Geoffrey West: The surprising math of cities and corporations

170,139 views ・ 2011-07-26

TED


μ•„λž˜ μ˜λ¬Έμžλ§‰μ„ λ”λΈ”ν΄λ¦­ν•˜μ‹œλ©΄ μ˜μƒμ΄ μž¬μƒλ©λ‹ˆλ‹€.

λ²ˆμ—­: Jeong-Lan Kinser κ²€ν† : Kyo young Chu
00:16
Cities are the crucible of civilization.
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λ„μ‹œλŠ” λ¬Έλͺ…μ˜ λ„κ°€λ‹ˆμž…λ‹ˆλ‹€
00:19
They have been expanding,
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λ„μ‹œλ“€μ€ ν™•μž₯ν•˜κ³ 
00:21
urbanization has been expanding,
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λ„μ‹œν™”λŠ” μ§€λ‚œ 200λ…„ κ°„
00:23
at an exponential rate in the last 200 years
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κΈ°ν•˜κΈ‰μˆ˜μ μΈ μ†λ„λ‘œ μ§„ν–‰λ˜μ—ˆμŠ΅λ‹ˆλ‹€
00:25
so that by the second part of this century,
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κ·Έλž˜μ„œ 이 μ„ΈκΈ°μ˜ ν›„λ°˜λΆ€κ°€ 되면
00:28
the planet will be completely dominated
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이 행성은 λ„μ‹œλ“€μ— μ˜ν•΄μ„œ μ™„μ „νžˆ
00:30
by cities.
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지배될 κ²ƒμž…λ‹ˆλ‹€
00:33
Cities are the origins of global warming,
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λ„μ‹œλŠ” 지ꡬ μ˜¨λ‚œν™”,
00:36
impact on the environment,
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ν™˜κ²½μ— λ―ΈμΉ˜λŠ” 영ν–₯λ“€,
00:38
health, pollution, disease,
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건강, μ˜€μ—Ό, μ§ˆλ³‘,
00:41
finance,
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μž¬μ •,
00:43
economies, energy --
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경제, μ—λ„ˆμ§€μ˜ μ›μ²œμž…λ‹ˆλ‹€
00:46
they're all problems
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이 λͺ¨λ“  λ¬Έμ œλ“€μ€
00:48
that are confronted by having cities.
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λ„μ‹œκ°€ 있기 λ•Œλ¬Έμ— μ§λ©΄ν•˜κ²Œ λ˜λŠ” κ²ƒλ“€μž…λ‹ˆλ‹€
00:50
That's where all these problems come from.
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μš°λ¦¬κ°€ μ§€μ†μ„±μ˜ μΈ‘λ©΄μ—μ„œ
00:52
And the tsunami of problems that we feel we're facing
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직면해 μžˆλ‹€κ³  λŠλΌλŠ”
00:55
in terms of sustainability questions
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μ—„μ²­λ‚˜κ²Œ λ§Žμ€ λ¬Έμ œμ λ“€μ€
00:57
are actually a reflection
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μ‹€μ œλ‘œ 이 ν–‰μ„±μ—μ„œ
00:59
of the exponential increase
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μžˆμ–΄λ‚˜κ³  μžˆλŠ” κΈ°ν•˜κΈ‰μˆ˜μ μΈ
01:01
in urbanization across the planet.
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λ„μ‹œν™”μ˜ λ‹€λ₯Έ λͺ¨μŠ΅μž…λ‹ˆλ‹€
01:04
Here's some numbers.
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λͺ‡ 가지 숫자λ₯Ό 보죠
01:06
Two hundred years ago, the United States
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200λ…„ 전에 미ꡭ은
01:08
was less than a few percent urbanized.
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거의 λ„μ‹œν™” λ˜μ§€ μ•Šμ•˜μ—ˆμŠ΅λ‹ˆλ‹€
01:10
It's now more than 82 percent.
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μ§€κΈˆμ€ 82% 이상이 λ„μ‹œμž…λ‹ˆλ‹€
01:12
The planet has crossed the halfway mark a few years ago.
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μ „ μ§€κ΅¬μ μœΌλ‘œλŠ” λͺ‡ λ…„ 전에 절반이 λ„μ‹œν™”κ°€ μ΄λ£¨μ–΄μ‘ŒμŠ΅λ‹ˆλ‹€
01:15
China's building 300 new cities
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쀑ꡭ은 20λ…„ μ•ˆμ— 300개의 λ„μ‹œλ₯Ό
01:17
in the next 20 years.
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λ§Œλ“€ κ²ƒμž…λ‹ˆλ‹€
01:19
Now listen to this:
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이 이야기λ₯Ό ν•œ 번 λ“€μ–΄λ³΄μ„Έμš”
01:21
Every week for the foreseeable future,
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μ˜ˆμΈ‘κ°€λŠ₯ν•œ 미래인 2050λ…„κΉŒμ§€
01:24
until 2050,
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맀 주
01:26
every week more than a million people
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100만λͺ… μ΄μƒμ˜ μ‚¬λžŒλ“€μ΄
01:28
are being added to our cities.
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우리 λ„μ‹œμ— νŽΈμž…λ  κ²ƒμž…λ‹ˆλ‹€
01:30
This is going to affect everything.
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이 사싀은 λͺ¨λ“  것듀에 영ν–₯을 λ―ΈμΉ κ²λ‹ˆλ‹€
01:32
Everybody in this room, if you stay alive,
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κ·Έλ•ŒκΉŒμ§€ μ‚΄μ•„μžˆλ‹€λ©΄, 여기에 μžˆλŠ” λͺ¨λ“  μ‚¬λžŒλ“€μ€
01:34
is going to be affected
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λ„μ‹œμ—μ„œ μΌμ–΄λ‚˜κ³  μžˆλŠ”
01:36
by what's happening in cities
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이 μ—„μ²­λ‚œ 사싀듀에 μ˜ν•΄μ„œ
01:38
in this extraordinary phenomenon.
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영ν–₯을 받을 κ²ƒμž…λ‹ˆλ‹€
01:40
However, cities,
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ν•˜μ§€λ§Œ,
01:43
despite having this negative aspect to them,
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이런 뢀정적인 μΈ‘λ©΄μ—μ„œ λΆˆκ΅¬ν•˜κ³ ,
01:46
are also the solution.
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ν•΄κ²°μ±… λ˜ν•œ λ„μ‹œμž…λ‹ˆλ‹€
01:48
Because cities are the vacuum cleaners and the magnets
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λ„μ‹œλŠ” λ˜ν•œ 창의적인 μ‚¬λžŒλ“€, μƒˆλ‘œμš΄ 아이디어,
01:52
that have sucked up creative people,
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ν˜μ‹ , 그리고 λΆ€ 등을 λŒμ–΄λͺ¨μœΌλŠ”
01:54
creating ideas, innovation,
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진곡 μ²­μ†ŒκΈ°μ΄μž
01:56
wealth and so on.
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μžμ„μ΄κΈ° λ•Œλ¬Έμ΄μ£ 
01:58
So we have this kind of dual nature.
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κ·Έλž˜μ„œ μš°λ¦¬λŠ” λ™μ‹œμ— 두 가지 츑면을 가지고 μžˆλŠ” μ…ˆμž…λ‹ˆλ‹€
02:00
And so there's an urgent need
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κ·Έλž˜μ„œ λ„μ‹œμ— λŒ€ν•œ 과학적 이둠이
02:03
for a scientific theory of cities.
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μ•„μ£Ό κΈ‰ν•˜κ²Œ ν•„μš”ν•©λ‹ˆλ‹€
02:07
Now these are my comrades in arms.
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이듀이 무μž₯ν•œ μ €μ˜ λ™λ£Œλ“€μž…λ‹ˆλ‹€
02:10
This work has been done with an extraordinary group of people,
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이 일은 이 λ›°μ–΄λ‚œ μ‚¬λžŒλ“€μ— μ˜ν•΄ μ§„ν–‰λ˜μ—ˆμŠ΅λ‹ˆλ‹€
02:12
and they've done all the work,
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그듀은 μ•„μ£Ό ν›Œλ₯­νžˆ 일을 ν•΄λƒˆκ³ ,
02:14
and I'm the great bullshitter
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μ €λŠ” 이것듀을 ν•œ ꡰ데 λͺ¨μ•„μ„œ
02:16
that tries to bring it all together.
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ν—›νŠΌ μ†Œλ¦¬λ₯Ό ν•˜λŠ” μ‚¬λžŒμž…λ‹ˆλ‹€
02:18
(Laughter)
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(μ›ƒμŒ)
02:20
So here's the problem: This is what we all want.
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문제λ₯Ό λ΄…μ‹œλ‹€: 이것이 μš°λ¦¬κ°€ μ›ν•˜λŠ” κ²ƒμž…λ‹ˆλ‹€
02:22
The 10 billion people on the planet in 2050
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2050년에 지ꡬ에 μ‚¬λŠ” 100μ–΅λͺ…μ˜ μ‚¬λžŒλ“€μ€
02:25
want to live in places like this,
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이런 것듀을 가지고,
02:27
having things like this,
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이런 것듀을 ν•˜λ©°,
02:29
doing things like this,
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μ΄λ ‡κ²Œ μ„±μž₯ν•˜λŠ” κ²½μ œμ—μ„œ
02:31
with economies that are growing like this,
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μ‚΄κ³  μ‹Άμ–΄ ν•©λ‹ˆλ‹€
02:34
not realizing that entropy
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ν•˜μ§€λ§Œ 이런 κ²ƒμ΄λ‚˜,
02:36
produces things like this,
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이것, λ˜λŠ” 이것이
02:38
this, this
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λ§Œλ“€μ–΄ λ‚΄λŠ” μ—”νŠΈλ‘œν”ΌλŠ”
02:42
and this.
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깨닫지 λͺ»ν•œ μ±„λ‘œ 말이죠
02:44
And the question is:
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μ§ˆλ¬Έμ€ μ΄λ ‡μŠ΅λ‹ˆλ‹€
02:46
Is that what Edinburgh and London and New York
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2050λ…„μ˜ μ—λ”˜λ²„λŸ¬, 런던, λ‰΄μš•μ€
02:48
are going to look like in 2050,
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이런 λͺ¨μŠ΅μΌκΉŒμš”
02:50
or is it going to be this?
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μ•„λ‹ˆλ©΄ μ΄λ ‡κ²Œ λ³΄μΌκΉŒμš”.
02:52
That's the question.
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이것이 λ°”λ‘œ μ§ˆλ¬Έμž…λ‹ˆλ‹€
02:54
I must say, many of the indicators
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이것같은 λ§Žμ€ μ§€ν‘œλ“€μ΄
02:56
look like this is what it's going to look like,
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μ‹€μ œλ‘œ λ³΄μ΄λŠ” λͺ¨μŠ΅μΌκ±°λΌκ΅¬μš”
02:59
but let's talk about it.
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ν•˜μ§€λ§Œ 그것에 λŒ€ν•΄ 이야기 ν•΄ λ΄…μ‹œλ‹€
03:02
So my provocative statement
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λ„λ°œμ μΈ μ €μ˜ μ§„μˆ μ€
03:05
is that we desperately need a serious scientific theory of cities.
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μš°λ¦¬λŠ” λ„μ‹œμ— λŒ€ν•΄ μ§„μ§€ν•˜κ³  과학적인 이둠이 μ ˆμ‹€νžˆ ν•„μš”ν•˜λ‹€λŠ” κ²ƒμž…λ‹ˆλ‹€
03:08
And scientific theory means quantifiable --
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그리고 과학적 μ΄λ‘ μ΄λΌλŠ” 것은
03:11
relying on underlying generic principles
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예츑 μ‹œμŠ€ν…œμ΄ 될 수 μžˆλŠ” 기초적인 일반적
03:14
that can be made into a predictive framework.
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원리에 μž…κ°ν•œ μˆ˜λŸ‰ν™”λ₯Ό μ˜λ―Έν•©λ‹ˆλ‹€
03:16
That's the quest.
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이게 저희가 ν•΄μ•Όν•  μΌμž…λ‹ˆλ‹€
03:18
Is that conceivable?
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κ°€λŠ₯ν• κΉŒμš”?
03:20
Are there universal laws?
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일반적인 법칙이 μ‘΄μž¬ν• κΉŒμš”?
03:22
So here's two questions
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이 λ¬Έμ œμ— λŒ€ν•΄μ„œ
03:24
that I have in my head when I think about this problem.
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이게 μ œκ°€ 이 λ¬Έμ œμ— λŒ€ν•΄ κ°–κ³  μžˆλŠ” 두 가지 μ˜λ¬Έμ μž…λ‹ˆλ‹€
03:26
The first is:
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μ²«λ²ˆμ§ΈλŠ”,
03:28
Are cities part of biology?
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"λ„μ‹œλŠ” μƒλ¬Όν•™μ˜ 일뢀인가?"μž…λ‹ˆλ‹€
03:30
Is London a great big whale?
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λŸ°λ˜μ€ 큰 κ³ λž˜μΈκ°€μš”?
03:32
Is Edinburgh a horse?
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μ—λ”˜λ²„λŸ¬λŠ” λ§μΈκ°€μš”?
03:34
Is Microsoft a great big anthill?
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λ§ˆμ΄ν¬λ‘œμ†Œν”„νŠΈλŠ” κ±°λŒ€ν•œ κ°œλ―Ένƒ‘μΈκ°€μš”?
03:36
What do we learn from that?
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μ΄κ²ƒλ“€λ‘œλΆ€ν„° 무엇을 배울 수 μžˆμ„κΉŒμš”?
03:38
We use them metaphorically --
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μš°λ¦¬λŠ” 생물학을 'νšŒμ‚¬μ˜ DNA'λ‚˜
03:40
the DNA of a company, the metabolism of a city, and so on --
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'λ„μ‹œμ˜ μ‹ μ§„λŒ€μ‚¬' λ“±κ³Ό 같이 λΉ„μœ μ μœΌλ‘œ μ‚¬μš©ν•©λ‹ˆλ‹€
03:42
is that just bullshit, metaphorical bullshit,
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이게 단지 μ€μœ μ μΈ ν‘œν˜„μ— 에 λΆˆκ³Όν•œ λ§μΌκΉŒμš”,
03:45
or is there serious substance to it?
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μ•„λ‹ˆλ©΄ μ§„μ§€ν•œ 싀체가 μžˆμ„κΉŒμš”?
03:48
And if that is the case,
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ν•˜μ§€λ§Œ 이것이 사싀이라면
03:50
how come that it's very hard to kill a city?
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μ–΄μ§Έμ„œ λ„μ‹œλ₯Ό μ£½μ΄λŠ” 것이 그토둝 μ–΄λ €μšΈκΉŒμš”?
03:52
You could drop an atom bomb on a city,
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μš°λ¦¬λŠ” λ„μ‹œμ— μ›μžν­νƒ„μ„ λ–¨μ–΄νŠΈλ¦΄ μˆ˜λ„ μžˆκ² μ§€λ§Œ,
03:54
and 30 years later it's surviving.
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30λ…„ λ’€μ—” λ‹€μ‹œ μ‚΄μ•„λ‚  κ²ƒμž…λ‹ˆλ‹€
03:56
Very few cities fail.
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μ•„μ£Ό 적은 수의 λ„μ‹œλ§Œμ΄ λ¬΄λ„ˆμ§€μ§€μš”
03:59
All companies die, all companies.
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λͺ¨λ“  기업은 μ£½μŠ΅λ‹ˆλ‹€
04:02
And if you have a serious theory, you should be able to predict
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λ§Œμ•½ μ—¬λŸ¬λΆ„μ΄ μ œλŒ€λ‘œ 된 이둠을 가지고 μžˆλ‹€λ©΄, ꡬ글이 μ–Έμ œ
04:04
when Google is going to go bust.
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νŒŒμ‚°ν• μ§€ μ˜ˆμΈ‘ν•  수 μžˆμ–΄μ•Όν•©λ‹ˆλ‹€
04:07
So is that just another version
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κ·Έλ ‡λ‹€λ©΄ 그것은 μ΄κ²ƒμ˜ 단지
04:10
of this?
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λ‹€λ₯Έ λ²„μ „μΌκΉŒμš”?
04:12
Well we understand this very well.
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이런 것듀에 λŒ€ν•΄μ„œ μš°λ¦¬λŠ” 잘 μ΄ν•΄ν•˜κ³  μžˆμŠ΅λ‹ˆλ‹€
04:14
That is, you ask any generic question about this --
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즉, μ—¬λŸ¬λΆ„μ€
04:16
how many trees of a given size,
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μ–Όλ§ˆλ‚˜ λ§Žμ€ νŠΉμ •ν•œ 크기의 λ‚˜λ¬΄λ“€μ΄ μžˆλŠ”μ§€,
04:18
how many branches of a given size does a tree have,
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λ‚˜λ¬΄ ν•œ 그루가 μ–Όλ§ˆλ‚˜ λ§Žμ€ 가지λ₯Ό 가지고 μžˆλŠ”μ§€,
04:20
how many leaves,
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μ–Όλ§ˆλ‚˜ λ§Žμ€ μžŽμ„ 가지고 μžˆλŠ”μ§€,
04:22
what is the energy flowing through each branch,
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가지듀 μ‚¬μ΄λ‘œ 흐λ₯΄λŠ” μ—λ„ˆμ§€λŠ” 무엇인지,
04:24
what is the size of the canopy,
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μΊλ…Έν”Όμ˜ ν¬κΈ°λŠ” μ–΄λŠ 정도인지,
04:26
what is its growth, what is its mortality?
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μ„±μž₯κ³Ό μ£½μŒμ€ μ–΄λ–€ 것인지와 같은 μ§ˆλ¬Έλ“€μ„ ν•˜μ‹€ 수 μžˆμ„ κ²λ‹ˆλ‹€
04:28
We have a mathematical framework
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μš°λ¦¬λŠ” 이런 μ§ˆλ¬Έλ“€μ— λŒ€λ‹΅ν•  수 μžˆλŠ”
04:30
based on generic universal principles
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일반적인 원칙에 κ·Όκ±°ν•œ
04:33
that can answer those questions.
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μˆ˜ν•™μ  ν”„λ ˆμž„μ›Œν¬λ₯Ό 가지고 μžˆμŠ΅λ‹ˆλ‹€
04:35
And the idea is can we do the same for this?
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그리고 κ·Έ 쀑심 μ•„μ΄λ””μ–΄λŠ” "μš°λ¦¬κ°€ 여기에도 같은 것을 μ μš©ν•  수 μžˆμ„κΉŒ?" ν•˜λŠ” κ²ƒμž…λ‹ˆλ‹€
04:40
So the route in is recognizing
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κ·Έλž˜μ„œ κ·Έ λ…Έμ„ μ—μ„œ
04:43
one of the most extraordinary things about life,
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생λͺ…에 λŒ€ν•œ κ°€μž₯ λ†€λΌμš΄ 사싀이 μΈμ§€λ˜κ³  μžˆλŠ” 것은,
04:45
is that it is scalable,
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그것이 ν™•μž₯κ°€λŠ₯ν•˜λ‹€λŠ” μ μž…λ‹ˆλ‹€.
04:47
it works over an extraordinary range.
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생λͺ…은 μ—„μ²­λ‚œ λ²”μœ„μ—μ„œ μž‘μš©ν•©λ‹ˆλ‹€
04:49
This is just a tiny range actually:
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이것은 μ‹€μ œλ‘œ μ•„μ£Ό μž‘μ€ λ²”μœ„μž…λ‹ˆλ‹€
04:51
It's us mammals;
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단지 우리 포유λ₯˜μ£ 
04:53
we're one of these.
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μš°λ¦¬λŠ” μ΄κ²ƒλ“€μ˜ μΌλΆ€μž…λ‹ˆλ‹€
04:55
The same principles, the same dynamics,
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같은 원리, 같은 μ—­ν•™
04:57
the same organization is at work
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같은 쑰직이 우리λ₯Ό ν¬ν•¨ν•œ 이 λͺ¨λ“  κ²ƒλ“€μ—μ„œ
04:59
in all of these, including us,
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ν™œλ™μ€‘μ΄κ³ ,
05:01
and it can scale over a range of 100 million in size.
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그리고 ν¬κΈ°λ©΄μ—μ„œ 1μ–΅μ˜ λ²”μœ„κΉŒμ§€ ν™•μž₯ν•  수 μžˆμŠ΅λ‹ˆλ‹€
05:04
And that is one of the main reasons
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그리고 이것이 생λͺ…이 그토둝
05:07
life is so resilient and robust --
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볡원λ ₯이 κ°•ν•˜κ³  κ°•κ±΄ν•œ μ΄μœ μ€‘ ν•˜λ‚˜μΈ--
05:09
scalability.
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μΈ‘μ •κ°€λŠ₯μ„±μž…λ‹ˆλ‹€
05:11
We're going to discuss that in a moment more.
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이것에 λŒ€ν•΄μ„œλŠ” μž μ‹œ 후에 λ‹€μ‹œ μ΄μ•ΌκΈ°ν•˜λ„λ‘ ν•˜κ² μŠ΅λ‹ˆλ‹€
05:14
But you know, at a local level,
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ν•˜μ§€λ§Œ 지역적인 μˆ˜μ€€μ—μ„œ
05:16
you scale; everybody in this room is scaled.
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μ—¬λŸ¬λΆ„, 그리고 이 방의 λͺ¨λ‘λŠ” ν™•μž₯ λ˜μ—ˆμŠ΅λ‹ˆλ‹€
05:18
That's called growth.
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그것을 μ„±μž₯이라고 λΆ€λ₯΄μ£ 
05:20
Here's how you grew.
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μ—¬λŸ¬λΆ„μ€ μ΄λ ‡κ²Œ μ„±μž₯ν•©λ‹ˆλ‹€
05:22
Rat, that's a rat -- could have been you.
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저것은 μ₯μΈλ°--μ—¬λŸ¬λΆ„μΌμˆ˜λ„ 있죠
05:24
We're all pretty much the same.
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우리 λͺ¨λ‘λŠ” κ°™μŠ΅λ‹ˆλ‹€
05:27
And you see, you're very familiar with this.
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μ—¬λŸ¬λΆ„λ“€μ€ 이것에 μ•„μ£Ό μ΅μˆ™ν•  κ²ƒμž…λ‹ˆλ‹€
05:29
You grow very quickly and then you stop.
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μ—¬λŸ¬λΆ„μ€ μ•„μ£Ό λΉ λ₯΄κ²Œ μ„±μž₯ν•˜κ³  곧 멈μΆ₯λ‹ˆλ‹€
05:31
And that line there
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그리고 μ €κΈ° μžˆλŠ” 선은
05:33
is a prediction from the same theory,
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같은 원리에 κ·Όκ±°ν•œ
05:35
based on the same principles,
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같은 μ΄λ‘ μ—μ„œ λ‚˜μ˜¨ μˆ²μ— λŒ€ν•΄ κΈ°μˆ ν•œ
05:37
that describes that forest.
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μ˜ˆμΈ‘μž…λ‹ˆλ‹€
05:39
And here it is for the growth of a rat,
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μ—¬κΈ° μ₯μ˜ μ„±μž₯에 λŒ€ν•œ 것이 μžˆμŠ΅λ‹ˆλ‹€
05:41
and those points on there are data points.
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μ €κΈ° μžˆλŠ” 점듀은 데이터 κ°’λ“€μž…λ‹ˆλ‹€
05:43
This is just the weight versus the age.
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이것은 λ‚˜μ΄μ— λŒ€ν•œ λͺΈλ¬΄κ²Œμ˜ κ·Έλž˜ν”„μž…λ‹ˆλ‹€
05:45
And you see, it stops growing.
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λ³΄μ‹œλŠ” 바와 같이, μ–΄λŠ μ‹œμ μ—μ„œ μ„±μž₯을 멈μΆ₯λ‹ˆλ‹€
05:47
Very, very good for biology --
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이것은 μƒλ¬Όν•™μ—κ²ŒλŠ” μ•„μ£Ό μ•„μ£Ό μ’‹κ³ 
05:49
also one of the reasons for its great resilience.
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λŒ€λ‹¨ν•œ 볡원λ ₯에 λŒ€ν•œ μ΄μœ λ“€ 쀑 ν•˜λ‚˜μ΄κΈ°λ„ ν•˜μ£ 
05:51
Very, very bad
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우리의 ν˜„μž¬ νŒ¨λŸ¬λ‹€μž„μ—μ„œ
05:53
for economies and companies and cities
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κ²½μ œμ™€ νšŒμ‚¬,
05:55
in our present paradigm.
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그리고 λ„μ‹œμ—λŠ” μ•„μ£Ό μ•„μ£Ό λ‚˜μ˜μ£ 
05:57
This is what we believe.
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이것이 μš°λ¦¬κ°€ λ―ΏλŠ” λ°”μž…λ‹ˆλ‹€
05:59
This is what our whole economy
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이것이 우리의 경제 전체가 μš°λ¦¬μ—κ²Œ
06:01
is thrusting upon us,
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λ§Ήκ³΅κ²©ν•˜λŠ” κ²ƒμž…λ‹ˆλ‹€
06:03
particularly illustrated in that left-hand corner:
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특히 μ™ΌνŽΈ ꡬ석에 λ¬˜μ‚¬λœ
06:06
hockey sticks.
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ν•˜ν‚€μŠ€ν‹± λ§μž…λ‹ˆλ‹€
06:08
This is a bunch of software companies --
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이것듀은 μ—¬λŸ¬ μ†Œν”„νŠΈμ›¨μ–΄ νšŒμ‚¬λ“€μ˜
06:10
and what it is is their revenue versus their age --
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λ‚˜μ΄μ™€ μˆ˜μ΅μ„ λ‚˜νƒ€λ‚΄λŠ” κ·Έλž˜ν”„μž…λ‹ˆλ‹€
06:12
all zooming away,
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λ©€λ¦¬μ„œ 보면
06:14
and everybody making millions and billions of dollars.
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λͺ¨λ‘κ°€ 수 백만, 수 μ‹­μ–΅ λ‹¬λŸ¬λ₯Ό 벌고 μžˆμŠ΅λ‹ˆλ‹€
06:16
Okay, so how do we understand this?
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이것을 μ–΄λ–»κ²Œ 이해해야 ν• κΉŒμš”?
06:19
So let's first talk about biology.
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λ¨Όμ € 생물학에 λŒ€ν•΄μ„œ μ΄μ•ΌκΈ°ν•΄λ΄…μ‹œλ‹€
06:22
This is explicitly showing you
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이것은 μ—¬λŸ¬λΆ„λ“€μ—κ²Œ λͺ…λ°±ν•˜κ²Œ
06:24
how things scale,
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사물이 μ–΄λ–»κ²Œ ν™•μž₯ν•˜λŠ”μ§€ λ³΄μ—¬μ€λ‹ˆλ‹€
06:26
and this is a truly remarkable graph.
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이것은 μ§„μ •μœΌλ‘œ κ΄„λͺ©ν• λ§Œν•œ κ·Έλž˜ν”„μΈλ°μš”
06:28
What is plotted here is metabolic rate --
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μ—¬κΈ° μ œλ„λœ 것은 μ‹ μ§„λŒ€μ‚¬μ  λΉ„μœ¨μž…λ‹ˆλ‹€
06:31
how much energy you need per day to stay alive --
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μ—¬λŸ¬λΆ„μ˜ 무게, λ©μΉ˜μ— λΉ„λ‘€ν•΄μ„œ 우리 λͺ¨λ“  생λͺ…체가
06:34
versus your weight, your mass,
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μ‚΄μ•„κ°€κΈ° μœ„ν•΄μ„œ
06:36
for all of us bunch of organisms.
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ν•˜λ£¨μ— μ–΄λŠ μ •λ„μ˜ μ—λ„ˆμ§€κ°€ ν•„μš”ν•œμ§€λ₯Ό λ³΄μ—¬μ€λ‹ˆλ‹€
06:39
And it's plotted in this funny way by going up by factors of 10,
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이 κ·Έλž˜ν”„λŠ” 10의 μ§€μˆ˜λ‘œ μ¦κ°€λ˜λŠ” κ²ƒμœΌλ‘œ 재미있게 μ œλ„λ˜μ—ˆμŠ΅λ‹ˆλ‹€
06:42
otherwise you couldn't get everything on the graph.
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그렇지 μ•ŠμœΌλ©΄ 이 κ·Έλž˜ν”„μ— λͺ¨λ‘ 담을 μˆ˜κ°€ μ—†μ—ˆμŠ΅λ‹ˆλ‹€
06:44
And what you see if you plot it
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이런 μ•½κ°„ ν˜ΈκΈ°μ‹¬μ–΄λ¦° λ°©λ²•μœΌλ‘œ
06:46
in this slightly curious way
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μ—¬λŸ¬λΆ„μ΄ μ œλ„λ₯Ό ν•˜λŠ” 경우 보게 λ˜λŠ”κ²ƒμ€
06:48
is that everybody lies on the same line.
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λͺ¨λ‘κ°€ 같은 선에 λ†“μΈλ‹€λŠ” 것을 μ•Œκ²Œλ©λ‹ˆλ‹€
06:51
Despite the fact that this is the most complex and diverse system
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이것이 μš°μ£Όμ—μ„œ κ°€μž₯ λ³΅μž‘ν•˜κ³  λ‹€μ–‘ν•œ μ‹œμŠ€ν…œμ΄λΌλŠ” 사싀에도 λΆˆκ΅¬ν•˜κ³ 
06:54
in the universe,
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μ΄λ ‡κ²Œ ν‘œν˜„λ˜λŠ” κ²ƒμ—λŠ”
06:57
there's an extraordinary simplicity
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λ†€λΌμš΄ λ‹¨μˆœμ„±μ΄
06:59
being expressed by this.
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μ‘΄μž¬ν•©λ‹ˆλ‹€
07:01
It's particularly astonishing
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이것듀은 νŠΉλ³„νžˆ λ†€λΌμš΄λ°,
07:04
because each one of these organisms,
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이 λͺ¨λ“  생λͺ…μ²΄μ˜ 각각은, ν•˜λΆ€μ‘°μ§, 세포듀,
07:06
each subsystem, each cell type, each gene,
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각각의 μ„ΈλΆ€ μ‹œμŠ€ν…œμ΄, 각각의 세포 νƒ€μž…κ³Ό 각각의 μœ μ „μžκ°€,
07:08
has evolved in its own unique environmental niche
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각각의 κ³ μœ ν•œ ν™˜κ²½μ  ν‹ˆμƒˆμ—μ„œ κ³ μœ ν•œ 역사와 λ”λΆˆμ–΄
07:12
with its own unique history.
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진화해왔기 λ•Œλ¬Έμž…λ‹ˆλ‹€
07:15
And yet, despite all of that Darwinian evolution
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κ·ΈλŸΌμ—λ„ 이 λͺ¨λ“  λ‹€μœˆ 진화둠과 μžμ—° 선택에도 λΆˆκ΅¬ν•˜κ³ 
07:18
and natural selection,
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이 λͺ¨λ“  것듀은 ν•˜λ‚˜μ˜ μ„  μœ„μ—
07:20
they've been constrained to lie on a line.
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μ†λ°•λ‹Ήν•˜λ„λ‘ μ œν•œλ˜μ–΄μ™”μŠ΅λ‹ˆλ‹€
07:22
Something else is going on.
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무언가 λ‹€λ₯Έ 것이 μ§„ν–‰λ˜κ³  μžˆλŠ”κ±°μ£ 
07:24
Before I talk about that,
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그것에 λŒ€ν•΄ λ§ν•˜κΈ° 전에
07:26
I've written down at the bottom there
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μ•„λž˜μͺ½μ— 이 κ³‘μ„ μ˜ 기울기, 이 직선을
07:28
the slope of this curve, this straight line.
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κ·Έλ €λ’€μŠ΅λ‹ˆλ‹€
07:30
It's three-quarters, roughly,
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λŒ€κ°• 3/4μ •λ„μž…λ‹ˆλ‹€
07:32
which is less than one -- and we call that sublinear.
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1보닀 μž‘μ£ . μš°λ¦¬λŠ” 이것은 μ€€μ„ ν˜•μ  (sublinear)이라고 λΆ€λ¦…λ‹ˆλ‹€
07:35
And here's the point of that.
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μš”μ μ€ μ΄λ ‡μŠ΅λ‹ˆλ‹€
07:37
It says that, if it were linear,
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λ§Œμ•½ 이것이 κ°€μž₯ κ°€νŒŒλ₯Έ 기울기,
07:40
the steepest slope,
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즉 μ„ ν˜•μ μ΄μ—ˆλ‹€λ©΄
07:42
then doubling the size
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μš°λ¦¬κ°€ λ‘λ°°λ‘œ 컀질 λ•Œ
07:44
you would require double the amount of energy.
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μš°λ¦¬λŠ” λ‘λ°°μ˜ μ—λ„ˆμ§€κ°€ ν•„μš”ν•©λ‹ˆλ‹€
07:46
But it's sublinear, and what that translates into
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ν•˜μ§€λ§Œ μ‹€μ œλ‘œλŠ” μ€€μ„ ν˜•μ μ΄κΈ° λ•Œλ¬Έμ—
07:49
is that, if you double the size of the organism,
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μš°λ¦¬κ°€ λ‘λ°°λ‘œ 컀진닀고 해도
07:51
you actually only need 75 percent more energy.
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μ‹€μ œλ‘œλŠ” μ—λ„ˆμ§€λŠ” μ•½ 75%만이 더 ν•„μš”ν•©λ‹ˆλ‹€
07:54
So a wonderful thing about all of biology
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μƒλ¬Όν•™μ˜ 전뢀에 λŒ€ν•΄μ„œ λ†€λΌμš΄ 점은
07:56
is that it expresses an extraordinary economy of scale.
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그것이 μ•„μ£Ό νŠΉμ΄ν•œ 규λͺ¨μ˜ 경제λ₯Ό ν‘œν˜„ν•œλ‹€λŠ” μ μž…λ‹ˆλ‹€
07:59
The bigger you are systematically,
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잘 μ •μ˜λœ κ·œμΉ™μ— 따라
08:01
according to very well-defined rules,
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μ²΄κ³„μ μœΌλ‘œ 컀질 수둝
08:03
less energy per capita.
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1인당 μ—λ„ˆμ§€λŠ” 더 μž‘μ•„μ§‘λ‹ˆλ‹€
08:06
Now any physiological variable you can think of,
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이제 생각할 수 μžˆλŠ” μ–΄λ–€ 생리적 λ³€μˆ˜λ₯Ό μƒκ°ν•΄λ³΄μ„Έμš”,
08:09
any life history event you can think of,
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생각할 수 μžˆλŠ” μ–΄λ–€ μΈμƒμ˜ 역사 이벀트λ₯Ό μƒκ°ν•΄λ³΄μ„Έμš”.
08:11
if you plot it this way, looks like this.
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λ§Œμ•½ 그것을 μ΄λŸ°μ‹μœΌλ‘œ λ„μ œν•œλ‹€λ©΄, μ΄λ ‡κ²Œ λ³΄μž…λ‹ˆλ‹€.
08:14
There is an extraordinary regularity.
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그건 λΉ„λ²”ν•œ κ·œμΉ™μ„±μž…λ‹ˆλ‹€.
08:16
So you tell me the size of a mammal,
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κ·Έλž˜μ„œ μ—¬λŸ¬λΆ„μ΄ 제게 ν¬μœ λ™λ¬Όμ˜ 크기λ₯Ό μ–˜κΈ°ν•œλ‹€λ©΄,
08:18
I can tell you at the 90 percent level everything about it
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μ €λŠ” κ·Έ λ™λ¬Όμ˜ μƒλ¦¬ν•™μ΄λ‚˜, 생λͺ…μ˜ 역사 등에 λŒ€ν•΄μ„œ
08:21
in terms of its physiology, life history, etc.
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90%μˆ˜μ€€μ—μ„œ λͺ¨λ“  것듀을 λ§μ”€λ“œλ¦΄ 수 μžˆμŠ΅λ‹ˆλ‹€
08:25
And the reason for this is because of networks.
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이것에 λŒ€ν•œ μ΄μœ λŠ” λ„€νŠΈμ›Œν¬ λ•Œλ¬Έμž…λ‹ˆλ‹€
08:28
All of life is controlled by networks --
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λͺ¨λ“  μƒνƒœκ³„μ—μ„œ,
08:31
from the intracellular through the multicellular
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단세포 생물뢀터 닀세포 μƒλ¬ΌκΉŒμ§€,
08:33
through the ecosystem level.
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생λͺ…μ²΄μ˜ λͺ¨λ“  것은 λ„€νŠΈμ›Œν¬μ— μ˜ν•΄ μ œμ–΄λ©λ‹ˆλ‹€
08:35
And you're very familiar with these networks.
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μ—¬λŸ¬λΆ„μ€ 이 λ„€νŠΈμ›Œν¬μ— ꡉμž₯히 μΉœμˆ™ν•˜μ‹€ κ²λ‹ˆλ‹€
08:39
That's a little thing that lives inside an elephant.
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그것은 코끼리 μ•ˆμ— μ‚¬λŠ” μž‘μ€ κ²ƒμž…λ‹ˆλ‹€
08:42
And here's the summary of what I'm saying.
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μ œκ°€ λ§μ”€λ“œλ¦¬κ³ μž ν•˜λŠ” 것을 κ°„λž΅ν•˜κ²Œ 정리 ν•΄λ“œλ¦¬κ² μŠ΅λ‹ˆλ‹€
08:45
If you take those networks,
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λ§Œμ•½ 이 λ„€νŠΈμ›Œν¬λΌλŠ”
08:47
this idea of networks,
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κ°œλ…μ„ 가지고
08:49
and you apply universal principles,
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μˆ˜μΉ˜ν™”ν•  수 μžˆλŠ”
08:51
mathematizable, universal principles,
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보편적인 원리λ₯Ό μ μš©ν•œλ‹€λ©΄,
08:53
all of these scalings
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숲과 μ†Œν™”κ³„,
08:55
and all of these constraints follow,
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세포 내에
08:58
including the description of the forest,
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λŒ€ν•œ μ„€λͺ…을 ν¬ν•¨ν•΄μ„œ
09:00
the description of your circulatory system,
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λͺ¨λ“  크고 μž‘μ€ 것듀과
09:02
the description within cells.
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μ œμ•½μ΄ λ’€λ”°λ¦…λ‹ˆλ‹€
09:04
One of the things I did not stress in that introduction
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μ œκ°€ μ†Œκ°œλ§μ—μ„œ κ°•μ‘°ν•˜μ§€ μ•Šμ€ 것 쀑 ν•˜λ‚˜λŠ”
09:07
was that, systematically, the pace of life
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생λͺ…μ˜ μ†λ„λŠ” μ„±μž₯ν• μˆ˜λ‘
09:10
decreases as you get bigger.
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λ‹¨κ³„μ μœΌλ‘œ κ°μ†Œν•œλ‹€λŠ” κ²ƒμž…λ‹ˆλ‹€
09:12
Heart rates are slower; you live longer;
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심μž₯ 박동이 λŠλ €μ§€κ³ , 더 길게 μ‚΄κ³ ,
09:15
diffusion of oxygen and resources
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세포막에 걸친 μ‚°μ†Œμ™€ μžμ›μ˜ 확산은
09:17
across membranes is slower, etc.
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λŠλ €μ§€λŠ” λ“±μ˜ ν˜„μƒμ΄ μΌμ–΄λ‚˜μ£ 
09:19
The question is: Is any of this true
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μ œκ°€ λ“œλ¦¬κ³  싢은 μ§ˆλ¬Έμ€
09:21
for cities and companies?
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λ„μ‹œλ‚˜ νšŒμ‚¬μ—λ„ λ™μΌν•œ 사싀이 μ μš©λ˜λŠλƒλŠ” κ²ƒμž…λ‹ˆλ‹€
09:24
So is London a scaled up Birmingham,
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κ·Έλž˜μ„œ λŸ°λ˜μ€ 버밍햄이 컀진 것이고,
09:27
which is a scaled up Brighton, etc., etc.?
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버밍햄은 λΈŒλΌμ΄νŠΌμ„ 크게 λ§Œλ“  것이고...
09:30
Is New York a scaled up San Francisco,
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λ‰΄μš•μ€ μ‚°νƒ€νŽ˜μ˜ ν™•μž₯ λͺ¨λΈμΈ
09:32
which is a scaled up Santa Fe?
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μƒŒν”„λž€μ‹œμŠ€μ½”λ₯Ό 크게 λ§Œλ“  κ²ƒμΌκΉŒμš”?
09:34
Don't know. We will discuss that.
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κΈ€μŽ„μš”, μ•žμœΌλ‘œ 이야기 ν•΄ 보도둝 ν•˜μ£ 
09:36
But they are networks,
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ν•˜μ§€λ§Œ λ„μ‹œλ“€μ€ λ„€νŠΈμ›Œν¬μž…λ‹ˆλ‹€
09:38
and the most important network of cities
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그리고 λ„μ‹œμ˜ κ°€μž₯ μ€‘μš”ν•œ λ„€νŠΈμ›Œν¬λŠ”
09:40
is you.
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μ—¬λŸ¬λΆ„μž…λ‹ˆλ‹€
09:42
Cities are just a physical manifestation
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λ„μ‹œλ“€μ€ 단지
09:45
of your interactions,
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μ—¬λŸ¬λΆ„μ˜ μƒν˜Έμž‘μš©μ˜,
09:47
our interactions,
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우리의 μƒν˜Έμž‘μš©μ˜,
09:49
and the clustering and grouping of individuals.
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그리고 개인의 무리와 μ§‘λ‹¨μ˜ λ°œν˜„μΌ λΏμž…λ‹ˆλ‹€
09:51
Here's just a symbolic picture of that.
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μ—¬κΈ° λ°”λ‘œ κ·Έκ²ƒμ˜ 상징적인 그림이 μžˆμŠ΅λ‹ˆλ‹€
09:54
And here's scaling of cities.
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그리고 μ—¬κΈ° λ„μ‹œλ₯Ό ν™•μž₯μ‹œν‚¨κ²ƒμ΄ μžˆμŠ΅λ‹ˆλ‹€
09:56
This shows that in this very simple example,
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이 μ•„μ£Ό λ‹¨μˆœν•œ μ˜ˆμ—μ„œ λ³΄μ—¬μ£ΌλŠ” 것은,
09:59
which happens to be a mundane example
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즉 ν‰λ²”ν•œ μ˜ˆκ°€ 된 경우인데
10:01
of number of petrol stations
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μ£Όμœ μ†Œμ˜ 숫자λ₯Ό
10:03
as a function of size --
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κΈ°λŠ₯의 ν¬κΈ°λ‘œμ„œ
10:05
plotted in the same way as the biology --
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μƒλ¬Όν•™μ—μ„œμ™€ 같은 λ°©λ²•μœΌλ‘œ λ„μ œν•˜λ©΄
10:07
you see exactly the same kind of thing.
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λ˜‘κ°™μ€ μ’…λ₯˜μ˜ 것을 λ³΄μ—¬μ€€λ‹€λŠ” κ²ƒμž…λ‹ˆλ‹€
10:09
There is a scaling.
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그건 ν™•μž₯μž…λ‹ˆλ‹€
10:11
That is that the number of petrol stations in the city
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저건 λ„μ‹œμ—μ„œ μ—¬λŸ¬λΆ„κ»˜
10:15
is now given to you
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μ£Όμœ μ†Œμ˜ μˆ«μžκ°€
10:17
when you tell me its size.
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μ—¬λŸ¬λΆ„μ΄ κ·Έ 크기λ₯Ό λ§ν• λ•Œ μ£Όμ–΄μ§„λ‹€λŠ” κ²λ‹ˆλ‹€
10:19
The slope of that is less than linear.
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μ €κ²ƒμ˜ κ²½μ‚¬λŠ” μ„ ν˜•μ μΈ κ²ƒμ΄κΈ°μ—λŠ” μ•½κ°„ λͺ¨μžλžλ‹ˆλ‹€
10:22
There is an economy of scale.
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규λͺ¨μ˜ κ²½μ œκ°€ μ μš©λ˜λŠ” κ²ƒμž…λ‹ˆλ‹€
10:24
Less petrol stations per capita the bigger you are -- not surprising.
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더 적은 μ£Όμœ μ†Œκ°€ μžˆμ„μˆ˜λ‘ 1 인당 μ£Όμœ μ†Œ μ†Œμœ λŠ” μ»€μ§‘λ‹ˆλ‹€--λ†€λΌμš΄κ²ƒμ΄ μ•„λ‹ˆμ£ 
10:27
But here's what's surprising.
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ν•˜μ§€λ§Œ 여기에 λ†€λΌμš΄ 것이 μžˆμŠ΅λ‹ˆλ‹€
10:29
It scales in the same way everywhere.
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그건 μ–΄λ””μ—μ„œλ“ μ§€ 같은 λ°©μ‹μœΌλ‘œ ν™•μž₯ν•©λ‹ˆλ‹€
10:31
This is just European countries,
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이건 단지 μœ λŸ½κ΅­κ°€λ“€ μ΄μ§€λ§Œ
10:33
but you do it in Japan or China or Colombia,
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μΌλ³Έμ΄λ‚˜ μ€‘κ΅­μ΄λ‚˜ μ½œλ‘¬λΉ„μ•„μ—μ„œλ‚˜
10:36
always the same
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항상 같이
10:38
with the same kind of economy of scale
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같은 μ •λ„λ‘œ
10:40
to the same degree.
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ν™•μž₯의 κ²½μ œμ™€ 같은 μ’…λ₯˜λ‘œ ν™•μž₯ν•©λ‹ˆλ‹€
10:42
And any infrastructure you look at --
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또 μ–΄λŠ μ‚¬νšŒκΈ°λ°˜μ‹œμ„€μ„ 보든지-
10:45
whether it's the length of roads, length of electrical lines --
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λ„λ‘œμ˜ κΈΈμ΄λ‚˜, μ „μ„ μ˜ κΈΈμ΄λ‚˜μ— 상관없이
10:48
anything you look at
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어떀것을 보더라도
10:50
has the same economy of scale scaling in the same way.
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같은 λ°©μ‹μœΌλ‘œ ν™•μž₯ν•˜λŠ” λ˜‘κ°™μ€ 규λͺ¨μ˜ 경제λ₯Ό 가지고 μžˆμŠ΅λ‹ˆλ‹€
10:53
It's an integrated system
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μ΄λŠ” λͺ¨λ“  κ³„νš 등에도 λΆˆκ΅¬ν•˜κ³ 
10:55
that has evolved despite all the planning and so on.
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μ§„ν™”ν•œ ν†΅ν•©λœ μ‹œμŠ€ν…œμž…λ‹ˆλ‹€
10:58
But even more surprising
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ν•˜μ§€λ§Œ 보닀 더 λ†€λΌμš΄κ²ƒμ€
11:00
is if you look at socio-economic quantities,
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만일 μ‚¬νšŒ κ²½μ œν•™μ˜ 숫자λ₯Ό μ‚΄νŽ΄λ³΄λ©΄,
11:02
quantities that have no analog in biology,
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μƒλ¬Όν•™μ—μ„œλŠ” μˆ«μžλŠ”
11:05
that have evolved when we started forming communities
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8μ²œλ…„μ—μ„œ μΌλ§Œλ…„μ „μ— μš°λ¦¬κ°€ 곡동체λ₯Ό ν˜•μ„±ν•˜κΈ° μ‹œμž‘ν–ˆμ„λ•Œ μ§„ν™”ν–ˆλ˜
11:08
eight to 10,000 years ago.
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상사체 (μ•„λ‚ λ‘œκ·Έ : μœ λž˜λŠ” λ‹€λ₯΄μ§€λ§Œ 역할이 λΉ„μŠ·ν•œ ꡬ쑰) κ°€ μ—†λ‹€λŠ” κ²ƒμž…λ‹ˆλ‹€.
11:10
The top one is wages as a function of size
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λ§¨μœ„μ— μžˆλŠ”κ²ƒμ€ 같은 λ°©μ‹μœΌλ‘œ
11:12
plotted in the same way.
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봉급과 κ·Έ κΈ°λŠ₯의 크기λ₯Ό λ„μ œν•œ κ²ƒμž…λ‹ˆλ‹€
11:14
And the bottom one is you lot --
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μ•„λž˜μ˜ 것은 같은 λ°©μ‹μœΌλ‘œ
11:16
super-creatives plotted in the same way.
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λ‹€λŸ‰μ˜ 숫자λ₯Ό ꡉμž₯히 창쑰적으둜 λ§Œλ“ κ²ƒμž…λ‹ˆλ‹€
11:19
And what you see
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μ—¬λŸ¬λΆ„μ΄ λ³΄μ‹œλŠ”κ²ƒμ€
11:21
is a scaling phenomenon.
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ν™•μž₯의 ν˜„μƒμž…λ‹ˆλ‹€
11:23
But most important in this,
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ν•˜μ§€λ§Œ μ—¬κΈ°μ—μ„œ κ°€μž₯ μ€‘μš”ν•œ 것은,
11:25
the exponent, the analog to that three-quarters
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κ·Έ λŒ€μ‚¬μœ¨μ˜ 3/4에 ν•΄λ‹Ήν•˜λŠ” 상사체,
11:27
for the metabolic rate,
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즉 μ§€μˆ˜λŠ”
11:29
is bigger than one -- it's about 1.15 to 1.2.
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1.15μ—μ„œ 1.2 μ‚¬μ΄λ‘œ 1보닀 ν¬λ‹€λŠ” μ‚¬μ‹€μž…λ‹ˆλ‹€
11:31
Here it is,
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즉, μƒλ¬Όν•™κ³ΌλŠ” λ‹€λ₯΄κ²Œ
11:33
which says that the bigger you are
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컀질수둝
11:36
the more you have per capita, unlike biology --
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1인당 κ°€μ§€κ²Œ λ˜λŠ” 봉급,
11:39
higher wages, more super-creative people per capita as you get bigger,
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창쑰적인 μ‚¬λžŒμ˜ 수,
11:43
more patents per capita, more crime per capita.
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νŠΉν—ˆ 건수, 범죄 μˆ˜λŠ” 더 λ†’μ•„μ§€κ²Œ λ˜λŠ” 것이죠
11:46
And we've looked at everything:
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μš°λ¦¬λŠ” AIDSλ‚˜ 독감 λ“±
11:48
more AIDS cases, flu, etc.
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λͺ¨λ“ κ²ƒμ„ μ‘°μ‚¬ν–ˆμŠ΅λ‹ˆλ‹€
11:51
And here, they're all plotted together.
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여기에, 그것듀이 λͺ¨λ‘ ν•¨κ»˜ κ·Έλ €μ Έ μžˆμŠ΅λ‹ˆλ‹€
11:53
Just to show you what we plotted,
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μš°λ¦¬κ°€ μ–΄λ–»κ²Œ κ·Έλž˜ν”„λ₯Ό κ·Έλ ΈλŠ”μ§€ λ³΄μ—¬λ“œλ¦¬μžλ©΄,
11:55
here is income, GDP --
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이게 μˆ˜μž…,
11:58
GDP of the city --
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즉 ν•œ λ„μ‹œμ˜ GDP이고,
12:00
crime and patents all on one graph.
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ν•œ κ·Έλž˜ν”„ μ•ˆμ— 범죄와 νŠΉν—ˆμ˜ μˆ˜λ„ λ‚˜μ™€ μžˆμŠ΅λ‹ˆλ‹€
12:02
And you can see, they all follow the same line.
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보싀 수 μžˆλ“―μ΄, 그것듀은 같은 선을 λ”°λ¦…λ‹ˆλ‹€
12:04
And here's the statement.
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이 말인 μ¦‰μŠ¨,
12:06
If you double the size of a city from 100,000 to 200,000,
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λ„μ‹œμ˜ 크기λ₯Ό 10λ§Œμ—μ„œ 20만,
12:09
from a million to two million, 10 to 20 million,
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100λ§Œμ—μ„œ 200만, 1000λ§Œμ—μ„œ 2000만으둜,
12:11
it doesn't matter,
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μ–΄λ–»κ²Œ 증가 μ‹œν‚€λ“ μ§€ 2λ°°κ°€ μ¦κ°€ν•˜κ²Œ 되면,
12:13
then systematically
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μˆ˜μž…, λΆ€,
12:15
you get a 15 percent increase
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AIDS λ°œμƒ 건수, κ²½μ°°κ΄€μ˜ 수 λ“±
12:17
in wages, wealth, number of AIDS cases,
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μ—¬λŸ¬λΆ„μ΄ 생각할 수 μžˆλŠ”
12:19
number of police,
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λͺ¨λ“  κ²ƒμ—μ„œ μ²΄κ³„μ μœΌλ‘œ
12:21
anything you can think of.
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15%의 증가가 μΌμ–΄λ‚˜κ²Œ λ©λ‹ˆλ‹€
12:23
It goes up by 15 percent,
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15%κ°€ μ¦κ°€ν•˜κ²Œ λ˜λŠ” κ²ƒμž…λ‹ˆλ‹€
12:25
and you have a 15 percent savings
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그러면 μΈν”„λΌμ—μ„œ
12:28
on the infrastructure.
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15%λ₯Ό μ ˆκ°ν•  수 있게 되죠
12:31
This, no doubt, is the reason
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이게 λ°”λ‘œ
12:34
why a million people a week are gathering in cities.
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맀 μ£Ό 100만λͺ…μ˜ μ‚¬λžŒλ“€μ΄ λ„μ‹œλ‘œ μœ μž…λ˜λŠ” μ΄μœ μž…λ‹ˆλ‹€
12:37
Because they think that all those wonderful things --
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μ™œλƒλ©΄ 그듀은
12:40
like creative people, wealth, income --
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λͺ¨λ“  μΆ”μ•…ν•˜κ³  λ‚˜μœ 것듀을 λ§κ°ν•˜κ³ 
12:42
is what attracts them,
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창쑰적인 μ‚¬λžŒλ“€, ν’μš”λ‘œμ›€, μˆ˜μž… λ“±κ³Ό 같은 멋진 것듀이
12:44
forgetting about the ugly and the bad.
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μžμ‹ λ“€μ„ λ§€λ£Œμ‹œν‚¨λ‹€κ³ λ§Œ μƒκ°ν•˜κΈ° λ•Œλ¬Έμž…λ‹ˆλ‹€
12:46
What is the reason for this?
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κ·Έ μ΄μœ λŠ” λ¬΄μ—‡μΌκΉŒμš”?
12:48
Well I don't have time to tell you about all the mathematics,
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μ €λŠ” μˆ˜ν•™μ— κ΄€ν•œ λͺ¨λ“ κ²ƒμ„ μ—¬λŸ¬λΆ„μ—κ²Œ 말할 μ‹œκ°„μ€ μ—†μ§€λ§Œ,
12:51
but underlying this is the social networks,
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μ΄κ²ƒμ˜ κΈ°μ΄ˆλŠ” μ‚¬νšŒμ μΈ λ„€νŠΈμ›Œν¬λΌλŠ” κ²ƒμž…λ‹ˆλ‹€
12:54
because this is a universal phenomenon.
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μ™œλƒλ©΄ 이것은 보편적인 ν˜„μƒμ΄κΈ° λ•Œλ¬Έμž…λ‹ˆλ‹€
12:57
This 15 percent rule
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이 15%의 법칙은
13:00
is true
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μ‚¬μ‹€μž…λ‹ˆλ‹€
13:02
no matter where you are on the planet --
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μ—¬λŸ¬λΆ„μ΄ μ§€κ΅¬μƒμ˜ μ–΄λŠ 곳에 μžˆλ“ μ§€-
13:04
Japan, Chile,
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일본, 칠레,
13:06
Portugal, Scotland, doesn't matter.
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포λ₯΄νˆ¬κ°ˆ, μŠ€μ½”ν‹€λžœλ“œ, 상관 μ—†μŠ΅λ‹ˆλ‹€
13:09
Always, all the data shows it's the same,
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이런 λŒ€λ„μ‹œλ“€μ΄ μ„œλ‘œ λ…λ¦½μ μœΌλ‘œ λ°œμ „ν–ˆλ‹€λŠ” 사싀에도 λΆˆκ΅¬ν•˜κ³ ,
13:12
despite the fact that these cities have evolved independently.
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λͺ¨λ“  λ°μ΄ν„°λŠ” 이것듀이 항상 κ°™λ‹€λŠ” 사싀을 λ³΄μ—¬μ€λ‹ˆλ‹€
13:15
Something universal is going on.
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λ­”κ°€ λ³΄νŽΈμ μΈκ²ƒμ΄ μ§„ν–‰λ˜κ³  μžˆμŠ΅λ‹ˆλ‹€.
13:17
The universality, to repeat, is us --
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λ°˜λ³΅ν•΄μ„œ λ§ν•˜μ§€λ§Œ, κ·Έ λ³΄νŽΈμ„±μ€, μš°λ¦¬μž…λ‹ˆλ‹€
13:20
that we are the city.
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즉, μš°λ¦¬κ°€ λ„μ‹œλΌλŠ” κ²ƒμž…λ‹ˆλ‹€
13:22
And it is our interactions and the clustering of those interactions.
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그리고 말씀 λ“œλ Έλ‹€μ‹œν”Ό, 그것은 우리의 μƒν˜Έμž‘μš©κ³Ό
13:25
So there it is, I've said it again.
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κ·Έ μƒν˜Έμž‘μš©μ˜ λ¬΄λ¦¬μž…λ‹ˆλ‹€
13:27
So if it is those networks and their mathematical structure,
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κ·Έλž˜μ„œ 만일 κ·Έ λ„€νŠΈμ›Œν¬λ“€μΈ 경우 κ·Έ μˆ˜ν•™μ μΈ κ΅¬μ‘°λŠ”
13:30
unlike biology, which had sublinear scaling,
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μ€€μ„ ν˜•μ μΈ ν™•μž₯인 μƒλ¬Όν•™κ³ΌλŠ” λ‹€λ₯΄κ²Œ,
13:33
economies of scale,
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규λͺ¨μ˜ κ²½μ œμž…λ‹ˆλ‹€
13:35
you had the slowing of the pace of life
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μ—¬λŸ¬λΆ„μ΄ μ„±μž₯함에 따라
13:37
as you get bigger.
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생λͺ…μ˜ μ†λ„λŠ” λŠλ €μ§‘λ‹ˆλ‹€
13:39
If it's social networks with super-linear scaling --
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κ·Έ 초 μ„ ν˜•μ μΈ ν™•μž₯성을 가진 μ‚¬νšŒμ  λ„€νŠΈμ›Œν¬κ°€
13:41
more per capita --
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1인당 더 λ§Žλ‹€λ©΄
13:43
then the theory says
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κ·Έ 이둠은
13:45
that you increase the pace of life.
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생λͺ…μ˜ 속도λ₯Ό μ¦κ°€μ‹œν‚¨λ‹€κ³  μ„€λͺ…ν•©λ‹ˆλ‹€
13:47
The bigger you are, life gets faster.
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μ—¬λŸ¬λΆ„μ΄ 더 μ„±μž₯ν• μˆ˜λ‘, 생λͺ…은 더 λΉ¨λΌμ§‘λ‹ˆλ‹€
13:49
On the left is the heart rate showing biology.
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μ™Όμͺ½μ—λŠ” 심μž₯박동 λΉ„μœ¨μ΄ 생물학을 λ³΄μ—¬μ€λ‹ˆλ‹€.
13:51
On the right is the speed of walking
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였λ₯Έμͺ½μ—λŠ”
13:53
in a bunch of European cities,
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유럽 μ—¬λŸ¬ λ„μ‹œλ“€μ—μ„œ μ¦κ°€ν•˜λŠ”
13:55
showing that increase.
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μ„±μž₯의 μ†λ„μž…λ‹ˆλ‹€
13:57
Lastly, I want to talk about growth.
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λ§ˆμ§€λ§‰μœΌλ‘œ, μ €λŠ” μ„±μž₯에 λŒ€ν•΄ μ–ΈκΈ‰ν•˜κ³  μ‹ΆμŠ΅λ‹ˆλ‹€
14:00
This is what we had in biology, just to repeat.
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λ°˜λ³΅ν•˜μžλ©΄, 이것이 μš°λ¦¬κ°€ μƒλ¬Όν•™μ—μ„œ κ°€μ‘Œλ˜ κ²ƒμž…λ‹ˆλ‹€
14:03
Economies of scale
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규λͺ¨μ˜ κ²½μ œλŠ”
14:06
gave rise to this sigmoidal behavior.
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S 자 λͺ¨μ–‘μ˜ ν–‰νƒœλ₯Ό λ°œμƒμ‹œν‚΅λ‹ˆλ‹€
14:09
You grow fast and then stop --
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μ—¬λŸ¬λΆ„μ€ 빨리 μ„±μž₯ν•˜κ³  κ·Έ λ‹€μŒμ—λŠ” 멈μΆ₯λ‹ˆλ‹€--
14:12
part of our resilience.
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우리 볡원λ ₯의 λΆ€λΆ„μœΌλ‘œμ„œμš”
14:14
That would be bad for economies and cities.
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그건 우리의 κ²½μ œμ™€ λ„μ‹œμ— 쒋지 μ•Šμ„ κ²ƒμž…λ‹ˆλ‹€
14:17
And indeed, one of the wonderful things about the theory
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또, κ·Έ 이둠이 ν›Œλ₯­ν•œ 점의 ν•˜λ‚˜λŠ”
14:19
is that if you have super-linear scaling
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λΆ€μœ ν•¨μ˜ 창쑰와 ν˜μ‹ μ—μ„œ
14:22
from wealth creation and innovation,
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μ΄ˆμ„ ν˜•μ˜ ν™•μž₯을 ν•˜λ©΄,
14:24
then indeed you get, from the same theory,
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그러면 결과적으둜, 같은 μ΄λ‘ μ—μ„œ
14:27
a beautiful rising exponential curve -- lovely.
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μ•„λ¦„λ‹΅κ²Œ μ¦κ°€ν•˜λŠ” μ§€μˆ˜μ˜ 곑선을 μ–»λŠ”λ‹€λŠ” κ²ƒμž…λ‹ˆλ‹€--μ‚¬λž‘μŠ€λŸ½μ£ 
14:29
And in fact, if you compare it to data,
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그리고 사싀, 그것을 데이터에 λΉ„κ΅ν•˜λ©΄,
14:31
it fits very well
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λ„μ‹œμ™€ 경제의 λ°œλ‹¬μ—
14:33
with the development of cities and economies.
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κΌ­ λ“€μ–΄ λ§žμŠ΅λ‹ˆλ‹€
14:35
But it has a terrible catch,
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ν•˜μ§€λ§Œ 그건 λ”μ°ν•œ 함정이 μžˆμŠ΅λ‹ˆλ‹€
14:37
and the catch
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κ·Έ 함정은
14:39
is that this system is destined to collapse.
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이 μ‹œμŠ€ν…œμ΄ 뢕괴될 운λͺ…을 κ°€μ‘Œλ‹€λŠ” κ²ƒμž…λ‹ˆλ‹€
14:42
And it's destined to collapse for many reasons --
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그건 λ§Žμ€ μ΄μœ μ—μ„œ 뢕괴될 운λͺ…을 μ§€λ…”μ§€μš”--
14:44
kind of Malthusian reasons -- that you run out of resources.
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λ§¬λ”μŠ€(Thomas Malthus) ν•™νŒŒ[이둠]의 μ’…λ₯˜μΈλ°--μžμ›μ΄ κ³ κ°ˆλœλ‹€λŠ” κ²ƒμž…λ‹ˆλ‹€.
14:47
And how do you avoid that? Well we've done it before.
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그러면 κ·Έκ±Έ νšŒν”Όν•  방법은 λ­˜κΉŒμš”? κΈ€μŽ„μš”, μš°λ¦¬λŠ” 이전에 ν”Όν•œ 적이 μžˆμŠ΅λ‹ˆλ‹€
14:50
What we do is,
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μš°λ¦¬κ°€ ν•˜λŠ” 것은,
14:52
as we grow and we approach the collapse,
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μš°λ¦¬κ°€ μ„±μ •ν•˜κ³  κ·Έ 뢕괴에 접근함에 따라,
14:55
a major innovation takes place
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μ£Όμš” ν˜μ‹ μ΄ λ°œμƒν•˜κ³ 
14:58
and we start over again,
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λ‹€μ‹œ μ‹œμž‘ν•˜λŠ” κ²ƒμž…λ‹ˆλ‹€.
15:00
and we start over again as we approach the next one, and so on.
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λ‹€μŒμ— 뢕괴점에 λ„λ‹¬ν–ˆμ„ λ•Œ 또 λ‹€μ‹œ μ‹œμž‘ν•˜κ³ , 또 λ‹€μ‹œ μ‹œμž‘ν•˜λŠ” 것이죠
15:03
So there's this continuous cycle of innovation
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κ·Έλž˜μ„œ μ„±μž₯을 μ§€μ†ν•˜κ³ 
15:05
that is necessary
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λΆ•κ΄΄λ₯Ό ν”Όν•˜κΈ° μœ„ν•΄μ„œλŠ”
15:07
in order to sustain growth and avoid collapse.
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ν˜μ‹ μ˜ 계속적인 반볡이 ν•„μˆ˜μ μž…λ‹ˆλ‹€
15:10
The catch, however, to this
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ν•˜μ§€λ§Œ, 이것에 λŒ€ν•œ 함정은,
15:12
is that you have to innovate
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점점 더 빨리
15:14
faster and faster and faster.
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ν˜μ‹ μ„ 감행해야 ν•œλ‹€λŠ” κ²ƒμž…λ‹ˆλ‹€
15:17
So the image
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κ·Έλž˜μ„œ κ·Έ μ΄λ―Έμ§€λŠ”
15:19
is that we're not only on a treadmill that's going faster,
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μš°λ¦¬κ°€ 더 빨리 μ›€μ§μ΄λŠ” λŸ¬λ‹λ¨Έμ‹  μœ„μ— μžˆλŠ”κ²ƒλΏλ§Œμ΄ μ•„λ‹ˆλΌ
15:22
but we have to change the treadmill faster and faster.
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κ·Έ λŸ¬λ‹λ¨Έμ‹ μ„ λ”λ”μš± λΉ λ₯΄κ²Œ λ°”κΎΈμ–΄μ•Ό ν•œλ‹€λŠ” κ²ƒμž…λ‹ˆλ‹€
15:25
We have to accelerate on a continuous basis.
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즉, 지속적인 기반 μœ„μ— λ°•μ°¨λ₯Ό κ°€ν•΄μ•Όν•©λ‹ˆλ‹€
15:28
And the question is: Can we, as socio-economic beings,
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λ¬Έμ œλŠ” μ‚¬νšŒ-경제적인 μ‘΄μž¬λ‘œμ„œ
15:31
avoid a heart attack?
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μš°λ¦¬κ°€ 심μž₯λ§ˆλΉ„λ₯Ό ν”Όν•  수 μžˆλƒλŠ” κ²ƒμž…λ‹ˆλ‹€
15:34
So lastly, I'm going to finish up in this last minute or two
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κ·Έλž˜μ„œ λ§ˆμ§€λ§‰μœΌλ‘œ, μ €λŠ” λ§ˆμ§€λ§‰ 1~2뢄을
15:37
asking about companies.
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νšŒμ‚¬μ— λŒ€ν•΄ λ¬»λŠ”κ²ƒμœΌλ‘œ 마치고자 ν•©λ‹ˆλ‹€
15:39
See companies, they scale.
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νšŒμ‚¬λ“€μ„ λ³΄μ„Έμš”, 그듀은 ν™•μž₯ν•©λ‹ˆλ‹€
15:41
The top one, in fact, is Walmart on the right.
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κ°€μž₯ λ§¨μœ„μ—λŠ”, 사싀, μ›”λ§ˆνŠΈκ°€ 였λ₯Έμͺ½μ— μžˆμŠ΅λ‹ˆλ‹€.
15:43
It's the same plot.
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그건 같은 κ΅¬μ„±μž…λ‹ˆλ‹€
15:45
This happens to be income and assets
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이건 고용인의 μˆ«μžμ— μ˜ν•΄ ν‘œμ‹œλœ 것과 같이
15:47
versus the size of the company as denoted by its number of employees.
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νšŒμ‚¬μ˜ 크기 λŒ€ μˆ˜μž…κ³Ό μžμ‚°μ„ μΆ•μœΌλ‘œ κ·Έλ ΈμŠ΅λ‹ˆλ‹€
15:49
We could use sales, anything you like.
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μ—¬λŸ¬λΆ„μ΄ μ›ν•˜μ‹œλŠ” μ–΄λ–€ 것이라도, 판맀λ₯Ό μ΄μš©ν•  수 μžˆμ§€μš”
15:52
There it is: after some little fluctuations at the beginning,
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즉, μ΄ˆλ°˜μ— μ•½κ°„μ˜ 변동이 μžˆμ€ 후에
15:55
when companies are innovating,
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νšŒμ‚¬λ“€μ΄ ν˜μ‹ μ„ ν•˜λ©΄μ„œ
15:57
they scale beautifully.
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μ•„λ¦„λ‹΅κ²Œ ν™•μž₯ν•©λ‹ˆλ‹€
15:59
And we've looked at 23,000 companies
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κ·Έλž˜μ„œ μš°λ¦¬λŠ” λ§μ”€λ“œλ¦¬μžλ©΄, 미ꡭ에 μžˆλŠ”
16:02
in the United States, may I say.
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2만 3천개의 νšŒμ‚¬λ₯Ό μ‘°μ‚¬ν–ˆμŠ΅λ‹ˆλ‹€
16:04
And I'm only showing you a little bit of this.
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μ €λŠ” 단지 이것 μ€‘μ˜ μ•½κ°„λ§Œμ„ λ³΄μ—¬λ“œλ¦΄ λ”°λ¦„μž…λ‹ˆλ‹€
16:07
What is astonishing about companies
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νšŒμ‚¬λ“€μ— λŒ€ν•œ λ†€λΌμš΄ 것은
16:09
is that they scale sublinearly
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μƒλ¬Όν•™μ—μ„œμ™€λ„ 같이
16:12
like biology,
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그듀이 μ€€μ„ ν˜•μ μœΌλ‘œ ν™•μž₯ν•œλ‹€λŠ” κ²ƒμž…λ‹ˆλ‹€
16:14
indicating that they're dominated,
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즉 νšŒμ‚¬λ“€μ€ 초-μ„ ν˜•μ μΈ
16:16
not by super-linear
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ν˜μ‹ κ³Ό 아이디어듀에 μ˜ν•΄
16:18
innovation and ideas;
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영ν–₯을 크게 받은것이 μ•„λ‹ˆλΌλŠ” 것을 λ‚˜νƒ€λ‚΄λ©΄μ„œ
16:21
they become dominated
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νšŒμ‚¬λ“€μ€ 규λͺ¨μ˜ κ²½μ œμ— μ˜ν•΄
16:23
by economies of scale.
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영ν–₯을 크게 λ°›κ²Œ λ©λ‹ˆλ‹€
16:25
In that interpretation,
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κ΄€λ£Œμ™€ 행정에 μ˜ν•œ
16:27
by bureaucracy and administration,
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κ·ΈλŸ¬ν•œ ν•΄μ„μ—μ„œλŠ”,
16:29
and they do it beautifully, may I say.
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λ§ν•˜μžλ©΄, νšŒμ‚¬λŠ” ν™•μž₯을 μ•„λ¦„λ‹΅κ²Œ ν•©λ‹ˆλ‹€.
16:31
So if you tell me the size of some company, some small company,
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κ·Έλž˜μ„œ μ–΄λŠ νšŒμ‚¬, μž‘μ€ νšŒμ‚¬μ˜ 크기λ₯Ό μ—¬λŸ¬λΆ„κ»˜μ„œ 제게 λ§ν•œλ‹€λ©΄,
16:34
I could have predicted the size of Walmart.
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μ €λŠ” μ›”λ§ˆνŠΈμ˜ 크기λ₯Ό μ˜ˆμΈ‘ν•  수 μžˆμ„ κ²ƒμž…λ‹ˆλ‹€
16:37
If it has this sublinear scaling,
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만일 그것이 이 μ€€μ„ ν˜•μ μΈ ν™•μž₯성을 κ°€μ‘Œλ‹€λ©΄,
16:39
the theory says
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κ·Έ 이둠은
16:41
we should have sigmoidal growth.
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Sμžν˜•μ˜ μ„±μž₯을 κ°€μ§€κ²Œ 될 거라고 μ„€λͺ…ν•©λ‹ˆλ‹€
16:44
There's Walmart. Doesn't look very sigmoidal.
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μ—¬κΈ° μ›”λ§ˆνŠΈκ°€ μžˆλŠ”λ°, λ³„λ‘œ Sμžν˜•μœΌλ‘œ 보이지 μ•ŠλŠ”κ΅°μš”
16:46
That's what we like, hockey sticks.
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μš°λ¦¬κ°€ μ’‹μ•„ν•˜λŠ” ν•˜ν‚€μŠ€ν‹±μ²˜λŸΌ μƒκ²Όλ„€μš”
16:49
But you notice, I've cheated,
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ν•˜μ§€λ§Œ μ œκ°€ 덜 λ³΄μ—¬λ“œλ¦° 것을 눈치 채셨을 κ²λ‹ˆλ‹€
16:51
because I've only gone up to '94.
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μ™œλƒν•˜λ©΄ μ €λŠ” 94λ…„κΉŒμ§€λ°–μ— 가지 μ•Šμ•˜κ±°λ“ μš”
16:53
Let's go up to 2008.
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2008λ…„κΉŒμ§€ μ˜¬λΌκ°€ λ΄…μ‹œλ‹€
16:55
That red line is from the theory.
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μ € 빨간선은 이둠을 λ°”νƒ•μœΌλ‘œ λ‚˜μ˜¨ κ²ƒμž…λ‹ˆλ‹€
16:58
So if I'd have done this in 1994,
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κ·Έλž˜μ„œ μ œκ°€ 이것을 1994년에 ν•œ 경우,
17:00
I could have predicted what Walmart would be now.
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μ €λŠ” μ›”λ§ˆνŠΈκ°€ μ§€κΈˆ μ–΄λ–»κ²Œ 될지 μ˜ˆμΈ‘ν•  수 μžˆμ—ˆμŠ΅λ‹ˆλ‹€
17:03
And then this is repeated
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κ·Έλ‹€μŒμ— 이것을
17:05
across the entire spectrum of companies.
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νšŒμ‚¬μ˜ 전체 μŠ€νŽ™νŠΈλŸΌμ— 걸쳐 λ°˜λ³΅ν–ˆμŠ΅λ‹ˆλ‹€
17:07
There they are. That's 23,000 companies.
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μ—¬κΈ° 2만 3천개의 νšŒμ‚¬λ“€μ΄ μžˆμŠ΅λ‹ˆλ‹€
17:10
They all start looking like hockey sticks,
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그것듀은 ν•˜ν‚€ μŠ€ν‹±μ²˜λŸΌ 보이기 μ‹œμž‘ν•˜λ‹€κ°€,
17:12
they all bend over,
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그것듀은 λͺ¨λ‘ μ ‘ν˜€μ§€κ³ ,
17:14
and they all die like you and me.
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μ—¬λŸ¬λΆ„κ³Ό μ €μ²˜λŸΌ λͺ¨λ‘ μ£½μŠ΅λ‹ˆλ‹€
17:16
Thank you.
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κ°μ‚¬ν•©λ‹ˆλ‹€
17:18
(Applause)
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(λ°•μˆ˜)
이 μ›Ήμ‚¬μ΄νŠΈ 정보

이 μ‚¬μ΄νŠΈλŠ” μ˜μ–΄ ν•™μŠ΅μ— μœ μš©ν•œ YouTube λ™μ˜μƒμ„ μ†Œκ°œν•©λ‹ˆλ‹€. μ „ 세계 졜고의 μ„ μƒλ‹˜λ“€μ΄ κ°€λ₯΄μΉ˜λŠ” μ˜μ–΄ μˆ˜μ—…μ„ 보게 될 κ²ƒμž…λ‹ˆλ‹€. 각 λ™μ˜μƒ νŽ˜μ΄μ§€μ— ν‘œμ‹œλ˜λŠ” μ˜μ–΄ μžλ§‰μ„ 더블 ν΄λ¦­ν•˜λ©΄ κ·Έκ³³μ—μ„œ λ™μ˜μƒμ΄ μž¬μƒλ©λ‹ˆλ‹€. λΉ„λ””μ˜€ μž¬μƒμ— 맞좰 μžλ§‰μ΄ μŠ€ν¬λ‘€λ©λ‹ˆλ‹€. μ˜κ²¬μ΄λ‚˜ μš”μ²­μ΄ μžˆλŠ” 경우 이 문의 양식을 μ‚¬μš©ν•˜μ—¬ λ¬Έμ˜ν•˜μ‹­μ‹œμ˜€.

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