and talk 
            about some of the big bets you*ve made and I was very excited to 
            hear that one of the big bets you*re making relates to Trustworthy 
            Computing. This is the most important issue in software today. In 
            some ways it*s not that sexy because if you get it right, it*s just 
            something that you don*t run into. People don*t call you up and say, 
            "Hey, I didn*t have a virus today, thank you." (Laughter.) But in 
            order to realize the potential of these systems for e-commerce and 
            collaboration and communication, all the things that essentially 
            society implicitly is starting to rely on these networks for very 
            important information, we have to have a level of reliability, 
            security, and isolation that we just don*t have today.
            And this is leading to so many fascinating problems in computer 
            science, whether it*s the languages themselves and the kind of 
            explicit typing systems and constraints, making those very easy for 
            people to express, finally taking something that was slightly in 
            vogue in computer science when I left school, which was this idea of 
            proving programs and actually saying can this program ever have a 
            memory fault. We*re actually, based on some work that was done here 
            at CMU, some work at MSR, now taking very large bodies of code like 
            Windows device drivers, and able to say, hey, this thing has a 
            problem, because it can actually leak memory. And the way the 
            proving works is it actually shows you the exact path and the 
            example of how that*s allowed. And so these very rich tools are 
            important. 
            Security is a very deep set of issues that will continue to be a 
            top issue for some time to come. There will be progress. The ability 
            to keep software up to date, the ability to firewall up systems, 
            already we*ve made a lot of progress on those things. So the actual 
            level of these problems will get reduced but in order to get where 
            we need to go, there is certainly a good decade*s worth of work 
            there.
            Some other tough problems: The most interesting problem of all in 
            computer science, the one that*s always been the most appealing and 
            the toughest, is artificial intelligence. CMU even going back to the 
            *60s was a pioneer of looking at those problems and thinking about 
            what progress could be made.
            And progress has been very modest. Maybe someone in this audience 
            will be the one to make the breakthrough that we need here.
            I happen to be an AI optimist myself. I think these are very much 
            solvable problems. I think that some of the modeling techniques 
            around Bayesian networks and other learning technologies really are 
            starting to mature.
            The only product in the market that uses AI today is this thing 
            that goes around and vacuums the floor and tries not to get lost, so 
            that*s the level we*re at today, just down there on the rug trying 
            to keep it clean. (Laughter.)
            A next generation of using these technologies will include things 
            like computer games. Computer games are a great domain to try things 
            out in. Often when you play against the computer it becomes 
            repetitive and boring, and the computer doesn*t know how to get 
            better or how to be at the right level.
            Well, by using what we call Xbox Live! where we get to monitor 
            gaming experiences and seeing how people are playing and what 
            strategies they have, we can use machine learning technology to 
            create really wonderful opponents that try out these different 
            strategies and have those available. And so if you want to train and 
            get really good or if you just want it to work at a basic level, we 
            have a reasonably rich AI engine in there that*s learning on an 
            ongoing basis.
            And, in fact, these AI engines can be applied to so many 
            different problems, low level problems like being smart about memory 
            management, high level problems about looking at systems and seeing 
            are they behaving in a natural way. Machine translation, this is 
            another thing that we*re extremely optimistic about that there*s 
            been enough progress that it will be practical to have extremely 
            high quality translation within a domain commercially available 
            literally in the next several years. So the breakthroughs, the 
            opportunities for the breakthroughs, are pretty phenomenal.
            One thing that has always been a theme here at CMU is getting the 
            various disciplines to work together. And that*s particularly 
            appropriate now because many of the hard sciences are relying more 
            and more on data. Just take astronomy. Jim Gray, who*s one of our 
            researchers; he*s a great computer scientist and he*s a hobbyist in 
            astronomy. Well, astronomy used to be that you*d be there at that 
            telescope at three in the morning and some supernova would blow up 
            and you*d write a paper about it and that was a big contribution. 
            But today, the amount of scanning information at various wavelengths 
            and various time periods is a monster database, and yet it*s not 
            really a database because it*s stored in different locations and no 
            one has characterized the nature of the data in each of those 
            things.
            And so the problem that Jim took on with some collaborators in 
            that field was saying this science is going to be data driven, so 
            let*s create a national virtual observatory where all of these 
            observation things are available and so you can have a query like 
            have any quasars been seen in a galaxy like this in this time period 
            and see what the correlations are and test out theories and have 
            deep understanding of the information that*s been observed.
            Now, astronomy was a good place to start with this, but we see 
            this in even tough areas like biology. The amount of data, genomic 
            data, proteomic data, trial data is phenomenal, and yet that isn*t 
            gathered together, and so it*s really a computer science problem to 
            take that data, understand that data. The characteristics of 
            biological systems makes people from computer science are very 
            important there. And so I*d just pick those as two examples of areas 
            where it*s people with a computer science background who will make 
            the breakthroughs. It*s the rich modeling techniques that come out 
            of our discipline that will be, I believe, a primary 
            contribution.
            Now, computer science has a lot of challenges. One of them is 
            that the Internet and the PC have become such basic important tools 
            that we want everyone to have access. And this is often talked about 
            as the digital divide. Now, of course, the most direct way to help 
            with this problem is to make sure that the price of software and PCs 
            and broadband networking continues to come down. That drives up 
            availability. But there*s even special outreach efforts that all of 
            us should consider and hopefully get personally involved in.
            One of the most exciting ones that Microsoft and my foundation 
            did together was going around to the librarians in the United States 
            and saying, "Would you like to have a PC in the library?" And we 
            were worried about it, because would they find it a negative thing 
            and if the kids came in to use it, would they use it for appropriate 
            things, could we keep those systems up and running in a very 
            effective way, even if people were kind of hacking around. And, in 
            fact, that project, which took place over a five-year period, is now 
            complete and that is that 18,000 libraries that did not have 
            computers in there now have a total of 50,000 computers. And these 
            things are monitored for reliability. There are training programs. 
            
            And the phenomenal thing is the librarians love it. More people 
            come in, the rate of using books has actually gone up as people are 
            coming in to use this tool, so it hasn*t been a substitution effect, 
            and it*s really reinforced this idea that the library plays a role 
            in equity, that any kid who doesn*t have a computer at home, if they 
            can reach a library can get in and use these state-of-the-art 
            things.
            Now, if we look on a global basis and look at education, it*s 
            just scratching the surface, so there is a lot to be done there.
            As we think globally, there is a new dimension coming to global 
            competition. People are just starting to get used to the fact that 
            the advances in the Internet and software are making it so that when 
            we think about jobs being done anywhere in the world, that it*s not 
            just manufacturing. Global shipping and logistics systems meant that 
            manufacturing jobs were moving around the globe even 20 years ago. 
            Now any job, including doing architecture work, answering phone 
            calls, not just software development, through the use of technology 
            can be done wherever you find the most qualified people.
            And this is creating opportunity. This is going to create better 
            products and services, it*s going to tap into the incredible human 
            resources and energy in countries around the world, but it will be 
            an interesting challenge in terms of the United States renewing its 
            edge, saying, okay, research and a commitment to long-term tough 
            problems has gotten us and kept us in the lead and are we going to 
            maintain that even as countries like China and India are coming and 
            becoming major players, major contributors. I think it*s very much a 
            win-win situation and some of the concern and humility will get us 
            to folks who can do the right thing.
            After all, it was during the 1980s when U.S. computer science was 
            doing very good work that led to what happened in the *90s, where 
            there was a humility, and in that case it was about Japan, that was 
            Japan a superior industrial model, did their sort of centralized 
            research where they had this fourth generation project. There was a 
            question of whether that going to make some big breakthrough versus 
            the sort of diverse approach, using U.S. universities, and I think 
            we very wisely didn*t follow exactly what they did, we strengthened 
            the things that we did well and what came out of that was a 
            phenomenal contribution, both at a national level and at a global 
            level.
            And so there*s going to be a lot of good debate here about what 
            this means to the U.S. and a need both at the university level and 
            commercial level to up the ante in terms of the research that gets 
            done.
            Well, one limiting factor in all these breakthroughs is having 
            great people to do the work. And when I talk about the work, it*s 
            important to know I*m not just talking about writing code; I*m 
            talking about people who understand the customers, the business. 
            There is such a range of activities and yet to do those jobs well, 
            really a background in computer science and understanding in 
            computer science is pretty important.
            It is interesting the challenge that we face in terms of getting 
            a diverse set of people to go into these fields, and again I would 
            congratulate Carnegie Mellon for very early on recognizing this 
            problem and trying different things, making people aware of the 
            problem and making some progress, not solving the problem but being 
            a model for some of the things that can be done well.
            One of the things I*ve done personally through my foundation is 
            create what*s called the Millennium Scholarship Program, and that*s 
            for minorities to be able to go in both at the undergraduate level 
            and graduate level and be in the sciences and create a role model 
            who will hopefully bootstrap and get these numbers up in a very big 
            way.
            If you think of what are the exciting places to work, I*ll admit 
            I*m very biased, but if you go, say, into law -- and my dad*s a 
            lawyer -- things aren*t going to change that dramatically. If they 
            change, it will be because of technology and the issues around 
            technology. If you go into investment banking, it*s not going to 
            change that much.
            There are only two fields that you can make argument I*d say that 
            they are going to improve the world in a very dramatic way, and 
            those are the things around engineering and computer science, both 
            hardware and software, and the things around biology and medicine, 
            and with a lot of very interesting things at the intersection. The 
            biology and medicine guys will move forward in large part because 
            they can take the data, the visualization, the tools that we*ll 
            create out of these things.
            And so I think this should be the most attractive field, and I*m 
            very excited to be part of it. Even though I*ve gotten to 
            participate in a lot of milestones, I think the milestones of most 
            interest are the ones to come in the next 10 years. And I know a lot 
            of you here are going to make huge contributions to that, and I look 
            forward to seeing what you*ll do.
            Thank you. (Applause.) <!--START RIGHT NAVBAR--></TD>