BOX SET: 6 Minute English - 'Technology 2' English mega-class! Thirty minutes of new vocabulary!

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2022-10-16 ใƒป BBC Learning English


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BOX SET: 6 Minute English - 'Technology 2' English mega-class! Thirty minutes of new vocabulary!

168,381 views ใƒป 2022-10-16

BBC Learning English


์•„๋ž˜ ์˜๋ฌธ์ž๋ง‰์„ ๋”๋ธ”ํด๋ฆญํ•˜์‹œ๋ฉด ์˜์ƒ์ด ์žฌ์ƒ๋ฉ๋‹ˆ๋‹ค. ๋ฒˆ์—ญ๋œ ์ž๋ง‰์€ ๊ธฐ๊ณ„ ๋ฒˆ์—ญ๋ฉ๋‹ˆ๋‹ค.

00:05
Hello. This is 6 Minute English
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์•ˆ๋…•ํ•˜์„ธ์š”. BBC Learning English์˜ 6๋ถ„ ์˜์–ด
00:07
from BBC Learning English.
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์ž…๋‹ˆ๋‹ค.
00:09
Iโ€™m Sam.
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00:09
And Iโ€™m Neil.
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์ €๋Š” ์ƒ˜์ž…๋‹ˆ๋‹ค.
๊ทธ๋ฆฌ๊ณ  ์ €๋Š” ๋‹์ž…๋‹ˆ๋‹ค.
00:10
On Saturday mornings I love going
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ํ† ์š”์ผ ์•„์นจ์— ๋‚˜๋Š”
00:12
to watch football in the park.
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๊ณต์›์—์„œ ์ถ•๊ตฌ๋ฅผ ๋ณด๋Š” ๊ฒƒ์„ ์ข‹์•„ํ•ฉ๋‹ˆ๋‹ค.
00:14
The problem is when itโ€™s cold and
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๋ฌธ์ œ๋Š” ์ถฅ๊ณ  ๋น„๊ฐ€ ์˜ฌ ๋•Œ์ž…๋‹ˆ๋‹ค.
00:16
rainy - I look out the bedroom window
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์ €๋Š” ์นจ์‹ค ์ฐฝ ๋ฐ–์„ ๋‚ด๋‹ค๋ณด๊ณ 
00:18
and go straight back to bed!
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๋ฐ”๋กœ ์นจ๋Œ€๋กœ ๋Œ์•„๊ฐ‘๋‹ˆ๋‹ค!
00:20
Well, instead of going to the park, why
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๊ธ€์Ž„์š”, ๊ณต์›์— ๊ฐ€๋Š” ๋Œ€์‹ ์—
00:22
not bring the park to you? Imagine
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๊ณต์›์„ ๋‹น์‹ ์—๊ฒŒ ๊ฐ€์ ธ๋‹ค์ฃผ๋Š” ๊ฒƒ์€ ์–ด๋–จ๊นŒ์š”?
00:24
watching a live version of the
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00:26
football match at home in the warm,
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๋”ฐ๋œปํ•œ ์ง‘์—์„œ
00:28
with friends. Sound good, Sam?
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์นœ๊ตฌ์™€ ํ•จ๊ป˜ ์ถ•๊ตฌ ๊ฒฝ๊ธฐ์˜ ๋ผ์ด๋ธŒ ๋ฒ„์ „์„ ๋ณด๋Š” ๊ฒƒ์„ ์ƒ์ƒํ•ด ๋ณด์‹ญ์‹œ์˜ค. ์ข‹์€๋ฐ, ์ƒ˜?
00:30
Sounds great! โ€“ but how can I be in
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์ข‹์€๋ฐ! โ€“ ํ•˜์ง€๋งŒ ์–ด๋–ป๊ฒŒ
00:32
two places at once? Is there some
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ํ•œ ๋ฒˆ์— ๋‘ ๊ณณ์— ์žˆ์„ ์ˆ˜ ์žˆ์Šต๋‹ˆ๊นŒ? ์ด๋ฅผ ์œ„ํ•œ
00:34
amazing invention to do that?
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๋†€๋ผ์šด ๋ฐœ๋ช…ํ’ˆ์ด ์žˆ์Šต๋‹ˆ๊นŒ?
00:36
There might be, Sam - and it could
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์žˆ์„ ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค, ์ƒ˜ - VR ๋˜๋Š” ๊ฐ€์ƒ ํ˜„์‹ค์˜ ๋ฐœ์ „ ๋•๋ถ„
00:38
be happening sooner than you think,
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์— ์ƒ๊ฐ๋ณด๋‹ค ๋นจ๋ฆฌ ์ผ์–ด๋‚  ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค
00:40
thanks to developments in VR, or
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00:42
virtual reality. According to Facebook
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. Facebook์˜
00:44
boss, Mark Zuckerberg, in the future
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์‚ฌ์žฅ์ธ Mark Zuckerberg์— ๋”ฐ๋ฅด๋ฉด ๋ฏธ๋ž˜์—
00:46
weโ€™ll all spend much of our time
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์šฐ๋ฆฌ ๋ชจ๋‘
00:48
living and working in the โ€˜metaverseโ€™ โ€“ a
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๋Š” ์ผ๋ จ์˜ ๊ฐ€์ƒ ์„ธ๊ณ„์ธ '๋ฉ”ํƒ€๋ฒ„์Šค'์—์„œ ์ƒํ™œํ•˜๊ณ  ์ผํ•˜๋Š” ๋ฐ ๋งŽ์€ ์‹œ๊ฐ„์„ ํ• ์• ํ•˜๊ฒŒ ๋  ๊ฒƒ
00:51
series of virtual worlds.
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์ž…๋‹ˆ๋‹ค.
00:53
Virtual reality is a topic weโ€™ve discussed
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๊ฐ€์ƒ ํ˜„์‹ค์€
00:56
before at 6 Minute English. But when
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์ด์ „์— 6 Minute English์—์„œ ๋…ผ์˜ํ•œ ์ฃผ์ œ์ž…๋‹ˆ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜
00:59
Facebook announced that it was
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Facebook
01:00
hiring ten thousand new workers
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01:02
to develop VR for the โ€˜metaverseโ€™, we
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์ด '๋ฉ”ํƒ€๋ฒ„์Šค'๋ฅผ ์œ„ํ•œ VR์„ ๊ฐœ๋ฐœํ•˜๊ธฐ ์œ„ํ•ด 10,000๋ช…์˜ ์‹ ๊ทœ ์ง์›์„ ๊ณ ์šฉํ•œ๋‹ค๊ณ  ๋ฐœํ‘œํ–ˆ์„ ๋•Œ ์šฐ๋ฆฌ
01:05
thought it was time for another look.
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๋Š” ๋‹ค์‹œ ํ•œ ๋ฒˆ ์‚ดํŽด๋ณผ ๋•Œ๋ผ๊ณ  ์ƒ๊ฐํ–ˆ์Šต๋‹ˆ๋‹ค.
01:06
Is this programme, weโ€™ll be hearing two
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์ด ํ”„๋กœ๊ทธ๋žจ์—์„œ ์šฐ๋ฆฌ๋Š”
01:08
different opinions on the โ€˜metaverseโ€™
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'๋ฉ”ํƒ€๋ฒ„์Šค'
01:10
and how it might shape the future.
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์™€ ๊ทธ๊ฒƒ์ด ๋ฏธ๋ž˜๋ฅผ ์–ด๋–ป๊ฒŒ ํ˜•์„ฑํ•  ์ˆ˜ ์žˆ๋Š”์ง€์— ๋Œ€ํ•œ ๋‘ ๊ฐ€์ง€ ๋‹ค๋ฅธ ์˜๊ฒฌ์„ ๋“ฃ๊ฒŒ ๋  ๊ฒƒ์ž…๋‹ˆ๋‹ค.
01:12
But first I have a question for you, Neil.
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ํ•˜์ง€๋งŒ ๋จผ์ € ์งˆ๋ฌธ์ด ์žˆ์Šต๋‹ˆ๋‹ค, ๋‹. ๊ฒŒ์ž„ ํšŒ์‚ฌ Thrive Analytics
01:15
According to a 2021 survey by
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์˜ 2021๋…„ ์„ค๋ฌธ ์กฐ์‚ฌ์— ๋”ฐ๋ฅด๋ฉด
01:17
gaming company, Thrive Analytics, what
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01:20
percentage of people who try virtual
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๊ฐ€์ƒ
01:22
reality once want to try it again? Is it:
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ํ˜„์‹ค์„ ํ•œ ๋ฒˆ ์‹œ๋„ํ•œ ์‚ฌ๋žŒ ์ค‘ ๋ช‡ ํผ์„ผํŠธ๊ฐ€ ๋‹ค์‹œ ์‹œ๋„ํ•˜๊ณ  ์‹ถ์Šต๋‹ˆ๊นŒ?
01:26
a) 9 percent?
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a) 9%์ž…๋‹ˆ๊นŒ?
01:28
b) 49 percent? or,
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b) 49ํผ์„ผํŠธ? ๋˜๋Š”
01:31
c) 79 percent?
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c) 79ํผ์„ผํŠธ?
01:33
I guess with VR you either love it
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VR์„ ์‚ฌ์šฉํ•˜๋ฉด ์ข‹์•„
01:35
or hate it, so Iโ€™ll say b) 49 percent of
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ํ•˜๊ฑฐ๋‚˜ ์‹ซ์–ดํ•˜๊ธฐ ๋•Œ๋ฌธ์— b) 49%์˜
01:38
people want to try it again.
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์‚ฌ๋žŒ๋“ค์ด ๋‹ค์‹œ ์‹œ๋„ํ•˜๊ณ  ์‹ถ๋‹ค๊ณ  ๋งํ•  ๊ฒƒ์ž…๋‹ˆ๋‹ค.
01:40
OK, Iโ€™ll reveal the correct answer
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์•Œ๊ฒ ์Šต๋‹ˆ๋‹ค. ์ •๋‹ต์€
01:41
later in the programme. But what
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๋‚˜์ค‘์— ํ”„๋กœ๊ทธ๋žจ์—์„œ ๊ณต๊ฐœํ•˜๊ฒ ์Šต๋‹ˆ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜
01:43
Neil said is true: people tend to either
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Neil์ด ๋งํ•œ ๊ฒƒ์€ ์‚ฌ์‹ค์ž…๋‹ˆ๋‹ค. ์‚ฌ๋žŒ๋“ค์€
01:46
love virtual reality or hate it.
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๊ฐ€์ƒ ํ˜„์‹ค์„ ์ข‹์•„ํ•˜๊ฑฐ๋‚˜ ์‹ซ์–ดํ•˜๋Š” ๊ฒฝํ–ฅ์ด ์žˆ์Šต๋‹ˆ๋‹ค.
01:48
Somebody who loves it is
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๊ทธ๊ฒƒ์„ ์ข‹์•„ํ•˜๋Š” ์‚ฌ๋žŒ์€ VR ๊ธฐ์ˆ ์„ ๊ฐœ๋ฐœ
01:50
Emma Ridderstad, CEO of Warpinโ€™, a
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ํ•˜๋Š” ํšŒ์‚ฌ์ธ Warpin'์˜ CEO์ธ Emma Ridderstad
01:52
company which develops
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01:54
VR technology.
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์ž…๋‹ˆ๋‹ค.
01:55
Here she is telling BBC World
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์—ฌ๊ธฐ์—์„œ ๊ทธ๋…€๋Š” ๋ฏธ๋ž˜์— ๋Œ€ํ•œ
01:57
Service programme, Tech Tent, her
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๊ทธ๋…€์˜ ๋น„์ „์ธ BBC World Service ํ”„๋กœ๊ทธ๋žจ์ธ Tech
01:59
vision of the future:
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02:00
In ten years, everything that you
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Tent์— ๋Œ€ํ•ด ์ด์•ผ๊ธฐํ•˜๊ณ 
02:02
do on your phone today, you will
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02:04
do in 3-D, through your classes
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02:06
for example. You will be able to do
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์žˆ์Šต๋‹ˆ๋‹ค.
02:09
your shopping, you will be able to
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์‡ผํ•‘์„ ํ•  ์ˆ˜ ์žˆ๊ณ 
02:10
meet your friends, you will be able
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, ์นœ๊ตฌ๋ฅผ ๋งŒ๋‚  ์ˆ˜ ์žˆ๊ณ , ์›ํ•˜๋Š”
02:12
to work remotely with whomever
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์‚ฌ๋žŒ๊ณผ ์›๊ฒฉ์œผ๋กœ ์ž‘์—…
02:15
you want, you will be able to share
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ํ•  ์ˆ˜ ์žˆ๊ณ ,
02:17
digital spaces, share music, share
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๋””์ง€ํ„ธ ๊ณต๊ฐ„์„ ๊ณต์œ ํ•˜๊ณ , ์Œ์•…์„ ๊ณต์œ ํ•˜๊ณ ,
02:21
art, share projects in digital spaces
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์˜ˆ์ˆ ์„ ๊ณต์œ ํ•˜๊ณ , ๋””์ง€ํ„ธ ๊ณต๊ฐ„์—์„œ ํ”„๋กœ์ ํŠธ๋ฅผ ๊ณต์œ ํ•  ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค.
02:24
between each other. And you will also
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์„œ๋กœ ์‚ฌ์ด. ๋˜ํ•œ
02:26
be able to integrate the digital objects
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02:28
in your physical world, making the
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๋ฌผ๋ฆฌ์  ์„ธ๊ณ„์— ๋””์ง€ํ„ธ ๊ฐœ์ฒด๋ฅผ ํ†ตํ•ฉํ•˜์—ฌ ์˜ค๋Š˜๋‚ ๋ณด๋‹ค ํ›จ์”ฌ ๋” ๋ฌผ๋ฆฌ์ ์ธ ์„ธ๊ณ„๋ฅผ ๋งŒ๋“ค
02:31
world much more phygital than
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02:33
is it today.
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์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค.
02:35
Virtual reality creates 3-D, or
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๊ฐ€์ƒ ํ˜„์‹ค์€
02:37
three-dimensional experiences where
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02:39
objects have the three dimensions of
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๊ฐ์ฒด๊ฐ€ ๊ธธ์ด, ๋„ˆ๋น„ ๋ฐ ๋†’์ด์˜ 3์ฐจ์›์„ ๊ฐ–๋Š” 3D ๋˜๋Š” 3์ฐจ์› ๊ฒฝํ—˜์„ ์ƒ์„ฑํ•ฉ๋‹ˆ๋‹ค
02:42
length, width and height. This makes
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. ์ด๊ฒƒ์€
02:44
them look lifelike and solid, not
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๊ทธ๊ฒƒ๋“ค์„ 2์ฐจ์›์ ์ด๊ณ  ํ‰๋ฉด์ ์ด์ง€ ์•Š๊ณ  ์ƒ์ƒํ•˜๊ณ  ๊ฒฌ๊ณ ํ•˜๊ฒŒ ๋ณด์ด๊ฒŒ
02:47
two-dimensional and flat.
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ํ•ฉ๋‹ˆ๋‹ค.
02:49
Emma says that in the future VR will
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Emma๋Š” ๋ฏธ๋ž˜์— VR์ด
02:52
mix digital objects and physical
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๋””์ง€ํ„ธ ๊ฐœ์ฒด์™€ ๋ฌผ๋ฆฌ์ 
02:54
objects to create exciting new
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๊ฐœ์ฒด๋ฅผ ํ˜ผํ•ฉํ•˜์—ฌ ํฅ๋ฏธ์ง„์ง„ํ•˜๊ณ  ์ƒˆ๋กœ์šด ๊ฒฝํ—˜์„ ๋งŒ๋“ค ๊ฒƒ์ด๋ผ๊ณ  ๋งํ–ˆ์Šต๋‹ˆ๋‹ค
02:55
experiences โ€“ like staying home to
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02:58
watch the same football match
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02:59
that is simultaneously happening in
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03:01
the park. She blends the words
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. ๊ทธ๋…€๋Š”
03:04
โ€˜physicalโ€™ and โ€˜digitalโ€™ to make a new
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'physical'๊ณผ 'digital'
03:06
word describing this
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์ด๋ผ๋Š” ๋‹จ์–ด๋ฅผ ํ˜ผํ•ฉํ•˜์—ฌ ์ด
03:07
combination: phygital.
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์กฐํ•ฉ์„ ์„ค๋ช…ํ•˜๋Š” ์ƒˆ๋กœ์šด ๋‹จ์–ด์ธ phygital์„ ๋งŒ๋“ญ๋‹ˆ๋‹ค.
03:09
But while a โ€˜phygitalโ€™ future sounds
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๊ทธ๋Ÿฌ๋‚˜ '๋ฌผ๋ฆฌ์ ' ๋ฏธ๋ž˜
03:11
like paradise to some, others are
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๊ฐ€ ์–ด๋–ค ์‚ฌ๋žŒ์—๊ฒŒ๋Š” ๋‚™์›์ฒ˜๋Ÿผ ๋“ค๋ฆฌ์ง€๋งŒ ๋‹ค๋ฅธ ์‚ฌ๋žŒ์€
03:13
more sceptical โ€“ they doubt that
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๋” ํšŒ์˜์ ์ž…๋‹ˆ๋‹ค. ๊ทธ๋“ค์€
03:15
VR will come true or be useful.
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VR์ด ์‹คํ˜„๋˜๊ฑฐ๋‚˜ ์œ ์šฉํ• ์ง€ ์˜์‹ฌํ•ฉ๋‹ˆ๋‹ค.
03:18
One such sceptic is technology
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๊ทธ๋Ÿฌํ•œ ํšŒ์˜๋ก ์ž ์ค‘ ํ•œ ๋ช…์€ ๊ธฐ์ˆ 
03:20
innovator, Dr Nicola Millard. For one
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ํ˜์‹ ๊ฐ€์ธ Nicola Millard ๋ฐ•์‚ฌ์ž…๋‹ˆ๋‹ค.
03:23
thing, she doesnโ€™t like wearing a
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์šฐ์„ , ๊ทธ๋…€๋Š”
03:24
VR headset โ€“ the heavy helmet and
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VR ํ—ค๋“œ์…‹(์ฐฉ์šฉ์ž์—๊ฒŒ
03:26
glasses that create virtual reality
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๊ฐ€์ƒ ํ˜„์‹ค์„ ์ œ๊ณตํ•˜๋Š” ๋ฌด๊ฑฐ์šด ํ—ฌ๋ฉง๊ณผ ์•ˆ๊ฒฝ)์„ ์ฐฉ์šฉํ•˜๋Š”
03:29
for the wearer โ€“ something she
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๊ฒƒ์„ ์ข‹์•„ํ•˜์ง€ ์•Š์Šต๋‹ˆ๋‹ค. ๊ทธ๋…€
03:30
explained to BBC World Serviceโ€™s,
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๋Š” BBC World Service์˜
03:32
Tech Tent:
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Tech
03:34
There are some basic things to
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Tent์— ๋‹ค์Œ๊ณผ ๊ฐ™์ด ์„ค๋ช…ํ–ˆ์Šต๋‹ˆ๋‹ค
03:36
think about. So, how do we
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. ์–ด๋–ป๊ฒŒ
03:37
access it? So, the reason, sort of,
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์•ก์„ธ์Šคํ•ฉ๋‹ˆ๊นŒ? ๊ทธ๋ž˜์„œ ์ผ์ข…์˜
03:40
social networks took off was, weโ€™ve
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์†Œ์…œ ๋„คํŠธ์›Œํฌ๊ฐ€ ์‹œ์ž‘๋œ ์ด์œ ๋Š” ์šฐ๋ฆฌ
03:42
got mobile technologies that let
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๊ฐ€ ์‚ฌ์šฉํ•  ์ˆ˜ ์žˆ๋Š” ๋ชจ๋ฐ”์ผ ๊ธฐ์ˆ ์ด
03:44
us use it. Now, obviously one of
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์žˆ๊ธฐ ๋•Œ๋ฌธ์ž…๋‹ˆ๋‹ค. ์ž, ๋ถ„๋ช…ํžˆ ์žฅ๋ฒฝ ์ค‘ ํ•˜๋‚˜
03:46
the barriers can be that VR or AR
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๋Š” VR ๋˜๋Š” AR ํ—ค๋“œ์…‹์ผ ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค.
03:48
headsets - so VR, Iโ€™ve always been
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๊ทธ๋ž˜์„œ ์ €๋Š” VR์—
03:51
slightly sceptical about. Iโ€™ve called
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๋Œ€ํ•ด ํ•ญ์ƒ ์•ฝ๊ฐ„ ํšŒ์˜์ ์ด์—ˆ์Šต๋‹ˆ๋‹ค. ๋‚˜๋Š”
03:53
it โ€˜vomity realityโ€™ for a while because,
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ํ•œ๋™์•ˆ ๊ทธ๊ฒƒ์„ '๊ตฌํ†  ํ˜„์‹ค'์ด๋ผ๊ณ  ๋ถˆ๋ €์Šต๋‹ˆ๋‹ค. ์™œ๋ƒํ•˜๋ฉด
03:55
frankly, I usually need a bucket
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์†”์งํžˆ ํ—ค๋“œ์…‹
03:58
somewhere close if youโ€™ve got a
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์ด ์žˆ์œผ๋ฉด ๋ณดํ†ต ๊ฐ€๊นŒ์šด ๊ณณ์— ์–‘๋™์ด๊ฐ€ ํ•„์š”ํ•˜๊ธฐ ๋•Œ๋ฌธ์ž…๋‹ˆ๋‹ค.
04:00
headset on meโ€ฆ and also, do I want
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๋˜ํ•œ ๋‹ค๋ฃจ๊ธฐ ํž˜๋“  ํ—ค๋“œ์…‹
04:01
to spend vast amounts of time in
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์—์„œ ๋งŽ์€ ์‹œ๊ฐ„์„ ๋ณด๋‚ด๊ณ  ์‹ถ์Šต๋‹ˆ๊นŒ?
04:03
those rather unwieldy headsets?
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?
04:05
Now, I know theyโ€™re talking AR as
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์ด์ œ ์ €๋Š” ๊ทธ๋“ค์ด AR์— ๋Œ€ํ•ด์„œ๋„ ์ด์•ผ๊ธฐํ•˜๊ณ  ์žˆ๋‹ค๋Š” ๊ฒƒ์„ ์•Œ๊ณ 
04:07
well and obviously that does not
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์žˆ์œผ๋ฉฐ ๋ถ„๋ช…ํžˆ
04:08
necessarily need a headset, but I
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ํ—ค๋“œ์…‹์ด ๋ฐ˜๋“œ์‹œ ํ•„์š”ํ•œ ๊ฒƒ์€ ์•„๋‹ˆ์ง€๋งŒ ํ˜„์žฌ
04:10
think weโ€™re seeing some quite
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์ƒ๋‹นํžˆ
04:12
immersive environments coming
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๋ชฐ์ž…๊ฐ ์žˆ๋Š” ํ™˜๊ฒฝ์ด ๋‚˜์˜ค๋Š”
04:13
out at the moment as well.
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๊ฒƒ์„ ๋ณด๊ณ  ์žˆ๋‹ค๊ณ  ์ƒ๊ฐํ•ฉ๋‹ˆ๋‹ค.
04:15
Nicola called VR โ€˜vomity realityโ€™
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Nicola๋Š” ํ—ค๋“œ์…‹์„ ์ฐฉ์šฉํ•˜๋ฉด ๋ฉ”์Šค๊บผ์›€์„ ๋Š๋ผ๊ธฐ ๋•Œ๋ฌธ์— VR์„ '๊ตฌํ†  ํ˜„์‹ค'์ด๋ผ๊ณ  ๋ถˆ๋ €
04:18
because wearing a headset makes
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์Šต๋‹ˆ๋‹ค. ํ—ค๋“œ์…‹์ด
04:20
her feel sick, maybe because itโ€™s
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04:22
so unwieldy โ€“ difficult to move or
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04:25
wear because itโ€™s big and heavy.
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๋„ˆ๋ฌด ํฌ๊ณ  ๋ฌด๊ฒ๊ธฐ ๋•Œ๋ฌธ์— ์›€์ง์ด๊ฑฐ๋‚˜ ์ฐฉ์šฉํ•˜๊ธฐ๊ฐ€ ์–ด๋ ต๊ธฐ ๋•Œ๋ฌธ์ผ ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค.
04:27
She also makes a difference
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๊ทธ๋…€๋Š”
04:28
between VR - virtual reality- and AR,
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๋˜ํ•œ VR(๊ฐ€์ƒ ํ˜„์‹ค)๊ณผ ์ฆ๊ฐ•
04:32
which stands for augmented
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04:33
reality โ€“ tech which adds to the
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ํ˜„์‹ค(๋ณดํ†ต ์•ˆ๊ฒฝ์„ ์ฐฉ์šฉํ•˜๊ฑฐ๋‚˜ ํœด๋Œ€ํฐ์„ ์‚ฌ์šฉํ•˜์—ฌ ๊ฐ€์ƒ์˜ ๋‹จ์–ด, ๊ทธ๋ฆผ ๋ฐ ๋ฌธ์ž๋ฅผ ํˆฌ์‚ฌํ•˜์—ฌ ์ผ์ƒ์ ์ธ ๋ฌผ๋ฆฌ์  ์„ธ๊ณ„์— ์ถ”๊ฐ€ํ•˜๋Š” ๊ธฐ์ˆ )์„ ์˜๋ฏธํ•˜๋Š” AR์„ ๊ตฌ๋ถ„ํ•ฉ๋‹ˆ๋‹ค
04:36
ordinary physical world by
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04:37
projecting virtual words, pictures
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04:40
and characters, usually by wearing
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04:42
glasses or with a mobile phone.
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.
04:44
While virtual reality replaces what
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๊ฐ€์ƒ ํ˜„์‹ค
04:46
you hear and see, augmented
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์ด ๋“ฃ๊ณ  ๋ณด๋Š” ๊ฒƒ์„ ๋Œ€์ฒดํ•œ๋‹ค๋ฉด ์ฆ๊ฐ•
04:48
reality adds to it. Both VR and AR
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ํ˜„์‹ค์€ ์—ฌ๊ธฐ์— ์ถ”๊ฐ€๋ฉ๋‹ˆ๋‹ค. VR๊ณผ AR
04:52
are immersive experiences โ€“ they
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์€ ๋ชจ๋‘ ๋ชฐ์ž…ํ˜• ๊ฒฝํ—˜์ž…๋‹ˆ๋‹ค.
04:54
stimulate your senses and surround
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๊ฐ๊ฐ์„ ์ž๊ทนํ•˜๊ณ 
04:56
you so that you feel completely
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๊ฒฝํ—˜์— ์™„์ „ํžˆ ๋ชฐ์ž…ํ•  ์ˆ˜ ์žˆ๋„๋ก ์ฃผ๋ณ€์„ ๋‘˜๋Ÿฌ์Œ‰๋‹ˆ๋‹ค
04:58
involved in the experience.
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.
04:59
In fact, the experience feels so real
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์‚ฌ์‹ค, ๊ฒฝํ—˜์ด ๋„ˆ๋ฌด ํ˜„์‹ค์ 
05:02
that people keep coming back
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์ด์–ด์„œ ์‚ฌ๋žŒ๋“ค์ด ๋” ๋งŽ์€ ๊ฒƒ์„ ์œ„ํ•ด ๊ณ„์†ํ•ด์„œ ๋‹ค์‹œ ๋ฐฉ๋ฌธ
05:03
for more.
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ํ•ฉ๋‹ˆ๋‹ค.
05:04
Right! In my question I asked
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์˜ค๋ฅธ์ชฝ! ๋‚ด ์งˆ๋ฌธ์—์„œ
05:06
Neil how many people who try
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Neil์—๊ฒŒ VR์„ ์ฒ˜์Œ ์‹œ๋„ํ•˜๋Š” ์‚ฌ๋žŒ์ด ๋ช‡ ๋ช…์ด๋‚˜ ๋‹ค์‹œ ์‹œ๋„ํ•˜๊ณ 
05:08
VR for the first time want to try
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์‹ถ์€์ง€ ๋ฌผ์—ˆ
05:10
it again.
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์Šต๋‹ˆ๋‹ค.
05:11
I guessed it was about half โ€“
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๋‚˜๋Š” ๊ทธ๊ฒƒ์ด ์•ฝ ์ ˆ๋ฐ˜ โ€“
05:12
49 percent. Was I right?
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49 %๋ผ๊ณ  ์ƒ๊ฐํ–ˆ์Šต๋‹ˆ๋‹ค. ๋‚ด๊ฐ€ ๋งž์•˜์–ด?
05:14
You wereโ€ฆ wrong, Iโ€™m afraid.
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๋‹น์‹ ์€... ํ‹€๋ ธ์Šต๋‹ˆ๋‹ค. ์œ ๊ฐ์Šค๋Ÿฝ๊ฒŒ๋„.
05:17
The correct answer is much
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์ •๋‹ต์€ ํ›จ์”ฌ
05:18
higher - 79 percent of people
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๋†’์Šต๋‹ˆ๋‹ค. 79%์˜ ์‚ฌ๋žŒ๋“ค
05:21
would give VR another try.
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์ด VR์„ ๋‹ค์‹œ ์‹œ๋„ํ•  ๊ฒƒ์ž…๋‹ˆ๋‹ค.
05:23
I suppose because the experience
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๊ฒฝํ—˜์ด ๋„ˆ๋ฌด ๋ชฐ์ž…๊ฐ์ด ์žˆ์—ˆ๊ธฐ ๋•Œ๋ฌธ์ด๋ผ๊ณ  ์ƒ๊ฐํ•ฉ๋‹ˆ๋‹ค.
05:24
was so immersive โ€“ stimulating,
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์ž๊ทน์ ์ด๊ณ 
05:27
surrounding and realistic.
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์ฃผ๋ณ€์ ์ด๋ฉฐ ํ˜„์‹ค์ ์ž…๋‹ˆ๋‹ค.
05:29
Ok, A, letโ€™s recap the other
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์ข‹์•„, A
05:30
vocabulary from this programme
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05:32
on the โ€˜metaverseโ€™, a kind of
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, ์ผ์ข…์˜ ์ฆ๊ฐ• ํ˜„์‹ค์ธ '๋ฉ”ํƒ€๋ฒ„์Šค'์— ๋Œ€ํ•œ ์ด ํ”„๋กœ๊ทธ๋žจ์˜ ๋‹ค๋ฅธ ์–ดํœ˜๋ฅผ ์š”์•ฝํ•ด ๋ณด์ž. ๊ธฐ์ˆ 
05:34
augmented reality โ€“ reality which
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05:37
is enhanced or added to
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์— ์˜ํ•ด ๊ฐ•ํ™”๋˜๊ฑฐ๋‚˜ ์ถ”๊ฐ€๋˜๋Š” ํ˜„์‹ค์ด๋‹ค
05:38
by technology.
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.
05:40
3-D objects have three
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3์ฐจ์› ๊ฐ์ฒด๋Š” 3์ฐจ์›์„ ๊ฐ€์ง€
05:41
dimensions, making them
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05:42
appear real and solid.
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๋ฏ€๋กœ ์‹ค์ œ์ ์ด๊ณ  ์ž…์ฒด์ ์œผ๋กœ ๋ณด์ž…๋‹ˆ๋‹ค.
05:44
Phygital is an invented word
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Phygital์€
05:46
which combines the features of
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05:47
โ€˜physicalโ€™ and โ€˜digitalโ€™ worlds.
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'๋ฌผ๋ฆฌ์ ' ์„ธ๊ณ„์™€ '๋””์ง€ํ„ธ' ์„ธ๊ณ„์˜ ํŠน์ง•์„ ๊ฒฐํ•ฉํ•˜์—ฌ ๋ฐœ๋ช…ํ•œ ๋‹จ์–ด์ž…๋‹ˆ๋‹ค.
05:50
A sceptical person is doubtful
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ํšŒ์˜์ ์ธ ์‚ฌ๋žŒ์€
05:52
about something.
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๋ฌด์–ธ๊ฐ€์— ๋Œ€ํ•ด ์˜์‹ฌํ•ฉ๋‹ˆ๋‹ค.
05:53
And finally, unwieldy means
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๊ทธ๋ฆฌ๊ณ  ๋งˆ์ง€๋ง‰์œผ๋กœ ๋‹ค๋ฃจ๊ธฐ
05:55
difficult to move or carry because
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ํž˜๋“ค๋‹ค๋Š” ๊ฒƒ์€ ๋„ˆ๋ฌด ํฌ๊ณ  ๋ฌด๊ฑฐ์›Œ์„œ ์˜ฎ๊ธฐ๊ฑฐ๋‚˜ ์šด๋ฐ˜ํ•˜๊ธฐ ์–ด๋ ต๋‹ค๋Š” ๋œป
05:56
itโ€™s so big and heavy.
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์ž…๋‹ˆ๋‹ค. ์–ด์จŒ๋“ 
05:58
Thatโ€™s our six minutes up, in this
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์ด ํ˜„์‹ค์—์„œ ์šฐ๋ฆฌ์˜ 6๋ถ„
06:00
reality anyway. See you in the
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์ž…๋‹ˆ๋‹ค.
06:02
โ€˜metaverseโ€™ soon!
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๊ณง '๋ฉ”ํƒ€๋ฒ„์Šค'์—์„œ ๋งŒ๋‚˜์š”!
06:03
Goodbye!
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์•ˆ๋…•ํžˆ ๊ฐ€์„ธ์š”!
06:10
Hello. This is 6 Minute English
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์•ˆ๋…•ํ•˜์„ธ์š”. BBC Learning English์˜ 6๋ถ„ ์˜์–ด
06:12
from BBC Learning English.
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์ž…๋‹ˆ๋‹ค.
06:13
Iโ€™m Neil.
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์ €๋Š” ๋‹์ž…๋‹ˆ๋‹ค.
06:14
And Iโ€™m Sam.
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๊ทธ๋ฆฌ๊ณ  ์ €๋Š” ์ƒ˜์ž…๋‹ˆ๋‹ค.
06:15
What do shopping with a credit
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์‹ ์šฉ์นด๋“œ๋กœ ์‡ผํ•‘ํ•˜๋Š” ๊ฒƒ, ์ธํ„ฐ๋„ท ๋ฐ์ดํŠธ๋ฅผ
06:17
card, finding love through
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ํ†ตํ•ด ์‚ฌ๋ž‘์„ ์ฐพ๋Š” ๊ฒƒ,
06:18
internet dating and waiting for
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06:20
the traffic lights to change
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์‹ ํ˜ธ๋“ฑ์ด ๋ฐ”๋€Œ๊ธฐ๋ฅผ ๊ธฐ๋‹ค๋ฆฌ๋Š” ๊ฒƒ์˜
06:22
have in common?
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๊ณตํ†ต์ ์€ ๋ฌด์—‡์ผ๊นŒ์š”?
06:23
Hmmm, they all involve
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ํ , ๊ทธ๋“ค์€ ๋ชจ๋‘
06:25
computers?
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06:25
Good guess, Sam! But how
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์ปดํ“จํ„ฐ๋ฅผ ํฌํ•จํ•ฉ๋‹ˆ๊นŒ?
์ข‹์€ ์ถ”์ธก์ด์•ผ, ์ƒ˜! ๊ทธ๋Ÿฌ๋‚˜
06:27
exactly do those computers work?
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๊ทธ ์ปดํ“จํ„ฐ๋Š” ์ •ํ™•ํžˆ ์–ด๋–ป๊ฒŒ ์ž‘๋™ํ•ฉ๋‹ˆ๊นŒ?
06:29
The answer is that they all use
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๋Œ€๋‹ต์€ ๊ทธ๋“ค์ด ๋ชจ๋‘ ๋ฌธ์ œ์— ๋Œ€ํ•œ ํ•ด๊ฒฐ์ฑ…์„ ์ฐพ๋Š”
06:32
algorithms โ€“ sets of mathematical
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์ˆ˜ํ•™์  ์ง€์นจ ์„ธํŠธ์ธ ์•Œ๊ณ ๋ฆฌ์ฆ˜์„ ์‚ฌ์šฉํ•œ๋‹ค๋Š” ๊ฒƒ
06:34
instructions which find solutions
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06:36
to problems.
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์ž…๋‹ˆ๋‹ค.
06:37
Although they are often hidden,
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์ข…์ข… ์ˆจ๊ฒจ์ ธ ์žˆ์ง€๋งŒ
06:39
algorithms are all around us.
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์•Œ๊ณ ๋ฆฌ์ฆ˜์€ ์šฐ๋ฆฌ ์ฃผ๋ณ€์— ์žˆ์Šต๋‹ˆ๋‹ค.
06:41
From mobile phone maps to
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ํœด๋Œ€ํฐ ์ง€๋„์—์„œ
06:43
home delivery pizza, they play a
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ํƒ๋ฐฐ ํ”ผ์ž์— ์ด๋ฅด๊ธฐ๊นŒ์ง€
06:45
big part of modern life. And
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ํ˜„๋Œ€ ์ƒํ™œ์˜ ํฐ ๋ถ€๋ถ„์„ ์ฐจ์ง€ํ•ฉ๋‹ˆ๋‹ค. ๊ทธ๋ฆฌ๊ณ 
06:47
theyโ€™re the topic of this programme.
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๊ทธ๊ฒƒ๋“ค์ด ์ด ํ”„๋กœ๊ทธ๋žจ์˜ ์ฃผ์ œ์ž…๋‹ˆ๋‹ค.
06:49
A simple way to think of algorithms
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์•Œ๊ณ ๋ฆฌ์ฆ˜์„ ์ƒ๊ฐํ•˜๋Š” ๊ฐ„๋‹จํ•œ ๋ฐฉ๋ฒ•
06:51
is as recipes. To make pancakes
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์€ ๋ ˆ์‹œํ”ผ์ž…๋‹ˆ๋‹ค. ํŒฌ์ผ€์ดํฌ๋ฅผ ๋งŒ๋“ค๋ ค๋ฉด
06:54
you mix flour, eggs and milk, then
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๋ฐ€๊ฐ€๋ฃจ, ๊ณ„๋ž€, ์šฐ์œ ๋ฅผ ์„ž์€ ๋‹ค์Œ
06:56
melt butter in a frying pan and
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ํ”„๋ผ์ดํŒฌ์— ๋ฒ„ํ„ฐ๋ฅผ ๋…น
06:58
so on. Computers do this in more
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์ž…๋‹ˆ๋‹ค. ์ปดํ“จํ„ฐ๋Š” ์ˆ˜ํ•™ ๋ฐฉ์ •์‹
07:00
a complicated way by repeating
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์„ ๋ฐ˜๋ณตํ•ด์„œ ๋ฐ˜๋ณตํ•จ์œผ๋กœ์จ ๋ณด๋‹ค ๋ณต์žกํ•œ ๋ฐฉ์‹์œผ๋กœ ์ด ์ž‘์—…์„ ์ˆ˜ํ–‰
07:02
mathematical equations over
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07:04
and over again.
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ํ•ฉ๋‹ˆ๋‹ค.
07:06
Equations are mathematical
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๋ฐฉ์ •์‹์€
07:07
sentences showing how two
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๋‘
07:08
things are equal. Theyโ€™re similar
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๊ฐ€์ง€๊ฐ€ ์–ด๋–ป๊ฒŒ ๊ฐ™์€์ง€ ๋ณด์—ฌ์ฃผ๋Š” ์ˆ˜ํ•™ ๋ฌธ์žฅ์ž…๋‹ˆ๋‹ค. ๊ทธ๊ฒƒ๋“ค์€
07:11
to algorithms and the most famous
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์•Œ๊ณ ๋ฆฌ์ฆ˜๊ณผ ์œ ์‚ฌํ•˜๋ฉฐ ๊ฐ€์žฅ ์œ ๋ช…ํ•œ
07:13
scientific equation of all, Einstein's
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๊ณผํ•™์  ๋ฐฉ์ •์‹์ธ ์•„์ธ์Šˆํƒ€์ธ์˜
07:15
E=MC2, can be thought of as a
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E=MC2๋Š” ์„ธ ๋ถ€๋ถ„์œผ๋กœ ๊ตฌ์„ฑ๋œ ์•Œ๊ณ ๋ฆฌ์ฆ˜์œผ๋กœ ์ƒ๊ฐํ•  ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค
07:19
three-part algorithm.
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.
07:21
But before my brain gets squashed
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ํ•˜์ง€๋งŒ ์ด ๋ชจ๋“  ์ˆ˜ํ•™ ๋•Œ๋ฌธ์— ๋‚ด ๋‘๋‡Œ๊ฐ€ ์ฐŒ๊ทธ๋Ÿฌ์ง€๊ธฐ ์ „์—
07:23
by all this maths, I have a quiz
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07:25
question for you, Sam. As you know,
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, Sam, ๋‹น์‹ ์—๊ฒŒ ์ค„ ํ€ด์ฆˆ ์งˆ๋ฌธ์ด ์žˆ์Šต๋‹ˆ๋‹ค. ์•„์‹œ๋‹ค์‹œํ”ผ
07:27
Einsteinโ€™s famous equation is
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์•„์ธ์Šˆํƒ€์ธ์˜ ์œ ๋ช…ํ•œ ๋ฐฉ์ •์‹์€
07:29
E=MC2 - but what does the
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E=MC2์ž…๋‹ˆ๋‹ค. ๊ทธ๋Ÿฐ๋ฐ
07:32
โ€˜Eโ€™ stand for? Is it:
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'E'๋Š” ๋ฌด์—‡์„ ์˜๋ฏธํ•ฉ๋‹ˆ๊นŒ?
07:33
a) electricity?
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a) ์ „๊ธฐ?
07:35
b) energy? or
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b) ์—๋„ˆ์ง€? ๋˜๋Š”
07:37
c) everything?
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c) ๋ชจ๋“  ๊ฒƒ?
07:38
Iโ€™m tempted to say โ€˜Eโ€™ is for
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๋‚˜๋Š” 'E'๊ฐ€
07:40
โ€˜everythingโ€™ but I reckon I know
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'๋ชจ๋“  ๊ฒƒ'์„ ์˜๋ฏธํ•œ๋‹ค๊ณ  ๋งํ•˜๊ณ  ์‹ถ์ง€๋งŒ ๋‹ต์„ ์•Œ๊ณ  ์žˆ๋‹ค๊ณ  ์ƒ๊ฐ
07:42
the answer: b โ€“ โ€˜Eโ€™ stands
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ํ•ฉ๋‹ˆ๋‹ค. b โ€“ 'E'
07:44
for โ€˜energyโ€™.
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๋Š” '์—๋„ˆ์ง€'๋ฅผ ์˜๋ฏธํ•ฉ๋‹ˆ๋‹ค.
07:45
OK, Sam, weโ€™ll find out if youโ€™re
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์ข‹์•„์š”, ์ƒ˜, ๋‚˜์ค‘์— ํ”„๋กœ๊ทธ๋žจ์—์„œ ๋‹น์‹ ์ด ์˜ณ์€์ง€ ์•Œ์•„๋‚ผ ๊ฒƒ
07:46
right later in the programme.
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์ž…๋‹ˆ๋‹ค.
07:48
With all this talk of computers, you
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์ปดํ“จํ„ฐ์— ๋Œ€ํ•œ ์ด ๋ชจ๋“  ์ด์•ผ๊ธฐ์—์„œ
07:50
might think algorithms are a
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์•Œ๊ณ ๋ฆฌ์ฆ˜์ด ์ƒˆ๋กœ์šด ์•„์ด๋””์–ด๋ผ๊ณ  ์ƒ๊ฐํ•  ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค
07:51
new idea. In fact, theyโ€™ve been
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. ์‚ฌ์‹ค ๊ทธ๋“ค์€
07:54
around since Babylonian times,
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์•ฝ 4,000๋…„ ์ „์ธ ๋ฐ”๋นŒ๋กœ๋‹ˆ์•„ ์‹œ๋Œ€๋ถ€ํ„ฐ ์กด์žฌํ•ด ์™”์Šต๋‹ˆ๋‹ค
07:56
around 4,000 years ago.
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.
07:58
And their use today can be
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๊ทธ๋ฆฌ๊ณ  ์˜ค๋Š˜๋‚  ๊ทธ๋“ค์˜ ์‚ฌ์šฉ์€
07:59
controversial. Some algorithms
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๋…ผ๋ž€์˜ ์—ฌ์ง€๊ฐ€ ์žˆ์Šต๋‹ˆ๋‹ค.
08:01
used in internet search engines
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์ธํ„ฐ๋„ท ๊ฒ€์ƒ‰ ์—”์ง„์— ์‚ฌ์šฉ๋˜๋Š” ์ผ๋ถ€ ์•Œ๊ณ ๋ฆฌ์ฆ˜
08:03
have been accused of
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์€ ์ธ์ข…์  ํŽธ๊ฒฌ์œผ๋กœ ๊ณ ๋ฐœ๋˜์—ˆ์Šต๋‹ˆ๋‹ค
08:04
racial prejudice.
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.
08:06
Ramesh Srinivasan is Professor
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Ramesh Srinivasan์€ University of California
08:08
of Information Studies at the
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์˜ ์ •๋ณดํ•™ ๊ต์ˆ˜์ž…๋‹ˆ๋‹ค
08:09
University of California. Hereโ€™s what
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. ๋‹ค์Œ
08:12
he said when asked what the word
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08:13
โ€˜algorithmโ€™ actually means by
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์€
08:15
BBC World Serviceโ€™s programme,
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BBC World Service์˜ ํ”„๋กœ๊ทธ๋žจ์ธ
08:17
The Forum:
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The Forum์—์„œ '
08:20
My understanding of the term
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08:22
โ€˜algorithmโ€™ is that itโ€™s not necessarily
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์•Œ๊ณ ๋ฆฌ์ฆ˜'์ด๋ผ๋Š” ๋‹จ์–ด๊ฐ€ ์‹ค์ œ๋กœ ๋ฌด์—‡์„ ์˜๋ฏธ
08:24
the bogyman, or its not necessarily
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ํ•˜๋Š”์ง€ ๋ฌผ์—ˆ์„ ๋•Œ ๊ทธ๊ฐ€ ๋งํ•œ ๋‚ด์šฉ์ž…๋‹ˆ๋‹ค.
08:27
something that is, you know, inscrutable
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08:29
or mysterious to all people โ€“ itโ€™s the
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๋ชจ๋“  ์‚ฌ๋žŒ์—๊ฒŒ ๋ถˆ๊ฐ€ํ•ดํ•˜๊ฑฐ๋‚˜ ๋ถˆ๊ฐ€์‚ฌ์˜ํ•œ ๊ฒƒ โ€“ ๊ทธ๊ฒƒ์€
08:31
set of instructions that you write in
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๋‹น์‹ ์ด
08:35
some mathematical form or in
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์–ด๋–ค ์ˆ˜ํ•™์  ํ˜•์‹์ด๋‚˜
08:37
some software code โ€“ so itโ€™s the
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์–ด๋–ค ์†Œํ”„ํŠธ์›จ์–ด ์ฝ”๋“œ๋กœ ์ž‘์„ฑํ•˜๋Š” ์ผ๋ จ์˜ ์ง€์นจ์ž…๋‹ˆ๋‹ค โ€“ ๋”ฐ๋ผ์„œ
08:39
repeated set of instructions that
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08:41
are sequenced, that are used and
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08:44
applied to answer a question or
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์งˆ๋ฌธ์— ๋‹ตํ•˜๊ฑฐ๋‚˜
08:46
resolve a problem โ€“ itโ€™s a simple
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๋ฌธ์ œ๋ฅผ ํ•ด๊ฒฐํ•˜๊ธฐ ์œ„ํ•ด ์‚ฌ์šฉ ๋ฐ ์ ์šฉ๋˜๋Š” ๋ฐ˜๋ณต๋˜๋Š” ์ผ๋ จ์˜ ์ง€์นจ์ž…๋‹ˆ๋‹ค โ€“
08:48
as that, actually.
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์‹ค์ œ๋กœ ๊ทธ๋ ‡๊ฒŒ ๊ฐ„๋‹จํ•ฉ๋‹ˆ๋‹ค.
08:51
Some think that algorithms have
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์ผ๋ถ€์—์„œ๋Š” ์•Œ๊ณ ๋ฆฌ์ฆ˜
08:52
been controversial, but Professor
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์ด ๋…ผ๋ž€์˜ ์—ฌ์ง€๊ฐ€ ์žˆ๋‹ค๊ณ  ์ƒ๊ฐํ•˜์ง€๋งŒ
08:54
Srinivasan says they are not
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Srinivasan ๊ต์ˆ˜๋Š” ๊ทธ๋“ค์ด ๋ฐ˜๋“œ์‹œ bogyman์€ ์•„๋‹ˆ๋ผ๊ณ  ๋งํ•ฉ๋‹ˆ๋‹ค
08:56
necessarily the bogyman. The
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.
08:58
bogyman refers to something
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bogyman์€
09:00
people call โ€˜badโ€™ or โ€˜evilโ€™ to make
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์‚ฌ๋žŒ๋“ค์ด ๋‹ค๋ฅธ ์‚ฌ๋žŒ๋“ค์„ ๋‘๋ ค์›Œํ•˜๊ฒŒ ๋งŒ๋“œ๋Š” '๋‚˜์œ'๋˜๋Š” '์•…'์ด๋ผ๊ณ  ๋ถ€๋ฅด๋Š” ๊ฒƒ์„ ๋งํ•ฉ๋‹ˆ๋‹ค
09:03
other people afraid.
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.
09:04
Professor Srinivasan thinks
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Srinivasan ๊ต์ˆ˜
09:06
algorithms are neither evil nor
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๋Š” ์•Œ๊ณ ๋ฆฌ์ฆ˜์ด ์‚ฌ์•…ํ•˜๊ฑฐ๋‚˜ ๋ถˆ๊ฐ€ํ•ดํ•˜์ง€๋„ ์•Š๋‹ค๊ณ  ์ƒ๊ฐํ•ฉ๋‹ˆ๋‹ค.
09:08
inscrutable โ€“ not showing emotions
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๊ฐ์ •
09:11
or thoughts and therefore very
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์ด๋‚˜ ์ƒ๊ฐ์„ ๋‚˜ํƒ€๋‚ด์ง€ ์•Š๊ธฐ ๋•Œ๋ฌธ์—
09:13
difficult to understand.
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์ดํ•ดํ•˜๊ธฐ๊ฐ€ ๋งค์šฐ ์–ด๋ ต์Šต๋‹ˆ๋‹ค.
09:14
Still, it can be difficult to understand
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ํ•˜์ง€๋งŒ
09:16
exactly what algorithms are,
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์•Œ๊ณ ๋ฆฌ์ฆ˜์ด ๋ฌด์—‡์ธ์ง€ ์ •ํ™•ํžˆ ์ดํ•ดํ•˜๋Š” ๊ฒƒ์€ ์–ด๋ ค์šธ ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค.
09:18
especially when there are many
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ํŠนํžˆ ๋‹ค์–‘ํ•œ ์œ ํ˜•์ด ์žˆ๋Š” ๊ฒฝ์šฐ์—๋Š” ๋”์šฑ ๊ทธ๋ ‡์Šต๋‹ˆ๋‹ค
09:20
different types of them. So, letโ€™s
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.
09:22
take an example.
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์˜ˆ๋ฅผ ๋“ค์–ด ๋ณด๊ฒ ์Šต๋‹ˆ๋‹ค.
09:23
Itโ€™s autumn and we want to
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์ง€๊ธˆ์€ ๊ฐ€์„์ด๊ณ 
09:24
collect all the apples from our
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์šฐ๋ฆฌ ๊ณผ์ˆ˜์›์—์„œ ๋ชจ๋“  ์‚ฌ๊ณผ๋ฅผ ๋ชจ์•„
09:26
orchard and divide them into
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09:27
three groups โ€“ big, medium
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๋Œ€, ์ค‘, ์†Œ์˜ ์„ธ ๊ทธ๋ฃน์œผ๋กœ ๋‚˜๋ˆ„๊ณ  ์‹ถ์Šต๋‹ˆ๋‹ค
09:30
and small. One method is to
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. ํ•œ ๊ฐ€์ง€ ๋ฐฉ๋ฒ•์€
09:32
collect all the apples together
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๋ชจ๋“  ์‚ฌ๊ณผ๋ฅผ ํ•จ๊ป˜ ๋ชจ์•„
09:33
and compare their sizes.
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ํฌ๊ธฐ๋ฅผ ๋น„๊ตํ•˜๋Š” ๊ฒƒ์ž…๋‹ˆ๋‹ค.
09:35
But doing this would take hours!
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ํ•˜์ง€๋งŒ ์ด๋ ‡๊ฒŒ ํ•˜๋ฉด ๋ช‡ ์‹œ๊ฐ„์ด ๊ฑธ๋ฆด ๊ฒƒ์ž…๋‹ˆ๋‹ค!
09:37
Itโ€™s much easier to first collect
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๋จผ์ €
09:39
the apples from only one tree -
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ํ•˜๋‚˜์˜ ๋‚˜๋ฌด์—์„œ๋งŒ ์‚ฌ๊ณผ๋ฅผ ์ˆ˜์ง‘ํ•˜์—ฌ
09:41
divide those into big, medium
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ํฐ ๊ฒƒ, ์ค‘๊ฐ„ ๊ฒƒ
09:43
or small โ€“ and then repeat the
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๋˜๋Š” ์ž‘์€ ๊ฒƒ์œผ๋กœ ๋‚˜๋ˆˆ ๋‹ค์Œ
09:45
process for the other trees,
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๋‹ค๋ฅธ ๋‚˜๋ฌด์— ๋Œ€ํ•ด
09:47
one by one.
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ํ•˜๋‚˜์”ฉ ํ”„๋กœ์„ธ์Šค๋ฅผ ๋ฐ˜๋ณตํ•˜๋Š” ๊ฒƒ์ด ํ›จ์”ฌ ์‰ฝ์Šต๋‹ˆ๋‹ค.
09:48
Thatโ€™s basically what algorithms
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์ด๊ฒƒ์ด ๊ธฐ๋ณธ์ ์œผ๋กœ ์•Œ๊ณ ๋ฆฌ์ฆ˜์ด ํ•˜๋Š”
09:50
do โ€“ they find the most efficient
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์ผ์ž…๋‹ˆ๋‹ค. ๊ทธ๋“ค์€ ์ž‘์—…์„ ์ˆ˜ํ–‰ํ•˜๋Š” ๊ฐ€์žฅ ํšจ์œจ์ ์ธ ๋ฐฉ๋ฒ•์„ ์ฐพ์Šต๋‹ˆ๋‹ค.
09:52
way to get things done, or in other
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09:54
words, get the best results in the
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์ฆ‰, ๊ฐ€์žฅ ๋น ๋ฅธ ์‹œ๊ฐ„์— ์ตœ์ƒ์˜ ๊ฒฐ๊ณผ๋ฅผ ์–ป
09:56
quickest time.
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์Šต๋‹ˆ๋‹ค.
09:57
Mathematics professor Ian
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์ˆ˜ํ•™ ๊ต์ˆ˜ Ian
09:59
Stewart agrees. Listen as he
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Stewart๋„ ์ด์— ๋™์˜ํ•ฉ๋‹ˆ๋‹ค. ๊ทธ๊ฐ€
10:01
explains how the algorithm called
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10:03
โ€˜bubble sortโ€™ works to BBC World
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'๋ฒ„๋ธ” ์ •๋ ฌ'์ด๋ผ๋Š” ์•Œ๊ณ ๋ฆฌ์ฆ˜์ด BBC World
10:06
Serviceโ€™s programme, The Forum:
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Service์˜ ํ”„๋กœ๊ทธ๋žจ์ธ The Forum์—์„œ ์–ด๋–ป๊ฒŒ ์ž‘๋™ํ•˜๋Š”์ง€ ์„ค๋ช…ํ•˜๋Š” ๊ฒƒ์„ ๋“ค์–ด
10:10
Think of when your computer is
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๋ณด์„ธ์š”. ์ปดํ“จํ„ฐ๊ฐ€
10:11
sorting emails by date and maybe
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์ด๋ฉ”์ผ์„ ๋‚ ์งœ์ˆœ
10:13
youโ€™ve got 500 emails and it sorts
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์œผ๋กœ ์ •๋ ฌํ•˜๊ณ  500๊ฐœ์˜ ์ด๋ฉ”์ผ์ด ์žˆ์„
10:15
them by date in a flash.
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๋•Œ ์ˆœ์‹๊ฐ„์— ๋‚ ์งœ์ˆœ์œผ๋กœ ์ •๋ ฌํ•œ๋‹ค๊ณ  ์ƒ๊ฐํ•ด ๋ณด์„ธ์š”.
10:16
Now it doesnโ€™t use bubble sort,
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์ด์ œ ๋ฒ„๋ธ” ์ •๋ ฌ์„
10:18
but it does use a sorting method
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์‚ฌ์šฉํ•˜์ง€ ์•Š์ง€๋งŒ ์ •๋ ฌ ๋ฐฉ๋ฒ•์„ ์‚ฌ์šฉํ•˜๊ณ 
10:20
and if you tried to do that by hand
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์†์œผ๋กœ ์ •๋ ฌํ•˜๋ ค๊ณ  ํ•˜๋ฉด ์–ด๋–ค ๋ฐฉ๋ฒ•์„ ์‚ฌ์šฉ
10:22
it would take you a very long time,
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ํ•˜๋“  ์‹œ๊ฐ„์ด ์˜ค๋ž˜ ๊ฑธ๋ฆฝ๋‹ˆ๋‹ค
10:23
whatever method you used.
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.
10:27
Professor Stewart describes how
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Stewart ๊ต์ˆ˜๋Š”
10:29
algorithms sort emails. To sort is a
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์•Œ๊ณ ๋ฆฌ์ฆ˜์ด ์ด๋ฉ”์ผ์„ ๋ถ„๋ฅ˜ํ•˜๋Š” ๋ฐฉ๋ฒ•์„ ์„ค๋ช…ํ•ฉ๋‹ˆ๋‹ค. ์ •๋ ฌ์€ ์œ ์‚ฌ์„ฑ์„ ๊ณต์œ 
10:32
verb meaning to group together
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ํ•˜๋Š” ํ•ญ๋ชฉ์„ ํ•จ๊ป˜ ๊ทธ๋ฃนํ™”ํ•˜๋Š” ๊ฒƒ์„ ์˜๋ฏธํ•˜๋Š” ๋™์‚ฌ
10:33
things which share similarities.
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์ž…๋‹ˆ๋‹ค.
10:35
Just like grouping the apples by
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์‚ฌ๊ณผ๋ฅผ ํฌ๊ธฐ๋ณ„๋กœ ๊ทธ๋ฃนํ™”ํ•˜๋Š” ๊ฒƒ์ฒ˜๋Ÿผ
10:37
size, sorting hundreds of emails
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์ˆ˜๋ฐฑ ๊ฐœ์˜ ์ด๋ฉ”์ผ
10:39
by hand would take a long time.
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์„ ์†์œผ๋กœ ๋ถ„๋ฅ˜ํ•˜๋ ค๋ฉด ์‹œ๊ฐ„์ด ์˜ค๋ž˜ ๊ฑธ๋ฆฝ๋‹ˆ๋‹ค.
10:42
But using algorithms, computers
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๊ทธ๋Ÿฌ๋‚˜ ์•Œ๊ณ ๋ฆฌ์ฆ˜์„ ์‚ฌ์šฉํ•˜์—ฌ ์ปดํ“จํ„ฐ
10:44
do it in a flash โ€“ very quickly or
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๋Š” ๋งค์šฐ ๋น ๋ฅด๊ฒŒ ๋˜๋Š”
10:46
suddenly.
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๊ฐ‘์ž๊ธฐ ์ˆœ์‹๊ฐ„์— ์ž‘์—…์„ ์ˆ˜ํ–‰ํ•ฉ๋‹ˆ๋‹ค.
10:47
That phrase โ€“ in a flash โ€“ reminds
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์ด ๋ฌธ๊ตฌ๋Š” ์ˆœ์‹๊ฐ„์—
10:49
me of how Albert Einstein came up
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์•Œ๋ฒ„ํŠธ ์•„์ธ์Šˆํƒ€์ธ
10:51
with his famous equation, E=MC2.
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์ด ๊ทธ์˜ ์œ ๋ช…ํ•œ ๋ฐฉ์ •์‹์ธ E=MC2๋ฅผ ์ƒ๊ฐํ•ด๋‚ธ ๋ฐฉ๋ฒ•์„ ์ƒ๊ฐ๋‚˜๊ฒŒ ํ•ฉ๋‹ˆ๋‹ค.
10:55
And that reminds me of your quiz
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๊ทธ๋ฆฌ๊ณ  ๊ทธ๊ฒƒ์€ ๋‹น์‹ ์˜ ํ€ด์ฆˆ ์งˆ๋ฌธ์„ ์ƒ๊ฐ๋‚˜๊ฒŒ ํ•ฉ๋‹ˆ๋‹ค
10:57
question. You asked about the โ€˜Eโ€™
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.
11:00
in E=MC2. I said it stands for โ€˜energyโ€™.
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E=MC2์—์„œ 'E'์— ๋Œ€ํ•ด ์งˆ๋ฌธํ•˜์…จ์Šต๋‹ˆ๋‹ค. ๋‚˜๋Š” ๊ทธ๊ฒƒ์ด '์—๋„ˆ์ง€'๋ฅผ ์˜๋ฏธํ•œ๋‹ค๊ณ  ๋งํ–ˆ๋‹ค.
11:04
So, was I right?
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๊ทธ๋ž˜์„œ, ๋‚ด๊ฐ€ ๋งž์•˜์–ด?
11:05
โ€˜Energyโ€™ is the correct answer.
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์ •๋‹ต์€ '์—๋„ˆ์ง€'์ž…๋‹ˆ๋‹ค.
11:08
Energy equals โ€˜Mโ€™ for mass,
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์—๋„ˆ์ง€๋Š” ์งˆ๋Ÿ‰์˜ 'M'์— ๋น›์˜ ์†๋„์ธ
11:10
multiplied by the Constant โ€˜Cโ€™ which
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์ƒ์ˆ˜ 'C'๋ฅผ ๊ณฑํ•œ ๊ฐ’๊ณผ ๊ฐ™์Šต๋‹ˆ๋‹ค
11:12
is the speed of light, squared.
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.
11:15
OK, letโ€™s recap the vocabulary from
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์ข‹์•„, ๋ฐฉ์ •์‹
11:17
this programme, starting with
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์œผ๋กœ ์‹œ์ž‘ํ•˜์—ฌ ์ด ํ”„๋กœ๊ทธ๋žจ์˜ ์–ดํœ˜๋ฅผ ์š”์•ฝํ•ด ๋ณด์ž.
11:19
equation โ€“ a mathematical statement
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11:21
using symbols to show two
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๋‘ ๊ฐœ์˜ ๋™์ผํ•œ ๊ฒƒ์„ ๋ณด์—ฌ์ฃผ๊ธฐ ์œ„ํ•ด ๊ธฐํ˜ธ๋ฅผ ์‚ฌ์šฉํ•˜๋Š” ์ˆ˜ํ•™์  ์ง„์ˆ 
11:23
equal things.
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์ด๋‹ค.
11:24
If something is called a bogyman,
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bogyman์ด๋ผ๊ณ  ๋ถˆ๋ฆฌ๋Š” ๊ฒƒ์€
11:26
itโ€™s something considered bad
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11:28
and to be feared.
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๋‚˜์œ ๊ฒƒ์œผ๋กœ ๊ฐ„์ฃผ๋˜๊ณ  ๋‘๋ ค์›Œํ•˜๋Š” ๊ฒƒ์ž…๋‹ˆ๋‹ค.
11:29
Inscrutable people donโ€™t show
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๋ถˆ๊ฐ€ํ•ดํ•œ ์‚ฌ๋žŒ๋“ค์€
11:31
their emotions so are very difficult
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์ž์‹ ์˜ ๊ฐ์ •์„ ๋“œ๋Ÿฌ๋‚ด์ง€ ์•Š๊ธฐ ๋•Œ๋ฌธ์— ์•Œ๊ธฐ๊ฐ€ ๋งค์šฐ ์–ด๋ ต
11:33
to get to know.
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์Šต๋‹ˆ๋‹ค.
11:34
Efficient means working quickly
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ํšจ์œจ์ ์ด๋ž€ ์กฐ์ง์ ์ธ ๋ฐฉ์‹์œผ๋กœ ๋น ๋ฅด๊ณ  ํšจ๊ณผ์ ์œผ๋กœ ์ž‘์—…ํ•˜๋Š” ๊ฒƒ์„ ์˜๋ฏธ
11:36
and effectively in an
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11:37
organised way.
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ํ•ฉ๋‹ˆ๋‹ค.
11:38
The verb to sort means to group
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์ •๋ ฌํ•˜๋‹ค๋ผ๋Š” ๋™์‚ฌ๋Š” ์œ ์‚ฌ์„ฑ
11:40
together things which
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์„ ๊ณต์œ ํ•˜๋Š” ๊ฒƒ์„ ํ•จ๊ป˜ ๊ทธ๋ฃนํ™”ํ•˜๋Š” ๊ฒƒ์„ ์˜๋ฏธํ•ฉ๋‹ˆ๋‹ค
11:41
share similarities.
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.
11:43
And finally, if something happens
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๊ทธ๋ฆฌ๊ณ  ๋งˆ์ง€๋ง‰์œผ๋กœ ์–ด๋–ค ์ผ
11:44
in a flash, it happens quickly
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์ด ์ˆœ์‹๊ฐ„์— ์ผ์–ด๋‚œ๋‹ค๋ฉด ๊ทธ๊ฒƒ์€ ๋น ๋ฅด๊ฒŒ
11:47
or suddenly.
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๋˜๋Š” ๊ฐ‘์ž๊ธฐ ์ผ์–ด๋‚ฉ๋‹ˆ๋‹ค.
11:48
Thatโ€™s all the time we have to
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์šฐ๋ฆฌ๊ฐ€ ์•Œ๊ณ ๋ฆฌ์ฆ˜์— ๋Œ€ํ•ด ๋…ผ์˜ํ•ด์•ผ ํ•˜๋Š” ๋ชจ๋“  ์‹œ๊ฐ„
11:49
discuss algorithms. And if
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์ž…๋‹ˆ๋‹ค.
11:51
youโ€™re still not 100% sure about
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์•„์ง ์ •ํ™•ํžˆ ๋ฌด์—‡์ธ์ง€ 100% ํ™•์‹ ํ•˜์ง€ ๋ชปํ•œ๋‹ค๋ฉด
11:53
exactly what they are, we hope
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11:55
at least youโ€™ve learned some
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์ ์–ด๋„ ์œ ์šฉํ•œ ์–ดํœ˜๋ฅผ ๋ฐฐ์› ๊ธฐ๋ฅผ ๋ฐ”๋ž๋‹ˆ๋‹ค
11:56
useful vocabulary!
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! BBC Learning English์˜ 6๋ถ„ ์˜์–ด์—์„œ
11:57
Join us again soon for more
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๋” ๋งŽ์€
11:58
trending topics, sensational
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์ตœ์‹  ์ฃผ์ œ, ๋†€๋ผ์šด
12:00
science and useful vocabulary
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๊ณผํ•™ ๋ฐ ์œ ์šฉํ•œ ์–ดํœ˜๋ฅผ ์œ„ํ•ด ๊ณง ๋‹ค์‹œ ์ฐธ์—ฌํ•˜์„ธ์š”
12:02
here at 6 Minute English from
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12:04
BBC Learning English.
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.
12:05
Bye for now!
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์ง€๊ธˆ์€ ์•ˆ๋…•!
12:06
Goodbye!
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์•ˆ๋…•ํžˆ ๊ฐ€์„ธ์š”!
12:13
Hello. This is 6 Minute English
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์•ˆ๋…•ํ•˜์„ธ์š”. BBC Learning English์˜ 6๋ถ„ ์˜์–ด
12:14
from BBC Learning English.
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์ž…๋‹ˆ๋‹ค.
12:16
Iโ€™m Neil.
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์ €๋Š” ๋‹์ž…๋‹ˆ๋‹ค.
12:17
And Iโ€™m Sam.
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๊ทธ๋ฆฌ๊ณ  ์ €๋Š” ์ƒ˜์ž…๋‹ˆ๋‹ค.
12:19
In recent years, many people
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์ตœ๊ทผ ๋ช‡ ๋…„ ๋™์•ˆ ๋งŽ์€ ์‚ฌ๋žŒ๋“ค
12:20
have wanted to find out more
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์ด
12:22
about where they come from.
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์ž์‹ ์ด ์–ด๋””์—์„œ ์™”๋Š”์ง€ ๋” ์•Œ๊ณ  ์‹ถ์–ดํ–ˆ์Šต๋‹ˆ๋‹ค.
12:24
Millions have tried to trace
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์ˆ˜๋ฐฑ๋งŒ ๋ช…์ด
12:25
their family history and discover
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๊ทธ๋“ค์˜ ๊ฐ€์กฑ ์—ญ์‚ฌ๋ฅผ ์ถ”์ ํ•˜๊ณ 
12:27
how their ancestors lived
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๊ทธ๋“ค์˜ ์กฐ์ƒ์ด ์ˆ˜๋ฐฑ ๋…„ ์ „์— ์–ด๋–ป๊ฒŒ ์‚ด์•˜๋Š”์ง€ ์•Œ์•„๋‚ด๋ ค๊ณ  ๋…ธ๋ ฅํ–ˆ์Šต๋‹ˆ๋‹ค
12:28
hundreds of years ago.
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.
12:30
The internet has made it much
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์ธํ„ฐ๋„ท์€ ๊ฐ€์กฑ ์—ญ์‚ฌ์— ๊ด€ํ•œ
12:32
easier to find historical
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์—ญ์‚ฌ์  ๋ฌธ์„œ์™€ ๊ธฐ๋ก์„ ํ›จ์”ฌ ๋” ์‰ฝ๊ฒŒ ์ฐพ์„ ์ˆ˜ ์žˆ๊ฒŒ ํ•ด
12:33
documents and records about
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12:35
your family history - and one of
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12:37
the most useful documents for
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12:39
doing this is the census.
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์ฃผ์—ˆ์œผ๋ฉฐ ์ด๋ฅผ ์œ„ํ•œ ๊ฐ€์žฅ ์œ ์šฉํ•œ ๋ฌธ์„œ ์ค‘ ํ•˜๋‚˜๋Š” ์ธ๊ตฌ ์กฐ์‚ฌ์ž…๋‹ˆ๋‹ค.
12:42
A census is an official count of all
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์ธ๊ตฌ ์กฐ์‚ฌ๋Š”
12:45
the people living in a country.
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ํ•œ ๊ตญ๊ฐ€์— ์‚ด๊ณ  ์žˆ๋Š” ๋ชจ๋“  ์‚ฌ๋žŒ๋“ค์˜ ๊ณต์‹ ์ง‘๊ณ„์ž…๋‹ˆ๋‹ค.
12:46
It collects information about a
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๊ตญ๊ฐ€์˜ ์ธ๊ตฌ์— ๋Œ€ํ•œ ์ •๋ณด๋ฅผ ์ˆ˜์ง‘
12:48
countryโ€™s population and is usually
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ํ•˜๋ฉฐ ์ผ๋ฐ˜์ 
12:50
carried out by the government.
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์œผ๋กœ ์ •๋ถ€์—์„œ ์ˆ˜ํ–‰ํ•ฉ๋‹ˆ๋‹ค.
12:52
In Britain, a census has been
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์˜๊ตญ์—์„œ๋Š” 1801
12:54
carried out every ten years
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๋…„๋ถ€ํ„ฐ 10๋…„๋งˆ๋‹ค ์ธ๊ตฌ ์กฐ์‚ฌ๋ฅผ ์‹ค์‹œํ•˜๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค
12:56
since 1801. In 2002, when
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. 2002
13:00
census records from a hundred
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๋…„์—๋Š” 100๋…„ ์ „์˜ ์ธ๊ตฌ ์กฐ์‚ฌ ๊ธฐ๋ก
13:02
years before became available
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์ด
13:04
online, so many people rushed
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์˜จ๋ผ์ธ์— ๊ณต๊ฐœ๋˜์—ˆ์„ ๋•Œ ๋„ˆ๋ฌด ๋งŽ์€ ์‚ฌ๋žŒ๋“ค
13:06
to their computers to access
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์ด ์ปดํ“จํ„ฐ์— ์ ‘์†ํ•˜๊ธฐ ์œ„ํ•ด
13:07
them that the website crashed!
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๋ชฐ๋ ค๋“ค์–ด์„œ ์›น ์‚ฌ์ดํŠธ๊ฐ€ ๋‹ค์šด๋˜์—ˆ์Šต๋‹ˆ๋‹ค!
13:10
But before we find out more
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ํ•˜์ง€๋งŒ
13:12
about the census and its related
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์ธ๊ตฌ ์กฐ์‚ฌ ๋ฐ ๊ด€๋ จ ์–ดํœ˜์— ๋Œ€ํ•ด ์ž์„ธํžˆ ์•Œ์•„๋ณด๊ธฐ ์ „์—
13:13
vocabulary itโ€™s time for a quiz
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ํ€ด์ฆˆ ์งˆ๋ฌธ์„ ํ•  ์‹œ๊ฐ„์ž…๋‹ˆ๋‹ค
13:15
question, Sam. Someone who
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, Sam.
13:18
knows a lot about his family
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๊ทธ์˜ ๊ฐ€์กฑ์‚ฌ๋ฅผ ์ž˜ ์•„๋Š” ์‚ฌ๋žŒ
13:19
history is British actor, Danny
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์€ ์˜๊ตญ ๋ฐฐ์šฐ ๋Œ€๋‹ˆ
13:21
Dyer. When BBC television
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๋‹ค์ด์–ด๋‹ค. BBC TV
13:24
programme, Who Do You
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ํ”„๋กœ๊ทธ๋žจ์—์„œ
13:25
Think You Are? researched
402
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๋‹น์‹ ์€ ๋ˆ„๊ตฌ๋ผ๊ณ  ์ƒ๊ฐํ•ฉ๋‹ˆ๊นŒ?
13:26
his family history they discovered
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๊ทธ์˜ ๊ฐ€์กฑ์‚ฌ๋ฅผ ์กฐ์‚ฌํ•œ ๊ฒฐ๊ณผ
13:28
that the actor was related to
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๋ฐฐ์šฐ๊ฐ€ ๋งค์šฐ ์œ ๋ช…ํ•œ ์‚ฌ๋žŒ๊ณผ ๊ด€๋ จ์ด ์žˆ๋‹ค๋Š” ๊ฒƒ์„ ๋ฐœ๊ฒฌํ–ˆ์Šต๋‹ˆ๋‹ค.
13:30
someone very famous โ€“ but
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ํ•˜์ง€๋งŒ
13:32
who was it?
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๋ˆ„๊ตฌ์˜€์Šต๋‹ˆ๊นŒ?
13:33
A) King Edward III,
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2080
A) King Edward III,
13:35
B) William Shakespeare, or,
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2080
B) William Shakespeare, ๋˜๋Š”
13:37
C) Winston Churchill?
409
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2080
C) Winston Churchill?
13:39
Well, I know Danny Dyer usually
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๊ธ€์Ž„์š”, Danny Dyer๊ฐ€ ๋ณดํ†ต
13:42
plays tough-guy characters so
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ํ„ฐํ”„๊ฐ€์ด ์บ๋ฆญํ„ฐ๋ฅผ
13:44
maybe itโ€™s
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์—ฐ๊ธฐํ•œ๋‹ค๋Š” ๊ฒƒ์„ ์•Œ๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค.
13:45
C), war hero Winston Churchill?
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C), ์ „์Ÿ ์˜์›… Winston Churchill?
13:48
OK, Sam, weโ€™ll find out later if
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์ข‹์•„, ์ƒ˜, ๊ทธ๊ฒŒ ๋งž๋Š”์ง€ ๋‚˜์ค‘์— ์•Œ์•„๋ณด์ž
13:50
thatโ€™s correct. Now, although
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. ์ง€๊ธˆ
13:52
the first British census took
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์€ ์ตœ์ดˆ์˜ ์˜๊ตญ ์ธ๊ตฌ ์กฐ์‚ฌ
13:54
place in 1801, other censuses
417
834480
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๊ฐ€ 1801๋…„์— ์‹ค์‹œ๋˜์—ˆ์ง€๋งŒ ๋‹ค๋ฅธ ์ธ๊ตฌ ์กฐ์‚ฌ
13:57
have a much longer history.
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๋Š” ํ›จ์”ฌ ๋” ๊ธด ์—ญ์‚ฌ๋ฅผ ๊ฐ€์ง€๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค.
13:59
In fact, the bible story of Mary
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์‚ฌ์‹ค, ๋ฒ ๋“ค๋ ˆํ—ด์œผ๋กœ ์—ฌํ–‰ํ•˜๋Š” ๋งˆ๋ฆฌ์•„์™€ ์š”์…‰์˜ ์„ฑ์„œ ์ด์•ผ๊ธฐ๋Š”
14:01
and Joseph travelling to
420
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1200
14:02
Bethlehem is linked to a
421
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1440
14:04
Roman census.
422
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๋กœ๋งˆ ์ธ๊ตฌ ์กฐ์‚ฌ์™€ ์—ฐ๊ฒฐ๋˜์–ด ์žˆ์Šต๋‹ˆ๋‹ค.
14:06
So, what was the original
423
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๊ทธ๋ ‡๋‹ค๋ฉด
14:08
reason for counting people
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์‚ฌ๋žŒ ์ˆ˜๋ฅผ ์„ธ๋Š” ์›๋ž˜ ์ด์œ ๋Š”
14:10
and what did governments
425
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๋ฌด์—‡์ด๋ฉฐ ์ •๋ถ€
14:11
hope to achieve by doing so?
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๋Š” ๊ทธ๋ ‡๊ฒŒ ํ•จ์œผ๋กœ์จ ๋ฌด์—‡์„ ์„ฑ์ทจํ•˜๊ธฐ๋ฅผ ํฌ๋งํ–ˆ์Šต๋‹ˆ๊นŒ?
14:13
Hereโ€™s Dr Kathrin Levitan, author
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๋‹ค์Œ์€ ์ธ๊ตฌ ์กฐ์‚ฌ์˜ ๋ฌธํ™”์‚ฌ์— ๊ด€ํ•œ ์ฑ…์˜ ์ €์ž์ธ Kathrin Levitan ๋ฐ•์‚ฌ
14:16
of a book on the cultural history
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14:18
of the census, speaking to
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๊ฐ€
14:20
BBC World Service programme,
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BBC World Service ํ”„๋กœ๊ทธ๋žจ์ธ
14:21
The Forum:
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The Forum์—์„œ ์—ฐ์„คํ•œ ๋‚ด์šฉ์ž…๋‹ˆ๋‹ค.
14:24
I think there were probably
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์•„๋งˆ
14:25
two most common reasons.
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๋‘ ๊ฐ€์ง€ ๊ฐ€์žฅ ์ผ๋ฐ˜์ ์ธ ์ด์œ ๊ฐ€ ์žˆ๋‹ค๊ณ  ์ƒ๊ฐํ•ฉ๋‹ˆ๋‹ค.
14:27
One was in order to figure out
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ํ•˜๋‚˜๋Š”
14:29
who could fight in wars, so basically
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๋ˆ„๊ฐ€ ์ „์Ÿ์—์„œ ์‹ธ์šธ ์ˆ˜ ์žˆ๋Š”์ง€ ์•Œ์•„๋‚ด๊ธฐ ์œ„ํ•œ ๊ฒƒ์ด์—ˆ๊ณ , ๊ทธ๋ž˜์„œ ๊ธฐ๋ณธ์ ์œผ๋กœ
14:31
military conscription and in order
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๊ตฐ์‚ฌ ์ง•์ง‘์ด ์žˆ์—ˆ๊ณ 
14:33
to find out who could fight in wars
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๋ˆ„๊ฐ€ ์ „์Ÿ์—์„œ ์‹ธ์šธ ์ˆ˜ ์žˆ๋Š”์ง€ ์•Œ์•„๋‚ด๊ธฐ
14:35
ancient governments like the
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์œ„ํ•ด ๋กœ๋งˆ ์ œ๊ตญ๊ณผ ๊ฐ™์€ ๊ณ ๋Œ€ ์ •๋ถ€
14:36
Roman Empire had to find out how
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14:38
many men of a certain age there were.
440
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๋Š” ํŠน์ • ์—ฐ๋ น์˜ ๋‚จ์„ฑ์ด ๋ช‡ ๋ช…์ธ์ง€ ์•Œ์•„๋‚ด์•ผ ํ–ˆ์Šต๋‹ˆ๋‹ค.
14:41
And I would say that the other thing
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๊ทธ๋ฆฌ๊ณ  ์ €๋Š”
14:43
that censuses were most commonly
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์ธ๊ตฌ ์กฐ์‚ฌ๊ฐ€ ๊ฐ€์žฅ ์ผ๋ฐ˜์ ์œผ๋กœ
14:45
used for was for purposes of taxation.
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์‚ฌ์šฉ๋œ ๋˜ ๋‹ค๋ฅธ ๊ฒƒ์€ ๊ณผ์„ธ ๋ชฉ์ ์ด๋ผ๊ณ  ๋งํ•˜๊ณ  ์‹ถ์Šต๋‹ˆ๋‹ค.
14:48
According to Kathrin Levitan, ancient
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์บ์„œ๋ฆฐ ๋ ˆ๋น„ํƒ„(Kathrin Levitan)์— ๋”ฐ๋ฅด๋ฉด, ๊ณ ๋Œ€
14:51
censuses were used to figure out โ€“ or
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์ธ๊ตฌ ์กฐ์‚ฌ๋Š”
14:53
understand, how many men were
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์–ผ๋งˆ๋‚˜ ๋งŽ์€ ์‚ฌ๋žŒ๋“ค์ด ์ „์Ÿ์— ์ฐธ์—ฌํ•  ์ˆ˜ ์žˆ๋Š”์ง€ ์•Œ์•„๋‚ด๊ฑฐ๋‚˜ ์ดํ•ดํ•˜๋Š” ๋ฐ ์‚ฌ์šฉ๋˜์—ˆ์Šต๋‹ˆ๋‹ค
14:55
available to fight wars.
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.
14:57
The Roman Empire needed a strong
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๋กœ๋งˆ ์ œ๊ตญ์€ ๊ฐ•๋ ฅํ•œ
15:00
army, and this depended on
449
900080
1840
๊ตฐ๋Œ€๊ฐ€ ํ•„์š”ํ–ˆ๊ณ  ์ด๊ฒƒ์€ ์ง•์ง‘์— ์˜์กดํ–ˆ์Šต๋‹ˆ๋‹ค.
15:01
conscription โ€“ forcing people to
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์‚ฌ๋žŒ๋“ค
15:04
become soldiers and join the army.
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์ด ๊ตฐ์ธ์ด ๋˜์–ด ๊ตฐ๋Œ€์— ์ž…๋Œ€ํ•˜๋„๋ก ๊ฐ•์š”ํ–ˆ์Šต๋‹ˆ๋‹ค. ์ธ๊ตฌ ์กฐ์‚ฌ
15:06
The other main reason for taking
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๋ฅผ ํ•˜๋Š” ๋˜ ๋‹ค๋ฅธ ์ฃผ์š” ์ด์œ 
15:08
a census was taxation โ€“ the
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๋Š” ๊ณผ์„ธ์˜€์Šต๋‹ˆ๋‹ค
15:10
system of taxing people a certain
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15:12
amount of money to be paid to
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15:14
the government for public services.
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. ๊ณต๊ณต ์„œ๋น„์Šค๋ฅผ ์œ„ํ•ด ์ •๋ถ€์— ์ง€๋ถˆํ•  ์ผ์ • ๊ธˆ์•ก์„ ์‚ฌ๋žŒ๋“ค์—๊ฒŒ ๊ณผ์„ธํ•˜๋Š” ์‹œ์Šคํ…œ์ž…๋‹ˆ๋‹ค.
15:16
Ancient and early modern censuses
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๊ณ ๋Œ€ ๋ฐ ์ดˆ๊ธฐ ํ˜„๋Œ€ ์ธ๊ตฌ ์กฐ์‚ฌ
15:18
were large and difficult-to-organise
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๋Š” ๊ทœ๋ชจ๊ฐ€ ํฌ๊ณ  ์กฐ์งํ•˜๊ธฐ ์–ด๋ ค์šด
15:21
projects. They often involved
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ํ”„๋กœ์ ํŠธ์˜€์Šต๋‹ˆ๋‹ค. ๊ทธ๋“ค์€ ์ข…์ข…
15:23
government officials going from
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์ •๋ถ€ ๊ด€๋ฆฌ๋“ค์ด
15:25
house to house, asking questions
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์ง‘์ง‘์„ ๋ฐฉ๋ฌธํ•˜์—ฌ
15:27
about the people who lived there.
462
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๊ทธ๊ณณ์— ์‚ฌ๋Š” ์‚ฌ๋žŒ๋“ค์— ๋Œ€ํ•ด ์งˆ๋ฌธํ•˜๋Š” ์ผ์„ ํ–ˆ์Šต๋‹ˆ๋‹ค.
15:30
But over time governmentsโ€™ desire
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๊ทธ๋Ÿฌ๋‚˜ ์‹œ๊ฐ„์ด ์ง€๋‚จ
15:32
to know about, and control, its
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์— ๋”ฐ๋ผ ์‹œ๋ฏผ๋“ค์— ๋Œ€ํ•ด ์•Œ๊ณ  ํ†ต์ œํ•˜๋ ค๋Š” ์ •๋ถ€์˜ ์š•๊ตฌ
15:34
citizens gave rise to new
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๋Š”
15:35
technologies for counting people.
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์ธ๊ตฌ ์ˆ˜๋ฅผ ์„ธ๋Š” ์ƒˆ๋กœ์šด ๊ธฐ์ˆ ์„ ํƒ„์ƒ์‹œ์ผฐ์Šต๋‹ˆ๋‹ค.
15:38
Hereโ€™s statistician and economist
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๋‹ค์Œ์€ ํ†ต๊ณ„ํ•™์ž์ด์ž ๊ฒฝ์ œํ•™์ž์ธ
15:40
Andrew Whitby explaining how
468
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Andrew Whitby
15:42
this happened in the US to BBC
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2400
๊ฐ€ BBC
15:44
World Service programme,
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World Service ํ”„๋กœ๊ทธ๋žจ์ธ
15:45
The Forum:
471
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15:47
The 1890 census of the United
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The Forum์—์„œ ์–ด๋–ป๊ฒŒ ์ด๋Ÿฐ ์ผ์ด
15:49
States was the first in which some
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๋ฏธ๊ตญ์—์„œ
15:51
kind of electro-mechanical process
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์ผ์–ด๋‚ฌ๋Š”์ง€ ์„ค๋ช…ํ•˜๋Š”
15:52
was used to count peopleโ€ฆ so
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15:54
instead of armies of clerks reading
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๊ฒƒ์ž…๋‹ˆ๋‹ค. ๋งŽ์€ ์‚ฌ๋ฌด์›๋“ค์ด
15:57
off census schedules and tabulating
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์ธ๊ตฌ ์กฐ์‚ฌ ์ผ์ •์„ ์ฝ๊ณ 
16:00
these things by hand, for the first
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์ด๋Ÿฌํ•œ ๊ฒƒ๋“ค์„ ์†์œผ๋กœ ํ‘œ๋กœ ์ž‘์„ฑํ–ˆ์Šต๋‹ˆ๋‹ค. ์ฒ˜์Œ
16:01
time an individual census record
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์œผ๋กœ ๊ฐœ๋ณ„ ์ธ๊ตฌ ์กฐ์‚ฌ ๊ธฐ๋ก
16:03
would be punched onto a cardโ€ฆ so
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์ด ์นด๋“œ์— ํŽ€์นญ๋˜์—ˆ์Šต๋‹ˆ๋‹ค... ๊ทธ๋ž˜์„œ
16:05
that there were holes in this card
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์ด ์นด๋“œ์— ์‚ฌ๋žŒ์˜
16:06
representing different characteristics
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๋‹ค์–‘ํ•œ ํŠน์„ฑ
16:08
of the person and then those cards
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์„ ๋‚˜ํƒ€๋‚ด๋Š” ๊ตฌ๋ฉ์ด ์žˆ๋Š” ๋‹ค์Œ ๊ทธ ์นด๋“œ์—
16:09
could be fed through a machine.
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์Œ์‹์„ ๊ณต๊ธ‰ํ•  ์ˆ˜ ์žˆ์—ˆ์Šต๋‹ˆ๋‹ค. ๊ธฐ๊ณ„๋ฅผ ํ†ตํ•ด.
16:12
Old-fashioned censuses were managed
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๊ตฌ์‹ ์ธ๊ตฌ ์กฐ์‚ฌ๋Š”
16:14
by clerks โ€“ office workers whose job
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์‚ฌ๋ฌด์›, ์ฆ‰
16:16
involved keeping records.
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๊ธฐ๋ก ๋ณด๊ด€์„ ๋‹ด๋‹นํ•˜๋Š” ์‚ฌ๋ฌด์›์ด ๊ด€๋ฆฌํ–ˆ์Šต๋‹ˆ๋‹ค.
16:18
Thousands of clerks would record
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์ˆ˜์ฒœ ๋ช…์˜ ์‚ฌ๋ฌด์›์ด ์ธ๊ตฌ ์กฐ์‚ฌ
16:20
the information gathered in the
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์—์„œ ์ˆ˜์ง‘๋œ ์ •๋ณด๋ฅผ ๊ธฐ๋ก
16:22
census and tabulate it, in other words,
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982080
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ํ•˜๊ณ  ํ‘œ๋กœ ๋งŒ๋“ค์—ˆ์Šต๋‹ˆ๋‹ค. ์ฆ‰, ํ–‰๊ณผ ์—ด
16:25
show the information in the form of
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์ด ์žˆ๋Š” ํ‘œ ํ˜•์‹์œผ๋กœ ์ •๋ณด๋ฅผ ํ‘œ์‹œํ–ˆ์Šต๋‹ˆ๋‹ค
16:27
a table with rows and columns.
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.
16:30
The US census of 1890 was the first
493
990800
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1890๋…„์˜ ๋ฏธ๊ตญ ์ธ๊ตฌ ์กฐ์‚ฌ๋Š” ์ตœ์ดˆ๋กœ
16:33
to use machines, and many censuses
494
993600
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๊ธฐ๊ณ„๋ฅผ ์‚ฌ์šฉํ–ˆ์œผ๋ฉฐ ์˜ค๋Š˜๋‚  ๋งŽ์€ ์ธ๊ตฌ ์กฐ์‚ฌ
16:36
today are electronically updated to
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996000
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๋Š”
16:38
record new trends and shifts in
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2000
์ƒˆ๋กœ์šด ๊ฒฝํ–ฅ๊ณผ ์ธ๊ตฌ ๋ณ€ํ™”๋ฅผ ๊ธฐ๋ก
16:40
populations as they happen.
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ํ•˜๊ธฐ ์œ„ํ•ด ์ „์ž์ ์œผ๋กœ ์—…๋ฐ์ดํŠธ๋ฉ๋‹ˆ๋‹ค.
16:42
In fact, so much personal
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1002720
1920
์‚ฌ์‹ค, ๋„ˆ๋ฌด ๋งŽ์€ ๊ฐœ์ธ
16:44
information is now freely available
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์ •๋ณด๊ฐ€ ์ด์ œ
16:46
through social media and the
500
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1280
์†Œ์…œ ๋ฏธ๋””์–ด์™€
16:48
internet that some people have
501
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1920
์ธํ„ฐ๋„ท์„ ํ†ตํ•ด ๋ฌด๋ฃŒ๋กœ ์ œ๊ณต๋˜๋ฏ€๋กœ ์ผ๋ถ€ ์‚ฌ๋žŒ๋“ค
16:50
questioned the need for having
502
1010160
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์€ ์ธ๊ตฌ ์กฐ์‚ฌ์˜ ํ•„์š”์„ฑ์— ์˜๋ฌธ์„ ์ œ๊ธฐ
16:51
a census at all.
503
1011920
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ํ–ˆ์Šต๋‹ˆ๋‹ค.
16:53
Yes, it isnโ€™t hard to find out about
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์˜ˆ, TV ์Šคํƒ€์™€ ๊ฐ™์ด ์œ ๋ช…ํ•œ ์‚ฌ๋žŒ์— ๋Œ€ํ•ด ์•Œ์•„๋‚ด๋Š” ๊ฒƒ์€ ์–ด๋ ต์ง€ ์•Š์Šต๋‹ˆ๋‹ค
16:55
someone famous, like a TV star.
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.
16:58
Someone like Danny Dyer, you mean?
506
1018320
2400
๋Œ€๋‹ˆ ๋‹ค์ด์–ด ๊ฐ™์€ ์‚ฌ๋žŒ ๋ง์ด์•ผ?
17:00
Right. In my quiz question I asked
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์˜ค๋ฅธ์ชฝ. ๋‚ด ํ€ด์ฆˆ ์งˆ๋ฌธ์—์„œ ๋‚˜๋Š”
17:02
Sam which historical figure TV
508
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2400
์ƒ˜์—๊ฒŒ ์–ด๋–ค ์—ญ์‚ฌ์ ์ธ ์ธ๋ฌผ TV
17:05
actor, Danny Dyer, was related to.
509
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๋ฐฐ์šฐ์ธ ๋Œ€๋‹ˆ ๋‹ค์ด์–ด์™€ ๊ด€๋ จ์ด ์žˆ๋Š”์ง€ ๋ฌผ์—ˆ์Šต๋‹ˆ๋‹ค.
17:07
And I said it was
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1120
๊ทธ๋ฆฌ๊ณ  ๋‚˜๋Š” ๊ทธ๊ฒƒ์ด
17:08
C) Winston Churchill. Was I right?
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3200
C) ์œˆ์Šคํ„ด ์ฒ˜์น ์ด๋ผ๊ณ  ๋งํ–ˆ์Šต๋‹ˆ๋‹ค. ๋‚ด๊ฐ€ ๋งž์•˜์–ด?
17:12
It was a good guess, Sam, but
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์ข‹์€ ์ถ”์ธก์ด์—ˆ์ง€๋งŒ Sam,
17:13
the actual answer was
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์‹ค์ œ ๋Œ€๋‹ต์€
17:14
A) King Edward III. And no-one
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A) King Edward III์˜€์Šต๋‹ˆ๋‹ค. ๊ทธ๋ฆฌ๊ณ 
17:17
was more surprised that he was
515
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๊ทธ๊ฐ€ EastEnders ๋ฐฐ์šฐ ์ž์‹ ๋ณด๋‹ค ์™•์กฑ๊ณผ ๊ด€๋ จ์ด ์žˆ๋‹ค๋Š” ์‚ฌ์‹ค์— ๋” ๋†€๋ž€ ์‚ฌ๋žŒ์€ ์—†์—ˆ์Šต๋‹ˆ๋‹ค
17:18
related to royalty than the
516
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1600
17:20
EastEnders actor himself!
517
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2400
!
17:22
OK, Neil, letโ€™s recap the
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์ข‹์•„, Neil.
17:24
vocabulary from this programme
519
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1760
์ด ํ”„๋กœ๊ทธ๋žจ
17:26
about the census - the official
520
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์—์„œ ์ธ๊ตฌ ์กฐ์‚ฌ์— ๋Œ€ํ•œ ์–ดํœ˜๋ฅผ ์š”์•ฝํ•ด ๋ด…์‹œ๋‹ค
17:28
counting of a nationโ€™s population.
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. ๊ตญ๊ฐ€ ์ธ๊ตฌ์˜ ๊ณต์‹ ์ง‘๊ณ„์ž…๋‹ˆ๋‹ค.
17:30
To figure something out means
522
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๋ฌด์–ธ๊ฐ€๋ฅผ ์•Œ์•„๋‚ธ๋‹ค๋Š” ๊ฒƒ์€
17:32
to understand it.
523
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๊ทธ๊ฒƒ์„ ์ดํ•ดํ•œ๋‹ค๋Š” ๋œป์ž…๋‹ˆ๋‹ค.
17:34
The Romans used conscription
524
1054160
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๋กœ๋งˆ์ธ๋“ค์€
17:36
to force men to join the army by law.
525
1056160
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๋ฒ•์— ๋”ฐ๋ผ ๋‚จ์ž๋“ค์ด ๊ตฐ๋Œ€์— ์ž…๋Œ€ํ•˜๋„๋ก ๊ฐ•์ œํ•˜๊ธฐ ์œ„ํ•ด ์ง•๋ณ‘์ œ๋ฅผ ์‚ฌ์šฉํ–ˆ์Šต๋‹ˆ๋‹ค.
17:39
Taxation is the governmentโ€™s
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๊ณผ์„ธ๋Š” ๊ณต๊ณต ์„œ๋น„์Šค
17:40
system of taxing people to pay
527
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๋น„์šฉ์„ ์ง€๋ถˆํ•˜๊ธฐ ์œ„ํ•ด ์‚ฌ๋žŒ๋“ค์—๊ฒŒ ์„ธ๊ธˆ์„ ๋ถ€๊ณผํ•˜๋Š” ์ •๋ถ€ ์‹œ์Šคํ…œ์ž…๋‹ˆ๋‹ค
17:42
for public services.
528
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.
17:44
A clerk is an office worker whose
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2240
์ ์›์€
17:46
job involves keeping records.
530
1066960
3120
๊ธฐ๋ก์„ ๋ณด๊ด€ํ•˜๋Š” ์ผ์„ ํ•˜๋Š” ํšŒ์‚ฌ์›์ž…๋‹ˆ๋‹ค.
17:50
And tabulate means show
531
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๊ทธ๋ฆฌ๊ณ  ํ‘œ๋กœ ๋งŒ๋“ ๋‹ค๋Š”
17:51
information in the form of a table
532
1071760
1920
๊ฒƒ์€ ํ–‰๊ณผ ์—ด์ด ์žˆ๋Š” ํ‘œ ํ˜•์‹์œผ๋กœ ์ •๋ณด๋ฅผ ํ‘œ์‹œํ•œ๋‹ค๋Š” ๊ฒƒ์„ ์˜๋ฏธํ•ฉ๋‹ˆ๋‹ค
17:53
with rows and columns.
533
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2217
.
17:55
Thatโ€™s all for our six-minute look
534
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2023
์ธ๊ตฌ์กฐ์‚ฌ์— ๋Œ€ํ•œ 6๋ถ„๊ฐ„
17:57
at the census, but if weโ€™ve whetted
535
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1920
์˜ ์กฐ์‚ฌ๋Š” ์—ฌ๊ธฐ๊นŒ์ง€
17:59
your appetite for more why not
536
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2000
์ž…๋‹ˆ๋‹ค. ๋” ๋งŽ์€ ์ •๋ณด๋ฅผ ์›ํ•˜์‹ ๋‹ค๋ฉด
18:01
check out the whole episode โ€“ itโ€™s
537
1081840
2080
์ „์ฒด ์—ํ”ผ์†Œ๋“œ๋ฅผ ํ™•์ธํ•ด ๋ณด์‹ญ์‹œ์˜ค.
18:03
available now on the website of
538
1083920
1920
์ง€๊ธˆ
18:05
BBC World Service programme,
539
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1760
BBC World Service ํ”„๋กœ๊ทธ๋žจ์ธ
18:07
The Forum.
540
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The Forum ์›น์‚ฌ์ดํŠธ์—์„œ ๋ณผ ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค.
18:09
Bye for now!
541
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์ง€๊ธˆ์€ ์•ˆ๋…•!
18:10
Bye bye.
542
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์•ˆ๋…•.
18:17
Hello. This is 6 Minute English
543
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์•ˆ๋…•ํ•˜์„ธ์š”. BBC Learning English์˜ 6๋ถ„ ์˜์–ด
18:18
from BBC Learning English.
544
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์ž…๋‹ˆ๋‹ค.
18:20
Iโ€™m Neil.
545
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18:20
And Iโ€™m Georgina.
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์ €๋Š” ๋‹์ž…๋‹ˆ๋‹ค.
๊ทธ๋ฆฌ๊ณ  ์ €๋Š” ์กฐ์ง€๋‚˜์ž…๋‹ˆ๋‹ค.
18:22
What do Homer, Ray Charles
547
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Homer, Ray Charles
18:23
and Jorge Borges all have in
548
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, Jorge Borges์˜
18:25
common, Georgina?
549
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๊ณตํ†ต์ ์€ ๋ฌด์—‡์ž…๋‹ˆ๊นŒ, Georgina?
18:26
Hmm, so thatโ€™s the ancient Greek
550
1106720
2400
์Œ, ๊ทธ๊ฑด ๊ณ ๋Œ€ ๊ทธ๋ฆฌ์Šค
18:29
poet, Homer; American singer,
551
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์‹œ์ธ ํ˜ธ๋จธ์ž…๋‹ˆ๋‹ค. ๋ฏธ๊ตญ ๊ฐ€์ˆ˜
18:31
Ray Charles; and Argentine writer,
552
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2400
๋ ˆ์ด ์ฐฐ์Šค; ๊ทธ๋ฆฌ๊ณ  ์•„๋ฅดํ—จํ‹ฐ๋‚˜ ์ž‘๊ฐ€์ธ
18:33
Jorge Luis Borgesโ€ฆ I canโ€™t see
553
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Jorge Luis Borges...
18:36
much in common there, Neil.
554
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1440
๊ฑฐ๊ธฐ์—๋Š” ๊ณตํ†ต์ ์ด ๋ณ„๋กœ ์—†์–ด์š”, Neil.
18:37
Well, the answer is that they
555
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๋Œ€๋‹ต์€
18:38
were all blind.
556
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๊ทธ๋“ค์ด ๋ชจ๋‘ ๋ˆˆ์ด ๋ฉ€์—ˆ๋‹ค๋Š” ๊ฒƒ์ž…๋‹ˆ๋‹ค.
18:40
Ah! But that obviously didnโ€™t hold
557
1120240
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์•„! ๊ทธ๋Ÿฌ๋‚˜ ๊ทธ๊ฒƒ์€ ๋ถ„๋ช…ํžˆ ๊ทธ๋“ค์„ ์ œ์ง€ํ•˜์ง€ ๋ชปํ–ˆ์Šต๋‹ˆ๋‹ค.
18:42
them back - I mean, they were
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์ œ ๋ง์€, ๊ทธ๋“ค์€
18:43
some of the greatest artists ever!
559
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2160
์—ญ์‚ฌ์ƒ ๊ฐ€์žฅ ์œ„๋Œ€ํ•œ ์˜ˆ์ˆ ๊ฐ€ ์ค‘ ์ผ๋ถ€์˜€์Šต๋‹ˆ๋‹ค!
18:45
Right, but I wonder how easy they
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1125440
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๋งž์•„์š”, ํ•˜์ง€๋งŒ ๊ทธ๋“ค์ด ํ˜„๋Œ€ ์‚ฌํšŒ
18:47
would find it living and working in
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1600
์—์„œ ์ƒํ™œํ•˜๊ณ  ์ผํ•˜๋Š” ๊ฒƒ์„ ์–ผ๋งˆ๋‚˜ ์‰ฝ๊ฒŒ ์ฐพ์„ ์ˆ˜ ์žˆ์„์ง€ ๊ถ๊ธˆํ•ฉ๋‹ˆ๋‹ค
18:48
the modern world.
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.
18:49
Blind people can use a guide dog
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์‹œ๊ฐ ์žฅ์• ์ธ์€ ์•ˆ๋‚ด๊ฒฌ
18:51
or a white cane to help them
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์ด๋‚˜ ํฐ์ƒ‰ ์ง€ํŒก์ด๋ฅผ ์‚ฌ์šฉํ•˜์—ฌ ์ด๋™์„ ๋„์šธ ์ˆ˜
18:52
move around.
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์žˆ์Šต๋‹ˆ๋‹ค.
18:53
Yes, but a white cane is hardly
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๋„ค, ํ•˜์ง€๋งŒ ํ•˜์–€ ์ง€ํŒก์ด๋Š” ๊ฑฐ์˜
18:55
advanced technology! Recently,
567
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2240
์ฒจ๋‹จ ๊ธฐ์ˆ ์ด ์•„๋‹™๋‹ˆ๋‹ค! ์ตœ๊ทผ ์ „ ์„ธ๊ณ„
18:58
smartphone apps have been
568
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1440
18:59
invented which dramatically
569
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1520
19:01
improve the lives of blind people
570
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1760
์‹œ๊ฐ ์žฅ์• ์ธ์˜ ์‚ถ์„ ํš๊ธฐ์ ์œผ๋กœ ๊ฐœ์„ ํ•˜๋Š” ์Šค๋งˆํŠธํฐ ์•ฑ์ด ๋ฐœ๋ช…๋˜์—ˆ์Šต๋‹ˆ๋‹ค
19:02
around the world.
571
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1120
.
19:04
In this programme on blindness
572
1144000
1600
๋””์ง€ํ„ธ ์‹œ๋Œ€์˜ ์‹ค๋ช…์— ๊ด€ํ•œ ์ด ํ”„๋กœ๊ทธ๋žจ์—์„œ
19:05
in the digital age weโ€™ll be looking
573
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1920
์šฐ๋ฆฌ๋Š” ์ด์ฒด์ ์œผ๋กœ ๋ณด์กฐ ๊ธฐ์ˆ 
19:07
at some of these inventions, known
574
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2080
๋กœ ์•Œ๋ ค์ง„ ์ด๋Ÿฌํ•œ ๋ฐœ๋ช…ํ’ˆ ์ค‘ ์ผ๋ถ€๋ฅผ ์‚ดํŽด๋ณผ ๊ฒƒ์ž…๋‹ˆ๋‹ค. ์ด๋Š”
19:09
collectively as assistive technology โ€“
575
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3040
19:12
thatโ€™s any software or equipment
576
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2000
19:14
that helps people work around their
577
1154640
1920
์‚ฌ๋žŒ๋“ค์ด ์žฅ์• ๋‚˜ ๋ฌธ์ œ๋ฅผ ํ•ด๊ฒฐํ•˜๋Š” ๋ฐ ๋„์›€์ด ๋˜๋Š” ์†Œํ”„ํŠธ์›จ์–ด ๋˜๋Š” ์žฅ๋น„์ž…๋‹ˆ๋‹ค
19:16
disabilities or challenges.
578
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2080
.
19:18
But first itโ€™s time for my quiz
579
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ํ•˜์ง€๋งŒ ๋จผ์ € ๋‚ด ํ€ด์ฆˆ ์งˆ๋ฌธ์„ ํ•  ์‹œ๊ฐ„์ด์•ผ
19:20
question, Georgina. In 1842 a
580
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, Georgina. 1842๋…„์—
19:23
technique of using fingers to feel
581
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2240
19:25
printed raised dots was invented
582
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2240
์ธ์‡„๋œ ๋Œ์ถœ๋œ ์ ์„ ์†๊ฐ€๋ฝ์œผ๋กœ ๊ฐ์ง€ํ•˜๋Š” ๊ธฐ์ˆ ์ด ๋ฐœ๋ช…
19:27
which allowed blind people to read.
583
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๋˜์–ด ์‹œ๊ฐ ์žฅ์• ์ธ์ด ์ฝ์„ ์ˆ˜ ์žˆ๊ฒŒ ๋˜์—ˆ์Šต๋‹ˆ๋‹ค.
19:29
But who invented it? Was it:
584
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2000
๊ทธ๋Ÿฌ๋‚˜ ๋ˆ„๊ฐ€ ๊ทธ๊ฒƒ์„ ๋ฐœ๋ช… ํ–ˆ์Šต๋‹ˆ๊นŒ?
19:31
a) Margaret Walker?,
585
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2000
a) Margaret Walker?,
19:33
b) Louis Braille?, or
586
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1760
b) Louis Braille?, ๋˜๋Š”
19:35
c) Samuel Morse?
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c) Samuel Morse?
19:36
Hmm, Iโ€™ve heard of Morse code but
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ํ , ๋ชจ์Šค๋ถ€ํ˜ธ์— ๋Œ€ํ•ด ๋“ค์–ด๋ณธ ์ ์ด ์žˆ์ง€๋งŒ
19:39
that wouldnโ€™t help blind people
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์‹œ๊ฐ ์žฅ์• ์ธ์ด ์ฝ๋Š” ๋ฐ ๋„์›€์ด ๋˜์ง€ ์•Š์„
19:40
read, so I think itโ€™s, b) Louis Braille.
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๊ฒƒ ๊ฐ™์•„์„œ b) ๋ฃจ์ด ๋ธŒ๋ผ์œ ์ž…๋‹ˆ๋‹ค.
19:43
OK, Georgina, weโ€™ll find out the
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์ข‹์•„์š”, Georgina,
19:45
answer at the end of the programme.
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ํ”„๋กœ๊ทธ๋žจ์ด ๋๋‚  ๋•Œ ๋‹ต์„ ์ฐพ๊ฒ ์Šต๋‹ˆ๋‹ค.
19:47
One remarkable feature of the latest
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์ตœ์‹  ๋ณด์กฐ ๊ธฐ์ˆ ์˜ ์ฃผ๋ชฉํ• ๋งŒํ•œ ํŠน์ง• ์ค‘ ํ•˜๋‚˜
19:49
assistive technology is its practicality.
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๋Š” ์‹ค์šฉ์„ฑ์ž…๋‹ˆ๋‹ค.
19:52
Smartphone apps like โ€˜BeMyEyesโ€™
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'BeMyEyes'์™€ ๊ฐ™์€ ์Šค๋งˆํŠธํฐ ์•ฑ์„
19:55
allow blind users to find lost keys,
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์‚ฌ์šฉํ•˜๋ฉด ์‹œ๊ฐ ์žฅ์• ์ธ์ด ๋ถ„์‹คํ•œ ์—ด์‡ ๋ฅผ ์ฐพ๊ณ 
19:57
cross busy roads and even colour
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๋ฐ”์œ ๋„๋กœ๋ฅผ ๊ฑด๋„ˆ๊ณ  ์˜ท ์ƒ‰์ƒ์„ ๋งž์ถœ ์ˆ˜๋„ ์žˆ์Šต๋‹ˆ๋‹ค
19:59
match their clothes.
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.
20:01
Brian Mwenda is CEO of a Kenyan
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Brian Mwenda๋Š”
20:03
company developing this kind of
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์ด๋Ÿฐ ์ข…๋ฅ˜์˜ ๊ธฐ์ˆ ์„ ๊ฐœ๋ฐœํ•˜๋Š” ์ผ€๋ƒ ํšŒ์‚ฌ์˜ CEO์ž…๋‹ˆ๋‹ค
20:05
technology. Here he explains to
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. ์—ฌ๊ธฐ์—์„œ ๊ทธ๋Š”
20:07
BBC World Service programme,
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BBC World Service ํ”„๋กœ๊ทธ๋žจ์ธ
20:09
Digital Planet, how his devices seek
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Digital Planet์—์„œ ์ž์‹ ์˜ ์žฅ์น˜
20:12
to enhance, not replace, the
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๊ฐ€ ์ „ํ†ต์ ์ธ ํฐ์ƒ‰ ์ง€ํŒก์ด๋ฅผ ๋Œ€์ฒดํ•˜๋Š” ๊ฒƒ์ด ์•„๋‹ˆ๋ผ ํ–ฅ์ƒ์‹œํ‚ค๋Š” ๋ฐฉ๋ฒ•์— ๋Œ€ํ•ด ์„ค๋ช…ํ•ฉ๋‹ˆ๋‹ค
20:14
traditional white cane:
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.
20:16
The device is very compatible with
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์ด ์žฅ์น˜๋Š”
20:18
any kind of white cane. So, once you
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๋ชจ๋“  ์ข…๋ฅ˜์˜ ํฐ์ƒ‰ ์ง€ํŒก์ด์™€ ๋งค์šฐ ํ˜ธํ™˜๋ฉ๋‹ˆ๋‹ค. ๋”ฐ๋ผ์„œ
20:20
clip it on to any white cane it
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ํฐ์ƒ‰ ์ง€ํŒก์ด์— ํด๋ฆฝ์„ ๊ฝ‚์œผ๋ฉด ์•ž์—
20:22
works perfectly to detect the
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์žˆ๋Š” ์žฅ์• ๋ฌผ์„ ์™„๋ฒฝํ•˜๊ฒŒ ๊ฐ์ง€ํ•˜๊ณ 
20:24
obstacles in front of you, and it
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20:26
relies on echo-location. So,
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๋ฐ˜ํ–ฅ ์œ„์น˜์— ์˜์กดํ•ฉ๋‹ˆ๋‹ค. ๋”ฐ๋ผ์„œ
20:28
echo-location is the same technology
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์—์ฝ” ์œ„์น˜๋Š” ๋จน์ด์™€ ์žฅ์• ๋ฌผ ๋“ฑ
20:30
used by bats and dolphins to detect
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์„ ๊ฐ์ง€ํ•˜๊ธฐ ์œ„ํ•ด ๋ฐ•์ฅ์™€ ๋Œ๊ณ ๋ž˜๊ฐ€ ์‚ฌ์šฉํ•˜๋Š” ๊ฒƒ๊ณผ ๋™์ผํ•œ ๊ธฐ์ˆ 
20:33
prey and obstacles and all that. You
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์ž…๋‹ˆ๋‹ค.
20:36
send out a sound pulse and then
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1236160
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์‚ฌ์šด๋“œ ํŽ„์Šค๋ฅผ ๋ณด๋‚ธ ๋‹ค์Œ
20:38
once it bounces off an obstacle, you
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20:40
can tell how far the obstacle is.
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์žฅ์• ๋ฌผ์— ๋ถ€๋”ชํžˆ๋ฉด ์žฅ์• ๋ฌผ์ด ์–ผ๋งˆ๋‚˜ ๋ฉ€๋ฆฌ ์žˆ๋Š”์ง€ ์•Œ ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค.
20:42
When attached to a white cane, the
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ํฐ์ƒ‰ ์ง€ํŒก์ด์— ๋ถ€์ฐฉํ•˜๋ฉด
20:44
digital device - called โ€˜Sixth Senseโ€™ -
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์‹์Šค์„ผ์Šค(Sixth Sense)๋ผ๋Š” ๋””์ง€ํ„ธ ์žฅ์น˜๊ฐ€
20:46
can detect obstacles โ€“ objects which
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์žฅ์• ๋ฌผ
20:49
block your way, making it difficult for
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, ์ฆ‰
20:51
you to move forward.
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์•ž์„ ๊ฐ€๋กœ๋ง‰๋Š” ๋ฌผ์ฒด๋ฅผ ๊ฐ์ง€ํ•˜์—ฌ ์•ž์œผ๋กœ ๋‚˜์•„๊ฐ€๊ธฐ ์–ด๋ ต๊ฒŒ ๋งŒ๋“ญ๋‹ˆ๋‹ค.
20:52
โ€˜Sixth Senseโ€™ works using echo-location,
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'์‹์Šค ์„ผ์Šค'๋Š” ์ฃผ๋ณ€ ๋ฌผ์ฒด์—์„œ ๋ฐ˜์‚ฌ๋˜๋Š” ์ŒํŒŒ๋ฅผ ๋‚ด๋ณด๋‚ด๋Š” ๋ฐ•์ฅ
20:55
a kind of ultrasound like that used by
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๊ฐ€ ์‚ฌ์šฉํ•˜๋Š” ๊ฒƒ๊ณผ ๊ฐ™์€ ์ผ์ข…์˜ ์ดˆ์ŒํŒŒ์ธ ์—์ฝ” ์œ„์น˜๋ฅผ ์‚ฌ์šฉํ•˜์—ฌ ์ž‘๋™
20:58
bats who send out sound waves
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21:00
which bounce off surrounding objects.
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ํ•ฉ๋‹ˆ๋‹ค.
21:03
The returning echoes show where these
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๋ฐ˜ํ™˜๋˜๋Š” ์—์ฝ”๋Š” ์ด๋Ÿฌํ•œ
21:05
objects are located.
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๊ฐœ์ฒด๊ฐ€ ์žˆ๋Š” ์œ„์น˜๋ฅผ ๋ณด์—ฌ์ค๋‹ˆ๋‹ค.
21:07
Some of the assistive apps are so
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์ผ๋ถ€ ๋ณด์กฐ ์•ฑ์€ ๋„ˆ๋ฌด
21:09
smart they can even tell what kind of
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๋˜‘๋˜‘ํ•ด์„œ
21:11
object is coming up ahead โ€“ be it a
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21:13
friend, a shop door or a speeding car.
632
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์นœ๊ตฌ, ๊ฐ€๊ฒŒ ๋ฌธ, ๊ณผ์† ์ฐจ๋Ÿ‰ ๋“ฑ ์–ด๋–ค ๋ฌผ์ฒด๊ฐ€ ์•ž์— ์žˆ๋Š”์ง€๋„ ์•Œ ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค. ์ž์‹ 
21:16
I guess being able to move around
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์žˆ๊ฒŒ ๋Œ์•„๋‹ค๋‹ ์ˆ˜
21:18
confidently really boosts peopleโ€™s
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์žˆ๋‹ค๋Š” ๊ฒƒ์€ ์ •๋ง ์‚ฌ๋žŒ๋“ค์˜
21:20
independence.
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๋…๋ฆฝ์„ฑ์„ ๋†’์—ฌ์ฃผ๋Š” ๊ฒƒ ๊ฐ™์•„์š”.
21:21
Absolutely. And itโ€™s challenging
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์ „์ ์œผ๋กœ.
21:22
stereotypes around blindness too.
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์‹ค๋ช…์— ๋Œ€ํ•œ ๊ณ ์ •๊ด€๋…์—๋„ ๋„์ „ํ•˜๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค.
21:25
Blogger, Fern Lulham, who is blind
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๋งน์ธ์ธ ๋ธ”๋กœ๊ฑฐ Fern Lulham์€
21:27
herself, uses assistive apps every day.
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๋งค์ผ ๋ณด์กฐ ์•ฑ์„ ์‚ฌ์šฉํ•ฉ๋‹ˆ๋‹ค.
21:30
Here she is talking to
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์—ฌ๊ธฐ์—์„œ ๊ทธ๋…€๋Š”
21:32
BBC World Serviceโ€™s, Digital Planet:
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BBC World Service์˜ Digital Planet๊ณผ ์ด์•ผ๊ธฐํ•˜๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค.
21:35
I think the more that society sees
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์ €๋Š” ์‚ฌํšŒ๊ฐ€
21:37
blind people in the community, at work,
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์ง€์—ญ ์‚ฌํšŒ, ์ง์žฅ, ๊ด€๊ณ„์—์„œ ๋งน์ธ์„ ๋” ๋งŽ์ด
21:40
in relationships it does help to tackle
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๋ณผ์ˆ˜๋ก
21:43
all of these stereotypes, it helps
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์ด๋Ÿฌํ•œ ๋ชจ๋“  ๊ณ ์ •๊ด€๋…์„ ํ•ด๊ฒฐํ•˜๋Š” ๋ฐ ๋„์›€
21:44
people to see blind and
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์ด ๋œ๋‹ค๊ณ  ์ƒ๊ฐํ•ฉ๋‹ˆ๋‹ค.
21:46
visually-impaired people in a whole
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์‚ฌ๋žŒ๋“ค์ด ์™„์ „ํžˆ
21:47
new way and it just normalises
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์ƒˆ๋กœ์šด ๋ฐฉ์‹์œผ๋กœ ์žฅ์• ๋ฅผ ์ •์ƒํ™”ํ•ฉ๋‹ˆ๋‹ค. ๊ทธ๊ฒƒ์ด ์šฐ๋ฆฌ
21:49
disability โ€“ thatโ€™s what we need, we
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21:51
need to see people just getting on
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๊ฐ€
21:53
with their life and doing it and then
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21:54
people wonโ€™t see it as such a big
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21:56
deal anymore, itโ€™ll just be the ordinary.
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ํ•„์š”๋กœ ํ•˜๋Š” ๊ฒƒ์ž…๋‹ˆ๋‹ค. ํ‰๋ฒ”ํ•˜๋‹ค.
22:00
Fern distinguishes between people
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Fern
22:02
who are blind, or unable to see, and
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์€ ๋งน์ธ ๋˜๋Š” ๋ณผ ์ˆ˜
22:04
those who are visually impaired โ€“
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์—†๋Š” ์‚ฌ๋žŒ๊ณผ ์‹œ๊ฐ ์žฅ์• ๊ฐ€ ์žˆ๋Š” ์‚ฌ๋žŒ์„ ๊ตฌ๋ถ„
22:06
experience a decreased ability to see.
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ํ•ฉ๋‹ˆ๋‹ค.
22:09
Assistive tech helps blind people
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๋ณด์กฐ ๊ธฐ์ˆ ์€ ์‹œ๊ฐ ์žฅ์• ์ธ์ด
22:11
lead normal, independent lives within
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2400
์ง€์—ญ ์‚ฌํšŒ์—์„œ ์ •์ƒ์ ์ด๊ณ  ๋…๋ฆฝ์ ์ธ ์‚ถ์„ ์˜์œ„ํ•˜๋„๋ก ๋•์Šต๋‹ˆ๋‹ค
22:14
their local communities. Fern hopes
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. Fern์€
22:16
that this will help normalise disability โ€“
661
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์ด๊ฒƒ์ด ์žฅ์• ๋ฅผ ์ •์ƒํ™”ํ•˜๋Š” ๋ฐ ๋„์›€์ด ๋˜๊ธฐ๋ฅผ ํฌ๋งํ•ฉ๋‹ˆ๋‹ค. ์ด์ „์—๋Š” ์ •์ƒ์œผ๋กœ ๋ฐ›์•„๋“ค์—ฌ์ง€์ง€
22:19
treat something as normal which has
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์•Š์•˜๋˜ ๊ฒƒ์„ ์ •์ƒ์œผ๋กœ ์ทจ๊ธ‰ํ•˜๋Š” ๊ฒƒ์ž…๋‹ˆ๋‹ค
22:21
not been accepted as normal beforeโ€ฆ
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.
22:23
โ€ฆso being blind doesnโ€™t have to be a
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โ€ฆ๊ทธ๋ž˜์„œ ๋งน์ธ์ด ํฐ ๋ฌธ์ œ๊ฐ€ ๋  ํ•„์š”๋Š” ์—†์Šต๋‹ˆ๋‹ค. ๋ฌด์–ธ๊ฐ€
22:26
big deal โ€“ an informal way to say
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๋ฅผ ๋น„๊ณต์‹์ ์œผ๋กœ ๋งํ•˜๋Š”
22:28
something is not a serious problem.
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๊ฒƒ์€ ์‹ฌ๊ฐํ•œ ๋ฌธ์ œ๊ฐ€ ์•„๋‹™๋‹ˆ๋‹ค. ์ž ์‹œ
22:31
Just keep your eyes closed for a
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๋ˆˆ์„ ๊ฐ๊ณ  ๋ฐฉ ์•ˆ์„ ๋Œ์•„๋‹ค๋…€ ๋ณด์„ธ์š”
22:32
minute and try moving around the
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22:33
room. Youโ€™ll soon see how difficult
669
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.
22:36
it isโ€ฆ and how life changing this
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์ด ๊ธฐ์ˆ ์ด ์–ผ๋งˆ๋‚˜ ์–ด๋ ค์šด์ง€... ๊ทธ๋ฆฌ๊ณ  ์ด ๊ธฐ์ˆ ์ด ์–ผ๋งˆ๋‚˜ ์‚ถ์„ ๋ณ€ํ™”
22:37
technology can be.
671
1357840
1600
์‹œํ‚ฌ ์ˆ˜ ์žˆ๋Š”์ง€ ๊ณง ์•Œ๊ฒŒ ๋  ๊ฒƒ์ž…๋‹ˆ๋‹ค.
22:39
Being able to read books must also
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์ฑ…์„ ์ฝ์„ ์ˆ˜ ์žˆ๋‹ค๋Š” ๊ฒƒ์€
22:41
open up a world of imagination.
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์ƒ์ƒ์˜ ์„ธ๊ณ„๋„ ์—ด์–ด์ค˜์•ผ ํ•œ๋‹ค.
22:44
So what was the answer to your
674
1364000
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๋„ค ํ€ด์ฆˆ ์งˆ๋ฌธ์— ๋Œ€ํ•œ ๋Œ€๋‹ต์€
22:45
quiz question, Neil?
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1600
๋ญ์˜€๋‹ˆ, ๋‹?
22:46
Ah yes. I asked Georgina who
676
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์•„ ์˜ˆ. ๋‚˜๋Š”
22:48
invented the system of reading
677
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1760
22:50
where fingertips are used to feel
678
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์†๋
22:52
patterns of printed raised dots.
679
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์œผ๋กœ ์ธ์‡„๋œ ์œต๊ธฐ๋œ ์ ์˜ ํŒจํ„ด์„ ๋Š๋ผ๋Š” ์ฝ๊ธฐ ์‹œ์Šคํ…œ์„ ๋ฐœ๋ช…ํ•œ ์กฐ์ง€๋‚˜์—๊ฒŒ ๋ฌผ์—ˆ๋‹ค.
22:54
What did you say, Georgina?
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๋ญ๋ผ๊ณ  ํ–ˆ์–ด, ์กฐ์ง€๋‚˜?
22:55
I thought it was, b) Louis Braille.
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๋‚˜๋Š” ๊ทธ๊ฒƒ์ด b) Louis Braille์ด๋ผ๊ณ  ์ƒ๊ฐํ–ˆ์Šต๋‹ˆ๋‹ค.
22:58
Which wasโ€ฆof course the correct
682
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๊ทธ๊ฒƒ์€โ€ฆ ๋ฌผ๋ก  ์ •๋‹ต์ด์—ˆ์Šต๋‹ˆ๋‹ค
23:00
answer! Well done, Georgina โ€“ Louise
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! ์ž˜ํ•˜์…จ์Šต๋‹ˆ๋‹ค, Georgina โ€“ Louise
23:02
Braille the inventor of a reading
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Braille์€
23:04
system which is known worldwide
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์ „ ์„ธ๊ณ„์ ์œผ๋กœ
23:06
simply as braille.
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๊ฐ„๋‹จํžˆ ์ ์ž๋กœ ์•Œ๋ ค์ง„ ์ฝ๊ธฐ ์‹œ์Šคํ…œ์˜ ๋ฐœ๋ช…๊ฐ€์ž…๋‹ˆ๋‹ค.
23:07
I suppose braille is an early example
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์ ์ž๋Š” ์žฅ์• ๊ฐ€ ์žˆ๋Š”
23:10
of assistive technology โ€“ systems
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23:12
and equipment that assist people
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์‚ฌ๋žŒ๋“ค์ด ์ผ์ƒ์ ์ธ ๊ธฐ๋Šฅ์„ ์ˆ˜ํ–‰ํ•˜๋Š” ๋ฐ ๋„์›€์ด ๋˜๋Š” ์‹œ์Šคํ…œ ๋ฐ ์žฅ๋น„์ธ ๋ณด์กฐ ๊ธฐ์ˆ ์˜ ์ดˆ๊ธฐ ์‚ฌ๋ก€๋ผ๊ณ  ์ƒ๊ฐ
23:14
with disabilities to perform everyday
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23:16
functions. Letโ€™s recap the rest of
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ํ•ฉ๋‹ˆ๋‹ค.
23:18
the vocabulary, Neil.
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Neil, ๋‚˜๋จธ์ง€ ์–ดํœ˜๋ฅผ ์š”์•ฝํ•ด ๋ด…์‹œ๋‹ค.
23:20
OK. An obstacle is an object that
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์ข‹์•„์š”. ์žฅ์• ๋ฌผ
23:22
is in your way and blocks your
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์€ ๋‹น์‹ ์˜ ๊ธธ์„ ๊ฐ€๋กœ๋ง‰๊ณ  ๋‹น์‹ ์˜
23:24
movement.
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์›€์ง์ž„์„ ๋ง‰๋Š” ๋ฌผ์ฒด์ž…๋‹ˆ๋‹ค.
23:25
Some assisted technology works
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์ผ๋ถ€ ๋ณด์กฐ ๊ธฐ์ˆ ์€ ๋ฐ•์ฅ๊ฐ€ ์‚ฌ์šฉํ•˜๋Š” ์ดˆ์ŒํŒŒ ๊ฐ์ง€
23:27
using echo-location โ€“ a system of
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์‹œ์Šคํ…œ์ธ ์—์ฝ” ์œ„์น˜๋ฅผ ์‚ฌ์šฉํ•˜์—ฌ ์ž‘๋™ํ•ฉ๋‹ˆ๋‹ค
23:30
ultrasound detection used by bats.
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.
23:33
Being blind is different from being
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๋งน์ธ์ด ๋œ๋‹ค๋Š” ๊ฒƒ์€
23:34
visually impaired - having a
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์žฅ์• ๊ฐ€
23:36
decreased ability to see, whether
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์žˆ๋“  ์—†๋“  ๋ณผ ์ˆ˜ ์žˆ๋Š” ๋Šฅ๋ ฅ์ด ๊ฐ์†Œ๋œ ์‹œ๊ฐ ์žฅ์• ์™€๋Š” ๋‹ค๋ฆ…๋‹ˆ๋‹ค
23:38
disabling or not.
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.
23:40
And finally, the hope is that
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๊ทธ๋ฆฌ๊ณ  ๋งˆ์ง€๋ง‰์œผ๋กœ,
23:42
assistive phone apps can help
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๋ณด์กฐ ์ „ํ™” ์•ฑ์ด ์žฅ์• ๋ฅผ ์ •์ƒํ™”ํ•˜๋Š” ๋ฐ ๋„์›€์ด ๋  ์ˆ˜ ์žˆ๊ธฐ๋ฅผ ๋ฐ”๋ž๋‹ˆ๋‹ค.
23:43
normalise disability โ€“ change the
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23:45
perception of something into
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์–ด๋–ค ๊ฒƒ์— ๋Œ€ํ•œ ์ธ์‹
23:47
being accepted as normalโ€ฆ
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์„ ์ •์ƒ์œผ๋กœ ๋ฐ›์•„๋“ค์ด๋Š” ๊ฒƒ์œผ๋กœ ๋ฐ”๊พธ๋Š” ๊ฒƒ์ž…๋‹ˆ๋‹ค. ..
23:49
..so that disability is no longer a
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์žฅ์• ๊ฐ€ ๋” ์ด์ƒ
23:51
big deal โ€“ not a big problem.
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ํฐ ๋ฌธ์ œ๊ฐ€ ์•„๋‹Œ ํฐ ๋ฌธ์ œ๊ฐ€ ์•„๋‹™๋‹ˆ๋‹ค.
23:53
Thatโ€™s all for this programme but
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์ด๊ฒƒ์ด ์ด ํ”„๋กœ๊ทธ๋žจ์˜ ์ „๋ถ€์ž…๋‹ˆ๋‹ค.
23:55
join us again soon at 6 Minute Englishโ€ฆ
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๊ณง 6๋ถ„ ์˜์–ด์— ๋‹ค์‹œ ์ฐธ์—ฌํ•˜์„ธ์š”...
23:57
โ€ฆand remember you can find many
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โ€ฆ ๊ทธ๋ฆฌ๊ณ  bbclearningenglish.com์— ๋ณด๊ด€๋œ
23:59
more 6 Minute topics and useful
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๋” ๋งŽ์€ 6๋ถ„ ์ฃผ์ œ์™€ ์œ ์šฉํ•œ
24:01
vocabulary archived on
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์–ดํœ˜๋ฅผ ์ฐพ์„ ์ˆ˜ ์žˆ๋‹ค๋Š” ๊ฒƒ์„ ๊ธฐ์–ตํ•˜์„ธ์š”
24:02
bbclearningenglish.com.
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. ์•ฑ ์Šคํ† ์–ด์—์„œ ๋ฌด๋ฃŒ๋กœ ๋‹ค์šด๋กœ๋“œํ•  ์ˆ˜
24:04
Donโ€™t forget we also have an app
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์žˆ๋Š” ์•ฑ๋„ ์žˆ๋‹ค๋Š” ์‚ฌ์‹ค์„ ์žŠ์ง€ ๋งˆ์„ธ์š”
24:06
you can download for free from
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24:08
the app stores. And of course we
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. ๊ทธ๋ฆฌ๊ณ  ๋ฌผ๋ก  ์šฐ๋ฆฌ
24:10
are all over social media, so come
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๋Š” ์†Œ์…œ ๋ฏธ๋””์–ด ์ „์ฒด์— ์žˆ์œผ๋ฏ€๋กœ
24:12
on over and say hi.
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์™€์„œ ์ธ์‚ฌํ•˜์‹ญ์‹œ์˜ค.
24:13
Bye for now!
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์ง€๊ธˆ์€ ์•ˆ๋…•!
24:14
Bye!
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์•ˆ๋…•!
24:21
Welcome to 6 Minute English, where
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6 Minute English์— ์˜ค์‹  ๊ฒƒ์„ ํ™˜์˜
24:22
we bring you an intelligent topic
724
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ํ•ฉ๋‹ˆ๋‹ค. ์ง€๋Šฅ์ ์ธ ์ฃผ์ œ
24:24
and six related items of vocabulary.
725
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์™€ 6๊ฐœ์˜ ๊ด€๋ จ ์–ดํœ˜ ํ•ญ๋ชฉ์„ ์ œ๊ณตํ•ฉ๋‹ˆ๋‹ค.
24:26
Iโ€™m Neil.
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์ €๋Š” ๋‹์ž…๋‹ˆ๋‹ค.
24:27
And Iโ€™m Tim. And today weโ€™re talking
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์ €๋Š” ํŒ€์ž…๋‹ˆ๋‹ค. ๊ทธ๋ฆฌ๊ณ  ์˜ค๋Š˜ ์šฐ๋ฆฌ๋Š”
24:30
about AI โ€“ or Artificial Intelligence.
728
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AI ๋˜๋Š” ์ธ๊ณต ์ง€๋Šฅ์— ๋Œ€ํ•ด ์ด์•ผ๊ธฐํ•˜๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค.
24:33
Artificial Intelligence is the ability of
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์ธ๊ณต ์ง€๋Šฅ์€
24:36
machines to copy human intelligent
730
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์ธ๊ฐ„์˜ ์ง€๋Šฅ์ ์ธ ํ–‰๋™์„ ๋ณต์‚ฌํ•˜๋Š” ๊ธฐ๊ณ„์˜ ๋Šฅ๋ ฅ์ž…๋‹ˆ๋‹ค.
24:38
behaviour โ€“ for example, an
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์˜ˆ๋ฅผ ๋“ค์–ด
24:40
intelligent machine can learn
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์ง€๋Šฅํ˜• ๊ธฐ๊ณ„
24:42
from its own mistakes, and make
733
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๋Š” ์ž์‹ ์˜ ์‹ค์ˆ˜๋กœ๋ถ€ํ„ฐ ๋ฐฐ์šฐ๊ณ  ๊ณผ๊ฑฐ
24:43
decisions based on whatโ€™s happened
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์— ์ผ์–ด๋‚œ ์ผ์„ ๊ธฐ๋ฐ˜์œผ๋กœ ๊ฒฐ์ •์„ ๋‚ด๋ฆด ์ˆ˜
24:45
in the past.
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์žˆ์Šต๋‹ˆ๋‹ค.
24:46
Thereโ€™s a lot of talk about AI these
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์š”์ฆ˜ AI์— ๋Œ€ํ•œ ์ด์•ผ๊ธฐ๊ฐ€ ๋งŽ์ด
24:48
days, Neil, but itโ€™s still just science
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๋‚˜์˜ค์ฃ , Neil, ํ•˜์ง€๋งŒ ์—ฌ์ „ํžˆ ๊ณต์ƒ๊ณผํ•™
24:50
fiction, isnโ€™t it?
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์†Œ์„ค์ผ ๋ฟ์ด์ฃ , ๊ทธ๋ ‡์ฃ ?
24:52
Thatโ€™s not true โ€“ AI is everywhere.
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๊ทธ๊ฒƒ์€ ์‚ฌ์‹ค์ด ์•„๋‹™๋‹ˆ๋‹ค. AI๋Š” ์–ด๋””์—๋‚˜ ์žˆ์Šต๋‹ˆ๋‹ค.
24:54
Machine thinking is in our homes,
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๊ธฐ๊ณ„ ์‚ฌ๊ณ ๋Š” ์šฐ๋ฆฌ ์ง‘,
24:57
offices, schools and hospitals.
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์‚ฌ๋ฌด์‹ค, ํ•™๊ต, ๋ณ‘์›์— ์žˆ์Šต๋‹ˆ๋‹ค.
24:59
Computer algorithms are helping
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์ปดํ“จํ„ฐ ์•Œ๊ณ ๋ฆฌ์ฆ˜์€
25:01
us drive our cars. Theyโ€™re diagnosing
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์šฐ๋ฆฌ๊ฐ€ ์ž๋™์ฐจ๋ฅผ ์šด์ „ํ•˜๋Š” ๋ฐ ๋„์›€์ด ๋ฉ๋‹ˆ๋‹ค. ๊ทธ๋“ค์€
25:03
whatโ€™s wrong with us in hospitals.
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๋ณ‘์›์—์„œ ์šฐ๋ฆฌ์—๊ฒŒ ๋ฌด์—‡์ด ์ž˜๋ชป๋˜์—ˆ๋Š”์ง€ ์ง„๋‹จํ•˜๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค.
25:06
Theyโ€™re marking student essaysโ€ฆ
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๊ทธ๋“ค์€ ํ•™์ƒ๋“ค์˜ ์—์„ธ์ด์— ํ‘œ์‹œ๋ฅผ ํ•˜๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค...
25:07
Theyโ€™re telling us what to read on
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๊ทธ๋“ค์€ ์šฐ๋ฆฌ์—๊ฒŒ ์Šค๋งˆํŠธํฐ์œผ๋กœ ๋ฌด์—‡์„ ์ฝ์–ด์•ผ ํ•˜๋Š”์ง€ ์•Œ๋ ค์ค๋‹ˆ๋‹ค
25:09
our smartphonesโ€ฆ
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...
25:10
Well, that really does sound like
748
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์Œ, ์ •๋ง
25:12
science fiction โ€“ but itโ€™s
749
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๊ณต์ƒ ๊ณผํ•™ ์†Œ์„ค์ฒ˜๋Ÿผ ๋“ค๋ฆฝ๋‹ˆ๋‹ค. ํ•˜์ง€๋งŒ
25:13
happening already, you say, Neil?
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์ด๋ฏธ ์ผ์–ด๋‚˜๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค, Neil?
25:15
Itโ€™s definitely happening, Tim.
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ํ™•์‹คํžˆ ์ผ์–ด๋‚˜๊ณ  ์žˆ์–ด์š”, ํŒ€.
25:17
And an algorithm, by the way, is
752
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๊ทธ๋Ÿฐ๋ฐ ์•Œ๊ณ ๋ฆฌ์ฆ˜์€ ๋ฌธ์ œ๋ฅผ ํ•ด๊ฒฐํ•˜๊ธฐ
25:19
a set of steps a computer follows
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์œ„ํ•ด ์ปดํ“จํ„ฐ๊ฐ€ ๋”ฐ๋ฅด๋Š” ์ผ๋ จ์˜ ๋‹จ๊ณ„
25:21
in order to solve a problem.
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์ž…๋‹ˆ๋‹ค.
25:23
So can you tell me what was the
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25:25
name of the computer which
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25:27
famously beat world chess
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25:28
champion Garry Kasparov
758
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25:30
using algorithms in 1997?
759
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1997๋…„์— ์•Œ๊ณ ๋ฆฌ์ฆ˜์„ ์‚ฌ์šฉํ•˜์—ฌ ์„ธ๊ณ„ ์ฒด์Šค ์ฑ”ํ”ผ์–ธ Garry Kasparov๋ฅผ ์ด๊ธด ๊ฒƒ์œผ๋กœ ์œ ๋ช…ํ•œ ์ปดํ“จํ„ฐ์˜ ์ด๋ฆ„์ด ๋ฌด์—‡์ธ์ง€ ๋ง์”€ํ•ด ์ฃผ์‹œ๊ฒ ์Šต๋‹ˆ๊นŒ?
25:33
Was itโ€ฆ
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25:33
a) Hal, b) Alpha 60,
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๊ทธ๊ฒƒ์€...
a) Hal, b) Alpha 60,
25:36
or, c) Deep Blue?
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๋˜๋Š” c) Deep Blue์˜€์Šต๋‹ˆ๊นŒ?
25:38
Iโ€™ll say Deep Blue.
763
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๋”ฅ ๋ธ”๋ฃจ๋ผ๊ณ  ํ•˜๊ฒ ์Šต๋‹ˆ๋‹ค.
25:41
Although Iโ€™m just guessing.
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๋‚˜๋Š” ๋‹จ์ง€ ์ถ”์ธกํ•˜๊ณ  ์žˆ์ง€๋งŒ.
25:42
Was it an educated guess, Tim?
765
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๊ต์œก๋ฐ›์€ ์ถ”์ธก ์ด์—ˆ์Šต๋‹ˆ๊นŒ, ํŒ€?
25:44
I know a bit about chessโ€ฆ
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์ €๋Š” ์ฒด์Šค์— ๋Œ€ํ•ด ์กฐ๊ธˆ ์•Œ๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค
25:46
An educated guess is based
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... ๊ต์œก๋ฐ›์€ ์ถ”์ธก์€
25:48
on knowledge and experience
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์ง€์‹๊ณผ ๊ฒฝํ—˜
25:49
and is therefore likely to be correct.
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์„ ๊ธฐ๋ฐ˜์œผ๋กœ ํ•˜๋ฏ€๋กœ ์ •ํ™•ํ•  ๊ฐ€๋Šฅ์„ฑ์ด ๋†’์Šต๋‹ˆ๋‹ค.
25:51
Well, weโ€™ll find out later on how
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๊ธ€์Ž„, ์ด ๊ฒฝ์šฐ์— ๋‹น์‹ ์˜ ์ถ”์ธก์ด ์–ผ๋งˆ๋‚˜ ๊ต์œก์  ์ด์—ˆ๋Š”์ง€ ๋‚˜์ค‘์— ์•Œ๊ฒŒ ๋  ๊ฒƒ์ž…๋‹ˆ๋‹ค
25:53
educated your guess was in
771
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25:54
this case, Tim!
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, ํŒ€!
25:55
Indeed. But getting back to AI
773
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๋ฌผ๋ก . ํ•˜์ง€๋งŒ AI
25:58
and what machines can do โ€“ are
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์™€ ๊ธฐ๊ณ„๊ฐ€ ํ•  ์ˆ˜ ์žˆ๋Š” ์ผ๋กœ ๋Œ์•„๊ฐ€์„œ
26:00
they any good at solving real-life
775
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์‹ค์ œ ๋ฌธ์ œ๋ฅผ ํ•ด๊ฒฐํ•˜๋Š” ๋ฐ ๋Šฅ์ˆ™
26:03
problems? Computers think in zeros
776
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ํ• ๊นŒ์š”? ์ปดํ“จํ„ฐ๋Š”
26:06
and ones donโ€™t they? That sounds
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0๊ณผ 1๋กœ ์ƒ๊ฐํ•˜์ง€ ์•Š์Šต๋‹ˆ๊นŒ?
26:07
like a pretty limited language when
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1600
26:09
it comes to life experience!
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1569360
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๊ทธ๊ฒƒ์€ ์‚ถ์˜ ๊ฒฝํ—˜์— ๊ด€ํ•œ ํ•œ ๊ฝค ์ œํ•œ๋œ ์–ธ์–ด์ฒ˜๋Ÿผ ๋“ค๋ฆฝ๋‹ˆ๋‹ค! 0๊ณผ 1
26:11
You would be surprised to what
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1571120
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์ด ๋ฌด์—‡์„ ํ•  ์ˆ˜ ์žˆ๋Š”์ง€ ์•Œ๋ฉด ๋†€๋ž„ ๊ฒ๋‹ˆ๋‹ค
26:12
those zeroes and ones can do, Tim.
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, ํŒ€.
26:14
Although youโ€™re right that AI does
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1920
ํ˜„์žฌ AI
26:16
have its limitations at the moment.
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1576800
1920
์— ํ•œ๊ณ„๊ฐ€ ์žˆ๋‹ค๋Š” ๊ฒƒ์€ ๋งž์ง€๋งŒ.
26:18
And if something has limitations
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๊ทธ๋ฆฌ๊ณ  ๋ฌด์–ธ๊ฐ€์—
26:20
thereโ€™s a limit on what it can do or
785
1580480
1920
ํ•œ๊ณ„๊ฐ€ ์žˆ๋‹ค๋ฉด ๊ทธ๊ฒƒ์ด ํ•  ์ˆ˜ ์žˆ๋Š” ๊ฒƒ ๋˜๋Š” ์–ผ๋งˆ๋‚˜ ์ข‹์€์ง€์— ๋Œ€ํ•œ ํ•œ๊ณ„
26:22
how good it can be.
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๊ฐ€ ์žˆ์Šต๋‹ˆ๋‹ค.
26:23
OK โ€“ well now might be a good time
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์ž, ์ง€๊ธˆ์ด ์ผ€์ž„๋ธŒ๋ฆฌ์ง€ ๋Œ€ํ•™๊ต
26:26
to listen to Zoubin Bharhramani,
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26:28
Professor of Information Engineering
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์ •๋ณด๊ณตํ•™๊ณผ ๊ต์ˆ˜์ด์ž
26:30
at the University of Cambridge and
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26:32
deputy director of the Leverhulme Centre
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Leverhulme Center
26:35
for the Future of Intelligence.
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2000
for the Future of Intelligence์˜ ๋ถ€์†Œ์žฅ์ธ Zoubin Bharhramani์˜ ์ด์•ผ๊ธฐ๋ฅผ ๋“ค์–ด๋ณผ ์ ๊ธฐ์ž…๋‹ˆ๋‹ค.
26:37
Heโ€™s talking about what limitations
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๊ทธ๋Š”
26:39
AI has at the moment.
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ํ˜„์žฌ AI๊ฐ€ ๊ฐ€์ง€๊ณ  ์žˆ๋Š” ํ•œ๊ณ„์— ๋Œ€ํ•ด ์ด์•ผ๊ธฐํ•˜๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค.
26:43
I think itโ€™s very interesting how many
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์ œ ์ƒ๊ฐ์—๋Š”
26:46
of the things that we take for granted โ€“
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์šฐ๋ฆฌ๊ฐ€ ๋‹น์—ฐํ•˜๊ฒŒ ์—ฌ๊ธฐ๋Š” ๊ฒƒ, ์šฐ๋ฆฌ ์ธ๊ฐ„์ด ๋‹น์—ฐํ•˜๊ฒŒ ์—ฌ๊ธฐ๋Š” ๊ฒƒ ์ค‘ ์–ผ๋งˆ๋‚˜ ๋งŽ์€
26:48
we humans take for granted โ€“ as being
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26:50
sort of things we donโ€™t even think about
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1600
26:51
like how do we walk, how do we reach,
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๊ฒƒ๋“ค์ด ์šฐ๋ฆฌ๊ฐ€ ์–ด๋–ป๊ฒŒ ๊ฑท๊ณ , ์–ด๋–ป๊ฒŒ ๋„๋‹ฌํ•˜๊ณ ,
26:54
how do we recognize our mother. You
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์–ด๋จธ๋‹ˆ.
26:57
know, all these things. When you start
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์ด ๋ชจ๋“  ๊ฒƒ. ์ปดํ“จํ„ฐ์—์„œ
26:59
to think how to implement them on a
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1619840
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๊ตฌํ˜„ํ•˜๋Š” ๋ฐฉ๋ฒ•์„ ์ƒ๊ฐํ•˜๊ธฐ ์‹œ์ž‘ํ•˜๋ฉด
27:01
computer, you realize that itโ€™s those
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27:04
things that are incredibly difficult to get
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1624800
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27:09
computers to do, and thatโ€™s where the
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์ปดํ“จํ„ฐ๊ฐ€ ์ˆ˜ํ–‰ํ•˜๊ธฐ๊ฐ€ ๋งค์šฐ ์–ด๋ ต๊ณ  ํ˜„์žฌ ์—ฐ๊ตฌ์˜ ์ตœ์ฒจ๋‹จ์ด ์žˆ๋Š” ๊ณณ์ด๋ผ๋Š” ๊ฒƒ์„ ๊นจ๋‹ซ๊ฒŒ
27:12
current cutting edge of research is.
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๋ฉ๋‹ˆ๋‹ค.
27:16
If we take something for granted we
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๋ฌด์–ธ๊ฐ€๋ฅผ ๋‹น์—ฐํ•˜๊ฒŒ ์—ฌ๊ธฐ๋ฉด ์šฐ๋ฆฌ
27:17
donโ€™t realise how important something is.
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๋Š” ๊ทธ๊ฒƒ์ด ์–ผ๋งˆ๋‚˜ ์ค‘์š”ํ•œ์ง€ ๊นจ๋‹ซ์ง€ ๋ชปํ•ฉ๋‹ˆ๋‹ค.
27:20
You sometimes take me for granted, I
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๋‹น์‹ ์€ ๊ฐ€๋” ๋‚˜๋ฅผ ๋‹น์—ฐํ•˜๊ฒŒ
27:22
think, Neil.
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1642240
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์ƒ๊ฐํ•˜๋Š” ๊ฒƒ ๊ฐ™์•„์š”, ๋‹.
27:23
No โ€“ I never take you for granted, Tim!
811
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์•„๋‹ˆ์˜ค โ€“ ๋‚˜๋Š” ๋‹น์‹ ์„ ๋‹น์—ฐํ•˜๊ฒŒ ์—ฌ๊ธฐ์ง€ ์•Š์Šต๋‹ˆ๋‹ค, ํŒ€!
27:25
Youโ€™re far too important for that!
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๊ทธ๋Ÿฌ๊ธฐ์—๋Š” ๋‹น์‹ ์ด ๋„ˆ๋ฌด ์ค‘์š”ํ•ฉ๋‹ˆ๋‹ค!
27:27
Good to hear! So things we take for
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์ž˜ ๋“ค์—ˆ์Šต๋‹ˆ๋‹ค! ๊ทธ๋ž˜์„œ ์šฐ๋ฆฌ๊ฐ€ ๋‹น์—ฐํ•˜๊ฒŒ
27:30
granted are doing every day tasks like
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3280
27:33
walking, picking something up, or
815
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์—ฌ๊ธฐ๋Š” ๊ฒƒ์€ ๊ฑท๊ธฐ, ๋ฌผ๊ฑด ์ค๊ธฐ,
27:35
recognizing somebody. We implement โ€“
816
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๋ˆ„๊ตฐ๊ฐ€๋ฅผ ์•Œ์•„๋ณด๋Š” ๊ฒƒ๊ณผ ๊ฐ™์€ ์ผ์ƒ์ ์ธ ์ผ์„ ํ•˜๋Š” ๊ฒƒ์ž…๋‹ˆ๋‹ค. ์šฐ๋ฆฌ๋Š” ์ƒ๊ฐ
27:38
or perform โ€“ these things without
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์—†์ด ์ด๋Ÿฌํ•œ ์ผ์„ ๊ตฌํ˜„ํ•˜๊ฑฐ๋‚˜ ์ˆ˜ํ–‰ํ•ฉ๋‹ˆ๋‹ค.
27:41
thinking โ€“ Whereas itโ€™s cutting edge
818
1661200
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๋ฐ˜๋ฉด ๊ธฐ๊ณ„๊ฐ€ ์ด๋ฅผ ์ˆ˜ํ–‰
27:43
research to try and program a
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ํ•˜๋„๋ก ์‹œ๋„ํ•˜๊ณ  ํ”„๋กœ๊ทธ๋ž˜๋ฐํ•˜๋Š” ๊ฒƒ์€ ์ตœ์ฒจ๋‹จ ์—ฐ๊ตฌ
27:45
machine to do them.
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์ž…๋‹ˆ๋‹ค.
27:46
Cutting edge means very new and
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์ตœ์ฒจ๋‹จ์ด๋ž€ ๋งค์šฐ ์ƒˆ๋กญ๊ณ 
27:48
advanced. Itโ€™s interesting isn't it, that
822
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์ง„๋ณด๋œ ๊ฒƒ์„ ์˜๋ฏธํ•ฉ๋‹ˆ๋‹ค.
27:50
over ten years ago a computer beat
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10๋…„ ์ „์— ์ปดํ“จํ„ฐ๊ฐ€
27:52
a chess grand master โ€“ but the
824
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์ฒด์Šค ๊ทธ๋žœ๋“œ ๋งˆ์Šคํ„ฐ๋ฅผ ์ด๊ฒผ๋‹ค๋Š” ๊ฒƒ์ด ํฅ๋ฏธ๋กญ์ง€ ์•Š์Šต๋‹ˆ๊นŒ? ํ•˜์ง€๋งŒ
27:54
same computer would find it incredibly
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๊ฐ™์€ ์ปดํ“จํ„ฐ๊ฐ€
27:56
difficult to pick up a chess piece.
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์ฒด์Šค ๋ง์„ ์ง‘๋Š” ๊ฒƒ์€ ์—„์ฒญ๋‚˜๊ฒŒ ์–ด๋ ต๋‹ค๋Š” ๊ฒƒ์„ ์•Œ๊ฒŒ ๋  ๊ฒƒ์ž…๋‹ˆ๋‹ค.
27:58
I know. Itโ€™s very strange. But now
827
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์•Œ์•„์š”. ๋งค์šฐ ์ด์ƒํ•ฉ๋‹ˆ๋‹ค. ํ•˜์ง€๋งŒ ์ด์ œ
28:01
youโ€™ve reminded me that we need
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28:02
the answer to todayโ€™s question.
829
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์˜ค๋Š˜์˜ ์งˆ๋ฌธ์— ๋Œ€ํ•œ ๋‹ต์ด ํ•„์š”ํ•˜๋‹ค๋Š” ๊ฒƒ์„ ์ƒ๊ธฐ์‹œ์ผœ ์ฃผ์…จ์Šต๋‹ˆ๋‹ค.
28:04
Which was: What was the name
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28:06
of the computer which famously
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28:08
beat world chess champion
832
1688320
1760
28:10
Garry Kasparov in 1997? Now, you
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1690080
2800
1997๋…„์— ์„ธ๊ณ„ ์ฒด์Šค ์ฑ”ํ”ผ์–ธ Garry Kasparov๋ฅผ ์ด๊ธด ๊ฒƒ์œผ๋กœ ์œ ๋ช…ํ•œ ์ปดํ“จํ„ฐ์˜ ์ด๋ฆ„์€ ๋ฌด์—‡์ด์—ˆ์Šต๋‹ˆ๊นŒ? ์ž, ๋‹น์‹ 
28:12
said Deep Blue, Tim, and โ€ฆ that was
834
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์€ Deep Blue, Tim, ๊ทธ๋ฆฌ๊ณ  โ€ฆ
28:15
the right answer!
835
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๊ทธ๊ฒƒ์€ ์ •๋‹ต์ด์—ˆ์Šต๋‹ˆ๋‹ค!
28:16
You see, my educated guess was
836
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์•Œ๋‹ค์‹œํ”ผ, ๋‚ด ๊ต์œก์ ์ธ ์ถ”์ธก์€
28:18
based on knowledge and experience!
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์ง€์‹๊ณผ ๊ฒฝํ—˜์„ ๊ธฐ๋ฐ˜์œผ๋กœ ํ•œ ๊ฒƒ์ž…๋‹ˆ๋‹ค!
28:20
Or maybe you were just lucky. So, the
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์•„๋‹ˆ๋ฉด ์šด์ด ์ข‹์•˜์„ ์ˆ˜๋„ ์žˆ์Šต๋‹ˆ๋‹ค. ๊ทธ๋ž˜์„œ
28:24
IBM supercomputer Deep Blue played
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IBM ์Šˆํผ์ปดํ“จํ„ฐ Deep Blue๋Š” ๋‘ ๋ฒˆ์˜ ์ฒด์Šค ๊ฒฝ๊ธฐ
28:26
against US world chess champion
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์—์„œ ๋ฏธ๊ตญ ์„ธ๊ณ„ ์ฒด์Šค ์ฑ”ํ”ผ์–ธ
28:28
Garry Kasparov in two chess matches.
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Garry Kasparov์™€ ๋Œ€๊ฒฐํ–ˆ์Šต๋‹ˆ๋‹ค.
28:31
The first match was played in
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1360
์ฒซ ๊ฒฝ๊ธฐ๋Š”
28:32
Philadelphia in 1996 and was
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1996๋…„ ํ•„๋ผ๋ธํ”ผ์•„์—์„œ ์น˜๋Ÿฌ
28:34
won by Kasparov. The second was
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์กŒ๊ณ  Kasparov๊ฐ€ ์ด๊ฒผ์Šต๋‹ˆ๋‹ค. ๋‘ ๋ฒˆ์งธ๋Š”
28:36
played in New York City in 1997
845
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1997๋…„ ๋‰ด์š•์—์„œ ์—ด๋ ธ์œผ๋ฉฐ
28:39
and won by Deep Blue. The 1997
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Deep Blue๊ฐ€ ์šฐ์Šนํ–ˆ์Šต๋‹ˆ๋‹ค. 1997๋…„
28:42
match was the first defeat of a
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๊ฒฝ๊ธฐ๋Š” ํ† ๋„ˆ๋จผํŠธ ์กฐ๊ฑด์—์„œ ์ปดํ“จํ„ฐ์— ์˜ํ•ด
28:43
reigning world chess champion
848
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๊ตฐ๋ฆผํ•˜๋Š” ์„ธ๊ณ„ ์ฒด์Šค ์ฑ”ํ”ผ์–ธ์˜ ์ฒซ ๋ฒˆ์งธ ํŒจ๋ฐฐ
28:45
by a computer under
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28:46
tournament conditions.
850
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์˜€์Šต๋‹ˆ๋‹ค.
28:48
Letโ€™s go through the words we
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์˜ค๋Š˜ ๋ฐฐ์šด ๋‹จ์–ด๋ฅผ ๋ณต์Šตํ•ด ๋ด…์‹œ๋‹ค
28:50
learned today. First up was
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. ์ฒซ ๋ฒˆ์งธ
28:52
โ€˜artificial intelligenceโ€™ or AI โ€“ the
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3200
28:55
ability of machines to copy human
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๋Š” ๊ธฐ๊ณ„๊ฐ€ ์ธ๊ฐ„์˜ ์ง€๋Šฅ์ ์ธ ํ–‰๋™์„ ๋ณต์‚ฌํ•  ์ˆ˜ ์žˆ๋Š” ๋Šฅ๋ ฅ์ธ '์ธ๊ณต ์ง€๋Šฅ' ๋˜๋Š” AI์˜€์Šต๋‹ˆ๋‹ค
28:58
intelligent behaviour.
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.
28:59
โ€œThere are AI programs that can
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โ€œ์‹œ๋ฅผ ์“ธ ์ˆ˜ ์žˆ๋Š” AI ํ”„๋กœ๊ทธ๋žจ์ด ์žˆ๋‹ค
29:01
write poetry.โ€
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.โ€ ์•”์†ก
29:02
Do you have any examples you
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ํ•  ์ˆ˜ ์žˆ๋Š” ์˜ˆ๊ฐ€
29:03
can recite?
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์žˆ์Šต๋‹ˆ๊นŒ?
29:04
Afraid I donโ€™t! Number two โ€“ an
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๋‘๋ ต์ง€ ์•Š์•„! ๋‘ ๋ฒˆ์งธ โ€“
29:07
algorithm is a set of steps a
861
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์•Œ๊ณ ๋ฆฌ์ฆ˜์€
29:08
computer follows in order to
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์ปดํ“จํ„ฐ
29:10
solve a problem. For example,
863
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๊ฐ€ ๋ฌธ์ œ๋ฅผ ํ•ด๊ฒฐํ•˜๊ธฐ ์œ„ํ•ด ๋”ฐ๋ฅด๋Š” ์ผ๋ จ์˜ ๋‹จ๊ณ„์ž…๋‹ˆ๋‹ค. ์˜ˆ๋ฅผ ๋“ค์–ด
29:12
โ€œGoogle changes its search
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"Google์€ ๊ฒ€์ƒ‰
29:13
algorithm hundreds of times
865
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์•Œ๊ณ ๋ฆฌ์ฆ˜์„ ๋งค๋…„ ์ˆ˜๋ฐฑ ๋ฒˆ ๋ณ€๊ฒฝํ•ฉ๋‹ˆ๋‹ค
29:15
every year.โ€
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880
."
29:16
The adjective is algorithmic โ€“ for
867
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ํ˜•์šฉ์‚ฌ๋Š” ์•Œ๊ณ ๋ฆฌ์ฆ˜์ž…๋‹ˆ๋‹ค.
29:19
example, โ€œGoogle has made many
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์˜ˆ๋ฅผ ๋“ค์–ด "Google์€
29:21
algorithmic changes.โ€
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์•Œ๊ณ ๋ฆฌ์ฆ˜์„ ๋งŽ์ด ๋ณ€๊ฒฝํ–ˆ์Šต๋‹ˆ๋‹ค."
29:23
Number three โ€“ if something has
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3๋ฒˆ - ๋ฌด์–ธ๊ฐ€์—
29:25
โ€˜limitationsโ€™ โ€“ thereโ€™s a limit on
871
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'์ œํ•œ'์ด ์žˆ๋Š” ๊ฒฝ์šฐ -
29:26
what it can do or how good it
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1520
ํ•  ์ˆ˜ ์žˆ๋Š” ๊ฒƒ ๋˜๋Š” ์–ผ๋งˆ๋‚˜ ์ข‹์€์ง€์— ๋Œ€ํ•œ ์ œํ•œ
29:28
can be. โ€œOur show has certain
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์ด ์žˆ์Šต๋‹ˆ๋‹ค. "์ €ํฌ ์‡ผ์—๋Š” ํŠน์ •
29:30
limitations โ€“ for example, itโ€™s only
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์ œํ•œ ์‚ฌํ•ญ์ด ์žˆ์Šต๋‹ˆ๋‹ค. ์˜ˆ๋ฅผ ๋“ค์–ด
29:32
six minutes long!โ€
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๊ธธ์ด๊ฐ€ 6๋ถ„์— ๋ถˆ๊ณผํ•ฉ๋‹ˆ๋‹ค!"
29:34
Thatโ€™s right โ€“ thereโ€™s only time to
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๋งž์Šต๋‹ˆ๋‹ค โ€“
29:35
present six vocabulary items.
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6๊ฐœ์˜ ์–ดํœ˜ ํ•ญ๋ชฉ์„ ์ œ์‹œํ•  ์‹œ๊ฐ„๋งŒ ์žˆ์Šต๋‹ˆ๋‹ค.
29:38
Short but sweet!
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์งง์ง€๋งŒ ๋‹ฌ์ฝค!
29:39
And very intelligent, too. OK, the
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๊ทธ๋ฆฌ๊ณ  ๋งค์šฐ ์ง€๋Šฅ์ ์ด๊ธฐ๋„ ํ•ฉ๋‹ˆ๋‹ค. ์ž,
29:41
next item is โ€˜take something for
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๋‹ค์Œ ํ•ญ๋ชฉ์€ '๋ฌด์–ธ๊ฐ€๋ฅผ
29:43
grantedโ€™ โ€“ which is when we donโ€™t
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๋‹น์—ฐํ•˜๊ฒŒ ์—ฌ๊ธฐ๋‹ค'์ž…๋‹ˆ๋‹ค. ์ด๊ฒƒ์€ ์šฐ๋ฆฌ๊ฐ€
29:45
realise how important something is.
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์–ด๋–ค ๊ฒƒ์ด ์–ผ๋งˆ๋‚˜ ์ค‘์š”ํ•œ์ง€ ๊นจ๋‹ซ์ง€ ๋ชปํ•˜๋Š” ๊ฒฝ์šฐ์ž…๋‹ˆ๋‹ค.
29:47
โ€œWe take our smart phones for granted
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"์š”์ฆ˜ ์šฐ๋ฆฌ๋Š” ์Šค๋งˆํŠธํฐ์„ ๋‹น์—ฐํ•˜๊ฒŒ ์—ฌ๊น๋‹ˆ๋‹ค. ํ•˜์ง€๋งŒ 1995๋…„ ์ด์ „์—๋Š” ์Šค๋งˆํŠธํฐ์„
29:49
these days โ€“ but before 1995 hardly
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29:52
anyone owned one.โ€
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์†Œ์œ ํ•œ ์‚ฌ๋žŒ์ด ๊ฑฐ์˜ ์—†์—ˆ์Šต๋‹ˆ๋‹ค."
29:54
Number five โ€“ โ€˜to implementโ€™ โ€“ means
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๋‹ค์„ฏ ๋ฒˆ์งธ โ€“ '๊ตฌํ˜„ํ•˜๋‹ค'
29:56
to perform a task, or take action.
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๋Š” ์ž‘์—…์„ ์ˆ˜ํ–‰ํ•˜๊ฑฐ๋‚˜ ์กฐ์น˜๋ฅผ ์ทจํ•˜๋Š” ๊ฒƒ์„ ์˜๋ฏธํ•ฉ๋‹ˆ๋‹ค.
29:58
โ€œNeil implemented some changes
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"Neil
30:00
to the show.โ€
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์€ ์‡ผ์— ๋ช‡ ๊ฐ€์ง€ ๋ณ€๊ฒฝ ์‚ฌํ•ญ์„ ์ ์šฉํ–ˆ์Šต๋‹ˆ๋‹ค."
30:01
The final item is โ€˜cutting edgeโ€™ โ€“ new
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๋งˆ์ง€๋ง‰ ํ•ญ๋ชฉ์€ '์ตœ์ฒจ๋‹จ' โ€“
30:03
and advanced โ€“ โ€œThis software is
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์ƒˆ๋กญ๊ณ  ์ง„๋ณด๋œ โ€“ โ€œ์ด ์†Œํ”„ํŠธ์›จ์–ด๋Š”
30:05
cutting edge.โ€
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์ตœ์ฒจ๋‹จ์ž…๋‹ˆ๋‹ค.โ€์ž…๋‹ˆ๋‹ค.
30:06
โ€œThe software uses cutting edge
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"์ด ์†Œํ”„ํŠธ์›จ์–ด๋Š” ์ตœ์ฒจ๋‹จ
30:08
technology.โ€
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๊ธฐ์ˆ ์„ ์‚ฌ์šฉํ•ฉ๋‹ˆ๋‹ค."
30:10
OK โ€“ thatโ€™s all we have time for on
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์ข‹์Šต๋‹ˆ๋‹ค โ€“ ์˜ค๋Š˜์˜ ์ตœ์ฒจ๋‹จ ์‡ผ์—์„œ ํ•  ์ˆ˜ ์žˆ๋Š” ์‹œ๊ฐ„์€ ์ด๊ฒƒ
30:11
todayโ€™s cutting edge show. But please
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๋ฟ์ž…๋‹ˆ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜
30:14
check out our Instagram, Twitter,
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Instagram, Twitter,
30:16
Facebook and YouTube pages.
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Facebook ๋ฐ YouTube ํŽ˜์ด์ง€๋ฅผ ํ™•์ธํ•˜์‹ญ์‹œ์˜ค.
30:18
Bye-bye!
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30:18
Goodbye!
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์•ˆ๋…•!
์•ˆ๋…•ํžˆ ๊ฐ€์„ธ์š”!
์ด ์›น์‚ฌ์ดํŠธ ์ •๋ณด

์ด ์‚ฌ์ดํŠธ๋Š” ์˜์–ด ํ•™์Šต์— ์œ ์šฉํ•œ YouTube ๋™์˜์ƒ์„ ์†Œ๊ฐœํ•ฉ๋‹ˆ๋‹ค. ์ „ ์„ธ๊ณ„ ์ตœ๊ณ ์˜ ์„ ์ƒ๋‹˜๋“ค์ด ๊ฐ€๋ฅด์น˜๋Š” ์˜์–ด ์ˆ˜์—…์„ ๋ณด๊ฒŒ ๋  ๊ฒƒ์ž…๋‹ˆ๋‹ค. ๊ฐ ๋™์˜์ƒ ํŽ˜์ด์ง€์— ํ‘œ์‹œ๋˜๋Š” ์˜์–ด ์ž๋ง‰์„ ๋”๋ธ” ํด๋ฆญํ•˜๋ฉด ๊ทธ๊ณณ์—์„œ ๋™์˜์ƒ์ด ์žฌ์ƒ๋ฉ๋‹ˆ๋‹ค. ๋น„๋””์˜ค ์žฌ์ƒ์— ๋งž์ถฐ ์ž๋ง‰์ด ์Šคํฌ๋กค๋ฉ๋‹ˆ๋‹ค. ์˜๊ฒฌ์ด๋‚˜ ์š”์ฒญ์ด ์žˆ๋Š” ๊ฒฝ์šฐ ์ด ๋ฌธ์˜ ์–‘์‹์„ ์‚ฌ์šฉํ•˜์—ฌ ๋ฌธ์˜ํ•˜์‹ญ์‹œ์˜ค.

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