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I think I'll start out
and just talk a little bit

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about what exactly autism is.

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Autism is a very big continuum

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that goes from very severe --
the child remains nonverbal --

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all the way up to brilliant
scientists and engineers.

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And I actually feel at home here,

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because there's a lot
of autism genetics here.

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(Laughter)

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You wouldn't have any --

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(Applause)

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It's a continuum of traits.

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When does a nerd turn into Asperger,
which is just mild autism?

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I mean, Einstein and Mozart and Tesla
would all be probably diagnosed

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as autistic spectrum today.

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And one of the things
that is really going to concern me

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is getting these kids to be the ones

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that are going to invent
the next energy things

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that Bill Gates talked about this morning.

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OK, now, if you want
to understand autism: animals.

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I want to talk to you now
about different ways of thinking.

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You have to get away from verbal language.

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I think in pictures.
I don't think in language.

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Now, the thing about the autistic mind
is it attends to details.

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This is a test where you either
have to pick out the big letters

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or the little letters,

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and the autistic mind picks out
the little letters more quickly.

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And the thing is, the normal brain
ignores the details.

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Well, if you're building a bridge,
details are pretty important

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because it'll fall down
if you ignore the details.

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And one of my big concerns
with a lot of policy things today

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is things are getting too abstract.

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People are getting away
from doing hands-on stuff.

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I'm really concerned
that a lot of the schools

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have taken out the hands-on classes,
because art, and classes like that --

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those are the classes where I excelled.

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In my work with cattle,

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I noticed a lot of little things
that most people don't notice

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would make the cattle balk.

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For example, this flag waving
right in front of the veterinary facility.

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This feed yard was going to tear down
their whole veterinary facility;

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all they needed to do was move the flag.

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Rapid movement, contrast.

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In the early '70s when I started,
I got right down in the chutes

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to see what cattle were seeing.

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People thought that was crazy.

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A coat on a fence would make them balk,
shadows would make them balk,

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a hose on the floor --
people weren't noticing these things.

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A chain hanging down ...

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And that's shown
very, very nicely in the movie.

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In fact, I loved the movie,
how they duplicated all my projects.

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That's the geek side.

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My drawings got to star in the movie, too.

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And, actually, it's called
"Temple Grandin,"

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not "Thinking in Pictures."

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So what is thinking in pictures?

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It's literally movies in your head.

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My mind works like Google for images.

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When I was a young kid,
I didn't know my thinking was different.

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I thought everybody thought in pictures.

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Then when I did my book,
"Thinking in Pictures,"

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I started interviewing people
about how they think.

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And I was shocked to find out
that my thinking was quite different.

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Like if I say, "Think
about a church steeple,"

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most people get this sort
of generalized generic one.

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Now, maybe that's not true in this room,

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but it's going to be true
in a lot of different places.

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I see only specific pictures.

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They flash up into my memory,
just like Google for pictures.

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And in the movie,
they've got a great scene in there,

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where the word "shoe" is said,
and a whole bunch of '50s and '60s shoes

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pop into my imagination.

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OK, there's my childhood church;
that's specific.

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There's some more, Fort Collins.

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OK, how about famous ones?

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And they just kind of come up,
kind of like this.

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Just really quickly,
like Google for pictures.

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And they come up one at a time,

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and then I think, "OK, well,
maybe we can have it snow,

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or we can have a thunderstorm,"

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and I can hold it there
and turn them into videos.

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Now, visual thinking
was a tremendous asset

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in my work designing
cattle-handling facilities.

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And I've worked really hard
on improving how cattle are treated

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at the slaughter plant.

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I'm not going to go
into any gucky slaughter slides.

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I've got that stuff up on YouTube,
if you want to look at it.

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(Laughter)

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But one of the things
that I was able to do in my design work

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is I could test-run a piece
of equipment in my mind,

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just like a virtual reality
computer system.

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And this is an aerial view
of a recreation of one of my projects

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that was used in the movie.

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That was like just so super cool.

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And there were a lot of, kind of,
Asperger types and autism types

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working out there on the movie set, too.

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(Laughter)

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But one of the things
that really worries me is:

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Where's the younger version
of those kids going today?

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They're not ending up in Silicon Valley,

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where they belong.

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(Laughter)

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(Applause)

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One of the things I learned very early on
because I wasn't that social,

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is I had to sell my work, and not myself.

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And the way I sold livestock jobs
is I showed off my drawings,

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I showed off pictures of things.

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Another thing that helped me
as a little kid

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is, boy, in the '50s,
you were taught manners.

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You were taught you can't pull
the merchandise off the shelves

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in the store and throw it around.

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When kids get to be
in third or fourth grade,

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you might see that this kid's going
to be a visual thinker,

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drawing in perspective.

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Now, I want to emphasize

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that not every autistic kid
is going to be a visual thinker.

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Now, I had this brain scan
done several years ago,

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and I used to joke around about having
a gigantic Internet trunk line

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going deep into my visual cortex.

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This is tensor imaging.

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And my great big Internet trunk line
is twice as big as the control's.

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The red lines there are me,

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and the blue lines are the sex
and age-matched control.

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And there I got a gigantic one,

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and the control over there, the blue one,
has got a really small one.

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And some of the research now is showing

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that people on the spectrum actually
think with the primary visual cortex.

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Now, the thing is, the visual thinker
is just one kind of mind.

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You see, the autistic mind
tends to be a specialist mind --

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good at one thing, bad at something else.

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And where I was bad was algebra.

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And I was never allowed
to take geometry or trig.

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Gigantic mistake.

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I'm finding a lot of kids
who need to skip algebra,

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go right to geometry and trig.

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Now, another kind of mind
is the pattern thinker.

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More abstract.

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These are your engineers,
your computer programmers.

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This is pattern thinking.

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That praying mantis is made
from a single sheet of paper --

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no scotch tape, no cuts.

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And there in the background
is the pattern for folding it.

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Here are the types of thinking:

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photo-realistic visual thinkers, like me;

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pattern thinkers, music and math minds.

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Some of these oftentimes
have problems with reading.

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You also will see these kind of problems
with kids that are dyslexic.

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You'll see these different kinds of minds.

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And then there's a verbal mind,
they know every fact about everything.

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Now, another thing is the sensory issues.

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I was really concerned about having
to wear this gadget on my face.

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And I came in half an hour beforehand

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so I could have it put on
and kind of get used to it,

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and they got it bent
so it's not hitting my chin.

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But sensory is an issue.

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Some kids are bothered
by fluorescent lights;

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others have problems
with sound sensitivity.

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You know, it's going to be variable.

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Now, visual thinking gave me
a whole lot of insight

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into the animal mind.

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Because think about it:
an animal is a sensory-based thinker,

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not verbal -- thinks in pictures,
thinks in sounds, thinks in smells.

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Think about how much information
there is on the local fire hydrant.

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He knows who's been there --

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(Laughter)

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When they were there.

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Are they friend or foe?
Is there anybody he can go mate with?

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There's a ton of information
on that fire hydrant.

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It's all very detailed information.

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And looking at these kind of details
gave me a lot of insight into animals.

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Now, the animal mind, and also my mind,

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puts sensory-based information
into categories.

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Man on a horse,

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and a man on the ground --

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that is viewed as two
totally different things.

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You could have a horse
that's been abused by a rider.

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They'll be absolutely fine
with the veterinarian

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and with the horseshoer,
but you can't ride him.

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You have another horse,
where maybe the horseshoer beat him up,

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and he'll be terrible for anything
on the ground with the veterinarian,

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but a person can ride him.

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Cattle are the same way.

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Man on a horse, a man on foot --
they're two different things.

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You see, it's a different picture.

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See, I want you to think
about just how specific this is.

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Now, this ability to put
information into categories,

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I find a lot of people
are not very good at this.

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When I'm out troubleshooting equipment

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or problems with something in a plant,

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they don't seem to be able to figure out:

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"Do I have a training-people issue?

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Or do I have something wrong
with the equipment?"

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In other words, categorize
equipment problem from a people problem.

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I find a lot of people
have difficulty doing that.

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Now, let's say I figure out
it's an equipment problem.

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Is it a minor problem,
with something simple I can fix?

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Or is the whole design
of the system wrong?

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People have a hard time figuring that out.

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Let's just look at something
like, you know,

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solving problems with making
airlines safer.

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Yeah, I'm a million-mile flier.

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I do lots and lots of flying,

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and if I was at the FAA,

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what would I be doing a lot
of direct observation of?

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It would be their airplane tails.

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You know, five fatal wrecks
in the last 20 years,

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the tail either came off,

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or steering stuff inside the tail
broke in some way.

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It's tails, pure and simple.

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And when the pilots walk
around the plane, guess what?

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They can't see that stuff inside the tail.

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Now as I think about that,

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I'm pulling up all of that
specific information.

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It's specific.

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See, my thinking's bottom-up.

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I take all the little pieces and I put
the pieces together like a puzzle.

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Now, here is a horse that was deathly
afraid of black cowboy hats.

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He'd been abused by somebody
with a black cowboy hat.

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White cowboy hats,
that was absolutely fine.

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Now, the thing is,
the world is going to need

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all of the different kinds of minds
to work together.

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We've got to work on developing
all these different kinds of minds.

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And one of the things
that is driving me really crazy

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as I travel around
and I do autism meetings,

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is I'm seeing a lot of smart,
geeky, nerdy kids,

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and they just aren't very social,

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and nobody's working
on developing their interest

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in something like science.

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And this brings up the whole thing
of my science teacher.

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My science teacher is shown
absolutely beautifully in the movie.

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I was a goofball student
when I was in high school.

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I just didn't care at all about studying,

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until I had Mr. Carlock's science class.

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He was now Dr. Carlock in the movie.

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And he got me challenged
to figure out an optical illusion room.

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This brings up the whole thing
of you've got to show kids

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interesting stuff.

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You know, one of the things
that I think maybe TED ought to do

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is tell all the schools about all
the great lectures that are on TED,

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and there's all kinds
of great stuff on the Internet

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to get these kids turned on.

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Because I'm seeing a lot
of these geeky, nerdy kids,

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and the teachers out in the Midwest
and other parts of the country

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when you get away from these tech areas,

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they don't know what to do
with these kids.

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And they're not going down the right path.

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The thing is, you can make a mind

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to be more of a thinking
and cognitive mind,

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or your mind can be wired
to be more social.

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And what some of the research
now has shown in autism

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is there may by extra wiring back here
in the really brilliant mind,

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and we lose a few social circuits here.

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It's kind of a trade-off
between thinking and social.

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And then you can get to the point
where it's so severe,

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you're going to have a person
that's going to be non-verbal.

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In the normal human mind,

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language covers up the visual thinking
we share with animals.

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This is the work of Dr. Bruce Miller.

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He studied Alzheimer's patients
that had frontal temporal lobe dementia.

00:11:33.252 --> 00:11:36.275
And the dementia ate out
the language parts of the brain.

00:11:36.299 --> 00:11:38.570
And then this artwork came out of somebody

00:11:38.594 --> 00:11:40.562
who used to install stereos in cars.

00:11:41.567 --> 00:11:45.233
Now, Van Gogh doesn't know
anything about physics,

00:11:45.257 --> 00:11:48.578
but I think it's very interesting
that there was some work done

00:11:48.602 --> 00:11:51.325
to show that this eddy pattern
in this painting

00:11:51.349 --> 00:11:54.497
followed a statistical model
of turbulence,

00:11:54.521 --> 00:11:56.540
which brings up the whole interesting idea

00:11:56.564 --> 00:12:00.302
of maybe some of this mathematical
patterns is in our own head.

NOTE Paragraph

00:12:00.326 --> 00:12:01.879
And the Wolfram stuff --

00:12:01.903 --> 00:12:06.469
I was taking notes and writing down
all the search words I could use,

00:12:06.493 --> 00:12:09.820
because I think that's going to go on
in my autism lectures.

00:12:09.844 --> 00:12:12.271
We've got to show
these kids interesting stuff.

00:12:12.295 --> 00:12:14.562
And they've taken out the auto-shop class

00:12:14.586 --> 00:12:16.686
and the drafting class and the art class.

00:12:16.710 --> 00:12:18.976
I mean, art was my best subject in school.

NOTE Paragraph

00:12:19.000 --> 00:12:21.859
We've got to think about all
these different kinds of minds,

00:12:21.883 --> 00:12:24.663
and we've got to absolutely
work with these kind of minds,

00:12:24.687 --> 00:12:26.975
because we absolutely are going to need

00:12:26.999 --> 00:12:29.520
these kinds of people in the future.

00:12:30.000 --> 00:12:31.779
And let's talk about jobs.

00:12:32.264 --> 00:12:34.457
OK, my science teacher got me studying,

00:12:34.481 --> 00:12:36.895
because I was a goofball
that didn't want to study.

00:12:36.919 --> 00:12:39.264
But you know what?
I was getting work experience.

00:12:39.288 --> 00:12:42.752
I'm seeing too many of these smart kids
who haven't learned basic things,

00:12:42.776 --> 00:12:46.224
like how to be on time -- I was taught
that when I was eight years old.

00:12:46.248 --> 00:12:48.803
How to have table manners
at granny's Sunday party.

00:12:48.827 --> 00:12:51.012
I was taught that
when I was very, very young.

00:12:51.486 --> 00:12:56.463
And when I was 13, I had a job
at a dressmaker's shop sewing clothes.

00:12:56.487 --> 00:12:59.075
I did internships in college,

00:12:59.099 --> 00:13:02.302
I was building things,

00:13:02.326 --> 00:13:05.343
and I also had to learn
how to do assignments.

NOTE Paragraph

00:13:05.367 --> 00:13:08.957
You know, all I wanted to do was draw
pictures of horses when I was little.

00:13:08.981 --> 00:13:11.809
My mother said, "Well let's do
a picture of something else."

00:13:11.833 --> 00:13:13.997
They've got to learn
how to do something else.

00:13:14.021 --> 00:13:15.865
Let's say the kid is fixated on Legos.

00:13:15.889 --> 00:13:18.586
Let's get him working
on building different things.

00:13:18.610 --> 00:13:22.206
The thing about the autistic mind
is it tends to be fixated.

00:13:22.230 --> 00:13:26.108
Like if the kid loves race cars,
let's use race cars for math.

00:13:26.132 --> 00:13:29.572
Let's figure out how long it takes
a race car to go a certain distance.

00:13:29.596 --> 00:13:32.709
In other words, use that fixation

00:13:32.733 --> 00:13:36.589
in order to motivate that kid,
that's one of the things we need to do.

00:13:36.613 --> 00:13:39.701
I really get fed up when the teachers,

00:13:39.725 --> 00:13:42.527
especially when you get away
from this part of the country,

00:13:42.551 --> 00:13:44.931
they don't know what to do
with these smart kids.

00:13:44.955 --> 00:13:46.118
It just drives me crazy.

NOTE Paragraph

00:13:46.142 --> 00:13:48.384
What can visual thinkers
do when they grow up?

00:13:48.408 --> 00:13:51.357
They can do graphic design,
all kinds of stuff with computers,

00:13:51.381 --> 00:13:54.764
photography, industrial design.

00:13:56.383 --> 00:14:00.315
The pattern thinkers -- they're the ones
that are going to be your mathematicians,

00:14:00.339 --> 00:14:02.846
your software engineers,
your computer programmers,

00:14:02.870 --> 00:14:04.833
all of those kinds of jobs.

00:14:04.857 --> 00:14:08.429
And then you've got the word minds;
they make great journalists,

00:14:08.453 --> 00:14:10.976
and they also make really,
really good stage actors.

00:14:11.000 --> 00:14:13.392
Because the thing about being autistic is,

00:14:13.416 --> 00:14:16.247
I had to learn social skills
like being in a play.

00:14:16.271 --> 00:14:18.644
You just kind of ...
you just have to learn it.

NOTE Paragraph

00:14:19.000 --> 00:14:21.976
And we need to be working
with these students.

00:14:22.000 --> 00:14:24.108
And this brings up mentors.

00:14:24.132 --> 00:14:27.232
You know, my science teacher
was not an accredited teacher.

00:14:27.256 --> 00:14:28.976
He was a NASA space scientist.

00:14:29.000 --> 00:14:32.404
Some states now are getting it to where,
if you have a degree in biology

00:14:32.428 --> 00:14:33.699
or in chemistry,

00:14:33.723 --> 00:14:36.560
you can come into the school
and teach biology or chemistry.

00:14:36.584 --> 00:14:38.110
We need to be doing that.

00:14:38.540 --> 00:14:40.330
Because what I'm observing is,

00:14:40.354 --> 00:14:42.403
the good teachers,
for a lot of these kids,

00:14:42.427 --> 00:14:44.075
are out in the community colleges.

00:14:44.099 --> 00:14:46.635
But we need to be getting
some of these good teachers

00:14:46.659 --> 00:14:47.810
into the high schools.

NOTE Paragraph

00:14:47.834 --> 00:14:51.390
Another thing that can be very,
very, very successful is:

00:14:51.414 --> 00:14:53.522
there's a lot of people
that may have retired

00:14:53.546 --> 00:14:55.368
from working in the software industry,

00:14:55.392 --> 00:14:56.780
and they can teach your kid.

00:14:56.804 --> 00:14:59.613
And it doesn't matter
if what they teach them is old,

00:14:59.637 --> 00:15:02.364
because what you're doing
is you're lighting the spark.

00:15:02.388 --> 00:15:04.852
You're getting that kid turned on.

00:15:04.876 --> 00:15:08.291
And you get him turned on,
then you'll learn all the new stuff.

00:15:08.315 --> 00:15:10.579
Mentors are just essential.

00:15:10.603 --> 00:15:14.336
I cannot emphasize enough
what my science teacher did for me.

00:15:14.944 --> 00:15:17.976
And we've got to mentor them, hire them.

NOTE Paragraph

00:15:18.000 --> 00:15:20.808
And if you bring them in
for internships in your companies,

00:15:20.832 --> 00:15:23.305
the thing about the autism,
Asperger-y kind of mind,

00:15:23.329 --> 00:15:25.297
you've got to give them a specific task.

00:15:25.321 --> 00:15:27.163
Don't just say, "Design new software."

00:15:27.187 --> 00:15:29.454
You've got to tell them
something more specific:

00:15:29.478 --> 00:15:31.375
"We're designing software for a phone

00:15:31.399 --> 00:15:33.199
and it has to do some specific thing,

00:15:33.223 --> 00:15:34.976
and it can only use so much memory."

00:15:35.000 --> 00:15:37.427
That's the kind of specificity you need.

NOTE Paragraph

00:15:37.451 --> 00:15:39.310
Well, that's the end of my talk.

00:15:39.334 --> 00:15:41.577
And I just want to thank
everybody for coming.

00:15:41.601 --> 00:15:42.976
It was great to be here.

NOTE Paragraph

00:15:43.000 --> 00:15:50.000
(Applause)

00:15:54.526 --> 00:15:56.717
(Applause ends)

NOTE Paragraph

00:15:56.741 --> 00:15:58.566
Oh -- you have a question for me? OK.

NOTE Paragraph

00:15:58.590 --> 00:16:00.987
(Applause)

NOTE Paragraph

00:16:01.011 --> 00:16:03.039
Chris Anderson:
Thank you so much for that.

00:16:03.063 --> 00:16:05.389
You know, you once wrote --
I like this quote:

00:16:05.413 --> 00:16:09.974
"If by some magic, autism had been
eradicated from the face of the Earth,

00:16:09.998 --> 00:16:12.975
then men would still be socializing
in front of a wood fire

00:16:12.999 --> 00:16:14.340
at the entrance to a cave."

NOTE Paragraph

00:16:14.364 --> 00:16:15.392
(Laughter)

NOTE Paragraph

00:16:15.416 --> 00:16:18.652
Temple Grandin: Because who do you think
made the first stone spear?

00:16:18.676 --> 00:16:19.834
It was the Asperger guy,

00:16:19.858 --> 00:16:22.411
and if you were to get rid
of all the autism genetics,

00:16:22.435 --> 00:16:26.100
there'd be no more Silicon Valley,
and the energy crisis would not be solved.

NOTE Paragraph

00:16:26.124 --> 00:16:27.465
(Applause)

NOTE Paragraph

00:16:27.489 --> 00:16:29.719
CA: I want to ask you
a couple other questions,

00:16:29.743 --> 00:16:33.507
and if any of these feel inappropriate,
it's OK just to say, "Next question."

00:16:33.531 --> 00:16:37.145
But if there is someone here
who has an autistic child,

00:16:37.169 --> 00:16:41.910
or knows an autistic child and feels
kind of cut off from them,

00:16:42.533 --> 00:16:44.380
what advice would you give them?

NOTE Paragraph

00:16:44.404 --> 00:16:46.733
TG: Well, first of all,
we've got to look at age.

00:16:46.757 --> 00:16:50.706
If you have a two, three or four-year-old,
no speech, no social interaction,

00:16:50.730 --> 00:16:53.019
I can't emphasize enough: Don't wait.

00:16:53.043 --> 00:16:56.173
You need at least 20 hours a week
of one-to-one teaching.

00:16:56.352 --> 00:16:58.845
The thing is, autism comes
in different degrees.

00:16:58.869 --> 00:17:02.376
About half of the people on the spectrum
are not going to learn to talk,

00:17:02.400 --> 00:17:04.501
and they won't be working
in Silicon Valley.

00:17:04.525 --> 00:17:06.975
That would not be a reasonable
thing for them to do.

NOTE Paragraph

00:17:06.999 --> 00:17:10.076
But then you get these smart,
geeky kids with a touch of autism,

00:17:10.100 --> 00:17:12.580
and that's where you've got
to get them turned on

00:17:12.604 --> 00:17:14.093
with doing interesting things.

00:17:14.117 --> 00:17:17.132
I got social interaction
through shared interests --

00:17:17.156 --> 00:17:21.113
I rode horses with other kids,
I made model rockets with other kids,

00:17:21.137 --> 00:17:23.115
did electronics lab with other kids.

00:17:23.139 --> 00:17:27.390
And in the '60s, it was gluing mirrors
onto a rubber membrane on a speaker

00:17:27.414 --> 00:17:28.595
to make a light show.

00:17:28.619 --> 00:17:30.841
That was, like,
we considered that super cool.

NOTE Paragraph

00:17:30.865 --> 00:17:31.871
(Laughter)

NOTE Paragraph

00:17:31.895 --> 00:17:33.392
CA: Is it unrealistic for them

00:17:33.416 --> 00:17:38.156
to hope or think that that child
loves them, as some might, as most, wish?

NOTE Paragraph

00:17:38.180 --> 00:17:40.414
TG: Well, I tell you,
that child will be loyal,

00:17:40.438 --> 00:17:43.813
and if your house is burning down,
they're going to get you out of it.

NOTE Paragraph

00:17:43.837 --> 00:17:47.496
CA: Wow. So most people, if you ask them
what they're most passionate about,

00:17:47.520 --> 00:17:50.368
they'd say things like,
"My kids" or "My lover."

00:17:51.010 --> 00:17:52.762
What are you most passionate about?

NOTE Paragraph

00:17:52.786 --> 00:17:55.817
TG: I'm passionate
about that the things I do

00:17:55.841 --> 00:17:57.878
are going to make
the world a better place.

00:17:57.902 --> 00:18:00.124
When I have a mother
of an autistic child say,

00:18:00.148 --> 00:18:02.210
"My kid went to college
because of your book

00:18:02.234 --> 00:18:03.434
or one of your lectures,"

00:18:03.458 --> 00:18:04.609
that makes me happy.

NOTE Paragraph

00:18:04.633 --> 00:18:07.346
You know, the slaughter plants
I worked with in the '80s;

00:18:07.370 --> 00:18:08.687
they were absolutely awful.

00:18:08.711 --> 00:18:11.987
I developed a really simple
scoring system for slaughter plants,

00:18:12.011 --> 00:18:13.563
where you just measure outcomes:

00:18:13.587 --> 00:18:14.829
How many cattle fell down?

00:18:14.853 --> 00:18:16.601
How many got poked with the prodder?

00:18:16.625 --> 00:18:18.656
How many cattle
are mooing their heads off?

00:18:19.018 --> 00:18:20.352
And it's very, very simple.

00:18:20.376 --> 00:18:22.353
You directly observe a few simple things.

00:18:22.377 --> 00:18:23.541
It's worked really well.

00:18:23.565 --> 00:18:25.904
I get satisfaction out of seeing stuff

00:18:25.928 --> 00:18:28.648
that makes real change in the real world.

00:18:28.672 --> 00:18:31.421
We need a lot more of that,
and a lot less abstract stuff.

NOTE Paragraph

00:18:31.445 --> 00:18:32.596
CA: Totally.

NOTE Paragraph

00:18:32.620 --> 00:18:37.703
(Applause)

NOTE Paragraph

00:18:37.727 --> 00:18:40.826
CA: When we were talking on the phone,
one of the things you said

00:18:40.850 --> 00:18:42.052
that really astonished me

00:18:42.076 --> 00:18:45.237
was that one thing you were passionate
about was server farms.

00:18:45.843 --> 00:18:46.994
Tell me about that.

NOTE Paragraph

00:18:47.018 --> 00:18:50.395
TG: Well, the reason why I got really
excited when I read about that,

00:18:50.419 --> 00:18:52.075
it contains knowledge.

00:18:52.099 --> 00:18:53.757
It's libraries.

00:18:53.781 --> 00:18:57.300
And to me, knowledge is something
that is extremely valuable.

00:18:57.324 --> 00:19:00.440
So, maybe over 10 years ago
now, our library got flooded.

00:19:00.464 --> 00:19:02.515
This is before the Internet
got really big.

00:19:02.539 --> 00:19:05.220
And I was really upset
about all the books being wrecked,

00:19:05.244 --> 00:19:07.220
because it was knowledge being destroyed.

00:19:07.244 --> 00:19:11.657
And server farms, or data centers,
are great libraries of knowledge.

NOTE Paragraph

00:19:11.681 --> 00:19:12.972
CA: Temple, can I just say,

00:19:12.996 --> 00:19:15.082
it's an absolute delight
to have you at TED.

00:19:15.106 --> 00:19:16.257
Thank you so much.

NOTE Paragraph

00:19:16.281 --> 00:19:18.176
TG: Well, thank you so much. Thank you.

NOTE Paragraph

00:19:18.200 --> 00:19:23.436
(Applause)