A talk at User Group University (1987)

Apple has finally decided that it's a product company what they mean by that

is that Apple one of the companies that

Apple sees itself as being like is sony Sony is a company that creates many of

the markets it sells in I think Apple came to that realization not so much

from the Apple two because the Apple two happened in a in a way where was hard

for them to even see that they had created in some sense a business for IBM

to move into but I think that the the

success of desktop publishing caught

their attention where they realized that oh yes Desktop iBM is just setting up a

2,000 person group in Colorado to do

desktop publishing that's about just about a third of the employees at the

Apple has I think now we realize oh yeah now we what we are is a product company

we're going to listen to customers but we also are going to try and come up

with new ideas creating new markets and see if the customers will go along with

us I like that very much of course because the the idea the the big problem

in all marketing theories where you go out and ask the customers what they want

is that customers almost always say oh I want something just like what I have

right now except with these little things fixed we have to listen to that

but you don't get new products from that a couple of months ago I was reading

Toynbee and the discussion was how do

you judge the worth of a civilization is

it by the quality of their art the size of their buildings the social systems

that they have and I think we 100 years

from now we will be judged yay by the complexity of the audio-visual

equipment we need to put on the presentation that's not much of a

picture is it now what I'm gonna try and

do is

instead of talking about future trends because I don't even believe in the word

trends and instead of just telling you

what I think the future is going to be I'd like what I'd like to do is to just

tell you the way I predict the future when people ask me what's going to happen so that you'll be able to do it

and then I won't have to give these talks anymore so four ways to predict

the future well the first way came about in the early days of Xerox PARC when we

had Xerox executives buzzing around like bees after honey saying what's the

future gonna be like what's gonna happen to us what's going to shape us and all

these things I finally got angry at them I said look the best way to predict the future is to invent it you want a future

come up with a vision and then build it and you've successfully produced the

future because you've simply made the future come out the way you want it

that's what research people are for is to invent the future another one very

sobering thing is it takes at least 10 years to go from a working good idea in

a laboratory to get it out in the outside world this is something I didn't

believe in for many years when I was younger because it was so depressing an

idea but in fact there are many instances of the 10-years story and if

it's a really basic technology like transistors it will it may take 20 years

does a basic technology has to displace the existing basic technology in order

to take hold I'm going to come back to that because one of the implications of

the 10-year idea is that it means that most things are going to happen to you

in the next five to eight years or in somebody's research lab right now so if

you want to know what's going to happen all you have to do is go around the country and visit people in their

research labs and see what they're doing and then you'll know the answer I

brought a satchel full of tapes of various things from people's research

labs and I'm going to show you at the end of the talk a lot of these tapes are older

than 10 years old and the reason for

that I'll explain in the last part of the talk another way of predicting the

future is to realize that what we're

about here is the invent the invention

of new kinds of information media there have already been bunches of information

media invented over the last several thousands of years so if you take

printing as an example there are four

phases to how you make money and how you make money pushes these media through

their four phases the first one is Hardware intensive when the new hardware

is invented you get high margins on the hardware the problem is that's the most

transitory phase because hardware is the

easiest thing for people to learn how to build and once you've learned how to

build it you are making it much more of a commodity item the margins go down you

have competition and so forth and that's really what happened to printing in the

early days of printing they made most of

their money actually on paper the margins on paper it wasn't until the

Industrial Revolution that made paper inexpensive that you started seeing

throwaway media throwaway media like the

novel now the novel have been around for several hundred years as an isolated art

form but it didn't take hold until paper became cheap and we had to go into the

second phase which is the software phase we all know that software is a lousy

business to be in alright because it's inherently a

cottage industry no publishing house has ever been able to sustain itself on

having a captive stable of authors they've always had to go out and most

people in publishing who have been smart going to distribution the distribution

is the first aspect of the third phase which I call service by service I don't

mean fixing things so much but in the

of going from these things which are basically selling items to selling

service you address much more closely this quaint idea that there's actually a

human being at the other end of the transaction and the business that we're

in is inescapably a service business even though most companies that are

selling computer products right now would think of themselves as either hardware manufacturers or software

designers but the urge sort of the the

medium the the forcing function of

networking especially forces us to become a service business and then the

one where you really make the money so if you can hang in there is the fourth

phase which is way of life a way of life i define as anything that

is only noticeable when it's not there so for instance if you walk into ten

years ago if you walked into somebody's office and you didn't see a telephone you would be really surprised nowadays

if you walk into a person's office and you don't see a telephone you would say

oh are you wearing yours now because your phone wired into your t-shirt we're

big on t-shirts down here now so let's

test this out here let's I like everybody in the room to hold up their

personal computer where is it okay some

watches a little calculator okay so I

rest my case I doubt if there's an Apple computer or anybody else's computer in this room and

that means that oh there's one over there well ignore that one

it's what physicists call experimental error I think the point is well made

that there's something about the computer right now that makes it not

it's it's basically not important enough for you to have one with you right now

something about it that causes you to leave it behind one of the things about

it is it's too big another thing about it is that it

doesn't do enough when you make it small so the real personal computer at least

the when I envisioned the phrase personal computer many years ago I

thought of something that you would never leave behind one of the tests at

Xerox PARC we came up with four is it a personal computer which would you be

willing to do anything so mundane with your personal computer as to put your

grocery list on it if you're willing to carry it into you at the supermarket and

then out again with two bags of groceries in other words a personal

computer is something first it is so portable you can carry something else

too because its own not the only thing you're gonna carry and secondly 0.5

herniation per block is not portability so this way of life Bayes is very

important it's the one that I have been

interested in for 20 years of what do you have to do to the damn thing to get

it to be a way of life for people and finally human trait amplification this

is sort of how you predict the big winners this is something I first

pointed out to Xerox many years ago least like to try and do market surveys

on things and I have to tell you what Xerox story that Xerox in the 50s was a

very small company in Rochester and they had developed this obscure technology

invented by Chester Carlson into a machine called the 914 and they didn't

have enough money to build factories for it so they took it to IBM I think it was

in 1956 this is all described by the way four

people are interested in this kind of lore in John des hours book which is

called my years with Xerox the billions nobody wanted this is sort of a perfect

parable of life in the twentieth century so that's our story goes on to say that

IBM Xerox took this to IBM and they said here take this build factories build it

and sell it all we want is a small royalty an IBM scratched its collective

head and said well we don't know about that so they went out and got hired a

consulting firm Arthur D little is Mike

hammer his definition of a consultant is a person who knows a hundred ways to

make love but doesn't have a girlfriend

my definition is it's a person who steals from the smart cells to the

stupid sort of a sort of an inverse

Robin Hood but anyway after 18 months of

carefully doing market surveys and other things consulting firms do Arthur D

little came back to IBM and said nope it'll never sell there's too great a

disparity between it and the a be dick mimeograph machine and nobody wants

plain paper copying and there isn't enough copy volume to sustain copying

and all that stuff and so IBM turned it down and that really pissed Joe Wilson

off who is the head of Haloid corporation in those days and they bunch

of the executives got together they used their life insurance as security this is

the same way controlled data got started by the way out of Remington Rand raised

the money for their first factories and that was about a hundred and twenty

billion dollars ago it's a perfect example of when the technology is

actually new it's almost impossible to go out and do a market survey and find

that there is a need for it because as we'll see in a minute really great stuff

creates a need that's what all the so I

pointed out to Xerox that another way of predicting these things was simply to

look at traits that human beings have

that if the trait was taken away we would call a person no longer human like

communication humans are not natural Hermits we have to communicate we don't

do it just because it's useful we do it because we need to so whenever you make

a communication amplifier and no matter

sort of case law back then was even if it costs ten times as much as the

technology is trying to displace if it's really a better amplifier for

communication it's going to drive it out perfect example is the railroads in the

early 1900's thought they were improving their business by making better track

and faster locomotives they were looking out like this along the tracks what they didn't

see was their competition starting to buzz overhead because they conclusively

proved that there is no way that aircraft transportation could be as

cheap as trains and they were absolutely right and totally irrelevant because

people were quite happy to pay five six seven ten times as much for being able

to get there much faster and even getting their Freight there much faster

so here's another one I pointed out to

Warner's in Atari that fantasy amplifiers are big also and the reason

for that is that even when we think we're in reality we're dwelling in a

fantasy or in a hallucination that is partly a product of our culture and our

upbringing as well as what our sentence our senses bring to us and a third one

is control one of the biggest traumatic

shocks we have as a child growing up is when we start dimly sensing that the

universe isn't in our control I remember that the guy first realized that when I

was about three years old and I've never gotten over it since but in fact this

this idea of trying to be able to control things that amplifiers that

allow us to control various things and so forth it very important also and

simply you can tell very often whether a new product is going to make it if it

really does amplify one of these or other human traits you don't have to go

out and ask people they can't tell you that just as Sony did not market tests

when they when they went out and tried to do the Walkman nobody wanted to

walkman until Sony built 5000 of them

and gave them to people if you can give something to people and they can hold it

in their hand then they know whether they like it or not that's one of the

reasons the Japanese have been so successful is that they know the way to do market analysis is not to go out and

ask the questions before you do the product what you do is you do the product and then see what people think

about it because then they actually have an aid to their

imagination let me just follow up on

three ways to invent something this is

the most popular way take whatever's around shove it together and ask what

you've got that's called brainstorming something

these these productivity books think is important but in fact it's the worst way

to do anything because people are usually lousy at thinking on their feet

and they're terrible at thinking inside of a room people need sand under their

feet to do good thoughts or maybe a shower or something better way is the

problem-solving method find a need and fill up but the one that really wins is

to make something that creates a problem only if can solve that's exactly what

the Xerox machine was nobody had a copying problem until the Xerox 914 came

along nobody had a calculation problem

until the HP 35 came along the HP 35 and

calculators were predicted against for the simple reason that nobody did

calculations up till then there are desk calculators around and people didn't

realize that the that the simple access

to calculation gratuitously was an important part of it and of

course the personal computer itself is an example of that nobody had a personal

computing problem until pcs came along and now we all do possibly very possibly

okay I'll just give you a few more slogans and homilies here

another one is about literacy my

definition of litter literacy is that literacy is fluency not familiarity I

usually show this slides to the educators because educators think if

they make a child familiar with the computer then the child is computer

literate but in fact it's not true I believe literacy has three parts

there's an access part that means

somebody else makes up the material and you have the skills to get to whatever

that material is we call that reading in the print medium and the Macintosh is a

good example of how to solve the access problem to operating systems and

applications second area we don't do so

well at which is called creation fluency and the print medium that's writing and

writing is an example of something where we expect somebody who's literate to be

able to write a 2-page two pages of something advancing a point of view and

substantiating it in order to convince somebody and this two-page thing is very

important because most people have a very difficult time dealing in large

number of pages of anything even for people who can write so it's very

important for English through the use of metaphor to be able to express fairly

complex ideas in a couple of pages programming languages are terrible for

that almost all programming languages to do anything interesting in takes you far

beyond several pages and one of the things we found out at Xerox PARC years ago is that the if it's a

trade-off between an easy programming language like say basic or logo that

requires tens and twenties and hundreds of pages of program to do something and

a very abstract programming language such as small talk which can do many

interesting things in a couple of pages then it's better to teach the abstract

language to end users non-programmers

than it is to try and teach the so-called easy programming because in fact having the programs be

very small allows the person to use their visual field as an augmentation to

their short-term memory and that is the critical thing in end-user programming

and finally the third fluency I call

shanwa fluency and by that I mean that

for anything you can be literate in has a literature and it's a very nature of

literature that the literature is in different styles so it's not just enough

to be able to read and write but you should be able to access other people's

ideas by being able to absorb other styles of talking about things and again

this is something that will be more and more important in the future as

networking allows us access to more and more potentially useful tools that right

now we can't use because we can't sit

down and absorb a different style and here we're talking about more than just

to use their interface having a uniform user interface like on the macintosh is

important but it's not enough

and one final set of ideas

McLuhan pointed out mentioned that

Whitehead had called the greatest invention of the 19th century being

invention itself and Whitehead substantiated that by pointing out that

the number of crackpot inventions in the

Patent Office in England had gone up by more than a factor of 30 starting in the

early 1800s that everybody was inventing people are inventing automatic hat

tipping of devices and strangely shaped bicycle seats and every other kind of

thing amazing anything that could be thought of in some things we'd never

think of were patented a huge explosion and the important thing about that was

that the number of good things went up by a factor of three that factor of

three coupled with the Industrial Revolution changed the way we do things

McLuhan said if the greatest invention of the 19th century was invented there

was invention then the 20th century is the century in which change changed our

whole notion of what we meant by change over the last 10,000 years has changed

in the 20th century and so here's an example this is a list compiled by a Jim

cook who's a corporate thinker on the East Coast is kind of interesting so the

mission of the Industrial Age was to amplify the body and the mission of the Information Age is to amplify the mind

he says structure of the Industrial Age of the hierarchy the Information Age is

naturally a network the output products and services but the new output is ideas

and decision decisions advantage economy of scale now it's timeliness and

leverage old gold efficiency new goal effectiveness manages activity now we

manage communication control with centralized now it's going to be

decentralized medium is immeasurables new medium is

concepts so forth evaluation as in reports now we

believe sensitivity is to organizational

structures now it's the talent cohesion is through discipline nucleation is

through commitment risk return incremental now it's volatile the

leaders used to be dogmatic now they're charismatic and the heroes used to be

specialists but now they're going to be generalists I subscribe to most of these

things that this way of looking at

things says that it's more than just incremental changes that are going on in

this century it's a whole different way of thinking about doing things

well it's just that the basically

there's a guy by the name of Lewis Mumford used to write interesting books

about how civil how civilizations organize themselves to accomplish tasks

one of the the terms he made up was

called that civilizations he called the mega machine he was very interested in

what the mega machine was set up to do he thought of offices and businesses as

being communications devices when you set up a business it's it's not it's

ostensibly to sell goods and services perhaps what it really is as a communications device he's very

interested in what what the business was

as a system and what you can do with a hierarchical organization what you can't

do how flexible is a hierarchical organization say to corruption at the

top versus how flexible is a network

organized organization to corruption anywhere he was interested in the

difference between simple mechanical systems as applied to human sociology

versus more biological systems systems that are more tissue-like and so I'm

just putting those out there as a as a way of pointing out that the the very

structures in which organizations use to

communicate and move ahead is changing is partly changing simply because the

information the way we can move information around is different one of the ways of thinking about how humans

have gotten ahead over the last 10,000

years could be thought of is each stage of civilization has found a way of

making an abstraction into an object 10,000 years ago words were not objects

oral society words are not objects they can't be put down in a way so that you

can stand back from them people marveled

at st. Augustine because he was one of

the few people in his time that could read without reading aloud and moving

his lips when people read meta evil manuscripts

even up to the 1400s they read aloud and

they read slowly because it was they were essentially an oral culture the

writing system that they had was a way of capturing oral culture not changing

the culture McLuhan tells a really interesting story fascinating story

about a tribe in Africa that had just recently achieved literacy via some

missionaries that had helped them make

up a syllabary like Hindi but a syllabary of some 60 or so signs that

stood for the syllables in their language and several people in each

village had learned to read this syllabary and the story that McLuhan

tells is that when a letter came into the village it would go to the person

who could read it to the family who would received the letter and if the

letter wasn't was a personal letter the person who read the letter to the family

would put his fingers in his ears as he read the letter so he couldn't hear now

think about that think about that because that's what I'm

trying to say that McLuhan said I don't know who discovered the wall who

discovered water but it wasn't a fish in

other words it is the stuff that we're embedded in that we take for granted

that shapes us there's no reason why human beings have to be the way they are

in any particular culture there are many different ways of doing things and the

thing that we're at least aware of is the way our culture does things so people like Mumford and McLuhan are

tremendously useful in that they point out how how different are the ways that

people have solved their problems and how different it is for instance to read

fluently in a print medium in which none

of the emotion is expressed in the form of the text the illuminated manuscripts

were there as a kind of a stage setting to bring forth the emotion that was

essentially a poetic expression of things

prose is something that really became possible with the printing press and our

reaction the way we read prose is totally different the way we get emotion

from prose is totally different from the way we do when we were in oral culture

so in fact this is a good good place for this another one of these triads solving

the problem is all is often futile it definitely is in futurism changing the

problem is what the books tell you to do but in fact changing the context is

almost always the most powerful the reason for this is that logic is basically a weak method we're not any

smarter than we were thousands of years ago and if we were put back take any

person in this room and put them back in 60 AD and try and get them to multiply

two numbers using Roman numerals we would see just how smart we looked the

representation systems are the things that are powerful our ability to do

logical thinking has changed about the same so this was a slogan that we liked

at Xerox PARC so I made up call point of view is worth ad IQ points and that

slogan was made up when we were developing the user interface that led to the Macintosh what we're trying to do

is instead of trying to change the human

species so that they could run ms-dos

or for the ms-dos of the day thank

goodness it wasn't around when Park was thriving but they were equally bad

systems back then what we asked was what is the context that can make people look

smart on a computer what is the one that allows them to use

the logical operations that they've learned all their life and well that

will translate into actually controlling the computer and that's what led to the

familiar Macintosh user interface

so

so what caught business data processing off-guard in the past decade

I think desktop micros certainly

surprised them they were out buying IBM mainframes spreadsheets surprised them

Universal bitmap graphics such as on the

Macintosh that is graphics without any modes where you don't have to say ahead

of time when you're designing the machine what can go on the screen

pointing window interfaces like the Macintosh desktop publishing local area

networking all of those things were a big surprise over the last ten years and

the business data processing people are still scrambling to try and figure out

what it all means they want to play it safe but they suspect now that sort of like a

Christian Scientist with appendicitis you know it's sort of one of those

ultimate conflicts that you don't quite know what to do I'm not going to talk

about I just want to go through a list that obvious changes the next five years

I'm not even going to talk about many of the changes in the next few years you can see by going over the Apple World

Expo multi megabyte Ram faster CPUs for

user pervasive networking three-pound computers application kits and

generators higher-level language programming very high level language

expert system prototyping fast deductive reasoning and some more attempt at

standards particularly at the network level those are all obvious things I

don't think they deserve too much comment here

so less obvious changes in the next five years now machines we did it park first

machine we did it park if you were to

bench market today was about as fast as

the Mac two which is wonderful wonderful

at the Mac to all of us that some of our

the old systems we used to do like small talk run beautifully on the Mac too and

we just love it and but what's been happening in the industry is something

is that's pretty good pretty annoying and it has to do a lot with the physical

form of RAM memory and that is the band the bandwidth per bit in memories has

been going down what do I mean by that well I mean that the you know you in

order to get bandwidth in memory you have to configure the memory you know in

a certain width if you make a 16-bit wide memory and you have to buy a one

megabit chip then 16 of those one megabyte megabit chips will give you 2

megabytes of memory 16 bits wide that's

not very fast these days so if you want

to go faster you can go to a 32-bit wide memory that says you have to buy 16 more

of those chips that get says that in order to have a single 32-bit wide

memory you have to have 4 megabytes of memory and it's still only 32 bits wide

what I mean because the memories get longer you have to configure enormous

memories in order to have a reasonable bandwidth per bit in memories and that's

not so good and what what that means is

that the MIPS per megabyte ratio has

been going down so the Macintosh for

instance has about is about a 1 MIT processor and it has about 1 megabyte of

storage and that we think is pretty bad because the machines we built at Parc

had three MIPS let's see let me work it

out it had about a myth per hundred

kilobytes so every hundred kilobytes of memory we built had a park we had 1

million instruction per second of processor and was we built a very big

machine we actually built in 1978 a machine that had 40 million instructions

per second for doing all that stock and no that is really important so today's

micros in my opinion are underpowered in processor speed for the amount of memory

they have on them that's going to change this is going to be this change of

having many many more millions of instructions per second for the size

memory you have on your machine is going to be a big surprise to people over the next few years would not surprise me at

all before 1990 to have 75 or even 100

nips on a desktop no

well show you why you need it say I told

you these weren't so obvious part of the

part of the way we're going to get that is we're going to have many more CPUs per user I'll give you an example there

are lots of different ways of trading off these two but in a good example of a

new kind of architecture is the system called the connection machine at

Thinking Machines Corporation ok this machine is is a machine that has 65,000

processors each processor is a one myth processor and each processor is attached

to four kilobytes of memory ok so this is a one MIT processor for four

kilobytes of memory and that's the machine so in fact there is no separate

Ram we have a one myth processor on four

kilobytes of memory you have 65,000 of them and that is now what can you do

with the machine like that well an example is inductive reasoning I'll give

you two examples that you find it hard

pressed to do on any other machine one of them is doing information retrieval

over large document spaces one of the hardest things to do is to get a set of

indexes that represent some theory you

have about a set of documents ok because

people have a hard time assigning keywords and full-text retrieval tends

to retrieve too much if you've ever used a good full-text system like Nexus so

the process on this machine is you start off like Nexus you come up with a couple

of keywords and it retrieves a bunch of documents and you look at these

documents and you see you score them you say oh this is just the kind of document

I want this one is way off and then what

it does is it takes all the documents you like and intersects every

non-trivial word in the document with

each other and when it comes back with is another set of keywords gotten out of

this massive intersection does this intersection in about one

second and then what it does it then it

retrieves from the entire database all the documents that matched those guys and you get to score again okay and

what's amazing about this and there are several papers you can get from Thinking

Machines Corporation if this intrigues you is that after you do this two or

three times the keywords stabilize and

you get a keyword set that will retrieve just the kinds of documents that you want and almost always exclude the

documents you don't want just a couple of passes and this whole process to

establish that it takes just a few minutes now this is just simply isn't

possible to do I'll give you one more example one of the problems in expert

systems is that expert systems know a

lot about a narrow domain but because

they're basically deductive there has to be a rule in the expert system to cover

every case so let's take a case where we're describing some symptoms to a

medical system and at some point the system needs to know the common-sense

fact that women that men don't get pregnant and somebody forgot to put that

in there and the typical expert system will just bolt that's the end of it

because the problem is is that the there we figure there are somewhere between

200,000 and 500,000 common-sense rules that we all learn over the first 20

years of our life that we used from getting from one expert island to another and it's very hard to codify

those and people are trying to codify them now because that's what's one of

the things that's holding back expert systems now in the connection machine

when it comes up to something like that it doesn't stop back it doesn't even

have a common-sense rule base what it actually looks at is the last six months

of reuters dispatches

they just got the last six months of Reuters fashion this is about 15

gigabytes of information and in a second

literally a second it is able to come up with a 99% probability that men don't

get pregnant because it has not found any mention of that in this general

corpus that has to do with human life and so it uses this inductive assumption

to carry on in the the the deductive

process of trying to figure out what disease has so there are many others I'm

gonna mention some of the the graphical needs for densely parallel processors in

a bit but I guess the point is that the

almost everything that has to do with the economics of building computers has

to do with what it costs you to package the components and most of the things

are going to surprise us in the next five years are going to be when certain

packaging thresholds change abruptly and surprisingly one of them as we see is

going to be 3d graphics 3d graphics that will in done in real-time has been

incredibly expensive for the last twenty

years or so I was in the original group at Utah that invented 3d graphics and

none of us had any idea it was going to take so long but it's completely

dictated by the economics of building systems that have 2,000 multipliers in

them and that's what it takes to do 3d graphics I'll get to that in a minute

another example is what you might call

ultra high level language end-user programming and tailoring this is this

again is sort of a prediction and I

believe it's going to come true not because it's easy but because it almost

has to become true if we're going to have a hundred million computers in the

United States instead of something like 20 million that there's no way

applications packages are going to be able to anticipate all of the needs

without getting much more patchwork quilt II than they are and there has to

be some way for users to tailor the end results of the

system and even build some from scratch it's not going to be in any programming

language that we know now common sense

database I've already talked about a bit this means the difference between

specific ways experts do things and those 200,000 facts that everybody knows

but are harder to write down there's a wonderful research project in Texas at

MCC right now done by Doug Glennon that

is using an ingenious set of techniques for coming up with a common sense

database interesting thing about how big is this database he's done enough

already he's been doing it for four years now he's done enough already to

establish that the database is somewhere between 8 megabytes and 100 megabytes in

size for all of the common-sense facts that people in our civilization know if

you think about it sounds large but in fact it's only 1/5 of a compact disk

only 1/5 of a compact this to have this and you can think of this common sense

database in many ways as being the quick-draw of expert systems in the

future it's that set of stuff you want to have an e ROM that every expert

system builder can rely on being there in a general inference engine in fact

this next point speaks to that fact the

next several points do that it's going to be the integration of expert systems

that will make expert systems as useful as the tools that you now enjoy on the

Macintosh expert systems right now are

completely isolated and they've partly isolated just because they're done in

different languages but a lot of it is that they're isolated that there's no way for the inferencing mechanism to

move from one place to the other another non-obvious technology this is a

technology that has been chugging along pretty nicely for 10 years but nobody

has noticed it in the micro world is what's called explanation generation

and a explanation generator is a program

that can look at a data structure knowing what the data structures are

generally attempting to represent and generate perfect English prose at any

level of detail about what that data structure is this is the exact opposite

of a system that understands English input which is a very hard problem but

systems that will be able to generate beautiful English output from

representational structures will burst

on the scene in the next five years there'll be an overnight sensation because it's only they've been worked on

for the last 20 years or so just a technic technology that there's no hint

of in the micro world right now I mentioned inductive reasoning another

less obvious change is that I believe that user interfaces are going to change

completely over the next five and ten years and the reason for that change is

going to be networking one of things you

probably noticed when you put a hard disk on the Macintosh is that the nice

browsing techniques of the finder don't work so well anymore you have to make

things real small and some people go back to lists and stuff and all of a

sudden being able to browse a hundred items changes completely when you have

to browse upwards of 2,000 items and this is something we found out at Xerox

PARC in the mid 70s we started thinking about what that meant especially when

you get hooked up to networks that are also hooked up to networks and you have

hundreds of thousands of resources and

we thought that was rather like what happens when you wander into the Library of Congress in Washington and you

discover to your dismay that the card catalog room is much larger than your

hometown library and what do you do at the Library of

Congress well the first thing you do is find a person who is an expert in where

things are that person will act as your agent during the time you're in the

Library of Congress the person does not know the answer to your question but the

person is an expert at the resources and pathways for finding the answer so this

notion of agent is an old the idea in computer science it goes back actually

to the early 50s McCarthy I mean late 50s McCarthy thought it up but there

hasn't been enough pressure from the technology to develop agent based

interfaces until now and finally one of

the things that we just absolutely need a factor of 100 more cycles for is what

I called remember we talked about the one of the messages of the Mac is

Universal bitmap graphics that means Universal just means you don't have to

know ahead of time of what's going to be shown on the screen and the big change

in the next five and 10 years is going to be extending that to 3d real-time the

animated graphics and simulation now let me give you some examples I'm sort of

going to be popping back and forth here

they're a clicker up here yes there is

it's always nice when every Apple celebrates their invention of the

personal computer I always like to show the actual first personal computer

because this is the machine called the

link and it was invented at Lincoln labs by Wesley Clark in 1962 near about 3000

of these built in the in the 60s and a lot of their architecture were adopted

by deck when deck invented the mini is

really kind of a shame because I sort of believe when deck look at this machine

they thought oh what a great idea but people don't understand displays so

we'll take that off and make it an option

and these tapes that look like deck tapes are actually invented for this

machine they actually held the pages of the virtual memory this first personal

computer had so it had a swapping virtual memory run off these tapes and

Dex said oh but people don't understand virtual memory we've got it we'll put

files on these tapes so they took this technology and made them back into

something like computer tapes so this was a great idea that was way ahead of

its time now this is the invention of computer

graphics Ivan Sutherlands sketch pad and sketch pad was not just a graphics

system but in fact a it was a system

that could do general-purpose simulations the graphics had meaning and in fact the system was called sketch pad

because it would actually complete the drawings for you the drawings you just

put it in roughly and then you told the system what the drawings should be and

sketchpad would complete the drawings all this in the very first graphic

system and I'll show you an example of that

some over 1962 you see the familiar rubberband technique Ivan and someone

actually invented it you something as easy for links to the edges and says I

want these to be all mutually perpendicular and sketchpad figures out how to do that so you're seeing a real

time expert system in action notice gets bad as the first system to ever have a

window here's another example

draws a couple of lines he points to them he says make them parallel and

mutually perpendicular to the edge and sketchpad straightens up the drawing a

sketch pad is also the first non procedural programming system and it's

far far more capable than visicalc

or Lotus 1-2-3 because it can solve nonlinear problems in many unknowns so

now he's making the guidelines invisible

you'll see this display jump around a lot because the tx2 computer that this

is running on is many times larger than this room and it's putting up every dot

on the screen by brute force that goes

the last computer to ever have its own roof so here's another example he wants

to draw a rivet he uses that cross place there as the center for the arc and now

by simply pointing to the edges and telling sketch pad to straighten it up

that will drag the cross pieces which will Center the rivet and sketchpad

completes the drawing

reason I'm showing you this stuff is because the Macintosh to here he's

showing it no matter how you distort it the same general rules or follow

Macintosh to is the first micro computer fast enough to be able to do this kind

of computer graphics and I predict that we'll see sketchpad what are called

constraint oriented graphics systems popping up in the next several years

have to have enormous computing power to

do this in real time now he's showing

that anything that you can make a drawing of you can get instances of the

instances can be dynamically again you see the contrast here between this and

Mac draw which doesn't allow you to dynamically drag complex things it makes

up a simplification of the complex thing

for dragging purposes and here are some more instances of the rivet the reason I

call them instances and not copies you'll see in a minute because he

doesn't like the cross piece on the rivet so he goes back to the master

drawing and makes the cross pieces transparent and we now see that the

rivet has the rivets have felt that change dynamically so sketchpad is also

the first true object-oriented programming system and this again we

will see on the Mac 2 in the next few years I asked Ivan once I said Ivan how could

you possibly have done the world's first graphics system the first non procedural

programming language and the first object-oriented programming system all

in one year all by yourself and he said well I didn't know it was hard

so this year is the 25th anniversary of

this system this is the 25th anniversary of computer graphics this year okay

yes here's another something that we're

going to see in the next few years I'm moving up in time this is Douglas

Engelbart in this is about 1968 or so

and Doug Lingle bar was the guy who invented hypertext systems and he also

invented the mouse as you see black on

white graphics view specs for windows

and he had this interesting idea that people shouldn't have to hunched over

their desk so the way you ran this system was this was a lap board that

went over your office chair so you could tilt put your feet up on your desk like

you're used to or scooted around the room it's an idea whose time is yet not yet

come in the microcomputer industry here's an example of that system what

I'm showing you here was taken live from the demonstration of the system done in

1968 so this is 19 years old and

something that I predict will be able to write you as an intellectual worker were

supplied with a computer display backed

up by a computer that was alive for you all day and was instantly responsible responsive

Anthony responsive every action you have how much value could you drive from that

well this basically characterizes what we've been pursuing for many years in

what we call the Augmented human intellect Research Center at Stanford Research Institute

so look what else we can do in here I've got this file is structured if I want to

see what's in there I can walk down

Cinci return but there's another thing I

can do does remove dice that I have here

so here I'm afraid I'll need different pictures of you so here's what I do with

a picture drawing capability here's this light map if I start from work and here's the route I seem to have to go to

to pick up all the materials and that's my plan for getting home tonight but if

I want to I can say the library what am I supposed to pick up there I can just

point to that you know I see overdue books and all while there was a

statement there with that name wanna go back what if I once my supposed to pick

up the drugstore mmm-hmm I see you've everything all right oh I've already

seen that J that's too much anyway so we

have this feature the structuring our material hierarchically being able to

move around it very well when we get a hierarchy

such as I can show you here

I can do things if I want to just say I'd like to interchange the Protestant

camp materials bingo know if I care to look

interchanging them very quickly cans are going to get interchanged with products

they do it and all gets me numbered so

I've ways of studying over making different views moving around going to

specified points okay well there's lots

more but you might have been surprised by the speed of that system all right

I've got a I'm sorry I have to show you a couple more things I have at the lab

of the love this this is one of the great inspirations of the stuff you did at the same time I've seen that I have a

repertoire of different entities my character knock off a character replace

the character make that P so I have

entities of all sorts that I can say I want to do operations on and this basic

structure that I can move over and study and get about very quickly so that is

the essence No

that's the essence of the tool we have a lot of details your character if I hit W

it'll say delete word the arrow moves back and forth to give me feedback my

tracking spot changes that gives me feedback now tells me since it's an

arrow that it's armed I can do something we get a lot of feedback let me restore

if you like this to show you this is more normally the way we work with

feedback up here okay now the thing to notice here is this is actually a

multiple multiple window system and each of the views had a view specs

he's going to be talking about those the view specs are much more than just that

mucis specs to control the level of detail he sees how things are presented

whether they're presented in an outline form or so forth it's something that has

never been done on a micro up till now I'm shown not working that's an echo

register that normally gives you the last six characters that you use the

last six characters and let shifts continuously so you can look up to any time and see what have I just struck and

that's for a good feedback here are characters that show me the different

viewing parameters few specs single

strokes I change those parameters now

notice here that the theory of interaction here is different ankle Bart

understood very early that the thing you don't want to do is go moving constantly

back and forth between the pointing device and the keyboard and so there's

five finger keyboard he has for the left hand allows him when he moves his hands

out to the outside he can do anything with a five finger keyboard that you can do with the regular keyboard just a

little bit slower and so when he's zooming through the system he'll just keep his hands constantly in

navigation mode it's only when he's typing paragraphs that he uses the

regular keyboard in the center it's a more efficient way of doing things than

we do things today and each of those

means something to me and they're being larger particular times tells me I can

have very quick abbreviation for changing the view so I can say I'd like

to go to produce but I'd like to go to

produce they get big I'd like to say one branch only and let me look just that

little can I see it oh I can say I'd

like to see one line only I can see so

these ways I move around the way I get feedback up here the way I use both

hands to coordinate to tell the computer what command and what's short literals I

want all perfectly designed to go together to make the repertoire I'd like

to link to bill and I don't know what his terminal is right now

so I have to ask for somebody connect me to him audibly audio so bro will you

come in through this intercom oh I I need to know what terminal you're on

though 13 okay I'd like to have him see

my text and so the special thing if I label 13 we'll switch switch over so I

just display he sees my text so I'll execute it and sure enough it does but

what's that running around well he's looking at my text he'd like to have

something to say about it so we put on a marker a tracking spot that he controls

so he's sitting at Menlo Park looking at this text and he can point to it but

we've carefully reserved from either right to control and operate on this somebody so what's going on here is

teleconferencing because this system is organized angle Bart is in San Francisco

and the rest of his group is in Menlo

Park but they're sharing the same screen and every time a person joins the

conferencing system they get a new cursor so that they can point to things

too now the system becomes a shared blackboard it's more powerful in yours

but we can have an argument yeah

so alright so in case you haven't been

listening bill we've been back to lots of examples and setting up in

collaboration here so that we can go on into information retrieval and we set up

now audio coupling and we're both looking at the same display and that'd be very handy to work we could talk to

each other in point and maybe later I could hand you the chalk on this

blackboard like saying here you control it but let's status mode now and add another feature that hardware-wise is

available to the kind of display we have I'd like to see you while I'm working on

it so before I can do that I have to set

up my display in a certain way

set it up so I see it over like that that leaves a corner up there and I say

now computer do the automatic switching that will bring in a camera picture from

the camera mounted on his console such as the camera mounted on - I built

that's great now we're connected audio you can see my work you can point out it

and I can see your face and we can talk so let's do some collaborate I had this

immensely intuitive feeling that humans are going to be able to drive a great deal of capability from this and along

without it coming with very real images of my mind is sitting at a display

console interacting with the computers seeing all sorts of strange symbology

coming up that we could invent and develop to facilitate our thinking since

we would no longer be limited to working with paper and laborious means like that

and other people could be sitting at similar consoles tied to the machine and

you could be collaborating and brand new exciting ways and that you could be just

doing all sorts of things to control a computer so I've enough engineering background even though I didn't at that

time know how the innards of a computer work but I certainly knew that if they can read a card they can sense keys and

any other action you want to do and if they could drive a printer or a card punch I knew plenty electronics to know

that they could put whatever you want or not display okay well that was one of

the great pioneers and a lot of what he predicted is going to come to pass

because what he predicted was what we need and the difference between these

guys in the 60s and much of what's been going on in the micro industry is that

these guys in the 60s seem to have these complete visions so Ivan Sutherland

didn't just invent computer graphics he realized that the graphics wanted to simulate something with meaning and

Engelbart didn't just invent the mouse and a few things he realized that the

whole idea was that for people not just one person but for multiple people to be

able to work together in a shared way now this is the first personal computer

I designed it's called the Flex machine in 1967 a habit

it was influenced a lot by Engelbart stuff turned out to be very hard to

in user interface like Engelbart's was actually a fairly hard one for people to

learn and a little bit later we saw a seymour papert's work with logo in 1968

and also this system done it RAND

Corporation this is about 1968 also

again on a multi-million dollar machine larger than this room for a bunch of

Randy Kannamma that complained that they couldn't type this list of processes

takes us back to the topmost level so they got really smart edit the flow

diagram first we erase a flow arrow then

move the connector toddled away so that we may draw a box in its place

recognising his handwriting here the printing in the box is being used as

commentary only in this case the box is

slightly too large so we may change its size we're back window control came from

literally then dry flow from the connector to the box attached a decision

element to the box and joy flow from it to scan we then erased the floor arrows

attached to the process post new area and move the box to a new position this

allows us to draw a new box

then chop off its corner and label it sub scan now notice it this is the end

here he goes up he sees it he has two dates but it's modeless draw flow so he

can just change it goes to sub scan correct the label add a decision on sub

scan so that control may flow to the connector a zero then complete the

diagram from scan to post well that was

that this system was the one that actually changed my way of thinking about computers because this is a system

life felt to me intimate I had a chance to use it for a half an hour in 1968 and I was not

notice that the command there's you didn't even see a pulldown menu there

every command was analogical if you want a box you drew a box itta made the box of that size if you

wanted a character on the screen you drew a character you want to get rid of something you scrubbed it out the text

editor in it took normal proofreading symbols so this is one of the great

systems of all time that nobody has ever heard of these days called Grail

graphical input language so that led to

this notion that the pencil was the best

metaphor that thing we'd never withhold from children and that the information

vehicle that Engelbart liked wasn't as powerful as this notion of giving

everybody a pencil and also in 1968 the

first plasma panel flat screen display was done and so we realized that one of

the destinies of all of this stuff had to be something that looked like this we call this the Dynabook and remember that

it can't be just like a lap computer of today because lap computers of today

don't allow you to carry other things easily it has to be really slim it has

to be really light has to be really good

it has to be really fast to test those ideas we do this is the forerunner of

the Macintosh it's a photograph about 1973 you can see the screen is about the

size fact is exactly the same number of pixels as the radius screen has 808 by

606 and this machine was about this the

the computing power of the Macintosh -

it's about three times or four times the computing power of the Macintosh Plus

Windows you're all familiar with invented on that machine small talk was

how we tried to work with creative literacy and get people to do their own

applications programs especially children here's a quick example so

here's a pro this is a wonderful crowd to explain this - because this is a an

applications program like Mac draw

so it's an object-oriented graphic system you just saw some selection

handles there here's a color change you

see the menu down at the bottom of the screen here's a size change now the only

thing interesting about this program is it wasn't bought in a store it was done

in 1975 and it was designed and implemented by a 12 year old girl after

just three months of programming in small talk 72 this is an example of a

real live tool done by a novice programmer a child and one of the nicest

things about the Macintosh - is it is the first micro computer fast enough to

be able to run a language like small talk so this is the kind of stuff we'll

be able to do with schoolchildren now for real and in fact Apple has a an

extensive project here in Los Angeles that uses powerful Macintosh's in a

grade one through six school so end-user

programming is something that's going to happen in the next few years

that's the vivarium project I'll say a

few words about it if I can hold your

interest for another few minutes so one of the questions you might ask is how

young a child can actually use these

techniques and here's a

here's a tape that I got about five months ago from the woman who's my my

accountant this little girl is the daughter of my

accountant and her parents both work at

home each of her parents has a Macintosh and when I found out the little girl was

interested in computers I gave her an Apple to which she rejected he wanted a

Macintosh just like her folks and in fact we actually did I did go against my

belief in market sir we tried a market survey on this 22 month old and

discovered that she vastly preferred Macintosh's with hard disks fact this is

this is what we used to call in the in the bad old days to years ago Mac pause

actually it's a little surprising to child psychologists that she can watch

the screen and use the mouse perform this displacement at such an early age

given that it's not too surprising that she can hit visible menu items in Mac

Paint here so when I saw this I wasn't

you know I was intrigued but I wasn't too surprised that she could do it but

what happened next really surprised me she wants a fresh sheet so she goes up

to the clothes box on the window saves

your file with the pop up wizard the pulldown

to get a new one and she's off and rolling again

that's spray painting and here's

something that Pia Jet Ian's say she shouldn't be able to do yet which is a reversible operation of erasing and she

she thinks of the hand as animation and

the fact we're starting to do some animation things with her now she was in

this she was 22 months old when this is

taking course kids have this compare she's not twenty-two months now unfortunately when something like this

happens you like to freeze them in stasis you know so great but after we

saw that her father had taken the picture what we got as a Mac with a

video out and we ran a line to a monitor in a bedroom and set up another camera

and then we got many hours of her interacting with the Machine and

determined that she was able to handle about 75% of the commands and the

pull-downs consistently and not just a Mac paint

but in several systems and in her

obvious interest in animation is something that we're planning on doing something about another thing that's

interesting is the intriguing possibility that if the Macintosh

interface is the first interface that reaches she was actually able to use the

mouse more jointly than she can use a crayon at this age and it raises the

possibility of building an ant question-answering system for a child

aged 3 to 6 they have lots of questions

then to allow them to ask and questions and get answers without having to use an

adult as an intermediary and that's something that I'm very interested in

but I fear it may change the sociology of the home

maybe for the better so very quickly

here's this this project that we're doing in Los Angeles very similar to the

one we did at Parc except at Parc we're asking the question what would it be

like for novice programmers especially children to do their own applications

programs and here in the vivarium project we're asking the question what

would it be like for novice programmers especially children to do their own

artificial intelligence programming so we want to know something fundamentally

new about what it means to program up mentalities and the way we're asking

that question is to set up a forcing function so we have this wonderful

School in Los Angeles called the open magnet school all 226 children and this

is actually an inner-city school though it doesn't look like it because this is part of their asphalt playground that

they tore up to make a garden where the 2nd and 3rd graders learn about biology

by actually growing things this is sort of the saran-wrap free system of

education food doesn't come in packaged

in saran wrap here's a typical thing that we do in the

vivarium is the children might study an ocean ecology like a tide pool lots of

different animals and plants interacting they might get interested in fish and

besides this drawing fish we would like to give them some magic computer stuff

like mac draw stuff that they can mold

use distortions like Darcy Thompson showed at the turn of the century that

related species are have related body plans conformal mappings can be made

from one end to the other animate the

fish and most importantly give the fish behavior actually program up a mentality

of the fish based on their observations of what fish do and for that we have to

invent lots of things we want to have multiple points of view like here's one

from the fish's point of view who want to see the world from the frogs point of

view from the herons point of view and from all the points of view simultaneously

because it's multiple points of view member points of view are worth ad IQ

points multiple points of view are how you actually learn and we want the

graphics to look something like this this is a scene from Bambi and we're

privileged to have with us the person who did Bambi Frank Thomas the old

Disney animator who is one of the advisers on this project and is in the

process of teaching every child in the school how to animate here's another

example a scene from Fantasia in which every frame was airbrushed by hand okay

only computers this this kind of

animation will never again be done by hand only computers can bring this level

of aesthetics and here's an example and

this to be able to do this in real time takes about ten times the power of the

of the Macintosh - so about 10 -

somewhere between 10 and 30 myths and you notice it's sort of hard to see

what's going on now to turn the Sun on like this the very same scene takes on

the order of a hundred nips now this is done by Bob Abel and it's done very

slowly this is done on a backs about the

about the same power to do this on a macintosh ii would take about twenty or

thirty minutes a frame but it's a very nice metaphor to make something alive

out of just raw material so the problem

with waiting twenty and thirty minutes a frame is they probably notice that children are very real-time devices

and so in order to to actually get

something that's closer to their rates of speed we use this Evans & Sutherland

flight simulator this is real-time computer graphics 60 frames a second and

there's a human pilot flying this plane the system does not know where he is

going to go wherever he goes it has to show him this planetoid size database

you get an idea of what the state-of-the-art this is the state-of-the-art in real-time computer

graphics you can get an idea of look at

the sky look at the leaves in the trees so the modeling is at a very high level

of detail and this system is able to show these simulations from multiple

points of view simultaneously

this is a Harrier Jump Jet

so this is the this is the equivalent so

we're seeing this from about a hundred feet off the ground and simultaneously

here's a ground level view

now think of it this is the equivalent of those million-dollar computers in the

60s that sketchpad and Grail we're done on and here's a third simultaneous view

from the cockpit of the second plane so

of course we weren't that interested in

marine jump jets as we've been talking

about fish so we took our Disney animators and a couple of Apple people

and we went off to Evans & Sutherland in Salt Lake City to see if we could do a

thousand miles of Australian Barrier Reef and some swimming things and Disney

animators have this way of turning everything into a character and one of

the things that's not been done successfully in real time graphics is sinuous motion so we got very interested

in how fish moved their tails and skull

their way through the water so we did lots of drawings of that and of course

sharks have a sort of a evil scanning eye which we put in so the result of one

long weekend with lots of cold pizza and

this several million dollar machine is this

so what you saw there was would be is

about somewhere between 100 and 150 million instructions per second to do

that in real time or about 50 McIntosh

two equivalents of computing now 50 is

an interesting number because that first machine I showed you at Xerox the

forerunner of the Macintosh was exactly 50 times as fast as a console on a PDP

10 time sharing system we forget what it

was like so many years ago it was incredibly slow to do computation

interactive computation back in the late 60s and early 70s and the real

breakthrough at Xerox PARC was that factor of 50 that made everything

different the breakthrough that we have today in the Macintosh 2 was a factor of

50 over the way people did things 20 years ago and another factor of 50 is

yet to come in the next few years the

most important thing about the 3d graphic stuff is that it has not been

possible to make a real-time system like this and anything smaller than a couple

of full racks of equipment because of the way packaging of chips has gone this

is one of these things that's going to go through an immense step function of several orders of magnitude change in

cost performance just in the next few years because the level of integration

of chips is quivering on the edge for being able to package a system like that

on a one or two cards that would fit inside a Macintosh to

don't need 50 slots so a lot of them a

lot of it I guess I should close this off with my favorite way of thinking

about this is that the Greeks held that the visual arts were the imitation of

life but the computer arts in which we're all interested are the imitation

of creation itself and Purvi see the

Italian philosopher said to know the

world one must construct it and it's

this through this constructive process the children actually learn computers

are the best construction material that we've ever come up with outside of our

own brains I see them as an amplifier to the things that we bring when we sit

down in front of the machine an amplifier not a prosthetic thank you

very much