Bill Gates on Software Breakthroughs & Computer Science Education – MIT 2004


[MUSIC PLAYING] PRESENTER: Welcome to
the Kresge Auditorium. If you will please
take your seats, we’ll be starting momentarily. We request that you make sure
all cell phones and pagers are turned off. And also, please note
that all audio and video recording is prohibited. Please limit any
flash photography to just the first one
minute of the presentation. Ladies and gentlemen, please
welcome MIT President Charles Vest. [APPLAUSE] VEST: Thank you. We want to welcome everyone
to today’s discussion and presentation by
Microsoft’s Bill Gates. I think one of the
first things you observe that is in the old days, the
academic used to come out in a sweater to introduce
the corporate leader in the pinstripe suit. Today, we’re going
to reverse that role. And I don’t think that
will surprise anyone. And then again, Bill is
not your typical CEO. In fact, he is not a CEO. As you may know, he is the
chief software architect of Microsoft. And he is indeed here today
to discuss with you some of the grand challenges
facing computer science as we move into the future. Bill’s been a good friend of
MIT in many different ways for many years. Starting next
September, many of you are going to be
studying, and meeting, and eating in the Gates Building
in the new Ray and Maria Stata Center. Many of you already
are the recipients of the work that
has been done here at MIT under our
iCampus program done and carried out in collaboration
with Microsoft Research. That has really
reinvigorated and reinvented much of teaching and
learning on the MIT campus. But I also want to say in
particular that Bill Gates has been a great enthusiast
for MIT’s OpenCourseWare initiative, something many
of us believe very deeply in. Because it is a way of taking
the knowledge and the pedagogy that is generated
here at MIT and making it accessible to people
in other institutions all around the nation
and throughout the world. Bill is here today
to talk, as I said, about the great
challenges facing the future of computer science. But before he comes out,
I want to say something quite personally. In addition to the work
that we’re all here to hear about today in computer
science and information technology, Bill
and Melinda Gates have done something
extraordinarily wonderful for our planet in the work
that they are sponsoring, to improve health and
to eradicate disease throughout the developing world
and improve the lives of people who live under conditions
that none of us in this room can even imagine. So please join me in
welcoming Bill Gates. [APPLAUSE] GATES: Thank you. Well, it’s great
to be here at MIT. MIT has invented so many things
and played such a key role in the advance of
computer science. I won’t have time
to name them all. But Microsoft has been very
privileged to be associated with MIT and in
helping collaborate on a number of projects here. Microsoft is also– has
some great employees who came from MIT. Most notably, people like
Gordon Bell, who’s doing some– still very creative after
making so many contributions. And also, Butler
Lampson, who’s actually back here teaching
courses as well as continuing to help Microsoft. The main thing I
want to present today is how I see the next 10
years of computer science as doing some really
amazing things, solving some problems that have
been out there for many decades and transforming most
things of interest, transforming the way
people work in businesses, the way they deal
with information and meet and
communicate, transforming the way that people at home find
information, the way that they create things and connect
up with other people and transform even the sciences,
bringing the methodologies– machine learning, and
modeling, and rich data mining into all of
the hard sciences and allowing those scientists
to move to the next level. It’s a paradox to me that
computer science today is poised to do all
these amazing things and yet, in some ways,
people’s expectation and even the excitement
level about computer science is not as high today as it
was, say, five years ago, when we were in the midst
of what we can now look back and say was the internet bubble. Many of the challenges,
the problems, the things that were hard to
live on during that period are exactly the kind of
things that a combination of great academic work and great
commercial work coming together has solved. And we’ll make sure that the
productivity advances that we see in the economy will
be dramatically higher, more than double what we
received in the 1990s. And that’s very profound
for innovation, employment, many things on a global basis. The computer industry
started by making very big, expensive machines. And in fact, when I was young,
people thought of computers as kind of these daunting
things in the back room that would often print out
bills that would be wrong and you could never
get corrected. People talked about taking
the punch card in your billing envelope and putting
staples in it or mutilating it to somehow
defeat the big machine. And I was lucky enough
to be young at a time when that changed. My friend Paul Allen saw the
very first microprocessor, the 8008– not very capable, but
better than a PDP-8 was. And he challenged me. He said, hey, Bill, could
you write software for this? Could you do a basic? And that really got
us going, saying that we wanted to be
on the ground floor, building the kind of
software that computing would need as it moved from
that back room onto the desktop, as it became a tool
of empowerment, a tool for creativity
and communications. Now, it started in
a very humble way. The kit computer that Paul
saw on the cover of Popular Electronics magazine–
a freezing cold day in Harvard Square and
brought back to me and said, you got to drop out. It’s happening without us. That machine was laughable. It at most had 8K of memory– had no peripherals
to the software we wrote– would flash
lights and do funny things. It was a major discovery
that because of the noisiness of the electronics in it,
that we could actually put a radio nearby. And if we did certain
construction patterns, cause predictable music
to come out of that radio. And it was kind of
limited what we could do, but that was the beginning. And the kind of
excitement around that, thinking where could this go? That got our industry
off to a great start. There was a generation of
machines that came after that, the so-called
[INAUDIBLE] machines– TRS-80, Commodore 64,
Apple II, all of which included Microsoft BASIC in
as their fundamental software. It was the equivalent of
not only the language, but the operating system. Everything. And you could type
in basic statements to do graphics, and games,
and business software. And we even gotten disks
connected up to these things. We moved away from cassette
tapes and paper tapes to these ridiculous
8-inch disks that hardly held any information at
all, but constant improvement. A big milestone in 1981 was
the entry of IBM with the PC into this business. And that had been a joint
project with Microsoft, where we’d convinced
them to use the 8086, created the DOS
operating system. Very limited system, but very
appropriate for that machine. And we kicked off an era
that was fairly different. Because starting
with that machine, we had a vision that we
wanted all the machines to be compatible. That is to use a
software layer to make it so that whenever you
wrote an application, it would run on machines
from IBM, or HP, or Digital Equipment, or
any of the other computers at the time. And that hadn’t been the case. And in fact, that prevented
the virtuous cycle that we wanted to have happen. It prevented it
from getting going. And that cycle was that as
more people saw applications that were meaningful to them,
they would buy machines. The more machines
that were bought, the more volume of
components would happen, the lower the cost those
components would be, and the more people would
invest in buying applications. So it would make sense to really
build a software industry. There essentially was
no software industry before the PC. There were about 20
different companies. And the highest
award in the industry was one that you got
for selling a thousand copies of a piece of software. It was called the ICP Award. And I filled out the
application after we’d sold two million copies of BASIC. I sent it in. And they said, well, we’d
love to give you this award, but there must be some
scientific notation error here. You’ve got too many zeros. And I said, no, I’m not kidding. We sold two million copies. And they said, well, geez, how
come we haven’t heard of you? And we said, well, I don’t
know where you’ve been, but we do have this very
high volume, low-price model. So we’re not like on
the New York Stock Exchange or anything, but we
have sold two million copies. And so personal computing
gained the momentum. It gained in excitement. One of the great
issues was the move from character mode interface
to graphics interface. It may seem strange today. Everyone takes that for granted. But the cycles
required, the difficulty of writing these programs
made a lot of people say, hey, we don’t need this. That’s just frilly. Too many icons, too many fonts. Let’s stick to
the serious stuff. We’d love these monospaced
characters up there on the screen. And there were about
six or seven years, where taking some of
the pioneering work from Xerox, Apple,
and Microsoft really pushed forward with this
idea of graphics interface. And that became– Microsoft Windows was integrated
in the operating system. And then we got to
the next frontier. That frontier was connecting
all the machines together. And year after year, we’d
always say, email is coming. Connectivity is coming. Online services are coming. And in fact, it didn’t
happen and didn’t happen. And then all of a sudden,
coming out of the university environment, the standards
of the internet exploded, along with the decrease
in the cost of optic fiber and the increase of the
speed of the network. And a critical
mass was achieved. And that was the period
where things definitely went a little crazy. But the gold rush
atmosphere actually accelerated the investment
people were making and raised the awareness that
people had of what a revolution this was. Now, some of the things that
are hard about e-commerce, or workflow, or modeling, or
making sure these systems are ultra-reliable, ultra-secure– some of those were
revealed as shortcomings that needed software
breakthroughs, needed software advances. And so as we look forward,
it’s kind of a bias I have. But the thing that’s really
going to make a difference is software. It is new generations
of software that let us interact in
natural ways, that connect these devices up in new ways. And problems that I see being
solved in the near future. Now, the hardware guys– I have to give them credit. They’ve always provided a
more powerful platform for us to exercise our software
creativity against. And that’s why Paul Allen
and I could say back in 1975, personal computers
will be mainstream. The slogan we had was a
computer on every desk and in every home. And in some small part
in some countries, we’ve come a long
ways towards that. It’s not yet the
machine that we envisage in terms of the ease
of use or breadth of things that can be done. But it’s certainly a good
rough draft that’s on its way. The hardware people have
given us Moore’s law that predicts doubling
in chip performance every 18 to 24 months. That’s held true
these last 25 years. And something like the
next 10 to 15 years it’s very likely to
continue to hold true. Now, that increase
in transistors– there are some very
interesting software techniques related to
parallelization that are needed to take transistor count
and map it into performance. It’s not automatic
that just because you have twice as many transistors
that you get that performance. And so finally,
some of these issues of automatic parallelization
and understanding the algorithms that let you do that– we’re making progress on those. The storage people
do an even better job than the chip people. Their doubling rate is
something like 12 to 18 months. And this is very important. Because when storage
was expensive, the idea that you could deal
with photos, and videos, and audio annotation, and
replicate information around, so it’d be immediately available
even if the system’s not connected up to the network. That just wasn’t possible. People didn’t think
in those terms. And in fact, storage
is so available now. We have to be creative
in thinking about what we’re going to do with it. We’re getting lots
and lots of that. In fact, a good example
of how cheap storage is, is that we have this device
that comes out this fall called the Portable
Media Center. It’s a 4-gig disk,
beautiful LCD display. And you can just connect
this to a PC that’s recording TV shows, or has your
movies, or whatever is there. And it automatically downloads
the movies, videos, photos onto this device that you can,
of course, carry around and use any way, anywhere you want. And these devices will come out
fairly inexpensive in the $400 range. And the price will
just come down, and down, and down, because this
is the magic of that hardware innovation. Eventually, we’ll just
take it for granted that kids who want
to watch movies, or people who want to watch
shows have this available. And so it won’t just be portable
music players, but devices that deal with the video as well. The screen is
another place where innovation is critical for us. If we think about
how we can move reading from paper to
the screen so that we get the rich searching,
updating, annotating, sharing that the digital
world allows, that requires screens with
very high resolution. It requires screens that we’re
comfortable holding in our lap and just sitting there paging
through the information. It requires a thin-like
device, long battery life. Big challenges. But certainly what’s
gone on with LCDs and other screen technologies
says that in the future, we can assume a 30-inch
LCD on a knowledge worker’s desktop or three
22-inch displays, which is the configuration
I’m using right now and lets me work
with information in a much better way. In the same way that a newspaper
gives you a big, wide field of vision, this does that. And there are
certainly some advances in Windows management and
use of the screen area, that it has to take place as
we get to extremely high DPI in big screen areas
that come with this. And we believe that reading will
move onto the digital platform, that the superiority of the
cost structure, all these things argue for that as we get
devices that are based on this new screen technology. A nice milestone in that is
the arrival of the tablet PC. That got kicked off
about a year ago. It’s based on the
miniaturization hardware, the ink software. Ink recognition
technology that we’ve been working on
for over 10 years is now bootstrapping in terms
of the quality of the hardware, learning from that software,
doing that better and better and making that mainstream. And so all the portable devices
will become tablet devices. And they really will
be like tablets, which they’re a little bit
heavier than a tablet today. The graphics processors–
there the improvements are you can get higher
transistor counts there because the number of
duplicated components. And actually, if we look to
the future of CPU architecture, we can see that more
predicted by what’s happening on the GPU level. Because they’ve thought
about parallelization. Now, they do it in a
domain specific way that we need to open up. But it’s really the
blending of those that is the next stage there. A big element, of
course, is wireless. As we get things like
ultra-wideband wireless, which is hundreds of
megabits, the idea that you connect a
computer to the screen will become obsolete. The computer will find
the screen that’s nearby and take advantage of it. The idea that the
computer and the storage have to be associated
with each other– there’s no reason for that. You can carry your
storage with you. And whatever PC is around
in a very secure way, your storage can be
made available to it. And you can be given guarantees
that that information isn’t left on that machine after
you log out from that machine. So we’ll see the desegregation
of the PC that way. We’ll see the arrival
of rich new peripherals. Digital cameras are now the
most popular way to take photos. And that’s happening in
the motion video space. Well, those devices will
have ultra-wideband. So they’ll mark not only
the time, but the location of that information and deliver
that to your storage system. Your storage system
would be a combination of data stored in the cloud
in sort of a far-sight, ocean stored-type way, where you
don’t have to worry about whether you’ve backed it up. Because there’s many
copies, but that are stored in encrypted
ways that mean only you have control of
that information. Or you’ll have the
storage that you carry with you physically
that’ll give you total control over it. And making those two
things work well together is very important. Now, in the area of wireless,
one of the top challenges has been the cost of broadband. When we think about what’s
expensive, getting a PC, say, into rural India. And the hardware is 3 or $400. The software is less than $50. It’s that broadband
cost, the monthly cost of paying again and again and
getting that infrastructure out there that’s really
the prohibited factor. And we believe through some
software techniques around mesh networks and some advances
in the wireless hardware, particularly the WiMAX-type
approaches bringing in not just
omnidirectional approaches, but directional antenna
as well, that we will get the kind of
connectivity that can make sure that connecting everyone on the
planet becomes very feasible. So you’ll have a
range of devices– wall-sized screen devices,
desktop, tablet, pocket size. We even believe in a
wrist-sized device. In fact, I’m wearing my SPOT
watch, which just came out in the last month. And this– I don’t
know if you’ve seen it. It lets you see
sports activities, stock prices, your schedule. You get messages on it. A lot of different
things that are being transmitted to this watch. It was actually when I was
at MIT over 10 years ago that I first saw a demonstration
of FM sideband data networking. And this watch is
based on that approach. Of course, the
modulation techniques are several generations later. There’s a microprocessor
in here that we paid National Semiconductor to
create that’s based on the ARM architecture. This microprocessor
just on my wrist has 10 times the power
of the original IBM PC. It’s got 10 times the memory
of the original IBM PC. Now, this thing is powerful. And of course, the
battery life is on the order of many, many
days, because these things are low power. We can download arbitrary
programs to this device. So as we get new ideas
about sports presentation, information
presentation, as people have neat things
they want to do, it can come down in
an automatic way. Today the watch is
in receive-only mode. But we actually
have the capability to send data as well
in a local area. And so you can find people
with common interest. A lot of applications that the
glancible information platform will be particularly
appropriate for, working with the other devices. Now, we have to think
in terms of scenarios– the photo scenario that you
use all the different devices, the scheduling scenario
using all those devices. And it’s way too
far today to get those things to work together. One of the big places that
software advances will change things is the
way business is done. The information visibility
that a typical information worker has is extremely low. They’re used to it in a way,
so they don’t know to complain. But their ability– say somebody
gives them a sales printout. They look at these numbers. And they must think, wow,
that one’s really big. Wow, what did we do? Now, that one is kind of small. Geez, are we in trouble? Well, their ability to
just dive into that data and see it by time
period, product, cost structure–
they don’t have it. It’s not there. The schematization
and model approach to bring that down
to every employee to just naturally expect that
they can see those things and understand those
things– that’s not there. The world of
business intelligence hasn’t delivered on that. The XMLFoundation that’s
advanced so fantastically over these last six years is the
foundation to make that happen, to build XML into
the spreadsheet, to build a knowledge
of business processes, so you can visually see, what’s
the state of this activity? Businesses today do all
these custom modifications to the applications
programs they run– the enterprise applications. And it’s very strange. Because the differences
between those businesses– you ought to be able to express
it in some other way than code. Code is complex. When people update
the applications, you don’t know how to
combine that new code with the other code,
because it’s not orthogonal. There shouldn’t be
code in that process. There should just be
visual business processes that you’re connecting up to and
explaining how this business is different than this business. How does the order process work? How does the collection
process work? How does the analysis
process work? And that’s kind of the thing
we’re really on the verge of. Because XML gets our
semantic level up and lets us finally address making this
information really available. If we looked at
meetings, meetings are a source of a
lot of inefficiency. Any information
worker will tell you things that they didn’t need
to be there for, things they– meetings they had to fly into
that they would have preferred to be able to do at a distance. Things that didn’t
get followed up on. Things that somebody
who wasn’t there. You wanted to explain to
them that you couldn’t just link in and see the transcript
or see the video of what went on there. Well, storage is almost free. And cameras and software to
scan and understand this stuff will be almost free. And so we can take the meeting
and have that be something that we bring a lot
of efficiency to. If you make meetings in
general 10% more efficient, that’s tens of billions of
dollars of X for productivity every year. And that can be used
just as cost savings. It can be used to
make better decisions, to drive quality into processes. And it will do every
one of those things. Even the basic process
of buying and selling hasn’t been made as
efficient as it should be. Can you find all the sellers of
a particular type of product? Can you check their reputation? If you engage in
a transaction, see the state of that transaction
in a very rich way? If your computer is
talking to their computer and their computer
is somehow malicious, are you protected from
that kind of behavior? If the software is talking
to the other software, what about the workers? Say that there’s a
delivery that’s defective. How do you coordinate
the negotiation on email in an ad hoc way with
these back end systems, so they can understand things
and check the state of things? These things are incredibly
inefficient today. So basic workflow
is not built in. E-commerce has not happened. E-commerce only really
happens where every seller can find every buyer. Every buyer can find every
seller independent of location or previous knowledge
of each other. And that rich transaction is
done in a pure digital way. In communications,
what we’ve got today is kind of a hodgepodge
of different things. The latest thing is blogging. That comes after
instant messaging, which comes after email. You’ve got your wireless
phone, your wired phone. Lots of times
you’re interrupted. The phone rings when
you don’t want it. Things come into your
inbox you don’t want. And your time is
a scarce resource. And so these activities
are wasting your time, causing a lack of productivity. Even in some cases,
you have enough spam that you filter out
or don’t have time to read mail that would
have been of value. Now, for me, spam– it’s this awful thing. But sometimes when I look
at these spams I get, I have to just step back
and laugh about them. I’ve got a few examples here. This is one of my first ones. [LAUGHTER] [APPLAUSE] And it’s clear once
I get out of debt, I’m going to be meeting
a lot of nice people who are going to
be friendly to me. The next one looked like
it might be more targeted. And this is not
one that any of you need worry about, since I
hope you won’t drop out. And finally, there
was one that really related to a serious
cost problem I’ve got. The shareholders really want
me to dig into this one, understand what’s
going on there. So it’s a serious problem. But it’s amazing the
things that are out there. Letting people send billions
of pieces of mail very, very cheaply devalues the time
of the person on the other end. And this is a very
solvable problem. We need mail that
comes from people we communicate with regularly
to be authenticatable. And we announce on Tuesday a way
of doing that, leveraging off the DNS that we think
can be applied and used as a standard,
literally within months. Mail that comes in
from a stranger– some type of proof is necessary. If the filter thinks
that looks like spam, then you need some type
of proof to distinguish it from the other email. And there’s several forms
of proof that will be used, and they all work in parallel. Any one of them is kind
of an “or” condition. Proof that’s
computational, where you solve one of
these problems that’s asymmetric in the opposite way
that cryptographic functions are. That is it’s asymmetric in the
sense that checking the answer is easy, but actually doing
the computation is hard. And so for somebody sending
a modest amount of mail, it’ll just happen in background. They won’t notice it. But if you were sending
millions of emails, it would be a significant
computation cost to do that. So you screen out. Human interactive proof where
you bounce back and make somebody solve– it’s something
that software alone can’t do– is another approach. Or if there’s a connection
into a payment system making somebody put a little
bit of money at risk, not that gets charged to
them– and this is only email from strangers,
but that is at risk. So that if it really is junk,
the person who receives it and spends time reading it– at
least they get the benefit that whatever the threshold
they set for their time, their inbox rate– that gets credited to them. But if it’s their long
lost brother or somebody saying their house is
on fire, hopefully they won’t debit that. They’ll say, okay,
that was just at risk. And I’m glad that person
can’t connect it up to me. In the home environment when we
think about media and memories, there’s so much
that can be done. And yet, we’re going to have
to deal with a lot of volume– all the music you
like, all the movies that you’re interested in, all
those photos that you take. It’s kind of amazing. We have a researcher at
Microsoft Research who wears this– as they go
around in the day– something that’s just a camera. And it notices when
there’s a big scene change, or when there’s people laughing,
or anything loud or something. And it takes photos. So at the end of the
day, that researcher has over 100 photos
that might be interesting to
put in her journal and save and even annotate
with some voice or something. But software has
got to help select which one of those
things are interesting and to navigate
amongst those things. And so there– a lot that
has to be done on that. We want to put users
in control in the home. This idea of watching TV
shows only on a schedule– slowly but surely
that’s going away. People use that. Whether it’s built into what
we call the Media Center PC, or a TiVo, or the
satellite receiver– get very addicted to it. It’s kind of like email
where it’s not perfect, but you don’t want
to give it up. You just want it to get better. And so as we think
about that, we think about what
kind of interfaces would deliver on that. And in fact, I’ve got just real
quickly a couple prototypes from Microsoft Research. I wanted to give
just a sense of this. In fact, these were both
done by an MIT graduate. The first one here is
pretty straightforward. Let’s say you’re
looking at movies. You’re looking at
Blade Runner here. And what it shows is– okay,
the director is Ridley Scott. Well, then I can go over here
and see other movies directed by Ridley Scott. And I can just
select one of those– Alien. That’s brought to the center. And of course,
then all the things related to that come out. And I can see–
okay, these actors and see the different
things they were in and see if one of those
might be interesting. And just pivot
through these sets of movies in a
simple, visual way. Of course, this will be
annotated with the reviews that you trust,
comments from friends. If you’ve seen the movie,
what you thought about it. And so very navigable to get
around the movies of interest. The other one I wanted to
show has to do with photos. And photos– we’re dealing
with lots and lots of photos. Literally, if you take your
lifetime, tens of thousands of photos that you and
your friends are sharing, and you’d like to be able to
get back to in a rich way. And so here we see
them as miniatures. I can just hover
over these things. Lots of photos. We’ve even mixed in
video clips as well. Here’s Gordon Bell at
the Computer Museum. Because we don’t think the
boundary between stills and motion will hold up. In fact, these audio
comments that we call photo stories bring a
lot more emotional connection to that experience. And so it’s just like this. It’s hard to find
exactly what you want. And so people will take
these things with keywords. Here is things that
relate to Thanksgiving. We can do software analysis. And so if we want the
photos with faces, we just select those. If we want the photos
that are indoors, the software can select those. If we want the outdoor
photos, we can select those. If we want to see
photos that are similar, let’s select this bridge
photo and say, okay, I can relax the constraint and
say, what’s similar to that? Okay, that’s a lot like it. That’s a little
bit more like it. And I can select groups
of things to be used. This software automatically–
when it brought the photos in, helped orient the photo
by being able to recognize the cases where
things were kind of– at least of the software looked
like they might be misoriented. We can also start
to use a 3D way of looking at these things
to group these things. And what that means– now, this is by timeline. So I can select a
set and take these. I can change the timeline,
get to finer groups in terms of when they were
taken or where they were taken. And this makes it very easy
to just step through these, but also deal with groups that
I want to organize and take in different ways. So in a general sense,
we can say, well, that’s just a database. But we need much better ways
of interacting with a database than just the common
query processor. People won’t be
writing SQL statements to navigate through
their photos. Now, this optimism I have
about computer science and its impact– a little bit the proof of
how serious we are about that is the R&D spending that has
been increasing at Microsoft. Today it’s $6.8 billion a year. It’s kind of an intimidating
number, at least to me, since 10 years from now people
will say to me whether that was wise or not. But I’m quite
confident that it is. That’s the largest technology
R&D budget that there is. IBM is about 20% less than that. But of course, not all
folks own software. And then other
commercial entities– you’d have a big drop down,
particularly if you take the long-term component– the equivalent of
Microsoft Research. We actually do our research work
in three different locations– in Cambridge, and in our
headquarters, and in Beijing. We have smaller groups
in some other areas, but those are the primary areas. We’ve had, as I mentioned
earlier, a strong collaboration on a number of things with MIT. For example, the
iCampus project. We’re a key partner in that. And I’m thrilled– the things
that are coming out of that. Some involve learning
at a distance. Some involve the tablet PC. And the idea that we can make
learning better– there’s no doubt. And I think that’s a
great planning project. Natural interfaces–
I’ll throw in. And that’s this
magic paper idea. That’s a fantastic thing. And we’ve gotten involved
in things that think. We’ve got a lot of
people on the faculty here that are helping
drive our agenda. For example, Victor Zue, who’s
on the technical advisory board for our group over in Beijing. So it’s been a good,
strong relationship. And the progress being
made in the combination of academia and
commercial research labs is really fascinating. It’s phenomenal and it’s not
getting that much visibility. And yet, these advances are
extremely relevant to problems that we have– the problems
that are of critical importance. Take for example, security. Of course, MIT has strong
programming on that. Of course, you’ve
got Professor Rivest, who just got the Turing Award,
which is a fantastic thing. Security is something
that if we’re going to achieve the
potential, these systems– has to get a lot better. And that’s a tough thing,
because code reliability gets into that, how you
configure up these systems. How you watch behavior
is part of that. So it’s going to take
some breakthroughs. Over 25 years ago when
I was leaving Harvard, this idea of proving
program correctness was sort of in vogue. And unfortunately
for many years, although there
was some progress, the scale of the program
that could be played against didn’t get very large–
hundreds of lines of code. And now, working
with universities, people in Microsoft Research
are taking literally things that are a million lines
of code and being able to go in and prove
very important things about those programs. Or if they can’t
prove them, they’re able to show the
counterexample that says, yes, this can touch memory
that it shouldn’t touch, or it can acquire the lock
and never release the lock. And so you see exactly what the
pattern is and how to fix that. Now, all this
proving technology is having a wonderful
effect on innovation in programming languages. Because we want
to take everything that the programmer
knows about the data types and the
constraints and express those in as high a level,
as strong in fashion as we can through contracts. And this idea of expressing
the contracts very easily, having languages that are very
explicit about those things– that takes all the theory
of language innovation and brings it into the
mainstream and says, we really need
those capabilities. Keeping systems up to date,
being able to look at a system and say, is its behavior normal? We need this both at the
single computer level and looking at the network. Is there a type
of traffic that’s exploded in terms of
usage, at a time where the overall traffic is starting
to be too heavy for the network to do it? There should be automatic tools
out there that are doing that. And in fact, machine
learning techniques that build the model
of typical behavior. And then see these
things that are unusual will be used at every
level of the system– at the memory management
level, at the API level, at the network sending level,
and the wide network monitoring level. And we call that
behavior blocking. And that’ll be a
critical component in solving those
security issues. Another set of
areas that I think are making wonderful
progress are getting a more natural interface
between users and the computer. Victor Zue here has been
a big advocate of that, building some
wonderful systems that take speech all the way
up into particular domains and let people
interact with those and making it so that it’s
not a huge technical exercise to build one of those systems. That you just have a general
runtime for that, I think, is something that will be
solved in the years ahead. The prowess in speech
recognition is very good. If you take a isolated,
simplistic case where there’s no
context and no noise and a perfect microphone– three great simplifications–
the difference between a human and a
computer is not very drastic. It’s as we relax
those constraints and bring in context– crummy microphones and noise– that then the divergence between
the computer and the human is quite substantial. And of course, human
users of these things are very demanding. Because speech doesn’t
operate at a conscious level, as it makes mistakes, you just
get irritated and talk louder. And of course,
it’s been trained. It’s learned you’re
speaking in normal tones. So it just gets worse and worse. And so it just generates while
you’re yelling at the system. Now, ink is not quite the same. It’s a little easier
because you process ink at a conscious level. And so although it’s irritating
when it doesn’t work, you can look and say, well, how
could I have recognized that? Is that E looped so closely
that it looks like a C? And in fact, as we monitor
people using our handwriting system, the plasticity is
partly in our subsystem. But a lot of it’s in
the user, that the user consciously or
subconsciously is actually writing more explicitly
the features that have caused the problem in the past. So that’s one where– that’s partly why ink is
coming into the mainstream, say, a few years in terms of
general input, the equivalent of dictation a
little bit faster. The place we’re seeing our
speech work really catch on is a combination of people
where the keyboard is unattractive for
them for any reason, including repetitive stress
injury or people in China, Japan, or Korea, where the
keyboard is relatively less effective as an input technique. We can already beat the
fastest typist of Chinese with a Chinese speech
recognition system. And so now, that’s a
milestone along the way that is pretty exciting. General artificial
intelligence– this is the holy grail. And when I was talking
to faculty today, I was impressed
that MIT has kept its commitment to this area
and throughout all the years. And it is one where
some very interesting approaches–
statistical approaches, Bayesian approaches
are now starting to be used in
different fashions. The actual product on the
market that apparently is a spin-off related
to a professor– here’s the thing that goes
around and vacuums the rug. And that’s pretty low
level, better than nothing. But we want to move up in
terms of the things that go on. For gaming, one place we’re
using our machine learning technology a lot is
we, on Xbox Live, can watch player behavior
and different strategies. And the machine can learn. And so if you want
to pick an opponent– typically if you play the
computer historically, it’s a road algorithm that
isn’t that much fun to play, because eventually you see
that as being very predictable. We can take all the
play styles that we’re seeing across this
network and create any sort of level of difficulty
or different fashion of play and make it as interesting
and as varied as playing with human opponents,
including letting you win every once in a while,
which on video games for me, that is pretty tough. You pick these things up. And they are geared to– well, to you and not to people
who haven’t used them nearly as much. And so we’ll make
these things appeal. And even if you start
to beat the system, boy, we’ll crank
it up to a level that will keep it challenging. So AI is going to be applied
in a lot of different ways– modeling things in
the other sciences happening with dynamic
behavior and systems– very, very important. All the natural interface
techniques– vision, speech– we’ll come to take those for
granted in a very strong way. Now, the boundary
between computer science and the other
sciences historically was a fairly hard boundary. And that is breaking down. One great example of
that is the research. We have Jim Gray who
looked at astronomy and said, boy, there’s
a lot of data there. And a lot of the advances
come in proposing something that you can either
validate by looking at that data or invalidate. And so we really need to get
all these databases connected together. And the semantics and
our very high level– it’s, again, not just
a relational problem. But collaborating with
a lot of astronomers who know the domain, he’s been
hooking up those databases and now navigating through this
logically connected database– is a very important
tool in astronomy. And many of the sciences are
going to where those rich data collections are necessary
for everyone to have access to in a high-level way. Biology, of course, is perhaps
one of the most challenging, because of the breadth and
the differences in the data. But even there, this
is starting to happen. And I had a great
discussion with some of the faculty who are
pushing off in that direction and really seen that the
boundary of computer science and biology are very
much coming together. And we need people who
understand both of those things to make advances in
solving diseases. And I’m very optimistic
about how fast that will move forward. Now, this tool that we’ve got– the PC connected to
the internet and all this great empowerment– it’s
such an important thing that we do have to worry that there
are people who are benefiting from this and people are not. And people talk about that
as the digital divide. It’s something that I think
people in computer science should care a lot about
and in various ways contribute to trying to
minimize that difference. One of the projects
that Microsoft got involved with together
with my foundation was saying, well,
what about libraries? Would it be appropriate
to have computers there? And we were a little
worried about this, because would the
librarian like it? Would it be at the
expense of the books? Would kids come in and
just hack up the machines? Would they be doing
enrichening things as they were using
those computers? It was unclear. But six years ago,
we kicked it off. We did pilot projects. And over six years in all 50
states in 18,000 libraries in a rural– everywhere in the country, we
put in over 50,000 computers. And the response of
librarians was just phenomenal of wanting to be trained,
wanting to reinforce the role of that library. And traffic to the library
increased, not just to come use the computer, but
also the number of books that were being lent out. And we were able to
monitor and support all these things in a
very efficient way that made it work very well. Throughout the project,
we learned things. We came up with a
version of the software. You can just hit a button to
switch from Spanish to English for a lot of these libraries. We had a button you can just
hit to switch to big print. So if you don’t like
reading the fonts that we typically use– boom. All of a sudden,
it’s a lot better. We came up with
things to help people with the common scenarios. And so it’s great to see if
you give people those tools, they’ll use them. And it really makes a
big difference for them. Getting these tools
out to schools, getting them out to all
different countries– a lot of challenges remain there
that need to be addressed. We think about computer science. One thing computer science
has done through the internet, through software– it’s made
the world a smaller place. In fact, people
now worry that this is going to create a new
level of global competition. And the answer is it is. People’s opportunity to have
great jobs in the future will be far more determined
by their level of education than by what country
they happen to be in. Historically, your education
level didn’t matter that much. If you were in a rich country,
you made a lot of money. And if you were
in a poor country, you made very little money. Now, the opportunity
for educated people worldwide to help out, to
contribute to products– not just software products,
but anything you can imagine– architecture, law,
answering the phone– it will be done where
people have those skills. And as people look at that, they
go, wow, what does that mean? Well, it means the US has
to keep its edge in terms of doing the best work. And that means research. It means intellectual property. It means improving the
education system, rededication. It’s very similar to what
happened in the 1980s when there was a lot
of angst about Japan. Japan at the time
appeared to have a model where they would just
pick an industry– the car industry, the computer industry,
the consumer electronics industry. And boom, they
would do it better. And the great
thing that happened in the ’80s was there was a lot
of humility, a lot of thinking, well, do we just match what
they do exactly that way? Or do we just push
forward on our strengths, our approach to things? During the ’80s, they
did this AI project. And it really– because
of the way it was done, it wasn’t done in the
diverse academic approach that we use here. It really ended up
not generating much. So we dedicate ourselves. And it’s actually the work
done during that period that led to that
productivity increase that benefited all
countries, but the US in particular during the 1990s. And I see that same
thing repeating itself as we question our
unique role and reinforce what needs to be done. One challenge that we have
in the field– in all science fields, but particularly
in computer science is the issue of diversity. To do the best work, we want
to draw on everybody’s talent and give everybody
a deep involvement. The variety of jobs, the
need for great people is pretty phenomenal. And the diversity numbers
in some professions like law and medicine have
been going pretty strongly in the favorable direction. One thing I’ve personally gotten
involved with to try and help push this forward is a
scholarship program that’s called the Gates
Millennium Scholarship. And here at MIT– out of
actually a thousand people who get those scholarships,
60 people are here at MIT. So it’s a great thing and
a real endorsement of MIT, that there are more Gates
Scholars at this school than at any other school. Now, these science
problems are tough, but they’re fun to work on. The jobs that are
involved with them are– you can have an impact. You can work with other people. It’s not just somebody
isolated, off coding all night, although if you want to
do that, that’s fine. We still have lots of
jobs that are like that. And so the sense of
reward, being involved in changing business,
changing entertainment, changing education, giving tools
to those new science sciences, including to help the disease– I think that’s a
phenomenal opportunity. And so that’s why I’m more
excited about computer science than ever. And I’m very excited
to see what some of you here can do, taking
that to the next level. Thank you. [APPLAUSE] MODERATOR: Thank you very much– interesting and fun. Now, maybe we come to
something– will also be fun. You’ll all get a chance
to ask him questions. I’d like to get as many
questions in as possible. There are microphones
in each aisle. So if you want to ask a
question, go to a microphone. And two up, please. And do me a favor. Have your question end
with a question mark. So it should actually
be a question and try and keep it
as short as you can. And then when you’re
done, go take your seat and give Bill a
chance to answer it. You’re up. AUDIENCE: Could you
explain to me .NET? I’ve seen a lot of
things about .NET– Never really understood
what it does, what it actually accomplishes. GATES: Well, there’s a
revolution in how information is represented around XML. And that’s something that
we and a few small companies got behind, now seven
or eight years ago. And in the year 2000, we said we
were really betting our company on taking those
XML representations and having some protocols
around them that are now called the web
services protocols, making those standards. Standards that would
exist on any operating system, any language
and letting those be the basis for
deep interoperability for applications like
e-commerce that I talked about. And so .NET is us embracing
XML, embracing web services, and building that into
the Windows platform. And it means building web
services and XML into Excel, building it into the
SQL Server database, having Windows use that to
be the way that you set it up and manage it,
so that management isn’t a set of
protocols, or approaches, or APIs that are separate
or off to the side. So bringing .NET to all of our
products and connecting it up this way is something that’s
a very broad project that we’re about 60% of
the way done with. And when we made that bet, it
looked like a very risky bet. But I have to say at this point
with the cooperation on the web services standards, the
excitement around XML– it’s not a bet that’s
risky at all at this point. AUDIENCE: Thanks. MODERATOR: Thank you AUDIENCE: Thank you for coming. If you were 19 years old again
and let’s say this time around, today you’re at MIT, and
Microsoft was already founded. Would you continue
your education and/or create a new company? And what type of
company and why? GATES: Well, I loved
going to school. MODERATOR: He didn’t go to MIT. GATES: But it was very similar. There were very smart people
around to talk to every day. They fed you every day. You didn’t have
to go to classes. If you worked a
little bit, they’d give you this positive
reinforcement, these grades every once in
a while to encourage you. And so what had
happened was my friend, Paul Allen, who saw
this microprocessor and really egged me on,
had come out to Boston and taken a job out
here at Honeywell to say to me every day, it’s
time to start our company, it’s time to start a company. Well, he didn’t
succeed until he had that cover of Popular
Electronics and said, it’s going to start without us. Let’s be the first. And so then officially,
I didn’t leave school. I went on leave. And I’m still on leave. [LAUGHTER] In fact, when Harvard has my
name in their publications, they always put ’77 after
it as though I graduated, which of course, I didn’t. And so I’d say that if
I was a student today, I’d certainly be looking
for some paradigm shift that could make a dramatic change. I don’t know if I’d work in
AI, computational biology. Those are two that
I really love. And I’m glad to hear
those are– there’s a strong increase in emphasis
in those things here at MIT. But I’d say that anyone who has
in mind a deep paradigm shift for an industry, go ahead. Take the risk. Go away for a couple years. And MIT will probably
let you come back if it wasn’t the paradigm
shifting thing that you’d hoped it would be. AUDIENCE: Thank you. MODERATOR: Thank you. AUDIENCE: Many people
consider you an inspiration. Who is your personal hero? [LAUGHTER] GATES: I have many heroes– people that I’ve been
lucky enough to work with, from my parents to a lot
of people at Microsoft. One that I’d really
highlight is Warren Buffett. His way of looking
at the world, looking at how business should be done,
showing that you can have fun while doing a very
important, tough job. He’s had an incredible
influence on me. And it’s part of the
reason I say, hey, I have the best job in
the world, because I can– I have had a chance to
meet somebody like Warren and get his advice
and his humor, which is really, really unique. MODERATOR: Please. AUDIENCE: Hi, how do
you feel about software patents and their role in
either promoting or stifling innovation? And are you concerned
about them long term? I know that Microsoft got sued
a little while ago for that. [INAUDIBLE] MODERATOR: Really? GATES: Oh, we got sued. It’s interesting because
we’re on really both sides of this patent thing. We, because of our
success, are a target for patents, some of them not
as good as they should be. And we’re also a company that
files lots and lots of patents. We file more software patents
than any other company. The patent system
is not perfect. And I think any freshman could
look at the patent system and suggest improvements
to the patent system. But it’s a system that
has worked amazingly well, despite its mistakes
and its problems. Over several hundred
years, starting with Benjamin Franklin, the kind
of incentives for invention, the creation of the
biotechnology field– is that a good thing? The pharmaceutical industry–
is that a good thing? These are industries that the
US leads in and have created immense improvement in human
welfare and all based on just taking the patent system
as it was and using it, so that as they would
do innovative work, there would be some
incentive there. And so I think we absolutely
can improve the patent system, but it’s something
that is important. And particularly if we look at
global competition, the things that generate jobs here or help
the US be a strong leader– a lot of that is that if
we’re super innovative, there’s a reward
that goes with it. AUDIENCE: All right, thanks. AUDIENCE: So there’s a
really interesting trend that I think you
started to touch on, but you didn’t dive
very fully into, which is the commoditization
of software and software innovation. And what I was wondering
was, how do you see Microsoft kind of
fitting into a world where software is cheap and
produced at very low cost? And what do you have to say to
your current and prospective fleet of software engineers? GATES: Current? AUDIENCE: Current
and prospective fleet of software engineers. GATES: Oh, great. Well, yes. Software has this
interesting property that unfortunately
it never wears out. And so when we sell somebody
a copy of Windows and Office, they can just use it forever. And they don’t owe us a dime. It’s theirs. They get to use it. And so all we get paid ever– it’s not like Coke where
they get thirsty again. That’s a good business. But it’s not as fun to be
in a business like that. All we get paid for
is our breakthroughs. We have to come up with a
version of Office that’s worth licensing,
worth installing, worth learning, worth dealing
with some effect it might have, or it might change things. And that’s our
economic proposition versus all the free
software that’s out there, all the installed base of our
best work of the years past that’s out there. And people don’t have
to pay us a thing for. We have to innovate enough that
it’s worthwhile to license. Now, there’s another way
to look at it, though, which is if you take a knowledge
worker most anywhere, even in Bangalore and Hyderabad,
they’re making $40,000 a year. They’ve got an office. They’ve got phone bills. They’ve even got paper clips. What we’re saying to people
is, hey, pay us less than $100 a year for the
right of that person to have the very best software
to communicate, create, collaborate,
organize their thing. So it’s a percentage
of what it costs you to have that
information worker, to have the very up to date,
the very best software. Is it worth something less
than $100 a year to do that? And when we hire
people, we say, hey, if you don’t think we can
do that, you shouldn’t join, because that’s the standard
we’re held to every year. And so far, we’ve done okay. And certainly, the customers– when I mean the customers,
I’ve never been in a meeting where they say, you’re done. You’re done. They say, hey, your stuff isn’t
easy enough to administer. It’s not secure enough. It doesn’t do this feature. It doesn’t let us do this
customization that we need. So the need for better software
and the impact of better software is super, super high. And the fact that we’ve created
this high-volume, low-cost model works very well. The fact that once
we solve workflow, there’s hundreds of
millions of people who will benefit from that. Once we get the spreadsheet
up to this modeling level, hundreds of millions of
people will benefit from that. It’s a model that has worked
and that I believe in. AUDIENCE: Thanks. AUDIENCE: You gave
us a broad overview of many different
aspects of where you see things going in the future. I wanted to focus on
the digital divide. How did you– there are a
lot of people with money that don’t do nearly
as much as you do. I’m wondering why you found
that very important– if there was a specific experience. And what’s your concrete
vision for Microsoft and for your
foundation, for bridging that divide between the
US and other countries around the world–
developing countries? GATES: Well, Microsoft– its
philanthropy focuses really in two areas. One is that whatever causes
our employees believe in, we match their donations. So if they want to
give to MIT, they want to give to
some local church. Whatever non-profit, we
match that, including they can take company
software and provide that at extremely low cost. The other thing is– the other focus
is digital divide. And this means going to
every country and thinking about, how can we get
computers to be available? It means the Boys & Girls Club–
the thing we’ve done in the US. The library thing
we’ve done in the US. There’s a group
called Empower that provides software to non-profits
and lets them do those things. So for Microsoft, it’s
very much digital divide. My foundation is a
little bit different. And for Microsoft,
why do we do it? Well, our employees love it. It speaks to our
mission of empowerment, that it’s not just empowerment
for people who are wealthy. It’s empowerment for everyone. So it’s a great morale thing. They get deeply
involved, and it builds relationships with
governments and other people we want to work with. For me personally, the
focus is a little broader. Because I didn’t
want my philanthropy to be just related
to that one thing. And I thought I wouldn’t do
philanthropy until I was old. I thought, okay, I’m going
to work and make money. And then I’ll stop doing that,
and then I’ll give money away. And I knew I was
going to give it away. Because I don’t
believe that passing substantial sums of
money to your children is necessarily good for them. They may not agree. In fact, there’s
one story about that where I was in bed this
weekend at 7:00 in the morning. And my daughter comes in and
wakes me up and says, dad, dad. I was using the computer. You got to come. I said, no, just keep
using the computer. It’s okay. No, you got to come. I won some money. And so we went. And of course, it was
one of those contests that you really
hadn’t won any money. They wanted her to
visit the website. And it made me think, geez, we
got to get rid of that stuff. So I had chosen that
my resources are going to go back to
society and in the best way that I can come up with. And that’s turned out
to really be two things. One is world health. That’s the biggest thing. That’s in my view the
most urgent problem in the world at large– very unaddressed. I could speak for
days about that. And then second is
the biggest problem in this country,
which is education. And that’s where the
library program– and the Gates Millennium
Scholarship Program comes out of that. And because of the urgency
of those two problems, I’ve ended up doing something
I didn’t expect to do, which is I have some days
where part of the day I’m trying to make money. And then part of the
day, I’m giving it away. And so far it hasn’t made me
schizophrenic to try and bridge those two [INAUDIBLE]. MODERATOR: Yeah? AUDIENCE: I had a question
relating to security. I guess it’s a
great responsibility and a big challenge, too. My question is more centered
on, I guess, a recent paper by Dr. [INAUDIBLE] about
the monoculture of Windows. You guys are so
popular that basically, if there’s a security
problem and a lot of people have it, first, do you think
that that is a problem? And second, what kind of
solutions do you guys think should be applied to that? GATES: Well, it is not– and if you say, okay, you’re– there’s two types of
security things that go on. There’s people who want fame. And they like to attack
the most popular system. And as we get down the
learning curve of making it so they don’t
succeed, that actually deals with the most
serious security threat. The serious security
threat is not somebody who just wants fame. It’s somebody who really
wants to steal information. And so as we beat the
fame-oriented IQ and drive that regularity down, we
actually create– we’ll create the
first system that’s truly secure that is tested
by lots and lots of IQ and come up with much
richer methodologies that allow that to work. And so there’s
breakthrough ideas that come out of
research in universities that are allowing us to get to
that extremely secure point. It’s a process of a number
of years looking toward. The approach where you
say, hey, let’s have– how many operating
systems do you want? 50? 100? That just says to
a company, hey, your salary data is on a hundred
different operating systems. And applications– people
have to try and write software for a hundred
different operating systems. Oops. Now, you can’t buy
the same applications. That would be monoculture. You’ve got to buy a hundred
different word processors. And everybody else
learned those, but they don’t change data. But what’s the
security statement? All you need is one bug in
one of the hundred operating systems or one of the
hundred word processors, and your salary data
is out to the world. Variety– just say
V equals variety. V increases the threat area. It may slow down the idea of
these spreading functions that are done for fame,
but it doesn’t make information any more secure. So what does the world need? The world needs a small
number of operating systems that have firewalling
techniques, and isolation techniques, and
verification techniques that makes them secure. And in a sense, we’re
on the fastest learning curve moving to that. It’s the most urgent thing
we’re doing and it’s of our R&D. That’s several billion a year,
just focused on that challenge. And so variety is
not the answer. Technology and the
investments we’re making are what drive
towards that answer. MODERATOR: I’m sorry to say
we have time for one more question, so please make it
one that Bill Gates has never heard before. [LAUGHTER] AUDIENCE: Wow,
that’s pretty tough. I guess this is a
finance question. Microsoft currently
has around $50 billion in cash equivalents or
short-term securities, a number that’s going to
reach about $100 billion in a few years. What do you see Microsoft
doing with that money? Or how do you justify
holding that much cash? [LAUGHTER] GATES: I sleep well at night. [LAUGHTER] No, your question is actually
a very serious question and one that we have. The interesting
thing about software is it’s not really based on
building a lot of factories or buying a lot of materials. And going back to the
early days of Microsoft, Microsoft has been profitable. And we never had an
internet business model. It’s ironic that we actually
took the company public at all, because we never– that money is still sitting
in our bank account. We never spent a
dime of that money. It was really just to
get the incentive system for the employees, which
as net has been more generous than any
incentive system that any company has ever done. And so that was a good
thing in that dimension. But it wasn’t to raise capital. And so we’ve
accumulated capital. We’ve done buybacks
over the years. I think we’ve spent
what? $30 billion on buybacks over the years. We’ve instituted a dividend
that was modest at first, then we doubled it. It’s still fairly modest. And as we’re moving
forward, we do need to continually
evaluate this. We’ve tried to manage the
investments and the money very well. But there’ll come a point where
we– either through buyback, or dividend, or whatever
other approach might exist, we probably will change the
balance sheet of the company and make it more pure. Because what we’re all
about is one thing– developing software. And we want– when
people buy our stock or think about our
company, that should be it. It shouldn’t be about how
we invest our treasury thing or anything else. Just about are we– is there that
opportunity in software? And are we the
company seizing it? MODERATOR: Thank you and
thank you for your questions. [APPLAUSE] VEST: Well, Bill,
thank you very much. And of course, you can’t leave
MIT without your very on MIT sweatshirt. GATES: It’s great. VEST: And we know that probably
every university gives you a sweatshirt, but we’re
the only one that’s also going to give you a hard hat. And on the front is a picture
of the William H. Gates Building taken a few minutes ago. GATES: Great. VEST: Good health. GATES: Thank you. [INAUDIBLE] Thanks.

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