Making a TED-Ed Lesson: Visualizing big ideas

228,855 views ใƒป 2013-11-25

TED-Ed


ืื ื ืœื—ืฅ ืคืขืžื™ื™ื ืขืœ ื”ื›ืชื•ื‘ื™ื•ืช ื‘ืื ื’ืœื™ืช ืœืžื˜ื” ื›ื“ื™ ืœื”ืคืขื™ืœ ืืช ื”ืกืจื˜ื•ืŸ.

ืžืชืจื’ื: Ido Dekkers ืžื‘ืงืจ: Boaz Hovav
00:06
Do you ever struggle to find the perfect description
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ื”ืื ืืชื ืื™ ืคืขื ืžืชืืžืฆื™ื ืœืžืฆื•ื ืืช ื”ืชื™ืื•ืจ ื”ืžื•ืฉืœื
00:08
when trying to convey an idea?
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ื›ืฉืืชื ืžื ืกื™ื ืœื”ืขื‘ื™ืจ ืจืขื™ื•ืŸ?
00:10
Like a foggy picture,
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ื›ืžื• ืชืžื•ื ื” ืžืขื•ืจืคืœืช,
00:12
adjectives and modifiers fail to depict
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ืคืขืœื™ื ื•ืฉืžื•ืช ืชื•ืืจ ืœื ืžืฆืœื™ื—ื™ื ืœืชืืจ
00:14
what's in your mind.
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ืžื” ื™ืฉ ืœื›ื ื‘ืจืืฉ.
00:15
Illustrators often face a similar challenge,
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ืžืื™ื™ืจื™ื ืขื•ืžื“ื™ื ื”ืจื‘ื” ืคืขืžื™ื ืœืคื ื™ ืืชื’ืจื™ื ื“ื•ืžื™ื,
00:18
especially when attempting to explain
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ื‘ืขื™ืงืจ ื›ืฉื”ื ืžื ืกื™ื ืœื”ืกื‘ื™ืจ
00:20
complex and difficult concepts.
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ืจืขื™ื•ื ื•ืช ืžื•ืจื›ื‘ื™ื ื•ืงืฉื™ื.
00:22
Sometimes the imagery is intangible
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ืœืคืขืžื™ื ื”ืชืžื•ื ื•ืช ื”ืŸ ืœื ืžื•ื—ืฉื™ื•ืช
00:24
or way too complicated to explain with a picture.
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ืื• ืžืกื•ื‘ื›ื•ืช ืžื“ื™ ืœื”ืกื‘ืจ ื‘ืชืžื•ื ื”.
00:28
Although complex information could be relayed
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ืœืžืจื•ืช ืฉืžื™ื“ืข ืžื•ืจื›ื‘ ื™ื›ื•ืœ ืœื”ื™ื•ืช ืžื•ืขื‘ืจ
00:31
using charts and stats,
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ื‘ืฉื™ืžื•ืฉ ื‘ื’ืจืคื™ื ื•ื ืชื•ื ื™ื,
00:33
this could get pretty boring.
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ื–ื” ื™ื›ื•ืœ ืœื”ื™ื•ืช ื“ื™ ืžืฉืขืžื.
00:34
Instead, just like when writing an essay
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ื‘ืžืงื•ื ื–ืืช, ื‘ื“ื™ื•ืง ื›ืžื• ืฉืืชื ื›ื•ืชื‘ื™ื ื—ื™ื‘ื•ืจ
00:36
to describe, for example, emotions,
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ื›ื“ื™ ืœืชืืจ, ืœื“ื•ื’ืžื”, ืชื—ื•ืฉื•ืช,
00:39
illustrators can use visual metaphors
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ืื™ื•ืจื™ื ื™ื›ื•ืœื™ื ืœืฉืžืฉ ื›ืžื˜ืืคื•ืจื•ืช ื•ื™ื–ื•ืืœื™ื•ืช
00:41
to bring to life difficult concepts.
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ื›ื“ื™ ืœื”ื‘ื™ื ืœื—ื™ื™ื ืจืขื™ื•ื ื•ืช ืžื•ืจื›ื‘ื™ื.
00:44
Just as a written metaphor is a description
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ื‘ื“ื™ื•ืง ื›ืžื• ืฉืžื˜ืืคื•ืจื” ื›ืชื•ื‘ื” ื”ื™ื ืชืื•ืจ
00:46
that relates one object to another,
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ืฉืžื™ื™ื—ืก ืชื›ื•ื ื” ืฉืœ ืขืฆื ืื—ื“ ืœืื—ืจ,
00:48
a visual metaphor uses imagery to suggest
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ืžื˜ืืคื•ืจื” ื•ื™ื–ื•ืืœื™ืช ืžืฉืชืžืฉืช ื‘ืชืžื•ื ื•ืช ื›ื“ื™ ืœื”ืฆื™ืข
00:51
a particular association or point of similarity.
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ืงืฉืจ ืžืกื•ื™ื ืื• ื ืงื•ื“ื•ืช ื“ืžื™ื•ืŸ.
ืื™ืš ื ื™ืชืŸ ืœืชืืจ ื‘ืชืžื•ื ื•ืช ืžืฉื”ื• ืฉืงืฉื” ืœื ื• ืœื”ืกื‘ื™ืจ?
00:59
Our lesson "Big Data" is a great example
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ื”ืฉื™ืขื•ืจ ืฉืœื ื• "ื‘ื™ื’ ื“ืื˜ื”" ื”ื•ื ื“ื•ื’ืžื” ืžืขื•ืœื”
01:01
of a situation where visual metaphors
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ืœืžืฆื‘ ื‘ื• ืžื˜ืืคื•ืจื•ืช ื•ื™ื–ื•ืืœื™ื•ืช
01:03
played a huge role in explaining the concept.
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ืžืฉื—ืงื•ืช ืชืคืงื™ื“ ื’ื“ื•ืœ ื‘ื”ืกื‘ืจืช ื”ืงื•ื ืกืคื˜.
01:06
What is Big Data in the first place?
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ืžื” ื”ื•ื ื‘ื™ื’ ื“ืื˜ื” ืงื•ื“ื ื›ืœ?
01:09
Good question!
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ืฉืืœื” ื˜ื•ื‘ื”!
01:10
Big Data is a huge amount of digital information
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ื‘ื™ื’ ื“ืื˜ื” ื”ื•ื ื›ืžื•ืช ืขืฆื•ืžื” ืฉืœ ืžื™ื“ืข ื“ื™ื’ื™ื˜ืœื™
01:13
produced worldwide on a daily basis,
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ืฉืžื™ื•ืฆืจ ื‘ืขื•ืœื ืขืœ ื‘ืกื™ืก ื™ื•ื ื™ื•ืžื™,
01:15
challenging us to find solutions
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ื•ืžืืชื’ืจ ืื•ืชื ื• ืœืžืฆื•ื ืคืชืจื•ื ื•ืช
01:17
for storing,
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ืœืื›ืกื•ืŸ,
01:18
analyzing,
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ื ื™ืชื•ื—,
01:19
and also imagining it visually.
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ื•ื’ื ืœื“ืžื™ื™ืŸ ืื•ืชื• ื•ื™ื–ื•ืืœื™ืช.
01:22
Quite an elusive concept!
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ืจืขื™ื•ืŸ ื“ื™ ื—ืžืงื ื™!
01:24
How should we depict this?
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ืื™ืš ื ืžื—ื™ืฉ ืื•ืชื•?
ืจืืฉื™ืช: ืขื™ื™ื ื• ื‘ืžื™ืœื™ื ื‘ืชืกืจื™ื˜ ื•ืชืจืื• ืื ืืชื ืžื“ืžื™ื™ื ื™ื ืชืžื•ื ื•ืช ืžืชืื™ืžื•ืช
ื‘ื•ืื• ื ืจืื” ืืช ืชืกืจื™ื˜ ื”ื‘ื™ื’ ื“ืื˜ื” ืฉืœื ื•.
01:30
Let's take a look at our "Big Data" script.
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01:32
We start with smaller computer servers
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ื ืชื—ื™ืœ ืขื ืฉืจืชื™ ืžื—ืฉื‘ ืงื˜ื ื™ื
01:34
that branch out into bigger networks
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ืฉืžืกืชืขืคื™ื ืœืจืฉืชื•ืช ื’ื“ื•ืœื•ืช ื™ื•ืชืจ
01:36
to produce data,
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ืœื™ืฆื•ืจ ื“ืื˜ื” (ื ืชื•ื ื™ื),
01:37
then even bigger networks
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ื•ืื– ืจืฉืชื•ืช ื™ื•ืชืจ ื’ื“ื•ืœื•ืช
01:38
and production of even more data.
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ื•ื™ื™ืฆื•ืจ ืฉืœ ืืคื™ืœื• ื™ื•ืชืจ ืžื™ื“ืข.
01:41
You see where we're going with this --
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ืืชื ืžื‘ื™ื ื™ื ืœืืŸ ืื ื—ื ื• ื”ื•ืœื›ื™ื ืขื ื–ื” --
01:42
an object growing and branching out in many directions
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ืขืฆื ืฉื’ื“ืœ ื•ืžืชืจื—ื‘ ืœื”ืจื‘ื” ื›ื™ื•ื•ื ื™ื
01:45
and producing something as a result?
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ื•ืžื™ื™ืฆืจ ืชื•ืฆืื•ืช?
01:48
Does that remind you of something?
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ื”ืื ื–ื” ืžื–ื›ื™ืจ ืœื›ื ืžืฉื”ื•?
01:49
Just like those computer networks,
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ื‘ื“ื™ื•ืง ื›ืžื• ืจืฉืชื•ืช ืžื—ืฉื‘ื™ื,
01:51
a tree grows and branches out
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ืขืฅ ื’ื“ืœ ื•ืžืชืขื ืฃ
01:53
to produce more leaves each year.
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ื›ื“ื™ ืœื™ืฆื•ืจ ื™ื•ืชืจ ืขืœื™ื ื›ืœ ืฉื ื”.
01:56
And every year, just as the data accumulates
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ื•ื›ืœ ืฉื ื”, ื‘ื“ื™ื•ืง ื›ืžื• ืฉืžื™ื“ืข ืžืฆื˜ื‘ืจ
01:58
and faces us with a challenge
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ื•ืžืขืžื™ื“ ื‘ืคื ื™ื ื• ืืชื’ืจื™ื
02:00
to find storage solutions,
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ืœืžืฆื•ื ืคืชืจื•ื ื•ืช ืื›ืกื•ืŸ,
02:01
it gets harder to collect those piles of leaves
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ื–ื” ื ืขืฉื” ืงืฉื” ื™ื•ืชืจ ืœืืกื•ืฃ ืืช ื›ืœ ืขืจืžื•ืช ื”ืขืœื™ื
02:03
when they fall off the tree.
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ื›ืฉื”ื ื ื•ืคืœื™ื ืžื”ืขืฆื™ื.
02:05
Aha! There's our visual metaphor!
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ืื”ื! ื”ื ื” ื”ืžื˜ืืคื•ืจื” ื”ื•ื™ื–ื•ืืœื™ืช ืฉืœื ื•!
ื”ืฉืœื‘ ื”ื‘ื: ืคืชื—ื• ืกื’ื ื•ืŸ ืฆื™ื•ืจ ื•ืขื™ืฆื•ื‘ ืœื“ืžื•ื™ื•ืช ื•ืœืกื‘ื™ื‘ืช ื”ืกืจื˜ื•ืŸ
02:11
Okay, so we have the script,
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ืื•ืงื™ื™, ืื– ื™ืฉ ืœื ื• ืืช ื”ืชืกืจื™ื˜,
02:13
audio,
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ืฆืœื™ืœื™ื,
02:14
and a visual metaphor.
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ื•ืžื˜ืืคื•ืจื” ื•ื™ื–ื•ืืœื™ื•ืช.
02:15
The next step in visual development
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ื”ืฆืขื“ ื”ื‘ื ื‘ืคื™ืชื•ื— ื•ื™ื–ื•ืืœื™
02:17
is to design the characters
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ื”ื•ื ืœืขืฆื‘ ืืช ื”ื“ืžื•ื™ื•ืช
02:18
and environments of the animation.
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ื•ื”ืกื‘ื™ื‘ื•ืช ืฉืœ ื”ืื ื™ืžืฆื™ื”.
02:20
To do so, we think
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ื›ื“ื™ ืœืขืฉื•ืช ืืช ื–ื”, ืื ื—ื ื• ื—ื•ืฉื‘ื™ื
02:22
of an appropriate and appealing style
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ืขืœ ืขื™ืฆื•ื‘ ืžืชืื™ื ื•ืžื•ืฉืš
02:23
to illustrate the ideas
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ื›ื“ื™ ืœื”ืžื—ื™ืฉ ืืช ื”ืจืขื™ื•ื ื•ืช
02:25
and help the viewer better understand
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ื•ืœืขื–ื•ืจ ืœืฆื•ืคื” ืœื”ื‘ื™ืŸ ื˜ื•ื‘ ื™ื•ืชืจ
02:26
what they're hearing.
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ืžื” ื”ื ืฉื•ืžืขื™ื.
02:28
Let's go back to the script
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ื‘ื•ืื• ื ื—ื–ื•ืจ ืœืชืกืจื™ื˜
02:29
and see if we can find any clues there.
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ื•ื ืจืื” ืื ืื ื—ื ื• ื™ื›ื•ืœื™ื ืœืžืฆื•ื ืจืžื–ื™ื ืฉื.
02:32
Our story starts in the 1960s
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ื”ืกื™ืคื•ืจ ืฉืœื ื• ืžืชื—ื™ืœ ื‘ืฉื ื•ืช ื”- 60 ืฉืœ ื”ืžืื” ื”- 20
02:34
when the first computer networks were built.
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ื›ืฉืจืฉืชื•ืช ื”ืžื—ืฉื‘ื™ื ื”ืจืืฉื•ื ื•ืช ื ื‘ื ื•.
02:36
This decade will serve as a good point
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ื”ืขืฉื•ืจ ื”ื–ื” ื™ืฉืžืฉ ื›ื ืงื•ื“ื” ื˜ื•ื‘ื”
02:38
to make the stylistic choice for our animation
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ืœื‘ื—ื™ืจืช ื”ืกื’ื ื•ืŸ ื‘ืกืจื˜ื•ืŸ ื”ืื ื™ืžืฆื™ื” ืฉืœื ื•
02:41
as it will allow us to refer to artwork
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ืžืื—ืจ ื•ื”ื•ื ื™ืืคืฉืจ ืœื ื• ืœืขืฆื‘ ืกื’ื ื•ืŸ ื”ื“ื•ืžื” ืœืขื‘ื•ื“ื•ืช ืื•ืžื ื•ืช
02:43
from that era.
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ืžื”ืชืงื•ืคื” ื”ื”ื™ื.
02:44
You may want to start
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ื›ื“ืื™ ืœื›ื ืœื”ืชื—ื™ืœ
02:45
by looking at some art books
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ื‘ืœื”ื‘ื™ื˜ ื‘ื›ืžื” ืกืคืจื™ ืื•ืžื ื•ืช
02:46
(design, illustrations, cartoons, etc.)
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(ืขื™ืฆื•ื‘, ืื™ื•ืจ, ืงืจื™ืงื˜ื•ืจื•ืช, ื•ื›ื•')
02:49
from that era
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ืžื”ืชืงื•ืคื” ื”ื”ื™ื
02:50
and find a style that may our own purpose.
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ื•ืœืžืฆื•ื ืกื’ื ื•ืŸ ืฉืื•ืœื™ ื™ืชืื™ื ืœืžื˜ืจื” ืฉืœื ื•.
02:53
Look closely,
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ืขื™ื™ื ื• ื‘ืกื‘ืœื ื•ืช,
02:54
study the material,
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ืœืžื“ื• ืืช ื”ื—ื•ืžืจ,
02:55
and try to understand the choices
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ื•ื ืกื• ืœื”ื‘ื™ืŸ ืืช ื”ื‘ื—ื™ืจื•ืช
02:56
artists of that time made and why.
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ืฉืื•ืžื ื™ื ืžืื•ืชื” ืชืงื•ืคื” ืขืฉื• ื•ืœืžื” ื”ื ืขืฉื• ืื•ืชืŸ?
02:59
For example, the 1960s minimalist animation style
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ืœื“ื•ื’ืžื”, ื”ืกื’ื ื•ืŸ ื”ืžื™ื ื™ืžืœื™ืกื˜ื™ ืฉืœ ืื ื™ืžืฆื™ื” ื‘ืฉื ื•ืช ื”- 60
03:03
was a significant departure
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ื”ื™ื” ืฉื•ื ื” ื‘ืื•ืคืŸ ืžืฉืžืขื•ืชื™
03:04
from the cinematic realism
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ืžื”ืกื’ื ื•ืŸ ื”ืจื™ืืœื™ืกื˜ื™
03:06
that was popular in animated films at the time.
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ืฉื”ื™ื” ืคื•ืคื•ืœืจื™ ื‘ืกืจื˜ื™ ืื ื™ืžืฆื™ื” ื‘ืื•ืชื• ื”ื–ืžืŸ.
03:08
The choice to use limited animation techniques
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ื”ื‘ื—ื™ืจื” ืœื”ืฉืชืžืฉ ื‘ื˜ื›ื ื™ืงื•ืช ืื ื™ืžืฆื™ื” ืžื•ื’ื‘ืœื•ืช
03:11
was originally made for budgetary reasons,
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ื”ื™ืชื” ื‘ืžืงื•ืจ ืžืกื™ื‘ื” ืชืงืฆื™ื‘ื™ืช,
03:13
but it became a signature style
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ืื‘ืœ ื”ืคื›ื” ืœืกื’ื ื•ืŸ ืื•ืคื™ื™ื ื™ ื•ื™ื™ื—ื•ื“ื™
03:15
that influenced many future generations of animators.
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ืฉื”ืฉืคื™ืข ืขืœ ื“ื•ืจื•ืช ืขืชื™ื“ื™ื™ื ืฉืœ ืื ื™ืžื˜ื•ืจื™ื.
03:18
In this stylistic approach,
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ื‘ื’ื™ืฉื” ื”ืขื™ืฆื•ื‘ื™ืช ื”ื–ื•,
03:20
the simplified characters,
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ื”ื“ืžื•ื™ื•ืช ื”ืžื•ืคืฉื˜ืช,
03:22
flat backgrounds,
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ื”ืจืงืขื™ื ืฉื˜ื•ื—ื™ื,
03:23
and angular shapes come together
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ื•ื”ืฆื•ืจื•ืช ื–ื•ื•ื™ืชื™ื•ืช
03:25
to create new interpretations of reality,
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ืžืชื—ื‘ืจื•ืช ื•ื™ื•ืฆืจื•ืช ืคืจืฉื ื•ืช ื—ื“ืฉื” ืœืžืฆื™ืื•ืช,
03:28
which also sounds like a good place
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ื•ื–ื” ื ืฉืžืข ื›ืžื• ืžืงื•ื ื˜ื•ื‘
03:29
to begin visualizing our own Big Data.
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ืœื”ืชื—ื™ืœ ืืช ื”ืžื—ืฉืช ืžื•ืฉื’ ื”ื‘ื™ื’ ื“ืื˜ื” ืฉืœื ื•.
ืžื” ื”ื—ืฉื™ื‘ื•ืช ืฉืœ ื‘ื—ื™ืจืช ืืœืžื ื˜ื™ื ื•ื™ื–ื•ืืœื™ื™ื?
03:37
Well, let's try an experiment.
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ื•ื‘ื›ืŸ, ื‘ื•ืื• ื ืขืจื•ืš ื ื™ืกื•ื™.
03:40
"In the 1980s islands of similar networks
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"ื‘ืฉื ื•ืช ื”ืฉืžื•ื ื™ื ืื™ื™ื ืฉืœ ืจืฉืชื•ืช ื“ื•ืžื•ืช
03:43
speaking different dialects
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ืฉืžื“ื‘ืจื•ืช ื‘ื ื™ื‘ื™ื ืฉื•ื ื™ื
03:44
sprung up all over Europe and the States,
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ืฆืฆื• ื‘ื›ืœ ืื™ืจื•ืคื” ื•ืืจืฆื•ืช ื”ื‘ืจื™ืช,
03:47
making remote access possible but tortuous."
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ื•ื”ืคื›ื• ื’ื™ืฉื” ืžืจื—ื•ืง ืœืืคืฉืจื™ืช ืื‘ืœ ืžืขืฆื‘ื ืช."
03:50
Is this better?
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ื”ืื ื–ื” ื˜ื•ื‘ ื™ื•ืชืจ?
03:51
"In the 1980s islands of similar networks
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"ื‘ืฉื ื•ืช ื”ืฉืžื•ื ื™ื ืื™ื™ื ืฉืœ ืจืฉืชื•ืช ื“ื•ืžื•ืช
03:54
speaking different dialects
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ืฉืžื“ื‘ืจื•ืช ื‘ื ื™ื‘ื™ื ืฉื•ื ื™ื
03:55
sprung up all over Europe and the States,
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ืฆืฆื• ื‘ื›ืœ ืืจื•ืคื” ื•ืืจืฆื•ืช ื”ื‘ืจื™ืช,
03:57
making remote access possible but tortuous.
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ื•ื”ืคื›ื• ื’ื™ืฉื” ืžืจื—ื•ืง ืœืืคืฉืจื™ืช ืื‘ืœ ืžืขืฆื‘ื ืช."
04:00
To make it easy for our physicists across the world
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ื›ื“ื™ ืœืœื”ืงืœ ืขืœ ื”ืคื™ื–ื™ืงืื™ื ืฉืœื ื• ื‘ืจื—ื‘ื™ ื”ืขื•ืœื
04:03
to access the ever-expanding Big Data
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ืœื’ืฉืช ืœื›ืžื•ื™ื•ืช ื”ืžื™ื“ืข ื”ื’ื“ืœื•ืช ืœืœื ื”ืคืกืง
04:05
stored at CERN without traveling,
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ืฉืžืื•ื›ืกืŸ ื‘- CERN ืœืœื ื ืกื™ืขื•ืช,
04:07
the networks needed to be talking
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ื”ืจืฉืชื•ืช ื”ื™ื• ื—ื™ื™ื‘ื•ืช ืœื“ื‘ืจ
04:08
with the same language."
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ื‘ืื•ืชื” ืฉืคื”."
04:10
As you probably observed,
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ื›ืžื• ืฉื‘ื•ื•ื“ืื™ ื”ื‘ื—ื ืชื,
04:11
graphic representations are a great way
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ื”ืฆื’ื•ืช ื’ืจืคื™ื•ืช ื”ืŸ ื“ืจืš ืžืขื•ืœื”
04:13
to capture the interest of your audience.
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ืœืชืคื•ืฉ ืืช ืชืฉื•ืžืช ืœื™ื‘ื• ืฉืœ ื”ืงื”ืœ ืฉืœื›ื.
04:15
By depicting what you want to present and explain
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ืขืœ ื™ื“ื™ ื”ืฆื’ืช ืžื” ืฉืืชื ืจื•ืฆื™ื ืœื”ืฆื™ื’ ื•ืœื”ืกื‘ื™ืจ
04:18
with strong, memorable visuals,
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ื‘ืขื–ืจืช ืชืžื•ื ื•ืช ื—ื–ืงื•ืช ื•ืงืœื•ืช ืœื–ื›ื™ืจื”,
04:20
you can communicate your idea more effectively.
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ืืชื ื™ื›ื•ืœื™ื ืœื”ืขื‘ื™ืจ ืืช ื”ืจืขื™ื•ืŸ ืฉืœื›ื ื‘ืฆื•ืจื” ื™ื•ืชืจ ื™ืขื™ืœื”.
04:22
So, now, challenge yourself.
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ืื–, ืขื›ืฉื™ื•, ืืชื’ืจื• ืืช ืขืฆืžื›ื.
04:24
Think of an abstract concept
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ื—ืฉื‘ื• ืขืœ ืงื•ื ืกืคื˜ ืžื•ืคืฉื˜
04:26
that cannot be explained with simple words.
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ืฉืื™ ืืคืฉืจ ืœื”ืกื‘ื™ืจ ื‘ืžื™ืœื™ื ืคืฉื•ื˜ื•ืช.
04:28
Go ahead and try your hand
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ื”ืžืฉื™ื›ื• ื•ื ืกื•
04:29
at visually developing that idea.
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ื‘ืคื™ืชื•ื— ื•ื™ื–ื•ืืœื™ ืฉืœ ื”ืจืขื™ื•ืŸ.
ืขืœ ืืชืจ ื–ื”

ืืชืจ ื–ื” ื™ืฆื™ื’ ื‘ืคื ื™ื›ื ืกืจื˜ื•ื ื™ YouTube ื”ืžื•ืขื™ืœื™ื ืœืœื™ืžื•ื“ ืื ื’ืœื™ืช. ืชื•ื›ืœื• ืœืจืื•ืช ืฉื™ืขื•ืจื™ ืื ื’ืœื™ืช ื”ืžื•ืขื‘ืจื™ื ืขืœ ื™ื“ื™ ืžื•ืจื™ื ืžื”ืฉื•ืจื” ื”ืจืืฉื•ื ื” ืžืจื—ื‘ื™ ื”ืขื•ืœื. ืœื—ืฅ ืคืขืžื™ื™ื ืขืœ ื”ื›ืชื•ื‘ื™ื•ืช ื‘ืื ื’ืœื™ืช ื”ืžื•ืฆื’ื•ืช ื‘ื›ืœ ื“ืฃ ื•ื™ื“ืื• ื›ื“ื™ ืœื”ืคืขื™ืœ ืืช ื”ืกืจื˜ื•ืŸ ืžืฉื. ื”ื›ืชื•ื‘ื™ื•ืช ื’ื•ืœืœื•ืช ื‘ืกื ื›ืจื•ืŸ ืขื ื”ืคืขืœืช ื”ื•ื•ื™ื“ืื•. ืื ื™ืฉ ืœืš ื”ืขืจื•ืช ืื• ื‘ืงืฉื•ืช, ืื ื ืฆื•ืจ ืื™ืชื ื• ืงืฉืจ ื‘ืืžืฆืขื•ืช ื˜ื•ืคืก ื™ืฆื™ืจืช ืงืฉืจ ื–ื”.

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