Shyam Sankar: The rise of human-computer cooperation

62,464 views ・ 2012-09-06

TED


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

00:00
Translator: Joseph Geni Reviewer: Morton Bast
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λ²ˆμ—­: K Bang κ²€ν† : Kyo young Chu
00:15
I'd like to tell you about two games of chess.
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μ €λŠ” 두 가지 체슀 κ²Œμž„μ— λŒ€ν•΄μ„œ λ§μ”€λ“œλ¦¬κ³ μž ν•©λ‹ˆλ‹€
00:18
The first happened in 1997, in which Garry Kasparov,
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첫 λ²ˆμ§ΈλŠ” 1997년에 μΌμ–΄λ‚¬μŠ΅λ‹ˆλ‹€ 개리 μΉ΄μŠ€νŒŒλ‘œν”„λΌλŠ” μ‚¬λžŒμ΄
00:22
a human, lost to Deep Blue, a machine.
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"λ”₯ 블루"λΌλŠ” 컴퓨터에 쑌던 일이죠
00:25
To many, this was the dawn of a new era,
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λ§Žμ€ μ΄λ“€μ—κ²Œ 이 사건은 인간이 기계에 μ••λ„λ˜λŠ” μ‹œλŒ€λΌλŠ”
00:28
one where man would be dominated by machine.
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μƒˆλ‘œμš΄ μ‹œλŒ€μ˜ λ„λž˜λ₯Ό μ˜λ―Έν–ˆμŠ΅λ‹ˆλ‹€
00:30
But here we are, 20 years on, and the greatest change
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20년이 μ§€λ‚œ μ§€κΈˆ, 컴퓨터와 μ–΄λ–»κ²Œ 관계λ₯Ό μœ μ§€ν•˜λŠ”κ°€μ— λŒ€ν•œ
00:34
in how we relate to computers is the iPad,
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κ°€μž₯ 큰 λ³€ν™”λŠ” iPad이지
00:36
not HAL.
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"ν•Ό(HAL)"이 μ•„λ‹™λ‹ˆλ‹€
00:38
The second game was a freestyle chess tournament
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두 번째 κ²Œμž„μ€ μžμœ ν˜• 체슀 λŒ€νšŒμ˜€μŠ΅λ‹ˆλ‹€
00:41
in 2005, in which man and machine could enter together
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2005λ…„, 이 λŒ€νšŒμ—μ„œλŠ” μ‚¬λžŒκ³Ό 기계가
00:44
as partners, rather than adversaries, if they so chose.
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μ„œλ‘œ λŒ€ν•­ν•˜λŠ” 것이 μ•„λ‹ˆλΌ, μ°Έκ°€μžκ°€ μ›ν•˜λ©΄ λ™λ£Œλ‘œ μ°Έκ°€ν•  수 μžˆμ—ˆμŠ΅λ‹ˆλ‹€
00:49
At first, the results were predictable.
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μ΄ˆλ°˜μ—λŠ” λ»”ν•œ κ²°κ³Όλ“€λ§Œ λ³΄μ˜€μ£ 
00:51
Even a supercomputer was beaten by a grandmaster
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심지어 μŠˆνΌμ»΄ν“¨ν„°μ‘°μ°¨λ„ μ €μ‚¬μ–‘μ˜ λ…ΈνŠΈλΆμ„ 가지고 μ°Έμ—¬ν•œ
00:53
with a relatively weak laptop.
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체슀의 λ‹¬μΈμ—κ²Œ 지고 λ§μ•˜μŠ΅λ‹ˆλ‹€
00:55
The surprise came at the end. Who won?
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그런데 λ§ˆμ§€λ§‰μ— λ°˜μ „μ΄ μΌμ–΄λ‚¬μŠ΅λ‹ˆλ‹€. λˆ„κ°€ μ΄κ²Όμ„κΉŒμš”?
00:58
Not a grandmaster with a supercomputer,
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μŠˆνΌμ»΄ν“¨ν„°λ₯Ό μ‚¬μš©ν•˜λŠ” 체슀의 달인이 이긴게 μ•„λ‹ˆμ—ˆμŠ΅λ‹ˆλ‹€
01:01
but actually two American amateurs
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3λŒ€μ˜ 비ꡐ적 저사양 λ…ΈνŠΈλΆμ„ 가지고 μ°Έκ°€ν•œ
01:03
using three relatively weak laptops.
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두 λͺ…μ˜ μ•„λ§ˆμΆ”μ–΄ 체슀 μ„ μˆ˜λ“€μ΄ μš°μŠΉμ„ ν–ˆμ£ 
01:07
Their ability to coach and manipulate their computers
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컴퓨터λ₯Ό μ‘°μ’…ν•˜μ—¬ νŠΉμ •ν•œ μœ„μΉ˜κΉŒμ§€ λͺ¨μ‘°λ¦¬ μƒκ°ν•΄λ‚΄λŠ”
01:09
to deeply explore specific positions
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이 두 μ‚¬λžŒλ“€μ˜ λŠ₯λ ₯ 덕뢄에
01:12
effectively counteracted the superior chess knowledge
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훨씬 더 μš°μˆ˜ν•œ 계산 λŠ₯λ ₯을 가진 컴퓨터λ₯Ό 가진 체슀 λ‹¬μΈμ˜ μˆ˜μ—λ„,
01:14
of the grandmasters and the superior computational power
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그리고 λ‹€λ₯Έ λ§žμˆ˜μ—κ²Œλ„ 효과적으둜
01:17
of other adversaries.
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λ§žλŒ€μ‘ν•  수 μžˆμ—ˆμŠ΅λ‹ˆλ‹€
01:18
This is an astonishing result: average men,
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이건 정말 λ†€λΌμš΄ κ²°κ³Όμž…λ‹ˆλ‹€
01:21
average machines beating the best man, the best machine.
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평균적인 μ‚¬λžŒκ³Ό 평균적인 기계가 졜고의 달인과 졜고의 기계λ₯Ό μ΄κ²ΌμœΌλ‹ˆκΉŒμš”
01:25
And anyways, isn't it supposed to be man versus machine?
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μ–΄μ¨Œλ“ , μ‚¬λžŒ λŒ€ κΈ°κ³„μ˜ 경쟁이 λ˜μ–΄μ•Όν•œ 것 μ•„λ‹ˆμ—ˆμ„κΉŒμš”?
01:29
Instead, it's about cooperation, and the right type of cooperation.
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그게 μ•„λ‹ˆλΌ, μš”μ μ€ ν˜‘λ ₯, μ˜³μ€ ν˜‘λ ₯에 λŒ€ν•œ κ²ƒμ΄μ—ˆμŠ΅λ‹ˆλ‹€
01:33
We've been paying a lot of attention to Marvin Minsky's
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μ €ν¬λŠ” μ§€λ‚œ 50μ—¬λ…„ κ°„ 인곡지λŠ₯에 λŒ€ν•œ
01:36
vision for artificial intelligence over the last 50 years.
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마빈 λ―ΌμŠ€ν‚€μ˜ μ˜ˆμΈ‘μ— μƒλ‹Ήνžˆ μ£Όλͺ©ν•΄ μ™”μŠ΅λ‹ˆλ‹€
01:39
It's a sexy vision, for sure. Many have embraced it.
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ν™•μ‹€νžˆ μ£Όλͺ©μ„ λ„λŠ” λΉ„μ „μ΄μ—ˆμ£  λ§Žμ€ μ‚¬λžŒλ“€μ΄ 여기에 μš°ν˜Έμ μ΄μ—ˆμŠ΅λ‹ˆλ‹€
01:41
It's become the dominant school of thought in computer science.
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이 생각은 컴퓨터 κ³Όν•™ λΆ„μ•Όμ—μ„œ 지배적인 사고(思考) μ„Έλ ₯이 λ˜μ—ˆμŠ΅λ‹ˆλ‹€
01:44
But as we enter the era of big data, of network systems,
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ν•˜μ§€λ§Œ μš°λ¦¬κ°€ λΉ… 데이터, λ„€νŠΈμ›Œν¬ μ‹œμŠ€ν…œ,
01:47
of open platforms, and embedded technology,
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곡개 ν”Œλž«νΌ, 그리고 μž„λ² λ””λ“œ 기술의 μ‹œλŒ€λ‘œ μ ‘μ–΄λ“€λ©΄μ„œ,
01:50
I'd like to suggest it's time to reevaluate an alternative vision
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μ €λŠ” 거의 λΉ„μŠ·ν•œ μ‹œλŒ€μ— 개발 된 λŒ€μ•ˆμ μΈ 비전에 λŒ€ν•΄μ„œ
01:53
that was actually developed around the same time.
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μž¬ν‰κ°€λ₯Ό ν•  μ‹œμ μ΄λΌκ³  μƒκ°ν•©λ‹ˆλ‹€
01:56
I'm talking about J.C.R. Licklider's human-computer symbiosis,
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μ œκ°€ λ§μ”€λ“œλ¦¬λŠ” 것은 J.C.R. λ¦­λΌμ΄λ”μ˜ "인간-컴퓨터 곡생체"에 λŒ€ν•œ κ²ƒμž…λ‹ˆλ‹€
01:59
perhaps better termed "intelligence augmentation," I.A.
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μ•„λ§ˆ "지λŠ₯ 증강(I.A.)" μ΄λΌλŠ” 말이 더 μ–΄μšΈλ¦¬κ² κ΅°μš”
02:03
Licklider was a computer science titan who had a profound
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λ¦­λΌμ΄λ”λŠ” 기술과 μΈν„°λ„·μ˜ λ°œμ „μ— μ—„μ²­λ‚œ 영ν–₯을 미친
02:06
effect on the development of technology and the Internet.
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컴퓨터 κ³Όν•™μ˜ λŒ€κ°€μ˜€μŠ΅λ‹ˆλ‹€
02:09
His vision was to enable man and machine to cooperate
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κ·Έκ°€ λ°”λΌλ˜ 것은 미리 κ²°μ •λœ ν”„λ‘œκ·Έλž¨μ—
02:12
in making decisions, controlling complex situations
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무쑰건적으둜 μ˜μ‘΄ν•˜μ§€ μ•Šκ³ ,
02:15
without the inflexible dependence
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μ˜μ‚¬κ²°μ •κ³Ό λ³΅μž‘ν•œ 상황을 κ΄€λ¦¬ν•˜λŠ” 데 μžˆμ–΄μ„œ
02:17
on predetermined programs.
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인간과 기계가 μƒν˜Έν˜‘λ ₯ν•  수 μžˆλ„λ‘ ν•˜λŠ” κ²ƒμ΄μ—ˆμŠ΅λ‹ˆλ‹€
02:20
Note that word "cooperate."
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"ν˜‘λ ₯"μ΄λΌλŠ” 단어에 μ£Όλͺ©ν•˜μ‹­μ‹œμ˜€
02:22
Licklider encourages us not to take a toaster
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λ¦­λΌμ΄λ”λŠ” ν† μŠ€ν„°λ₯Ό 가지고
02:25
and make it Data from "Star Trek,"
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"μŠ€νƒ€ νŠΈλž™(Star Trek)"μ—μ„œμ˜ 데이터라고 ν•˜λŠ” 것이 μ•„λ‹ˆλΌ,
02:27
but to take a human and make her more capable.
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인간을 훨씬 더 λŠ₯λ ₯μžˆλ„λ‘ λ§Œλ“€λΌκ³  μž₯λ €ν–ˆμŠ΅λ‹ˆλ‹€
02:31
Humans are so amazing -- how we think,
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인간은 μ•„μ£Ό λ†€λΌμš΄ μ‘΄μž¬μž…λ‹ˆλ‹€
02:33
our non-linear approaches, our creativity,
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μš°λ¦¬κ°€ μƒκ°ν•˜λŠ” 방법, λΉ„μ„ ν˜•μ μΈ 접근법, μ°½μ˜μ„±,
02:35
iterative hypotheses, all very difficult if possible at all
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반볡적인 κ°€μ •, 이런 λͺ¨λ“  것듀은 컴퓨터가 ν•  수 μžˆλ‹€κ³  μΉ˜λ”λΌλ„λ„
02:37
for computers to do.
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λŒ€λ‹¨νžˆ μ–΄λ €μš΄ μž‘μ—…λ“€μ΄μ£ 
02:39
Licklider intuitively realized this, contemplating humans
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λ¦­λΌμ΄λ”λŠ” μ‚¬λžŒμ΄ κΉŠμ€ 사고λ₯Ό 톡해 λͺ©ν‘œλ₯Ό μ •ν•˜κ³ ,
02:41
setting the goals, formulating the hypotheses,
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가정을 λ§Œλ“€μ–΄λ‚΄κ³ , 기쀀을 μ •ν•˜κ³ ,
02:44
determining the criteria, and performing the evaluation.
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그리고 ν‰κ°€κΉŒμ§€ ν•˜λŠ” 이런 사싀듀을 μ§κ΄€μ μœΌλ‘œ κΉ¨λ‹¬μ•˜μŠ΅λ‹ˆλ‹€
02:47
Of course, in other ways, humans are so limited.
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λ¬Όλ‘ , λ‹€λ₯Έ λ©΄μ—μ„œ, 인간은 μƒλ‹Ήνžˆ μ œν•œμ μ΄κΈ°λ„ ν•˜μ£ 
02:49
We're terrible at scale, computation and volume.
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μš°λ¦¬λŠ” λ‹¨μœ„μ™€ 계산, 그리고 뢀피에 μžˆμ–΄μ„œλŠ” μͺ½λ„ λͺ» μ”λ‹ˆλ‹€
02:52
We require high-end talent management
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μš°λ¦¬λŠ” 둝 λ°΄λ“œλ₯Ό μœ μ§€ν•˜κ³  ν•¨κ»˜ μ—°μ£Όλ₯Ό ν•˜λ„λ‘ ν•˜λŠ” 데에도
02:54
to keep the rock band together and playing.
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λŒ€λ‹¨ν•œ 경영 λŠ₯λ ₯을 ν•„μš”λ‘œ ν•©λ‹ˆλ‹€
02:56
Licklider foresaw computers doing all the routinizable work
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λ¦­λΌμ΄λ”λŠ” 컴퓨터가 세상에 λŒ€ν•œ 식견과 μ˜μ‚¬ κ²°μ • 방법을 μ€€λΉ„ν•˜λŠ”λ° ν•„μš”ν•œ
02:58
that was required to prepare the way for insights and decision making.
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λͺ¨λ“  λ‹¨μˆœ 반볡적인 일을 ν•˜κ²Œ 될거라고 μ˜ˆμΈ‘ν–ˆμŠ΅λ‹ˆλ‹€
03:01
Silently, without much fanfare,
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μ†Œλ¦¬λ„ 없이, λŒ€λ‹¨ν•œ ν™˜ν˜Έλ„ 받지 λͺ»ν•œ 채,
03:04
this approach has been compiling victories beyond chess.
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이런 μ ‘κ·Ό 방법은 체슀λ₯Ό λ„˜μ–΄ μ—¬λŸ¬ κ΅°λ°μ„œ 승리λ₯Ό μž₯식해 μ™”μŠ΅λ‹ˆλ‹€
03:07
Protein folding, a topic that shares the incredible expansiveness of chess β€”
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μ²΄μŠ€κ°™μ΄ μ—„μ²­λ‚˜κ²Œ λ°©λŒ€ν•œ λ‹¨λ°±μ§ˆ κ²°ν•©κ³Ό 같은 κ²½μš°μ—λ„ 말이죠
03:10
there are more ways of folding a protein than there are atoms in the universe.
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λ‹¨λ°±μ§ˆμ˜ κ²°ν•© 방법은 μš°μ£Όμ—μ„œ μ›μžκ°€ κ²°ν•©ν•˜λŠ” 것보닀 더 λ§ŽμŠ΅λ‹ˆλ‹€
03:13
This is a world-changing problem with huge implications
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인간이 μ§ˆλ³‘μ„ μ΄ν•΄ν•˜κ³  μΉ˜λ£Œν•˜λŠ” λŠ₯λ ₯에 μ—„μ²­λ‚œ 영ν–₯을 끼친,
03:16
for our ability to understand and treat disease.
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세상을 솑두리째 λ’€λ°”κΏ€λ§Œν•œ λ¬Έμ œμž…λ‹ˆλ‹€
03:18
And for this task, supercomputer field brute force simply isn't enough.
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이런 μΌμ—λŠ” μŠˆνΌμ»΄ν“¨ν„°μ˜ "Brute Force"λ‘œλ„ μΆ©λΆ„ν•˜μ§€ μ•ŠμŠ΅λ‹ˆλ‹€
03:22
Foldit, a game created by computer scientists,
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μ–΄λŠ 컴퓨터 κ³Όν•™μžκ°€ λ§Œλ“  κ²Œμž„ "Foldit"은
03:25
illustrates the value of the approach.
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이런 μ ‘κ·Όλ²•μ˜ μ€‘μš”μ„±λ₯Ό λ³΄μ—¬μ€λ‹ˆλ‹€
03:27
Non-technical, non-biologist amateurs play a video game
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κ³Όν•™μžλ„ μƒλ¬Όν•™μžλ„ μ•„λ‹Œ ν‰λ²”ν•œ μ‚¬λžŒμ΄
03:30
in which they visually rearrange the structure of the protein,
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μ»΄ν“¨ν„°λ‘œ ν•˜μ—¬κΈˆ μ›μžμ˜ 힘과 μƒν˜Έμž‘μš©μ„ μ œμ–΄ν•˜κ³ 
03:33
allowing the computer to manage the atomic forces
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ꡬ쑰적 문제λ₯Ό νŒŒμ•…ν•¨μœΌλ‘œμ¨
03:35
and interactions and identify structural issues.
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λΆ„μžμ˜ ꡬ쑰λ₯Ό μ‹œκ°μ μœΌλ‘œ μž¬λ°°μ—΄ν•˜λŠ” 컴퓨터 κ²Œμž„μ„ ν•©λ‹ˆλ‹€
03:38
This approach beat supercomputers 50 percent of the time
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이런 접근법은 μ•½ 50%의 ν™•λ₯ λ‘œ μŠˆνΌμ»΄ν“¨ν„°λ₯Ό 이기고,
03:41
and tied 30 percent of the time.
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30% μ •λ„λŠ” λΉ„κΉλ‹ˆλ‹€
03:43
Foldit recently made a notable and major scientific discovery
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μ΅œκ·Όμ— Foldit은 λ©”μ΄μŠ¨-νŒŒμ΄μ € μ›μˆ­μ΄ λ°”μ΄λŸ¬μŠ€μ˜ ꡬ쑰λ₯Ό νŒλ…ν•΄λ‚΄λ©΄μ„œ
03:46
by deciphering the structure of the Mason-Pfizer monkey virus.
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이λͺ©μ„ λ„λŠ” μ£Όμš”ν•œ 과학적인 λ°œκ²¬μ„ μ΄λŒμ–΄λƒˆμŠ΅λ‹ˆλ‹€
03:50
A protease that had eluded determination for over 10 years
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10λ…„ κ°„ 풀리지 μ•Šλ˜ λ‹¨λ°±μ§ˆ λΆ„ν•΄ νš¨μ†Œ(ν”„λ‘œν…Œμ•„μ œ)의 비밀이
03:53
was solved was by three players in a matter of days,
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겨우 λ©°μΉ  λ§Œμ— μ„Έ μ‚¬λžŒμ— μ˜ν•˜μ—¬ ν’€λ¦° κ²λ‹ˆλ‹€
03:55
perhaps the first major scientific advance
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μ•„λ§ˆλ„ λΉ„λ””μ˜€ κ²Œμž„μ„ μ΄μš©ν•΄μ„œ λ§Œλ“€μ–΄λ‚Έ
03:57
to come from playing a video game.
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졜초의 μ€‘μš”ν•œ 과학적 진보일 것 κ°™λ„€μš”
04:00
Last year, on the site of the Twin Towers,
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μž‘λ…„μ—, 쌍λ‘₯이 λΉŒλ”©μ΄ 있던 μžλ¦¬μ—μ„œ
04:02
the 9/11 memorial opened.
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9.11 μ‚¬κ±΄μ˜ μΆ”λ„νšŒκ°€ μ—΄λ ΈμŠ΅λ‹ˆλ‹€
04:03
It displays the names of the thousands of victims
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κ±°κΈ°μ—” 수천λͺ…μ˜ ν”Όν•΄μžλ“€μ˜ 이름이 "μ˜λ―ΈμžˆλŠ” 인접성"이라고 λΆˆλ¦¬λŠ”
04:06
using a beautiful concept called "meaningful adjacency."
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μ•„λ¦„λ‹€μš΄ κ°œλ…μ„ μ΄μš©ν•΄ μ „μ‹œλ˜μ—ˆμŠ΅λ‹ˆλ‹€
04:09
It places the names next to each other based on their
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"Meaningful Adjacency"λŠ” 친ꡬ, κ°€μ‘±, λ™λ£Œ 같이 μ„œλ‘œμ˜ 관계에 따라
04:11
relationships to one another: friends, families, coworkers.
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μ„œλ‘œμ˜ 이름을 μ΄μ›ƒν•˜μ—¬ λ‚˜μ—΄ν–ˆμŠ΅λ‹ˆλ‹€
04:13
When you put it all together, it's quite a computational
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κ·Έκ±Έ λ‹€ λͺ¨μœΌλ©΄, κ½€λ‚˜ λ§Žμ€ κ³„μ‚°μ˜ λ¬Έμ œκ°€ λ©λ‹ˆλ‹€
04:16
challenge: 3,500 victims, 1,800 adjacency requests,
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3,500λͺ…μ˜ ν”Όν•΄μžλ“€κ³Ό 1,800μ—¬κ°œμ˜ μΉœλ°€λ„,
04:21
the importance of the overall physical specifications
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그리고 전체적인 외적 μš”κ΅¬μ‚¬ν•­μ΄λ‚˜
04:24
and the final aesthetics.
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μ΅œμ’…μ μœΌλ‘œ 미적인 λ¬Έμ œκΉŒμ§€ 생각해야 ν•˜κ±°λ“ μš”
04:26
When first reported by the media, full credit for such a feat
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언둠에 처음 보도 λ˜μ—ˆμ„ λ•Œ, λͺ¨λ“  곡(功)은
04:28
was given to an algorithm from the New York City
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둜컬 ν”„λ‘œμ νŠΈ(Local Project)λΌλŠ” λ‰΄μš•μ‹œμ˜ λ””μžμΈ νšŒμ‚¬μ—μ„œ λ§Œλ“ 
04:30
design firm Local Projects. The truth is a bit more nuanced.
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μ•Œκ³ λ¦¬μ¦˜μœΌλ‘œ λŒλ €μ‘ŒλŠ”λ°, 사싀은 쑰금 λ‹€λ¦…λ‹ˆλ‹€
04:34
While an algorithm was used to develop the underlying framework,
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기초적인 골격을 κ°œλ°œν•˜λŠ”λ°λŠ” μ•Œκ³ λ¦¬μ¦˜μ΄ μ‚¬μš©λμ§€λ§Œ
04:37
humans used that framework to design the final result.
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κΈ°λ³Έ 골격을 μ‚¬μš©ν•΄μ„œ μ΅œμ’… κ²°κ³Όλ₯Ό λ””μžμΈ ν•œ 것은 μ‚¬λžŒμ΄μ—ˆκ±°λ“ μš”
04:40
So in this case, a computer had evaluated millions
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이런 κ²½μš°μ—, 컴퓨터가 수백 만 개의 κ°€λŠ₯ν•œ κ²°κ³Όλ₯Ό ν™•μΈν•˜κ³ ,
04:42
of possible layouts, managed a complex relational system,
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λ³΅μž‘ν•œ 관계도λ₯Ό μ‘°μ •ν•˜κ³ ,
04:46
and kept track of a very large set of measurements
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μƒλ‹Ήνžˆ 큰 λ³€μˆ˜μ™€ μΈ‘μ • 값을 μΆ”μ ν•˜μ˜€κ³ ,
04:48
and variables, allowing the humans to focus
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덕뢄에 μ‚¬λžŒλ“€μ΄ λ””μžμΈκ³Ό ꡬ성적인 선택에
04:51
on design and compositional choices.
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집쀑할 수 μžˆμ—ˆμŠ΅λ‹ˆλ‹€
04:53
So the more you look around you,
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κ·ΈλŸ¬λ‹ˆκΉŒ, 주변을 λ‘˜λŸ¬λ³΄λ©΄ 볼수둝,
04:54
the more you see Licklider's vision everywhere.
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μ–΄λ””μ„œλ“  더 λ§Žμ€ λ¦­λΌμ΄λ”μ˜ 비전을 찾을 수 μžˆμŠ΅λ‹ˆλ‹€
04:56
Whether it's augmented reality in your iPhone or GPS in your car,
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그것이 μ•„μ΄ν°μ˜ μ¦κ°•ν˜„μ‹€μ΄μ΄κ±΄, μžλ™μ°¨ λ„€λΉ„κ²Œμ΄μ…˜μ˜ κ·Έκ²ƒμ΄λ˜μ§€ 간에,
05:00
human-computer symbiosis is making us more capable.
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인간과 μ»΄ν“¨ν„°μ˜ 곡생은 μš°λ¦¬κ°€ 더 λ§Žμ€ 것을 ν•  수 있게 ν•©λ‹ˆλ‹€
05:03
So if you want to improve human-computer symbiosis,
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만일 인간과 μ»΄ν“¨ν„°μ˜ 곡생을 κ°œμ„ ν•˜λ €λ©΄
05:04
what can you do?
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μ–΄λ–»κ²Œ ν•˜λ©΄ λ κΉŒμš”?
05:06
You can start by designing the human into the process.
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μ•„λ§ˆλ„ μ‚¬λžŒμ„ 과정에 ν¬ν•¨μ‹œν‚€λŠ” 것을 톡해 μ‹œμž‘ν•΄λ³Ό 수 μžˆμ„ κ²λ‹ˆλ‹€
05:08
Instead of thinking about what a computer will do to solve the problem,
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문제λ₯Ό ν•΄κ²°ν•˜λŠ”λ° 컴퓨터가 무엇을 ν•  수 μžˆμ„μ§€ μƒκ°ν•˜λŠ” λŒ€μ‹ 
05:10
design the solution around what the human will do as well.
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μ‚¬λžŒλ“€μ΄ ν•  수 μžˆλŠ” 것을 μ£Όλ³€μœΌλ‘œ 해결책을 λ””μžμΈν•˜λŠ” 것이죠
05:14
When you do this, you'll quickly realize that you spent
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μ΄λ ‡κ²Œ ν•˜λ©΄, μ—¬λŸ¬λΆ„λ“€μ΄ 인간과 κΈ°κ³„μ˜ μƒν˜Έμž‘μš©μ—,
05:16
all of your time on the interface between man and machine,
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특히 κ·Έ μ‚¬μ΄μ˜ λ§ˆμ°°μ„ μ€„μ΄λ €λŠ”
05:19
specifically on designing away the friction in the interaction.
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데에 λŒ€λΆ€λΆ„μ˜ μ‹œκ°„μ„ μ‚¬μš©ν•œλ‹€λŠ” 것을 μ‰½κ²Œ κΉ¨λ‹¬μœΌμ‹€ κ²λ‹ˆλ‹€
05:22
In fact, this friction is more important than the power
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사싀 이런 λ§ˆμ°°μ€ 전체적인 λŠ₯λ ₯을 κ²°μ •ν•˜λŠ”λ° μžˆμ–΄μ„œ
05:25
of the man or the power of the machine
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μΈκ°„μ˜ νž˜μ΄λ‚˜ κΈ°κ³„μ˜ νž˜λ³΄λ‹€
05:27
in determining overall capability.
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훨씬 더 μ€‘μš”ν•©λ‹ˆλ‹€
05:29
That's why two amateurs with a few laptops
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그것이 λ°”λ‘œ λ…ΈνŠΈλΆ λͺ‡ λŒ€λ₯Ό 가진 ν‰λ²”ν•œ 두 μ‚¬λžŒμ΄
05:31
handily beat a supercomputer and a grandmaster.
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μŠˆνΌμ»΄ν“¨ν„°λ₯Ό 가진 달인을 이길 수 μžˆμ—ˆλ˜ κΉŒλ‹­μž…λ‹ˆλ‹€
05:33
What Kasparov calls process is a byproduct of friction.
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μΉ΄μŠ€νŒŒλ‘œν”„κ°€ 과정이라고 λΆ€λ₯΄λŠ” 것은 마찰의 λΆ€μ‚°λ¬Όμž…λ‹ˆλ‹€
05:36
The better the process, the less the friction.
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과정이 더 μ’‹μ„μˆ˜λ‘ λ§ˆμ°°μ€ 더 적은거죠
05:39
And minimizing friction turns out to be the decisive variable.
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그리고 λ§ˆμ°°μ„ μ€„μ΄λŠ” 것이 결정적인 λ³€μˆ˜λΌλŠ” λ°ν˜€μ‘Œμ£ 
05:43
Or take another example: big data.
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μ•„λ‹ˆλ©΄ 'λΉ… 데이터'λΌλŠ” λ‹€λ₯Έ 예λ₯Ό 듀어보죠
05:45
Every interaction we have in the world is recorded
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μ „μ„Έκ³„μ—μ„œ μš°λ¦¬κ°€ λ§Œλ“€κ³  μžˆλŠ” λͺ¨λ“  μƒν˜Έμž‘μš©μ€ μ „ν™”κΈ°, μ‹ μš©μΉ΄λ“œ, 컴퓨터 λ“±κ³Ό 같은
05:47
by an ever growing array of sensors: your phone,
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κ³„μ†ν•΄μ„œ λ°œμ „ν•˜λŠ” 감지μž₯μΉ˜μ— κΈ°λ‘λ©λ‹ˆλ‹€
05:50
your credit card, your computer. The result is big data,
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κ·Έ 결과물이 'λΉ… 데이터'이고,
05:53
and it actually presents us with an opportunity
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이 데이터가 μ‹€μ œλ‘œ 인간을 더 깊이 이해할 수 μžˆλŠ”
05:54
to more deeply understand the human condition.
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기회λ₯Ό μ œκ³΅ν•΄μ€λ‹ˆλ‹€
05:57
The major emphasis of most approaches to big data
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'λΉ… 데이터'에 λŒ€ν•œ λŒ€λΆ€λΆ„μ˜ μ ‘κ·Όλ²•μ˜ μ£Όμš”ν•œ μŸμ μ€
05:59
focus on, "How do I store this data? How do I search
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"이 자료λ₯Ό μ–΄λ–»κ²Œ μ €μž₯ν•˜μ§€? 이걸 μ–΄λ–»κ²Œ 찾을 수 μžˆμ„κΉŒ?
06:02
this data? How do I process this data?"
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이건 μ–΄λ–»κ²Œ μ²˜λ¦¬ν•˜μ§€?"에 μ§‘μ€‘ν•˜κ³  μžˆμŠ΅λ‹ˆλ‹€
06:04
These are necessary but insufficient questions.
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μ΄λŸ¬ν•œ 것듀이 κΌ­ ν•„μš”ν•˜κΈ΄ ν•˜μ§€λ§Œ μΆ©λΆ„ν•˜μ§„ μ•Šμ€ μ§ˆλ¬Έλ“€μ΄μ£ 
06:06
The imperative is not to figure out how to compute,
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μš°λ¦¬μ—κ²Œ ν•„μš”ν•œ 것은 μ–΄λ–»κ²Œ κ³„μ‚°ν•˜λŠλƒκ°€ μ•„λ‹Œ,
06:08
but what to compute. How do you impose human intuition
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무엇을 κ³„μ‚°ν•΄μ•Όν•˜λŠ”μ§€λ₯Ό μ•Œμ•„λ‚΄λŠ” κ²ƒμž…λ‹ˆλ‹€
06:11
on data at this scale?
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μ΄λ ‡κ²Œ λ°©λŒ€ν•œ μžλ£Œμ— μΈκ°„μ˜ 직관을 μ–΄λ–€ λ°©μ‹μœΌλ‘œ λ„μž…ν•  수 μžˆμ„κΉŒμš”?
06:12
Again, we start by designing the human into the process.
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λ‹€μ‹œ λ§μ”€λ“œλ¦¬μ§€λ§Œ, μ‚¬λžŒμ„ ν”„λ‘œμ„ΈμŠ€μ— ν¬ν•¨ν•΄μ„œ 섀계λ₯Ό ν•¨μœΌλ‘œμ¨ μ‹œμž‘ν•  수 μžˆμŠ΅λ‹ˆλ‹€
06:16
When PayPal was first starting as a business, their biggest
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"PayPal"이 처음 사업을 μ‹œμž‘ν–ˆμ„ λ•Œ κ·Έλ“€μ˜ κ°€μž₯ 큰 λ¬Έμ œλŠ”
06:19
challenge was not, "How do I send money back and forth online?"
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"μ–΄λ–»κ²Œ λˆμ„ 보내고 λ°›λŠ”κ°€?"κ°€ μ•„λ‹ˆμ—ˆμ–΄μš”
06:22
It was, "How do I do that without being defrauded by organized crime?"
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λ¬Έμ œλŠ” "쑰직적인 λ²”μ£„λ‘œλΆ€ν„° 사기λ₯Ό λ‹Ήν•˜μ§€ μ•Šκ³  그런걸 ν•  수 μžˆλŠ”κ°€?" μ˜€μ£ 
06:25
Why so challenging? Because while computers can learn
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그게 μ™œ μ–΄λ €μš΄ λ¬Έμ œλƒκ³ μš”? μ™œλƒν•˜λ©΄ μ»΄ν“¨ν„°λŠ”
06:28
to detect and identify fraud based on patterns,
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사기 ν–‰μœ„λ₯Ό νŒ¨ν„΄μ— κ·Όκ±°ν•΄μ„œ μ°Ύμ•„λ‚΄λŠ” 방법을 λ°°μš°λŠ”λ°,
06:31
they can't learn to do that based on patterns
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이전엔 μ „ν˜€ 보지 λͺ»ν–ˆλ˜ νŒ¨ν„΄μ„ κ·Όκ±°λ‘œλŠ” 사기λ₯Ό
06:32
they've never seen before, and organized crime
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μ λ°œν•  수 μ—†λŠ”λ°λ‹€κ°€, μ‘°μ§ν™”λœ λ²”μ£„λŠ”
06:34
has a lot in common with this audience: brilliant people,
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λŒ€μ€‘κ³Ό μƒλ‹Ήνžˆ μœ μ‚¬ν•œ 점이 많기 λ•Œλ¬Έμ΄μ£ 
06:37
relentlessly resourceful, entrepreneurial spirit β€” (Laughter) β€”
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λ˜‘λ˜‘ν•œ μ‚¬λžŒλ“€κ³Ό, μ—„μ²­λ‚˜κ²Œ λ›°μ–΄λ‚œ, κΈ°μ—…κ°€ 정신이 μœ μ‚¬ν•˜κ³  (μ›ƒμŒ)
06:41
and one huge and important difference: purpose.
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λͺ©μ μ— μžˆμ–΄μ„œλŠ” μ•„μ£Ό 큰 차이가 μ‘΄μž¬ν•©λ‹ˆλ‹€
06:43
And so while computers alone can catch all but the cleverest
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컴퓨터듀 λ§ŒμœΌλ‘œλ„ κ°€μž₯ λ˜‘λ˜‘ν•œ 사기꾼을 μ œμ™Έν•˜κ³ λŠ” λͺ¨λ‘ μž‘μ•„λ‚Ό 수 μžˆμ§€λ§Œ,
06:46
fraudsters, catching the cleverest is the difference
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κ·Έ μ‚¬λžŒμ„ μž‘λŠ” 것이
06:48
between success and failure.
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성곡과 μ‹€νŒ¨μ˜ μ°¨μ΄μž…λ‹ˆλ‹€
06:51
There's a whole class of problems like this, ones with
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μ λ‹Ήν•œ 적을 가지고 μžˆκΈ°λ„ ν•œ 이런 μ’…λ₯˜μ˜ λ¬Έμ œλŠ” μ—„μ²­λ‚˜κ²Œ λ§ŽμŠ΅λ‹ˆλ‹€
06:53
adaptive adversaries. They rarely if ever present with a
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λ°˜λ³΅λ˜λŠ” νŒ¨ν„΄μ΄ μžˆλŠ” κ²½μš°λŠ” λ“œλ¬Όμ§€λ§Œ,
06:56
repeatable pattern that's discernable to computers.
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μžˆλ‹€λ©΄ 컴퓨터가 μ°Ύμ•„λ‚Ό 수 μžˆμŠ΅λ‹ˆλ‹€
06:59
Instead, there's some inherent component of innovation or disruption,
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λŒ€μ‹ μ— λ‚΄μž¬μ μΈ ν˜μ‹ μ΄λ‚˜ μž₯μ•  μš”μ†Œκ°€ 있으며,
07:03
and increasingly these problems are buried in big data.
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μ΄λŸ¬ν•œ λ¬Έμ œλ“€μ€ κ³„μ†ν•΄μ„œ 'λΉ… 데이터'μ•ˆμ—μ„œ 파묻히게 λ©λ‹ˆλ‹€
07:05
For example, terrorism. Terrorists are always adapting
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예λ₯Ό λ“ λ‹€λ©΄, ν…ŒλŸ¬κ°€ μžˆκ² λ„€μš” ν…ŒλŸ¬λ¦¬μŠ€νŠΈλ“€μ€ 항상 μƒˆλ‘œμš΄ 상황에
07:08
in minor and major ways to new circumstances, and despite
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크고 μž‘μ€ 각색을 λ”ν•˜κ³ ,
07:10
what you might see on TV, these adaptations,
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μ—¬λŸ¬λΆ„λ“€μ΄ TVμ—μ„œ λ³΄λŠ” 것에도 λΆˆκ΅¬ν•˜κ³ 
07:13
and the detection of them, are fundamentally human.
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μ΄λŸ¬ν•œ 변화와 이λ₯Ό μ°Ύμ•„λ‚΄λŠ” 것은 기본적으둜 μΈκ°„μž…λ‹ˆλ‹€
07:15
Computers don't detect novel patterns and new behaviors,
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μ»΄ν“¨ν„°λŠ” κΈ°λ°œν•œ νŒ¨ν„΄μ΄λ‚˜ μƒˆλ‘œμš΄ 행동을 찾아내지 λͺ»ν•˜μ§€λ§Œ, μ‚¬λžŒλ“€μ€ 이게 κ°€λŠ₯ν•˜μ£ 
07:18
but humans do. Humans, using technology, testing hypotheses,
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μš°λ¦¬λŠ” 기계에 κΈ°μˆ μ„ μ‚¬μš©ν•˜κ³  가정을 κ²€μ¦ν•˜κ³ ,
07:22
searching for insight by asking machines to do things for them.
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톡찰을 μ°Ύκ³ , 이에 ν•„μš”ν•œ 것듀을 기계에 λ§‘κΉλ‹ˆλ‹€
07:26
Osama bin Laden was not caught by artificial intelligence.
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μ˜€μ‚¬λ§ˆ 빈 라덴은 인곡 지λŠ₯μ—κ²Œ λΆ™μž‘νžŒ 게 μ•„λ‹™λ‹ˆλ‹€
07:28
He was caught by dedicated, resourceful, brilliant people
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κ·ΈλŠ” ν—Œμ‹ μ μ΄κ³ , μ§€λž΅μ΄ 있고, λ˜‘λ˜‘ν•˜λ©°,
07:31
in partnerships with various technologies.
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λ‹€μ–‘ν•œ 기계와 ν˜‘λ ₯ν•œ μ‚¬λžŒλ“€μ—κ²Œ κ²€κ±°λ˜μ—ˆμŠ΅λ‹ˆλ‹€
07:35
As appealing as it might sound, you cannot algorithmically
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얼핏 λ“£κΈ°μ—λŠ” 섀득λ ₯이 μžˆμ§€λ§Œ, μ•Œκ³ λ¦¬μ¦˜μ μœΌλ‘œ
07:38
data mine your way to the answer.
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데이터 λ§ˆμ΄λ‹μ„ ν•΄μ„œ 정닡에 도달할 순 μ—†μŠ΅λ‹ˆλ‹€
07:40
There is no "Find Terrorist" button, and the more data
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"ν…ŒλŸ¬λ¦¬μŠ€νŠΈλ₯Ό 찾아라"와 같은 λ‹¨μΆ”λŠ” μ—†μœΌλ©°,
07:43
we integrate from a vast variety of sources
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μš°λ¦¬κ°€ μ„œλ‘œ λ‹€λ₯Έ μ‹œμŠ€ν…œμ—μ„œ μ•„μ£Ό λ‹€μ–‘ν•œ 데이터 포맷을,
07:45
across a wide variety of data formats from very
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ꡉμž₯히 λ‹€μ±„λ‘œμš΄ μΆœμ²˜μ—μ„œ λ‚˜μ˜¨ 데이터λ₯Ό ν†΅ν•©ν• μˆ˜λ‘
07:47
disparate systems, the less effective data mining can be.
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λ°μ΄ν„°λ§ˆμ΄λ‹μ€ 더 λΉ„νš¨μœ¨μ μ΄κ²Œ λ©λ‹ˆλ‹€
07:50
Instead, people will have to look at data
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κ·Έ λŒ€μ‹ , μš°λ¦¬κ°€ 자료λ₯Ό 직접 보고, 톡찰을 μ°Ύμ•„μ•Όν•  κ²ƒμž…λ‹ˆλ‹€
07:52
and search for insight, and as Licklider foresaw long ago,
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릭라이더가 였래 전에 μ˜ˆκ²¬ν–ˆλ“―μ΄,
07:56
the key to great results here is the right type of cooperation,
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μ—¬κΈ°μ„œ λŒ€λ‹¨ν•œ κ²°κ³Όλ₯Ό μ–»λŠ”λ° μžˆμ–΄μ„œμ˜ 핡심은 μ˜³μ€ ν˜•νƒœμ˜ ν˜‘λ ₯이며,
07:58
and as Kasparov realized,
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μΉ΄μŠ€νŒŒλ‘œν”„κ°€ κΉ¨λ‹¬μ•˜λ“―μ΄,
08:00
that means minimizing friction at the interface.
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μ΄λŠ” μΈν„°νŽ˜μ΄μŠ€μ—μ„œμ˜ λ§ˆμ°°μ„ μ΅œμ†Œν™”ν•˜μ—¬μ•Ό ν•œλ‹€λŠ” λ§μž…λ‹ˆλ‹€
08:03
Now this approach makes possible things like combing
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이제 이런 방법듀 덕뢄에 μ•„μ£Ό λ‹€μ–‘ν•œ μΆœμ²˜μ—μ„œ λ‚˜μ˜¨
08:06
through all available data from very different sources,
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λͺ¨λ“  κ°€λŠ₯ν•œ 데이터λ₯Ό ν†΅ν•©ν•˜λŠ” 것,
08:09
identifying key relationships and putting them in one place,
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μ€‘μš”ν•œ 관계λ₯Ό ν™•μΈν•˜κ³  λ¬ΆλŠ” 것 λ“±
08:12
something that's been nearly impossible to do before.
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μ΄μ „μ—λŠ” 거의 λΆˆκ°€λŠ₯ν–ˆλ˜ 것듀이 κ°€λŠ₯ν•˜κ²Œ λ˜μ—ˆμŠ΅λ‹ˆλ‹€
08:15
To some, this has terrifying privacy and civil liberties
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λˆ„κ΅°κ°€μ—κ²Œ 이 κΈ°μˆ μ€ μ‚¬μƒν™œκ³Ό μ‹œλ―Όμ˜ 자유λ₯Ό μœ„ν˜‘ν•˜λŠ” 것을 μ˜λ―Έν•©λ‹ˆλ‹€
08:17
implications. To others it foretells of an era of greater
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또 μ–΄λ–€ μ‚¬λžŒλ“€μ—κ²ŒλŠ” 더 λ‚˜μ€ μ‚¬μƒν™œκ³Ό μ‹œλ―Όμ˜ 자유λ₯Ό λ³΄ν˜Έν•˜λŠ” μ‹œλŒ€λ₯Ό
08:20
privacy and civil liberties protections,
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μ˜ˆμ–Έν•˜κΈ°λ„ ν•˜μ£ 
08:22
but privacy and civil liberties are of fundamental importance.
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ν•˜μ§€λ§Œ μ‚¬μƒν™œκ³Ό ꡭ민의 μžμœ λŠ” 근원이 λ˜λŠ” μ€‘μš”ν•œ κ²ƒμž…λ‹ˆλ‹€
08:25
That must be acknowledged, and they can't be swept aside,
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아무리 쒋은 μ˜λ„λ₯Ό κ°€μ‘Œλ‹€κ³  ν•˜λ”λΌλ„,
08:27
even with the best of intents.
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μ΄λŠ” μΈμ •λ˜μ–΄μ•Ό ν•˜λ©°, κ°„κ³Όλ˜μ–΄μ„œλŠ” μ•ˆλ©λ‹ˆλ‹€
08:30
So let's explore, through a couple of examples, the impact
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μ•½κ°„μ˜ 예λ₯Ό ν†΅ν•΄μ„œ
08:32
that technologies built to drive human-computer symbiosis
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인간과 μ»΄ν“¨ν„°μ˜ 곡생관계λ₯Ό μ΄λŒμ–΄ λ‚˜κ°€κΈ° μœ„ν•΄ λ§Œλ“€μ–΄μ§„ κΈ°μˆ λ“€μ΄
08:35
have had in recent time.
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ν˜„λŒ€μ— μ–΄λ–€ 영ν–₯을 λΌμ³€λŠ”μ§€ μ•Œμ•„λ³΄λ„λ‘ ν•˜μ£ 
08:38
In October, 2007, U.S. and coalition forces raided
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2007λ…„ 10μ›”, λ―Έκ΅­κ³Ό 연합ꡭ은 μ‹œλ¦¬μ•„μ— μžˆλŠ” μ΄λΌν¬μ™€μ˜ κ΅­κ²½μ§€λŒ€μ— μœ„μΉ˜ν•œ
08:41
an al Qaeda safe house in the city of Sinjar
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μ‹ μŸˆλ₯΄λΌλŠ” λ„μ‹œμ—μ„œ μ•ŒμΉ΄μ—λ‹€μ˜ μ€μ‹ μ²˜λ₯Ό
08:43
on the Syrian border of Iraq.
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κ³΅κ²©ν–ˆμŠ΅λ‹ˆλ‹€
08:45
They found a treasure trove of documents:
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그듀은 보물같이 κ·€μ€‘ν•œ 문건을 μ°Ύμ•„λƒˆμŠ΅λ‹ˆλ‹€
08:48
700 biographical sketches of foreign fighters.
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μ΄λŠ” 외ꡭ인 μš©λ³‘ 700μ—¬ λͺ…μ˜ 신상 μžλ£Œμ˜€μŠ΅λ‹ˆλ‹€
08:50
These foreign fighters had left their families in the Gulf,
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이 μš©λ³‘λ“€μ€ 이라크에 μžˆλŠ” μ•ŒμΉ΄μ—λ‹€μ— ν•©λ₯˜ν•˜κΈ° μœ„ν•΄
08:53
the Levant and North Africa to join al Qaeda in Iraq.
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페λ₯΄μ‹œμ•„ 만과 레반트 지역, 그리고 뢁아프리카에 가쑱을 λ‚¨κ²¨λ’€μŠ΅λ‹ˆλ‹€
08:56
These records were human resource forms.
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이런 기둝듀은 μΈμ μžμ›μ΄λΌκ³  ν•  수 μžˆμŠ΅λ‹ˆλ‹€
08:57
The foreign fighters filled them out as they joined the organization.
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외ꡭ인 μš©λ³‘λ“€μ΄ 이 단체에 κ°€μž…ν•˜λ©΄μ„œ μž‘μ„±ν–ˆμŠ΅λ‹ˆλ‹€
09:00
It turns out that al Qaeda, too,
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μ•ŒμΉ΄μ—λ‹€ μ—­μ‹œ κ΄€λ£Œμ  ν–‰νƒœλ₯Ό
09:02
is not without its bureaucracy. (Laughter)
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λ²—μ–΄λ‚˜μ§€ λͺ» ν–ˆλ‹€λŠ” κ²ƒμœΌλ‘œ λ°ν˜€μ‘Œλ„€μš” (μ›ƒμŒ)
09:04
They answered questions like, "Who recruited you?"
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그듀은 "λˆ„κ°€ 당신을 μ˜μž…ν–ˆλŠ”κ°€?", "κ³ ν–₯은 어디인가?"
09:06
"What's your hometown?" "What occupation do you seek?"
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"μ–΄λ–€ 직업을 κ΅¬ν•˜λŠ”κ°€?" 와 같은 μ§ˆλ¬Έμ— λ‹΅ν–ˆμŠ΅λ‹ˆλ‹€
09:09
In that last question, a surprising insight was revealed.
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μ € λ§ˆμ§€λ§‰ μ§ˆλ¬Έμ—μ„œ μ•„μ£Ό λ†€λΌμš΄ 톡찰λ ₯이 λ°ν˜€μ‘ŒμŠ΅λ‹ˆλ‹€
09:12
The vast majority of foreign fighters
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μ™Έκ΅­ μš©λ³‘λ“€μ˜ λŒ€λΆ€λΆ„μ€
09:15
were seeking to become suicide bombers for martyrdom --
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순ꡐλ₯Ό μœ„ν•œ μžμ‚΄ 폭탄 ν…ŒλŸ¬λ²”μ΄ 되고자 ν–ˆμŠ΅λ‹ˆλ‹€
09:17
hugely important, since between 2003 and 2007, Iraq
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μ΄λŠ” 2003λ…„μ—μ„œ 2007λ…„ 사이에 μ΄λΌν¬μ—μ„œλŠ” 1,382λͺ… 건의 μžμ‚΄ν­νƒ„ν…ŒλŸ¬κ°€ μžˆμ—ˆκ³ ,
09:21
had 1,382 suicide bombings, a major source of instability.
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이것이 λΆˆμ•ˆμ •ν•œ μ‹œκ΅­μ˜ μ£Όμš” μ›μΈμ΄μ—ˆκΈ°μ— μ•„μ£Ό μ€‘μš”ν•œ 자료라고 ν•  수 μžˆμŠ΅λ‹ˆλ‹€
09:26
Analyzing this data was hard. The originals were sheets
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이 자료λ₯Ό λΆ„μ„ν•˜λŠ”κ±΄ μ–΄λ €μ› μŠ΅λ‹ˆλ‹€
09:28
of paper in Arabic that had to be scanned and translated.
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쒅이에 μ•„λžμ–΄λ‘œ 쓰인 원본을 μŠ€μΊ”ν•΄μ„œ λ²ˆμ—­ν•΄μ•Ό ν–ˆμŠ΅λ‹ˆλ‹€
09:30
The friction in the process did not allow for meaningful
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이 κ³Όμ •μ—μ„œ λ‚˜νƒ€λ‚œ 어렀움 λ•Œλ¬Έμ—
09:33
results in an operational time frame using humans, PDFs
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μ‚¬λžŒκ³Ό PDF 파일, 그리고 끈질긴 λ…Έλ ₯으둜 λ§ŒμœΌλ‘œλŠ”
09:36
and tenacity alone.
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μž‘μ „ μ‹œκ°„μ΄λ‚΄μ— μ™„μˆ˜ν•  μˆ˜κ°€ μ—†μ—ˆμŠ΅λ‹ˆλ‹€
09:38
The researchers had to lever up their human minds
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연ꡬ원듀은 더 깊이 νŒŒκ³ λ“€κ³ , λΆˆλΆ„λͺ…ν•œ 가정듀을 νƒκ΅¬ν•˜κΈ° μœ„ν•΄
09:40
with technology to dive deeper, to explore non-obvious
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기술과 ν•¨κ»˜ 인간적 사고λ₯Ό λŒμ–΄μ˜¬λ €μ•Ό ν–ˆκ³ ,
09:43
hypotheses, and in fact, insights emerged.
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그러자 톡찰λ ₯이 μƒκ²¨λ‚¬μŠ΅λ‹ˆλ‹€
09:46
Twenty percent of the foreign fighters were from Libya,
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μ™Έκ΅­ μš©λ³‘λ“€μ˜ 20%λŠ” 리비아 μΆœμ‹ μ΄μ—ˆκ³ ,
09:48
50 percent of those from a single town in Libya,
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κ·Έλ“€ 쀑 50%λŠ” λ¦¬λΉ„μ•„μ˜ 같은 λ§ˆμ„ μΆœμ‹ μ΄μ—ˆμŠ΅λ‹ˆλ‹€
09:51
hugely important since prior statistics put that figure at
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μ΄μ „μ˜ ν†΅κ³„μžλ£Œμ—μ„œλŠ” 3%둜 λ΄€κΈ° λ•Œλ¬Έμ— μ΄λŠ” μ•„μ£Ό μ€‘μš”ν–ˆμŠ΅λ‹ˆλ‹€
09:54
three percent. It also helped to hone in on a figure
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μ΄λŠ” μ•ŒμΉ΄μ—λ‹€μ—μ„œ λ– μ˜€λ‘œλŠ” μ€‘μš” 인물이자
09:56
of rising importance in al Qaeda, Abu Yahya al-Libi,
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리비아 이슬람 투쟁 λ‹¨μ²΄μ˜ κ³ μœ„ 인사인
09:59
a senior cleric in the Libyan Islamic fighting group.
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μ•„λΆ€ μ•Όνžˆμ•Ό μ•Œλ¦¬λΉ„(Abu Yahya al-Libi)에 μ£Όλͺ©ν•˜λŠ” 것을 돕기도 ν–ˆμŠ΅λ‹ˆλ‹€
10:02
In March of 2007, he gave a speech, after which there was
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2007λ…„ 3μ›”, 그의 연섀이 μžˆμ—ˆκ³ , 이후에
10:04
a surge in participation amongst Libyan foreign fighters.
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리비아 μ™Έκ΅­ μš©λ³‘λ“€μ˜ μ°Έμ—¬κ°€ 급격이 λŠ˜μ–΄ λ‚¬μŠ΅λ‹ˆλ‹€
10:08
Perhaps most clever of all, though, and least obvious,
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λ¨Έλ¦Ώμ†μ—μ„œ 데이터λ₯Ό λ„˜κΈ°λ©΄μ„œ 비둝 거의 λΆˆλΆ„λͺ…ν–ˆμ§€λ§Œ,
10:11
by flipping the data on its head, the researchers were
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μ•„λ§ˆλ„ κ°€μž₯ ν˜„λͺ…ν–ˆλ˜ 것은, 연ꡬ원듀이
10:13
able to deeply explore the coordination networks in Syria
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μ™Έκ΅­ μš©λ³‘λ“€μ„ 듀이고, ꡭ경으둜 λ³΄λ‚΄λŠ”λ°
10:16
that were ultimately responsible for receiving and
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μ ˆλŒ€μ μΈ μ±…μž„μ„ 지고 있던 μ‹œλ¦¬μ•„ λ‚΄λΆ€μ˜ 쑰직 λ„€νŠΈμ›Œν¬λ₯Ό
10:19
transporting the foreign fighters to the border.
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μ‹¬λ„μžˆκ²Œ 탐ꡬ할 수 μžˆμ—ˆλ˜ 것일 κ²λ‹ˆλ‹€
10:21
These were networks of mercenaries, not ideologues,
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이듀은 이둠적 μ§€λ„μžλ“€μ΄ μ•„λ‹ˆλΌ,
10:24
who were in the coordination business for profit.
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이읡을 μœ„ν•œ 쑰직 사업에 μžˆλŠ” μš©λ³‘λ“€μ˜ λ„€νŠΈμ›Œν¬μ˜€μŠ΅λ‹ˆλ‹€
10:26
For example, they charged Saudi foreign fighters
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예λ₯Ό λ“€μ–΄, 그듀은 μ‚¬μš°λ”” μΆœμ‹  μš©λ³‘λ“€μ—κ²Œ
10:28
substantially more than Libyans, money that would have
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리비아인듀보닀 훨씬 더 λ§Žμ€ λΉ„μš©μ„ μ²­κ΅¬ν–ˆμŠ΅λ‹ˆλ‹€
10:30
otherwise gone to al Qaeda.
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그렇지 μ•Šμ•˜λ‹€λ©΄ 이 λˆμ€ μ•ŒμΉ΄μ—λ‹€λ‘œ ν˜λŸ¬κ°”κ² μ£ 
10:32
Perhaps the adversary would disrupt their own network
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그듀이 잠재적 μ§€ν•˜λ“œ 일당을 속이고 μžˆλ‹€λŠ” 것을 μ•Œκ²Œ λ˜μ—ˆλ‹€λ©΄,
10:34
if they knew they cheating would-be jihadists.
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μ•„λ§ˆλ„ 내뢀적인 반발둜 이 λ„€νŠΈμ›Œν¬λŠ” 흔듀렸을 κ²λ‹ˆλ‹€.
10:37
In January, 2010, a devastating 7.0 earthquake struck Haiti,
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2010λ…„ 1μ›”, 규λͺ¨ 7.0의 μ—„μ²­λ‚œ 지진이 ν•˜μ΄ν‹°λ₯Ό κ°•νƒ€ν–ˆμŠ΅λ‹ˆλ‹€
10:41
third deadliest earthquake of all time, left one million people,
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μ „ 역사λ₯Ό 톡해 μ„Έ 번째둜 κ°•λ ₯ν–ˆλ˜ 이 지진은
10:44
10 percent of the population, homeless.
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백만λͺ…, κ·ΈλŸ¬λ‹ˆκΉŒ 인ꡬ의 10%λ₯Ό 이재민으둜 λ§Œλ“€μŠ΅λ‹ˆλ‹€
10:47
One seemingly small aspect of the overall relief effort
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κ²‰μœΌλ‘œ λ³΄κΈ°μ—λŠ” λ―Έλ―Έν•œ ꡬ호의 손길쑰차도
10:50
became increasingly important as the delivery of food
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μŒμ‹κ³Ό μ‹μˆ˜κ°€ λ°”λ‹₯λ‚˜κΈ° μ‹œμž‘ν•˜λ©΄μ„œ
10:52
and water started rolling.
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점점 μ€‘μš”ν•œ 도움이 λ˜μ—ˆμŠ΅λ‹ˆλ‹€
10:54
January and February are the dry months in Haiti,
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ν•˜μ΄ν‹°μ˜ 1μ›”κ³Ό 2월은 κ±΄κΈ°μ˜€μ§€λ§Œ
10:56
yet many of the camps had developed standing water.
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λ§Žμ€ λŒ€ν”Όμ†Œμ—μ„œλŠ” 웅덩이λ₯Ό νŒ μŠ΅λ‹ˆλ‹€
10:59
The only institution with detailed knowledge of Haiti's
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ν•˜μ΄ν‹°μ˜ λ²”λžŒ 지역을 μžμ„Ένžˆ μ•Œκ³  있던
11:01
floodplains had been leveled
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단 ν•˜λ‚˜μ˜ 기관은 이미 지진에
11:02
in the earthquake, leadership inside.
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λ¬΄λ„ˆμ§„ μƒνƒœμ˜€μŠ΅λ‹ˆλ‹€ 주도λ ₯도 ν•¨κ»˜ 묻힌거죠
11:05
So the question is, which camps are at risk,
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λ¬Έμ œλŠ” μ–΄λŠ λŒ€ν”Όμ†Œκ°€ μœ„ν—˜μ— μ²˜ν•΄ 있으며,
11:08
how many people are in these camps, what's the
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μ–Όλ§ˆλ‚˜ λ§Žμ€ μ‚¬λžŒλ“€μ΄ 이런 λŒ€ν”Όμ†Œμ— 있고,
11:10
timeline for flooding, and given very limited resources
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ν™μˆ˜κ°€ μ–Έμ œ 일어날 것인지, 그리고 주어진 μ•„μ£Ό μ œν•œμ μΈ 정보와 κΈ°λ°˜μ‹œμ„€μ„ 가지고
11:12
and infrastructure, how do we prioritize the relocation?
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λŒ€ν”Ό μš°μ„ μˆœμœ„λŠ” μ–΄λ–»κ²Œ μ •ν•  것인가와 같은 κ²ƒλ“€μ΄μ—ˆμŠ΅λ‹ˆλ‹€
11:15
The data was incredibly disparate. The U.S. Army had
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μžλ£ŒλŠ” 정말 μ ˆμ‹€ν–ˆμŠ΅λ‹ˆλ‹€
11:18
detailed knowledge for only a small section of the country.
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λ―Έ μœ‘κ΅°μ€ μ•„νžˆν‹°μ˜ 극히 일뢀 지역에 λŒ€ν•΄μ„œλ§Œ μ„Έμ„Έν•œ 정보λ₯Ό 가지고 μžˆμ—ˆμŠ΅λ‹ˆλ‹€
11:21
There was data online from a 2006 environmental risk
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2006λ…„ ν™˜κ²½ μœ„ν—˜ νšŒμ˜λ‚˜ λ‹€λ₯Έ μ§€μ§ˆν•™μ  μžλ£Œλ“€μ΄ 인터넷에 μžˆμ—ˆμ§€λ§Œ
11:23
conference, other geospatial data, none of it integrated.
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μ–΄λŠ 것도 쒅합적이지 λͺ»ν–ˆμŠ΅λ‹ˆλ‹€
11:26
The human goal here was to identify camps for relocation
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이 경우, μ‚¬λžŒλ“€μ˜ λͺ©ν‘œλŠ” ν•„μš”ν•œ μš°μ„  μˆœμœ„μ— μ˜ν•΄
11:29
based on priority need.
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μ΄λ™μ‹œμΌœμ•Ό ν•  ν”Όλ‚œμ†Œλ₯Ό μ •ν•˜λŠ” κ²ƒμ΄μ—ˆμŠ΅λ‹ˆλ‹€
11:31
The computer had to integrate a vast amount of geospacial
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이 λ¬Έμ œμ— λŒ€ν•œ λŒ€λ‹΅μ„ λ‚΄κΈ° μœ„ν•΄μ„œ
11:33
information, social media data and relief organization
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컴퓨터가 μ—„μ²­λ‚œ μ–‘μ˜ 지리적 정보와 μ‚¬νšŒμ  자료,
11:36
information to answer this question.
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ꡬ호 λ‹¨μ²΄μ˜ 정보λ₯Ό μ’…ν•©ν•΄μ•Ό ν–ˆμŠ΅λ‹ˆλ‹€
11:40
By implementing a superior process, what was otherwise
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훨씬 더 μš°μˆ˜ν•œ 처리 방법을 μ μš©ν•¨μœΌλ‘œμ¨
11:42
a task for 40 people over three months became
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40λͺ…이 3κ°œμ›” λ™μ•ˆ 진행해야 ν–ˆμ„ μž„λ¬΄λ₯Ό
11:45
a simple job for three people in 40 hours,
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μ„Έ μ‚¬λžŒμ΄ 40μ‹œκ°„ λ§Œμ— ν•΄λ‚Ό 수 μžˆμ—ˆμŠ΅λ‹ˆλ‹€
11:48
all victories for human-computer symbiosis.
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이건 μ „μ μœΌλ‘œ 인간과 μ»΄ν“¨ν„°μ˜ κ³΅μƒμ˜ μŠΉλ¦¬μ˜€μŠ΅λ‹ˆλ‹€
11:50
We're more than 50 years into Licklider's vision
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μš°λ¦¬λŠ” λ¦­λΌμ΄λ”μ˜ λΉ„μ „ 이후 50λ…„μ΄λ‚˜ μ§€λ‚¬μœΌλ©°,
11:52
for the future, and the data suggests that we should be
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λ°μ΄ν„°λŠ” μš°λ¦¬λ“€μ΄ 인간과 기계가 μ„œλ‘œ ν˜‘λ ₯ν•¨μœΌλ‘œμ¨
11:55
quite excited about tackling this century's hardest problems,
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κΈˆμ„ΈκΈ°μ˜ κ°€μž₯ μ–΄λ €μš΄ λ¬Έμ œλ“€μ„ ν•΄κ²°ν•˜λŠ”λ°
11:58
man and machine in cooperation together.
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μ•„μ£Ό ν₯λΆ„λ˜μ–΄ μžˆμ–΄μ•Όν•œλ‹€κ³  보고 μžˆμŠ΅λ‹ˆλ‹€
12:01
Thank you. (Applause)
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κ°μ‚¬ν•©λ‹ˆλ‹€ .(λ°•μˆ˜)
12:03
(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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