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(λ°•μˆ˜) 이μͺ½μ€ Bill Lange 이고, μ €λŠ” David Galloμž…λ‹ˆλ‹€
(Applause) David Gallo: This is Bill Lange. I'm Dave Gallo.
μš°λ¦¬λŠ” μ—¬λŸ¬λΆ„μ—κ²Œ 바닷속 이야기λ₯Ό μ˜μƒκ³Ό ν•¨κ»˜ λ“€λ €μ£Όκ³ μž ν•©λ‹ˆλ‹€.
And we're going to tell you some stories from the sea here in video.
μ €ν¬λŠ” λλ‚΄μ£ΌλŠ” 타이타닉 λΉ„λ””μ˜€λ„ 있긴 ν•©λ‹ˆλ‹€λ§Œ 뭐..μ—¬κΈ°μ„œλŠ” λˆˆκΌ½λ§ŒνΌλ„ 보여쀄 μƒκ°μ΄μ—†μŠ΅λ‹ˆλ‹€.
We've got some of the most incredible video of Titanic that's ever been seen, and we're not going to show you any of it.
(μ›ƒμŒ) 비둝 타이타닉이 λ°•μŠ€μ˜€ν”ΌμŠ€μ—μ„œ ꡉμž₯ν•œ 싀적을 거두긴 ν–ˆμ§€λ§Œ λ°”λ‹€κ°€ λ“€λ €μ£ΌλŠ” 이야기 쀑 κ°€μž₯ μž¬λ°ŒλŠ” 것은 μ•„λ‹™λ‹ˆλ‹€.
(Laughter) The truth of the matter is that the Titanic -- even though it's breaking all sorts of box office records -- it's not the most exciting story from the sea.
문제라면 μš°λ¦¬λŠ” μš°λ¦¬κ°€ λ°”λ‹€λ₯Ό 이미 μ•Œκ³ μžˆλ‹€κ³  λ―ΏλŠ”κ±°μ£ .
And the problem, I think, is that we take the ocean for granted.
보톡 λ°”λ‹€κ°€ μ§€κ΅¬μ˜ 75%λ₯Ό 감싸고 μžˆλ‹€λŠ” 것,
When you think about it, the oceans are 75 percent of the planet.
지ꡬ상 λ°”λ‹€μ˜ λŒ€λΆ€λΆ„μ€
Most of the planet is ocean water.
평균 κΉŠμ΄κ°€ 2마일 (3.2Kmκ°€λŸ‰)정도 λœλ‹€λŠ”κ±Έ μ•Œκ³ μžˆμ£ 
The average depth is about two miles.
κ·Έλ¦¬κ³ λŠ” 해변가에 κ°€κ±°λ‚˜ 이런 λ°”λ‹·κ°€μ˜ 이미지λ₯Ό λ³΄κ³ λŠ” λ°”λ‹€λž€ κ·Έλƒ₯ κ±°λŒ€ν•œ νŒŒλž€μƒ‰μ˜ μ•„λ₯Έν•˜κ²Œ λ„˜μ‹€κ±°λ¦¬λŠ” νŒŒλ„μ™€ μ‘°μˆ˜κ°„λ§Œμ˜ μ°¨κ°€μžˆλ‹€ μ •λ„λ§Œ μƒκ°ν•˜μ£  사싀 κ·Έ 속에 무엇이 μžˆλŠ”μ§€λŠ” 상상도 λͺ»ν•˜λŠ”κ±°μ£ ...
Part of the problem, I think, is we stand at the beach, or we see images like this of the ocean, and you look out at this great big blue expanse, and it's shimmering and it's moving and there's waves and there's surf and there's tides, but you have no idea for what lies in there.
λ°”λ‹·μ†μ—λŠ” 지ꡬ상 κ°€μž₯ κΈ΄ μ‚°λ§₯κ³Ό
And in the oceans, there are the longest mountain ranges on the planet.
λŒ€λΆ€λΆ„μ˜ 생λͺ…체듀이 있고
Most of the animals are in the oceans.
λŒ€λΆ€λΆ„μ˜ 지진과 ν™”μ‚°ν™œλ™μ΄ λ°”λ‹·μ†μ—λŠ” μΌμ–΄λ‚©λ‹ˆλ‹€. μ € λ°”λ‹€ λ°‘ λ°”λ‹₯μ—λŠ”
Most of the earthquakes and volcanoes are in the sea, at the bottom of the sea.
밀림보닀도 더 λ§Žμ€ μ’…λ₯˜μ˜ 생λͺ…체듀이 훨씬 높은 밀집도λ₯Ό ν˜•μ„±ν•˜λ©° μ‚΄κ³  μžˆμŠ΅λ‹ˆλ‹€.
The biodiversity and the biodensity in the ocean is higher, in places, than it is in the rainforests.
이런 μΉœλ°€κ°μ„ μ£ΌλŠ” 맀λ ₯적인 멋진 λͺ¨μŠ΅λ“€ λ˜ν•œ λŒ€λΆ€λΆ„μ€ 아직 탐사쑰차 λ˜μ§€ μ•Šμ•˜μ£ 
It's mostly unexplored, and yet there are beautiful sights like this that captivate us and make us become familiar with it.
당신이 ν™€λ‘œ 해변에 μ„œμžˆκ²Œ λœλ‹€λ©΄ μžμ‹ μ΄ μ•„μ£Ό λ‚―μ„  μ„Έκ³„μ˜ κ°€μž₯μžλ¦¬μ— μžˆλ‹€λŠ”κ±Έ μ•Œμ•„μ£Όμ…¨μœΌλ©΄ ν•©λ‹ˆλ‹€.
But when you're standing at the beach, I want you to think that you're standing at the edge of a very unfamiliar world.
μ΄λ ‡κ²Œ λ‚―μ„  세계λ₯Ό νƒν—˜ν•˜κΈ° μœ„ν•΄μ„œ μš°λ¦¬λŠ” νŠΉλ³„ν•œ κΈ°μˆ λ“€μ„ κ°–μΆ°μ•Όλ§Œ ν–ˆμ—ˆμ£ .
We have to have a very special technology to get into that unfamiliar world.
Alvinμ΄λΌλŠ” μ΄λ¦„μ˜ μž μˆ˜ν•¨μ΄ λ™μ›λ˜μ—ˆκ³ , 카메라도 μ‚¬μš©ν–ˆμŠ΅λ‹ˆλ‹€ μΉ΄λ©”λΌλŠ” Bill Langeκ°€ 'μ†Œλ‹ˆ'의 ν˜‘μ°¬μœΌλ‘œ κ°œλ°œν•œ 특수 μΉ΄λ©”λΌμ˜€μŠ΅λ‹ˆλ‹€
We use the submarine Alvin and we use cameras, and the cameras are something that Bill Lange has developed with the help of Sony.
Marcel Proustκ°€ λ§ν•˜κΈΈ "κ°€μž₯ μ§„μ‹€λœ νƒν—˜μ΄λž€ λ‚―μ„  μž₯μ†Œλ₯Ό μ°Ύμ•„κ°€λŠ” 것이 μ•„λ‹ˆλΌ μƒˆλ‘œμš΄ μ‹œκ°μ„ κ°–λŠ” 것이닀"λΌκ³ μš”
Marcel Proust said, "The true voyage of discovery is not so much in seeking new landscapes as in having new eyes."
저희λ₯Ό ν˜‘μ°¬ν•΄μ£Όμ‹  뢄듀은 λ‹¨μˆœνžˆ λ°”λ‹€ μ•„λž˜μ— 무엇이 μ‘΄μž¬ν•˜κ³  μ–΄λ–€ μ§€ν˜•μ΄ 펼쳐져 μžˆλŠ”μ§€λ₯Ό μ•Œκ²Œ ν•΄μ£Όμ—ˆμ„ λΏλ§Œμ•„λ‹ˆλΌ 지ꡬ에 μ‚¬λŠ” 생λͺ…체듀에 λŒ€ν•œ 생각을 μƒˆλ‘œμ΄ ν•˜κ²Œ ν•΄μ£Όμ—ˆμŠ΅λ‹ˆλ‹€
People that have partnered with us have given us new eyes, not only on what exists -- the new landscapes at the bottom of the sea -- but also how we think about life on the planet itself.
μ—¬κΈ° μ œκ°€ μ’‹μ•„ν•˜λŠ” ν•΄νŒŒλ¦¬κ³Ό 생물이 μžˆμŠ΅λ‹ˆλ‹€.
Here's a jelly.
ν₯미둜운건 이녀석은 λ‚˜λ¦„ λΆ„μ—…ν™”λœ λͺΈμ„ κ°€μ§€κ³ μžˆλŠ”κ±΄λ°μš”
It's one of my favorites, because it's got all sorts of working parts.
κ·Έλ‘œμΈν•΄ λ°”λ‹€μ—μ„œ κ°€μž₯ κΈ΄ 생λͺ…체가 λ˜μ—ˆμ£ .
This turns out to be the longest creature in the oceans.
λŒ€λž΅ 150ν”ΌνŠΈ (45.7m)κ°€λŸ‰ 돼죠.
It gets up to about 150 feet long.
μ§€κΈˆ 각기 λ”°λ‘œ μ›€μ§μ΄λŠ” κ°œμ²΄λ“€μ΄ λ³΄μ΄μ‹œλ‚˜μš”?
But see all those different working things?
μ €λŠ” 이런게 λ„ˆλ¬΄ μ’‹λ”λΌκ΅¬μš”.
I love that kind of stuff.
마치 λ‚šμ‹œ 찌 같은것듀이 μ•„λž˜μ— λ‹¬λ €μ„œ κΉŒλ”±κΉŒλ”±κ±°λ¦¬μ£ 
It's got these fishing lures on the bottom. They're going up and down.
μ΄‰μˆ˜λ“€μ΄ 주렁주렁 λ‹¬λ €μ„œ μ €λ ‡κ²Œ 막 μ›€μ§μž…λ‹ˆλ‹€.
It's got tentacles dangling, swirling around like that.
이건 κ΅°μ²΄λ™λ¬Όμž…λ‹ˆλ‹€.
It's a colonial animal.
각각의 νŒŒνŠΈκ°€ λ‹€λ₯Έ 동물듀이 μ„œλ‘œ μ—°κ²°λ¨μœΌλ‘œμ¨ 이런 ν•˜λ‚˜μ˜ 생λͺ…체λ₯Ό λ§Œλ“œλŠ”κ²λ‹ˆλ‹€.
These are all individual animals banding together to make this one creature.
μ•žμ—λŠ” μ²­μ‚¬μ΄ˆλ‘±κ°™μ€κ²ƒλ„ λ‹¬λ €μžˆλŠ”λ°μš” 빛이 ν•„μš”ν•œ μˆœκ°„ μ‚¬μš©ν• μˆ˜μžˆμ£ 
And it's got these jet thrusters up in front that it'll use in a moment, and a little light.
μ§€κ΅¬μƒμ˜ λͺ¨λ“  큰 λ¬Όκ³ κΈ°λ“€κ³Ό λ¬Όκ³ κΈ° λ–Όμ˜ 무게λ₯Ό 합쳐 ν•œμͺ½ μ €μšΈμ— 달고 이런 ν•΄νŒŒλ¦¬κ³Ό 생λͺ…체λ₯Ό λ‹€λ₯Έμͺ½μ— 단닀면 이 녀석듀이 μ••λ„μ μœΌλ‘œ λ¬΄κ±°μšΈκ²λ‹ˆλ‹€.
If you take all the big fish and schooling fish and all that, put them on one side of the scale, put all the jelly-type of animals on the other side, those guys win hands down.
이런 생λͺ…체듀이 바닀속 생λͺ…μ²΄μ˜ λŒ€λ‹€μˆ˜λ₯Ό μ°¨μ§€ν•˜μ£ .
Most of the biomass in the ocean is made out of creatures like this.
이건 죽음의 μ—‘μŠ€μœ™ ν•΄νŒŒλ¦¬μΈλ°μš”
Here's the X-wing death jelly.
(μ›ƒμŒ) ꡐ미와 μ˜μ‚¬μ†Œν†΅μ„μœ„ν•΄ μ΄λ ‡κ²Œ 빛을 λ°œν•©λ‹ˆλ‹€.
(Laughter) The bioluminescence -- they use the lights for attracting mates and attracting prey and communicating.
ν•΄νŒŒλ¦¬μ— λŒ€ν•œ λ°©λŒ€ν•œ μžλ£ŒλŠ” 아직 λ³΄μ—¬λ“œλ¦¬μ§€λ„ λͺ»ν–ˆμŠ΅λ‹ˆλ‹€.
We couldn't begin to show you our archival stuff from the jellies.
ν•΄νŒŒλ¦¬λ“€μ€ λ„ˆλ¬΄λ‚˜ λ‹€μ–‘ν•œ 크기와 ν˜•νƒœλ₯Ό 가지고 있죠.
They come in all different sizes and shapes.
μš°λ¦¬λŠ” 잊곀 ν•©λ‹ˆλ‹€, λ°”λ‹€κ°€ μˆ˜μ²œλ―Έν„° μ΄μƒμ˜ κΉŠμ΄λΌλŠ”κ²ƒκ³Ό μš°λ¦¬κ°€ μ•„λŠ” λ°”λ‹€μ˜ 생λͺ…듀이 λŒ€λΆ€λΆ„μ΄ ν•΄μˆ˜λ©΄μ—μ„œ 60~100mμ΄λ‚΄μ˜ 얕은 물에 λͺ°λ €μžˆμœΌλ©° κ·Έ μ•„λž˜μ—μ„œλΆ€ν„° ν•΄μ €λ©΄κΉŒμ§€μ— λŒ€ν•΄μ„œλŠ” μ „ν˜€ λͺ¨λ₯Έλ‹€λŠ” μ‚¬μ‹€μ„μš”
Bill Lange: We tend to forget about the fact that the ocean is miles deep on average, and that we're real familiar with the animals that are in the first 200 or 300 feet, but we're not familiar with what exists from there all the way down to the bottom.
그리고 μ΄λŸ¬ν•œ 동물듀이 μš°λ¦¬κ°€ νƒν—˜ν•˜μ§€ λͺ»ν•œ μ’…λ₯˜λ“€μž…λ‹ˆλ‹€ λ°”λ‹€ λ°‘ 3차원적 κ³΅κ°„μ—μ„œ 쀑λ ₯이 거의 μ—†λŠ” ν™˜κ²½μ—μ„œ μ‚΄κ³  μžˆλŠ” 동물듀 λ§μ΄μ—μš”
And these are the types of animals that live in that three-dimensional space, that micro-gravity environment that we really haven't explored.
μ•„λ§ˆ κ±°λŒ€ μ˜€μ§•μ–΄κ°™μ€κ²ƒλ“€μ€ λ“€μ–΄λ³΄μ…¨μ„κ²λ‹ˆλ‹€ ν•˜μ§€λ§Œ 이 동물듀 쀑 μΌλΆ€λŠ” 40~50λ―Έν„°κΉŒμ§€ μžλΌλ‚˜μ£ 
You hear about giant squid and things like that, but some of these animals get up to be approximately 140, 160 feet long.
그리고 이듀은 거의 연ꡬ쑰차 λ˜μ§€ μ•Šμ•˜μ£ .
They're very little understood.
이녀석은 λ¬Έμ–΄μ²˜λŸΌ μƒκ²¨μ„œ 제일 μ’‹μ•„ν•˜λŠ” 녀석쀑 ν•˜λ‚˜μΈλ°μš”
DG: This is one of them, another one of our favorites, because it's a little octopod.
머리뢀뢄이 맀우 투λͺ…ν•©λ‹ˆλ‹€
You can actually see through his head.
그리고 νΌλŸ­μ΄λŠ” κ·€λ₯Ό μ΄μš©ν•΄μ„œ μš°μ•„ν•˜κ²Œ μˆ˜μ˜ν•©λ‹ˆλ‹€.
And here he is, flapping with his ears and very gracefully going up.
이듀 λͺ¨λ‘κ°€ λŒ€λΆ€λΆ„μ˜ ν•΄μ €λ©΄, 그리고 κ°€μž₯ κΉŠμ€ κ³³μ—μ„œλ„ λ°œκ²¬λ©λ‹ˆλ‹€.
We see those at all depths and even at the greatest depths.
μ΄λ“€μ˜ ν¬κΈ°λŠ” 2~3μ„Όν‹°λ―Έν„°λΆ€ν„° 50~60μ„Όν‹°λ―Έν„°κΉŒμ§€ λ‹€μ–‘ν•©λ‹ˆλ‹€.
They go from a couple of inches to a couple of feet.
μž μˆ˜ν•¨ λ°”λ‘œ μ•žκΉŒμ§€ μ™€μ„œλŠ” μž μˆ˜ν•¨ μ°½λ¬Έ λ„˜μ–΄ μš°λ¦¬λ“€μ„ λ°”λΌλ³΄κ³ λŠ” ν•©λ‹ˆλ‹€.
They come right up to the submarine -- they'll put their eyes right up to the window and peek inside the sub.
이건 μ™„μ „ 세상 μ†μ˜ λ˜λ‹€λ₯Έ 세상이죠. λͺ‡κ°€μ§€ 더 λ³΄μ—¬λ“œλ¦¬μ£ .
This is really a world within a world, and we're going to show you two.
μš”λ…€μ„μ€ 쀑앙해령 μ—μ„œ μ•„λž˜λ‘œ λ‚΄λ €κ°€λ˜μ€‘ λ°œκ²¬ν•œ λ…€μ„μž…λ‹ˆλ‹€. (쀑앙해령: λŒ€μ„œμ–‘, 인도양, λ‚¨νƒœν‰μ–‘μ„ κ±ΈμΉ˜λŠ” ν•΄μ €μ‚°λ§₯)
In this case, we're passing down through the mid-ocean and we see creatures like this.
바닀속 μˆ˜νƒ‰κ°™μ€ 녀석이죠
This is kind of like an undersea rooster.
μš”λ…€μ„μ€ μ–΄μ°Œλ³΄λ©΄ ꡉμž₯히 신사같아 보이죠
This guy, that looks incredibly formal, in a way.
였~ λ‚΄μ‚¬λž‘ μž˜μƒκ²Όμ£ ?
And then one of my favorites. What a face!
μ§€κΈˆ 보고 계신건 λ§ν•˜μžλ©΄ 과학적 μžλ£Œλ“€μž…λ‹ˆλ‹€.
This is basically scientific data that you're looking at.
과학적 λͺ©μ μ„ μœ„ν•΄ μš°λ¦¬κ°€ λͺ¨μ€ μžλ£Œλ“€μ΄μ£ .
It's footage that we've collected for scientific purposes.
그리고 이런 이녀석듀이 μ‚΄κ³ μžˆλŠ”κ³³μ—μ„œ 발견된 이런 λ…€μ„λ“€μ˜ 사진을 κ³Όν•™μžλ“€μ—κ²Œ μ œκ³΅ν•˜λŠ”κ²Œ Bill이 ν•˜λŠ” μ—­ν•  μ€‘μ˜ ν•˜λ‚˜μ΄κ΅¬μš”.
And that's one of the things that Bill's been doing, is providing scientists with this first view of animals like this, in the world where they belong.
μš°λ¦¬λŠ” 이 녀석듀을 μž‘μ§€λŠ” μ•ŠμŠ΅λ‹ˆλ‹€.
They don't catch them in a net.
κ·Έμ € 우린 바라볼 뿐이거죠.
They're actually looking at them down in that world.
그럼 μ‘°μ΄μŠ€ν‹±μ„ μ΄μš©ν•΄μ„œ 우리의 가상 지ꡬλ₯Ό νƒν—˜ν•΄λ³΄κ² μŠ΅λ‹ˆλ‹€ μ‘°μ΄μŠ€ν‹±μ„ μ΄μš©ν•΄ 지ꡬ μ—¬κΈ°μ €κΈ°λ₯Ό λ°”λΌλ³΄λŠ”κ±΄λ°μš”.
We're going to take a joystick, sit in front of our computer, on the Earth, and press the joystick forward, and fly around the planet.
μ€‘μ•™ν•΄λ Ήμ˜ 산등성이λ₯Ό λŒμ•„λ‹€λ…€λ³΄κ² μŠ΅λ‹ˆλ‹€. 64,000Km 길이의 λŒ€μ‚°λ§₯이죠
We're going to look at the mid-ocean ridge, a 40,000-mile long mountain range.
ν•΄λ Ήμ •μƒμ—μ„œ μˆ˜λ©΄κΉŒμ§€μ˜ 평균 κΉŠμ΄λŠ” 2.4Km 정도 λ©λ‹ˆλ‹€.
The average depth at the top of it is about a mile and a half.
λŒ€μ„œμ–‘μ„ κ±°μ³μ„œ..μ•„ μ €κΈ° μ‚° 등성이가 보이죠 μΊλ¦¬λΉ„μ•ˆν•΄μ™€ 쀑앙 아메리카λ₯Ό λ„˜μ–΄μ„œ μ—¬κΈ° νƒœν‰μ–‘μ—μ„œ 끝이 λ‚©λ‹ˆλ‹€. 뢁μͺ½μœΌλ‘œ 9λ„κ°€λŸ‰ λ˜λ„€μš”.
And we're over the Atlantic -- that's the ridge right there -- but we're going to go across the Caribbean, Central America, and end up against the Pacific, nine degrees north.
μ €ν¬λŠ” μˆ˜μ€‘ μŒνŒŒνƒμ§€κΈ°λ₯Ό λ™μ›ν•΄μ„œ 이 ν•΄μ € μ‚°λ§₯λ“€μ˜ 지도λ₯Ό μž‘μ„±ν–ˆμŠ΅λ‹ˆλ‹€. 그리고 이게 그쀑 일뢀이죠.
We make maps of these mountain ranges with sound, with sonar, and this is one of those mountain ranges.
우린 μ§€κΈˆ 였λ₯ΈνŽΈ ν•΄μ € μ ˆλ²½μ„ 타고 κ°€κ³ μžˆλŠ”λ°μš”
We're coming around a cliff here on the right.
이 μ–‘μͺ½ κ³„κ³‘μ˜ μ‚°λ΄‰μš°λ¦¬λ“€μ˜ λ†’μ΄λŠ” λŒ€λΆ€λΆ„ μ•Œν”„μŠ€μ‚°λ§₯보닀 훨씬 λ†’μŠ΅λ‹ˆλ‹€.
The height of these mountains on either side of this valley is greater than the Alps in most cases.
그리고 아직 수백 μˆ˜μ²œκ°œμ— 이λ₯΄λŠ” ν•΄μ €μ‚°λ§₯듀이 아직 μ§€λ„ν™”λ˜μ§€ μ•Šμ€ 채 λ‚¨μ•„μžˆμŠ΅λ‹ˆλ‹€.
And there's tens of thousands of those mountains out there that haven't been mapped yet.
μ—¬κΈ΄ ν™”μ‚°μ§€μ—­μΈλ°μš”
This is a volcanic ridge.
척도λ₯Ό ν™•λŒ€ν•΄ 내렀가닀보면
We're getting down further and further in scale.
κ²°κ΅­ μ΄λŸ°κ³³μ— λ‹€λ‹€λ₯΄κ²Œ λ©λ‹ˆλ‹€.
And eventually, we can come up with something like this.
이건 우리 λ‘œλ΄‡ Jason의 μ•„μ΄μ½˜μΈλ°μš”
This is an icon of our robot, Jason, it's called.
μ—¬λŸ¬λΆ„λ„ μ΄λ ‡κ²Œ 방에 앉아 μ‘°μ΄μŠ€ν‹±κ³Ό ν—€λ“œμ…‹μ„ μ΄μš©ν•΄ λ‘œλ΄‡μ„ 타고 μ‹€μ œλ‘œ ν•΄μ €λ°”λ‹₯을 μ‹€μ‹œκ°„μœΌλ‘œ λŒμ•„λ‹€λ‹ 수 μžˆμŠ΅λ‹ˆλ‹€.
And you can sit in a room like this, with a joystick and a headset, and drive a robot like that around the bottom of the ocean in real time.
저희가 Woods Holeμ—μ„œ νŒŒνŠΈλ„ˆλ“€κ³Ό μ§„ν–‰ν•˜λ €λŠ” μž‘μ—… 쀑 ν•˜λ‚˜κ°€ 이런 κ°€μƒμ˜ 세계λ₯Ό 아직 νƒμ‚¬λ˜μ§€ μ•Šμ€ 지역듀을, μ‹€ν—˜μ‹€λ‘œ λ‹€μ‹œ κ°€μ Έμ˜€λŠ”κ±°μ£ .
One of the things we're trying to do at Woods Hole with our partners is to bring this virtual world -- this world, this unexplored region -- back to the laboratory.
μ™œλƒλ©΄ μ§€κΈˆμ€ μžλ£Œκ°€ μž‘μ€ λΆ€λΆ„λ“€λ‘œ 흩어져 있기 λ•Œλ¬Έμ΄μ£ 
Because we see it in bits and pieces right now.
μ΄λ ‡κ²Œ μ†Œλ¦¬, λΉ„λ””μ˜€, 사진, ν˜Ήμ€ 화학적 μ„Όμ„œλ₯Ό μ΄μš©ν•œ μžλ£Œλ“€μ„ λͺ¨μ•˜μ§€λ§Œ λͺ¨λ“ κ±Έ 아직 μ™„λ²½ν•œ ν•œμž₯의 κ·Έλ¦ΌμœΌλ‘œλŠ” λ§Œλ“€μ§€ λͺ»ν–ˆμŠ΅λ‹ˆλ‹€.
We see it either as sound, or we see it as video, or we see it as photographs, or we see it as chemical sensors, but we never have yet put it all together into one interesting picture.
이게 Bill의 카메라가 κ°€μž₯ 빛을 λ°œν•˜λ˜ λ‚ μΈλ°μš”
Here's where Bill's cameras really do shine.
이게 λ°”λ‘œ ν•΄μ € λΆ„μΆœκ³΅ μž…λ‹ˆλ‹€.
This is what's called a hydrothermal vent.
그리고 이건 μˆ˜μ†Œμ™€ ν™©ν™”λ¬Όλ“€λ‘œ 가득 μ°¨μžˆλŠ” μ—°κΈ°μž…λ‹ˆλ‹€. μ‹¬ν•΄μ˜ ν™”μ‚°μ§€μ—­μ—μ„œ λΏœμ–΄μ Έ λ‚˜μ˜€λŠ”κ²ƒλ“€μΈλ°μš”
And what you're seeing here is a cloud of densely packed, hydrogen-sulfide-rich water coming out of a volcanic axis on the sea floor.
μ˜¨λ„λŠ” 섭씨 310 ~ 380도 κ°€λŸ‰ λ˜κ΅¬μš”
Gets up to 600, 700 degrees F, somewhere in that range.
λͺ¨λ‘ λ°”λ‹€ μ•„λž˜ 1.5~3λ§ˆμΌμ—μ„œ λ°œκ²¬ν•  수 μžˆλŠ” κ²ƒμž…λ‹ˆλ‹€.
So that's all water under the sea -- a mile and a half, two miles, three miles down.
μ €ν¬λŠ” 이게 60, 70λ…„λŒ€μ˜ 화산듀이라 μƒκ°ν–ˆλŠ”λ°μš”
And we knew it was volcanic back in the '60s, '70s.
μ–΄μ©Œλ‹€ 이게 μ•„μ§κΉŒμ§€ μ‘΄μž¬ν•œλ‹€λŠ” 힌트λ₯Ό 얻을 수 μžˆμ—ˆμŠ΅λ‹ˆλ‹€. ν™”μ‚°ν™œλ™μ΄ 있으면 물이 심해 λ°”λ‹₯의 ν‹ˆμœΌλ‘œ λ“€μ–΄κ°€λŠ”λ°μš” λ•Œλ¬Έμ— 물이 λ§ˆκ·Έλ§ˆμ™€ λ§Œλ‚˜κ²Œ 되면 이 좕을 따라 열을 λ°œμ‚°ν•˜κ²Œ λ©λ‹ˆλ‹€.
And then we had some hint that these things existed all along the axis of it, because if you've got volcanism, water's going to get down from the sea into cracks in the sea floor, come in contact with magma, and come shooting out hot.
μ €ν¬λŠ” ν™©ν™”μˆ˜μ†Œκ°€ κ·Έλ ‡κ²Œ ν’λΆ€ν•˜λ¦¬λΌκ³  μƒκ°μΉ˜λŠ” μ•Šμ•˜μŠ΅λ‹ˆλ‹€.
We weren't really aware that it would be so rich with sulfides, hydrogen sulfides.
'꡴뚝'이라고 μš°λ¦¬κ°€ λΆ€λ₯΄λŠ” 이것에 λŒ€ν•΄, μš°λ¦¬λŠ” μ „ν˜€ λͺ¨λ₯΄κ³  μžˆμ—ˆμŠ΅λ‹ˆλ‹€.
We didn't have any idea about these things, which we call chimneys.
이것이 μ—΄μˆ˜ λΆ„μΆœκ³΅ 쀑 ν•˜λ‚˜μž…λ‹ˆλ‹€.
This is one of these hydrothermal vents.
화씨 600λ„μ˜ 물이 μ§€κ΅¬λ‘œλΆ€ν„° λΆ„μΆœλ©λ‹ˆλ‹€.
Six hundred degree F water coming out of the Earth.
우리 μ–‘ μ˜†μœΌλ‘œλŠ” μ•Œν”„μŠ€λ³΄λ‹€ 더 높은 산이 μžˆμŠ΅λ‹ˆλ‹€. κ·Έλž˜μ„œ 이곳의 ν™˜κ²½μ€ 맀우 λ“œλΌλ§ˆν‹±ν•˜μ£ .
On either side of us are mountain ranges that are higher than the Alps, so the setting here is very dramatic.
이 ν•˜μ–€ λ¬Όμ§ˆμ€ λ°•ν…Œλ¦¬μ•„μ˜ μΌμ’…μΈλ°μš” 섭씨 180λ„μ—μ„œ 잘 μžλžλ‹ˆλ‹€.
BL: The white material is a type of bacteria that thrives at 180 degrees C.
κ°€μž₯ ν₯미둜운 점은 λ°”λ‘œ μš°λ¦¬κ°€ ν•΄μ €λ©΄μ—μ„œ λ³΄λŠ” 것, κ·ΈλŸ¬λ‹ˆκΉŒ λ°”λ‹€ μ†μ—μ„œμ˜ ν™”μ‚° 폭발 이후에 κ°€μž₯ 처음 λ³΄λŠ” 것이 λ°•ν…Œλ¦¬μ•„ λΌλŠ” κ±°μ£ .
DG: I think that's one of the greatest stories right now that we're seeing from the bottom of the sea, is that the first thing we see coming out of the sea floor after a volcanic eruption is bacteria.
그리고 μš°λ¦¬λŠ” 이게 λŒ€μ²΄ 여기에 μ–΄λ–»κ²Œ λ‚΄λ €μ™”μ„κΉŒμ— λŒ€ν•΄ μ•„μ£Ό μ˜€λž«λ™μ•ˆ κΆκΈˆν•΄ν–ˆμŠ΅λ‹ˆλ‹€.
And we started to wonder for a long time, how did it all get down there?
ν˜„μž¬λ‘œμ„œ 저희가 μ°Ύμ•„λ‚Έ 것은 μ•„λ§ˆ 지ꡬ μ†μ—μ„œ λ‚˜μ˜€μ§€ μ•Šμ„κΉŒ ν•˜λŠ” κ²ƒμž…λ‹ˆλ‹€.
What we find out now is that it's probably coming from inside the Earth.
단지 지ꡬ μ†μ—μ„œ λ‚˜μ˜¬ 뿐 μ•„λ‹ˆλΌ κ·ΈλŸ¬λ‹ˆκΉŒ, ν™”μ‚° ν™œλ™μ„ 톡해 λ§Œλ“€μ–΄μ§„ 생물일 뿐만 μ•„λ‹ˆλΌ 이 λ°•ν…Œλ¦¬μ•„λ“€μ΄ 생물 ꡰ락 ν˜•μ„±μ„ λ’·λ°›μΉ¨ν•œλ‹€λŠ” κ±°μ£ .
Not only is it coming out of the Earth -- so, biogenesis made from volcanic activity -- but that bacteria supports these colonies of life.
이곳의 μ••λ ₯은 1ν‰λ°©μΈμΉ˜λ‹Ή 4000νŒŒμš΄λ“œμž…λ‹ˆλ‹€.
The pressure here is 4,000 pounds per square inch.
ν•΄μˆ˜λ©΄μœΌλ‘œλΆ€ν„° 0.5~3마일 μ•„λž˜λΆ€ν„°λŠ” 햇볕이 단 ν•œ λ²ˆλ„ λΉ„μΆ˜ 적이 μ—†μŠ΅λ‹ˆλ‹€.
A mile and a half from the surface to two miles to three miles -- no sun has ever gotten down here.
생λͺ…체λ₯Ό κ΅¬μ„±ν•˜λŠ” λͺ¨λ“  μ—λ„ˆμ§€λŠ” μ§€κ΅¬λ‚΄λΆ€λ‘œλΆ€ν„° λ‚˜μ˜΅λ‹ˆλ‹€, 즉 화학합성이죠.
All the energy to support these life forms is coming from inside the Earth -- so, chemosynthesis.
μš°λ¦¬λŠ” 생λͺ…μ²΄λ“€μ˜ 밀집도가 μƒλ‹Ήνžˆ λ†’λ‹€λŠ” 것도 μ•Œ 수 μžˆμŠ΅λ‹ˆλ‹€.
And you can see how dense the population is.
이것듀은 μ„œκ΄€μΆ©μ΄λΌκ³  ν•˜λŠ”λ°μš”.
These are called tube worms.
이 λ²Œλ ˆλ“€μ€ μ†Œν™”κΈ°κ΄€μ΄ μ—†μŠ΅λ‹ˆλ‹€. μž…λ„ μ—†μ£ .
BL: These worms have no digestive system. They have no mouth.
ν•˜μ§€λ§Œ 이듀은 두 μ’…λ₯˜μ˜ μ•„κ°€λ―Έ ꡬ쑰λ₯Ό 가지고 μžˆμŠ΅λ‹ˆλ‹€.
But they have two types of gill structures.
ν•˜λ‚˜λŠ” μ‹¬ν•΄μˆ˜λ‘œλΆ€ν„° μ‚°μ†Œλ₯Ό μ–»μ–΄λ‚΄κΈ° μœ„ν•œ 것이고, λ‹€λ₯Έ ν•˜λ‚˜λŠ” 이런 ν™”ν•™ν•©μ„± λ°•ν…Œλ¦¬μ•„μ˜ 집 역할을 ν•˜λŠ” κ²ƒμž…λ‹ˆλ‹€. μ—΄μˆ˜μ˜ 흐름을 μž‘λŠ” κ±΄λ°μš” λ°”λ‹₯μ—μ„œ μ˜¬λΌμ˜€λŠ” 뜨거운 물이 λ³΄μ΄λŠ”λ°μš” 그러면 κ·Έκ±Έ λ‹¨μˆœλ‹Ή ν˜•νƒœλ‘œ λ°”κΏ”μ„œ μ„œκ΄€μΆ©μ΄ μ†Œν™” ν•  수 μžˆλ„λ‘ ν•˜λŠ” 것이죠
One for extracting oxygen out of the deep-sea water, another one which houses this chemosynthetic bacteria, which takes the hydrothermal fluid -- that hot water that you saw coming out of the bottom -- and converts that into simple sugars that the tube worm can digest.
λ³΄μ΄μ‹œμ£ - 이 μ•„λž˜μ— μ‚΄κ³  μžˆλŠ” κ²Œμž…λ‹ˆλ‹€.
DG: You can see, here's a crab that lives down there.
이런 벌레 끝을 κ°€κΉŒμŠ€λ‘œ μž‘μ•˜μŠ΅λ‹ˆλ‹€
He's managed to grab a tip of these worms.
보톡 λ²Œλ ˆλ“€μ€ κ²Œμ— λ‹Ώμžλ§ˆμž ν™• μ›€μΈ λŸ¬ λ“€μ£ 
Now, they normally retract as soon as a crab touches them.
YAML Metadata Warning: The task_categories "conditional-text-generation" is not in the official list: text-classification, token-classification, table-question-answering, question-answering, zero-shot-classification, translation, summarization, feature-extraction, text-generation, text2text-generation, fill-mask, sentence-similarity, text-to-speech, text-to-audio, automatic-speech-recognition, audio-to-audio, audio-classification, voice-activity-detection, depth-estimation, image-classification, object-detection, image-segmentation, text-to-image, image-to-text, image-to-image, image-to-video, unconditional-image-generation, video-classification, reinforcement-learning, robotics, tabular-classification, tabular-regression, tabular-to-text, table-to-text, multiple-choice, text-retrieval, time-series-forecasting, text-to-video, image-text-to-text, visual-question-answering, document-question-answering, zero-shot-image-classification, graph-ml, mask-generation, zero-shot-object-detection, text-to-3d, image-to-3d, image-feature-extraction, other
YAML Metadata Warning: The task_ids "machine-translation" is not in the official list: acceptability-classification, entity-linking-classification, fact-checking, intent-classification, language-identification, multi-class-classification, multi-label-classification, multi-input-text-classification, natural-language-inference, semantic-similarity-classification, sentiment-classification, topic-classification, semantic-similarity-scoring, sentiment-scoring, sentiment-analysis, hate-speech-detection, text-scoring, named-entity-recognition, part-of-speech, parsing, lemmatization, word-sense-disambiguation, coreference-resolution, extractive-qa, open-domain-qa, closed-domain-qa, news-articles-summarization, news-articles-headline-generation, dialogue-modeling, dialogue-generation, conversational, language-modeling, text-simplification, explanation-generation, abstractive-qa, open-domain-abstractive-qa, closed-domain-qa, open-book-qa, closed-book-qa, slot-filling, masked-language-modeling, keyword-spotting, speaker-identification, audio-intent-classification, audio-emotion-recognition, audio-language-identification, multi-label-image-classification, multi-class-image-classification, face-detection, vehicle-detection, instance-segmentation, semantic-segmentation, panoptic-segmentation, image-captioning, image-inpainting, image-colorization, super-resolution, grasping, task-planning, tabular-multi-class-classification, tabular-multi-label-classification, tabular-single-column-regression, rdf-to-text, multiple-choice-qa, multiple-choice-coreference-resolution, document-retrieval, utterance-retrieval, entity-linking-retrieval, fact-checking-retrieval, univariate-time-series-forecasting, multivariate-time-series-forecasting, visual-question-answering, document-question-answering

Dataset Card for english-korean-multitarget-ted-talks-task

Dataset Summary

  • Parallel English-Korean Text Corpus
  • Text was originally transcribed to English from various Ted Talks, then translated to Korean by TED translators
  • Approximately 166k train, 2k validation, and 2k test sentence pairs.

Supported Tasks and Leaderboards

  • Machine Translation

Languages

  • English
  • Korean

Additional Information

Dataset Curators

Kevin Duh, "The Multitarget TED Talks Task", http://www.cs.jhu.edu/~kevinduh/a/multitarget-tedtalks/, 2018

Licensing Information

TED makes its collection available under the Creative Commons BY-NC-ND license. Please acknowledge TED when using this data. We acknowledge the authorship of TED Talks (BY condition). We are not redistributing the transcripts for commercial purposes (NC condition) nor making derivative works of the original contents (ND condition).

Citation Information

@misc{duh18multitarget, author = {Kevin Duh}, title = {The Multitarget TED Talks Task}, howpublished = {\url{http://www.cs.jhu.edu/~kevinduh/a/multitarget-tedtalks/}}, year = {2018}, }

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