ABOUT THE SPEAKER
Gary Flake - Technologist
Gary Flake is a Technical Fellow at Microsoft, and the founder and director of Live Labs.

Why you should listen

Gary Flake is a Technical Fellow at Microsoft, where he focuses on Internet products and technologies including search, advertising, content, portals, community and application development. In this capacity, he helps define and evolve Microsoft's product vision, technical architecture and business strategy for online services. He is also the founder and director of Live Labs, a skunkworks that bridges research and development, and is widely recognized for inventing new best practices for catalyzing and managing innovation.

Prior to joining Microsoft, Flake founded Yahoo! Research Labs, ran Yahoo!'s corporate R&D activities and company-wide innovation effort, and was the Chief Science Officer of Overture, the company that invented the paid search business model. Flake also wrote the award-winning book The Computational Beauty of Nature, which is used in college courses worldwide.

More profile about the speaker
Gary Flake | Speaker | TED.com
TED2010

Gary Flake: Is Pivot a turning point for web exploration?

蓋瑞•弗雷克:「樞紐」是網路探索方法的轉捩點嗎?

Filmed:
751,479 views

蓋瑞•弗雷克示範了「樞紐」,一個幫助人們瀏覽和整理大量網路圖片和數據的新方法。人們透過這個在突破性的海龍技術基礎上所建造的網路技術,可以精彩紛呈地縮放網路資料庫,發現使用目前標準網路瀏覽方法所無法發現的格局與連結性。
- Technologist
Gary Flake is a Technical Fellow at Microsoft, and the founder and director of Live Labs. Full bio

Double-click the English transcript below to play the video.

00:16
If I can leave離開 you with one big idea理念 today今天,
0
1000
2000
如果我今天的演講可以留給你們一個新概念,
00:18
it's that the whole整個 of the data數據
1
3000
2000
那就是我們所消費的
00:20
in which哪一個 we consume消耗
2
5000
2000
資料整體是
00:22
is greater更大 that the sum of the parts部分,
3
7000
2000
大於其各個部分相加的總和的。
00:24
and instead代替 of thinking思維 about information信息 overload超載,
4
9000
3000
然而,與其擔心資訊爆炸,
00:27
what I'd like you to think about is how
5
12000
2000
不如思考一下怎樣使用
00:29
we can use information信息 so that patterns模式 pop流行的
6
14000
3000
這些資訊, 使其中的規律顯現,
00:32
and we can see trends趨勢 that would otherwise除此以外 be invisible無形.
7
17000
3000
幫助我們看見原本不可見的趨勢。
00:35
So what we're looking at right here is a typical典型 mortality死亡 chart圖表
8
20000
3000
在這裡,我們看到的是一個典型的死亡率表,
00:38
organized有組織的 by age年齡.
9
23000
2000
根據年齡排列。
00:40
This tool工具 that I'm using運用 here is a little experiment實驗.
10
25000
2000
我現在用的這個工具是一個小小的實驗,
00:42
It's called Pivot, and with Pivot what I can do
11
27000
3000
這個工具叫「樞紐」 (Pivot), 使用「樞紐」,
00:45
is I can choose選擇 to filter過濾 in one particular特定 cause原因 of deaths死亡 -- say, accidents事故.
12
30000
4000
我可以選擇過濾出某個特殊的死因, 例如說:事故身亡。
00:49
And, right away, I see there's a different不同 pattern模式 that emerges出現.
13
34000
3000
然後,馬上我就看見一組不同的模式顯現。
00:52
This is because, in the mid-area中間區域 here,
14
37000
2000
這是因爲, 中間這裡
00:54
people are at their most active活性,
15
39000
2000
人們處於他們最活躍的年齡,
00:56
and over here they're at their most frail脆弱.
16
41000
2000
而在這裡, 人們是最體弱多病的時候。
00:58
We can step back out again
17
43000
2000
我們可以退回來,
01:00
and then reorganize改組 the data數據 by cause原因 of death死亡,
18
45000
2000
重新根據死因來排列資料,
01:02
seeing眼看 that circulatory循環系統 diseases疾病 and cancer癌症
19
47000
3000
我們可以看到循環系統疾病和癌症
01:05
are the usual通常 suspects犯罪嫌疑人, but not for everyone大家.
20
50000
3000
是常見的致死因素,但並不適用於每一個人。
01:08
If we go ahead and we filter過濾 by age年齡 --
21
53000
3000
如果我們繼續過濾年齡,
01:11
say 40 years年份 or less --
22
56000
2000
比如說 40 歲以下的人群,
01:13
we see that accidents事故 are actually其實
23
58000
2000
我們會發現意外事故是
01:15
the greatest最大 cause原因 that people have to be worried擔心 about.
24
60000
3000
人們最需要小心的殺手
01:18
And if you drill鑽頭 into that, it's especially特別 the case案件 for men男人.
25
63000
3000
如果你進一步挖掘, 這個準則對男人尤其適用。
01:21
So you get the idea理念
26
66000
2000
所以,你對這個東西有點概念了,
01:23
that viewing觀看 information信息, viewing觀看 data數據 in this way,
27
68000
3000
用這種方法來瀏覽資訊、數據
01:26
is a lot like swimming游泳的
28
71000
2000
很像是在一個
01:28
in a living活的 information信息 info-graphic信息圖形.
29
73000
3000
鮮活的資訊圖片裡游泳。
01:31
And if we can do this for raw生的 data數據,
30
76000
2000
如果我們可以對原始資料這麼做,
01:33
why not do it for content內容 as well?
31
78000
3000
爲什麼不將內容也比照辦理呢?
01:36
So what we have right here
32
81000
2000
所以,我們在這裡顯示的
01:38
is the cover of every一切 single Sports體育 Illustrated插圖
33
83000
3000
是過去發表過的每一期
01:41
ever produced生成.
34
86000
2000
運動畫刊的封面。
01:43
It's all here; it's all on the web捲筒紙.
35
88000
2000
都在這裡了, 都在網路上
01:45
You can go back to your rooms客房 and try this after my talk.
36
90000
3000
演講完,你回到飯店房間後,可以試試這個工具。
01:48
With Pivot, you can drill鑽頭 into a decade.
37
93000
3000
用「樞紐」, 你可以深入某一個世代,
01:51
You can drill鑽頭 into a particular特定 year.
38
96000
2000
深入到具體的某一年,
01:53
You can jump right into a specific具體 issue問題.
39
98000
3000
你也可以直接進入某一期。
01:56
So I'm looking at this; I see the athletes運動員
40
101000
2000
所以當我看著這個的時候,
01:58
that have appeared出現 in this issue問題, the sports體育.
41
103000
2000
我看到出現在該期雜誌中的各種運動以及運動員們。
02:00
I'm a Lance Armstrong阿姆斯特朗 fan風扇, so I'll go ahead and I'll click點擊 on that,
42
105000
3000
我是蘭斯•阿姆斯壯迷, 所以我就點擊選取這一期,
02:03
which哪一個 reveals揭示, for me, all the issues問題
43
108000
2000
然後它為我展示了所有刊登過有關蘭斯•阿姆斯壯
02:05
in which哪一個 Lance Armstrong's阿姆斯特朗的 been a part部分 of.
44
110000
2000
內容的所有期數。
02:07
(Applause掌聲)
45
112000
3000
(掌聲)
02:10
Now, if I want to just kind of take a peek窺視 at these,
46
115000
3000
現在, 如果我只是簡單的瀏覽一眼這些內容
02:13
I might威力 think,
47
118000
2000
我可能會想
02:15
"Well, what about taking服用 a look at all of cycling循環?"
48
120000
2000
「好, 那把所有有關自行車運動的期刊都找出來如何?」
02:17
So I can step back, and expand擴大 on that.
49
122000
2000
所以我可以退回去, 然後在著重在那些內容。
02:19
And I see Greg格雷格 LeMond雷蒙德 now.
50
124000
2000
現在我看到 Greg Lemond 了。
02:21
And so you get the idea理念 that when you
51
126000
2000
你現在應該已經知道, 當你
02:23
navigate導航 over information信息 this way --
52
128000
2000
用這種方法在大量資訊中領航,
02:25
going narrower, broader更廣泛,
53
130000
2000
你可以縮小、擴大、
02:27
backing後盾 in, backing後盾 out --
54
132000
2000
深入、淺出,
02:29
you're not searching搜索, you're not browsing瀏覽.
55
134000
2000
你不是在搜索,你也不是在瀏覽
02:31
You're doing something that's actually其實 a little bit different不同.
56
136000
2000
你所做的事情跟這兩者都有些不同。
02:33
It's in between之間, and we think it changes變化
57
138000
3000
界於兩者之間, 我們認爲這改變了
02:36
the way information信息 can be used.
58
141000
2000
資訊可以被使用的方法。
02:38
So I want to extrapolate推斷 on this idea理念 a bit
59
143000
2000
所以我想對這個觀點做進一步的闡釋,
02:40
with something that's a little bit crazy.
60
145000
2000
是一些稍微有點瘋狂的想法。
02:42
What we're doneDONE here is we've我們已經 taken採取 every一切 single Wikipedia維基百科 page
61
147000
3000
我們在這裡所做的是,我們將每一頁維基百科,
02:45
and we reduced減少 it down to a little summary概要.
62
150000
3000
縮簡成一小段摘要。
02:48
So the summary概要 consists of just a little synopsis概要
63
153000
3000
這摘要只包括了一些簡介
02:51
and an icon圖標 to indicate表明 the topical局部的 area that it comes from.
64
156000
3000
和一個顯示標題範圍來源的圖示。
02:54
I'm only showing展示 the top最佳 500
65
159000
3000
我這裡只顯示維基百科中
02:57
most popular流行 Wikipedia維基百科 pages網頁 right here.
66
162000
2000
最熱門的 500 頁。
02:59
But even in this limited有限 view視圖,
67
164000
2000
但即使在這有限的展示中,
03:01
we can do a lot of things.
68
166000
2000
我們也可以做很多事情。
03:03
Right away, we get a sense of what are the topical局部的 domains
69
168000
2000
我們馬上可以知道,哪些主題
03:05
that are most popular流行 on Wikipedia維基百科.
70
170000
2000
在維基百科中最熱門。
03:07
I'm going to go ahead and select選擇 government政府.
71
172000
2000
我這裡選擇「政府」,
03:09
Now, having selected government政府,
72
174000
3000
選了「政府」以後,
03:12
I can now see that the Wikipedia維基百科 categories類別
73
177000
2000
我可以看到維基百科中
03:14
that most frequently經常 correspond對應 to that
74
179000
2000
與之對應最頻繁的類別是,
03:16
are Time magazine雜誌 People of the Year.
75
181000
3000
時代雜誌的年度風雲人物。
03:19
So this is really important重要 because this is an insight眼光
76
184000
3000
這真的很重要,因爲這種洞見,
03:22
that was not contained within any one Wikipedia維基百科 page.
77
187000
3000
並不包含在任何維基百科的網頁中。
03:25
It's only possible可能 to see that insight眼光
78
190000
2000
唯一可以看出這個關係的方法是,
03:27
when you step back and look at all of them.
79
192000
3000
退後一步,縱觀全局。
03:30
Looking at one of these particular特定 summaries摘要,
80
195000
2000
看著這些不同摘要的其中一個,
03:32
I can then drill鑽頭 into the concept概念 of
81
197000
3000
我可以接著深入探索
03:35
Time magazine雜誌 Person of the Year,
82
200000
2000
時代雜誌年度風雲人物這個概念,
03:37
bringing使 up all of them.
83
202000
2000
把他們都帶出來。
03:39
So looking at these people,
84
204000
2000
看著這些人,
03:41
I can see that the majority多數 come from government政府;
85
206000
3000
我發現他們中的多數來自政府,
03:45
some have come from natural自然 sciences科學;
86
210000
3000
有些來自自然科學,
03:49
some, fewer still, have come from business商業 --
87
214000
3000
有些,很少數,是商業人士。
03:53
there's my boss老闆 --
88
218000
2000
這是我老闆。
03:55
and one has come from music音樂.
89
220000
5000
其中一個是音樂界人士,
04:00
And interestingly有趣 enough足夠,
90
225000
2000
而有趣的是,
04:02
Bono波諾 is also a TEDTED Prize winner優勝者.
91
227000
3000
Bono 也是 TED 大獎得主。
04:05
So we can go, jump, and take a look at all the TEDTED Prize winners獲獎者.
92
230000
3000
所以我們可以直接跳進去,看看所有的 TED 大獎得主。
04:08
So you see, we're navigating導航 the web捲筒紙 for the first time
93
233000
3000
所以你看, 我們第一次在網路上航行了,
04:11
as if it's actually其實 a web捲筒紙, not from page-to-page頁到頁,
94
236000
3000
好像它真的是一大張網,不是一張張的頁面,
04:14
but at a higher更高 level水平 of abstraction抽象化.
95
239000
2000
而是一種更高層次抽象的概念。
04:16
And so I want to show顯示 you one other thing
96
241000
2000
我還想給你們看另一樣東西,
04:18
that may可能 catch抓住 you a little bit by surprise.
97
243000
3000
那可能會讓你覺得有點驚訝。
04:21
I'm just showing展示 the New York紐約 Times website網站 here.
98
246000
3000
我現在顯示的是紐約時報的網頁,
04:24
So Pivot, this application應用 --
99
249000
2000
所以「樞紐」,這個應用程式,
04:26
I don't want to call it a browser瀏覽器; it's really not a browser瀏覽器,
100
251000
2000
我不想稱它為瀏覽器,因爲它並不是一個瀏覽器,
04:28
but you can view視圖 web捲筒紙 pages網頁 with it --
101
253000
3000
但是你可以用它來看網頁。
04:31
and we bring帶來 that zoomable可縮放 technology技術
102
256000
2000
我們引進了可縮放技術,
04:33
to every一切 single web捲筒紙 page like this.
103
258000
3000
運用到每一個網頁。
04:36
So I can step back,
104
261000
3000
所以我可以退出,
04:39
pop流行的 right back into a specific具體 section部分.
105
264000
2000
快速回到一個特定的部分。
04:41
Now the reason原因 why this is important重要 is because,
106
266000
2000
為什麼這很重要?因為,
04:43
by virtue美德 of just viewing觀看 web捲筒紙 pages網頁 in this way,
107
268000
3000
這樣看網頁的好處是,
04:46
I can look at my entire整個 browsing瀏覽 history歷史
108
271000
2000
我可以將我的整個瀏覽歷史,
04:48
in the exact精確 same相同 way.
109
273000
2000
完整重現。
04:50
So I can drill鑽頭 into what I've doneDONE
110
275000
2000
所以我可以深入探索,
04:52
over specific具體 time frames.
111
277000
2000
在過去某段時間內,我曾經做過的事。
04:54
Here, in fact事實, is the state
112
279000
2000
這邊所顯示的,事實上, 就在剛剛
04:56
of all the demo演示 that I just gave.
113
281000
2000
我做過的所有的示範。
04:58
And I can sort分類 of replay重播 some stuff東東 that I was looking at earlier today今天.
114
283000
3000
我可以重播一些今天前些時間我在搜尋的東西。
05:01
And, if I want to step back and look at everything,
115
286000
3000
而如果我想退後一步,縱觀所局,
05:04
I can slice and dice骰子 my history歷史,
116
289000
2000
我可以層層切割我的歷史紀錄,
05:06
perhaps也許 by my search搜索 history歷史 --
117
291000
2000
例如我的搜尋紀錄。
05:08
here, I was doing some nepotistic裙帶關係 searching搜索,
118
293000
2000
我在這裡做一些相關的搜尋,
05:10
looking for Bing, over here for Live生活 Labs實驗室 Pivot.
119
295000
3000
搜尋 Bing,這裡是 Live 實驗室的 Pivot。
05:13
And from these, I can drill鑽頭 into the web捲筒紙 page
120
298000
2000
從那裡,我可以進入網頁,
05:15
and just launch發射 them again.
121
300000
2000
只要再打開就可以了。
05:17
It's one metaphor隱喻 repurposed改變用途 multiple times,
122
302000
3000
這是同樣的原始資料,因不同目的被多次組合使用,
05:20
and in each case案件 it makes品牌 the whole整個 greater更大
123
305000
2000
而每一次的重新組合使得它
05:22
than the sum of the parts部分 with the data數據.
124
307000
2000
比各個部分的總和更爲強大。
05:24
So right now, in this world世界,
125
309000
3000
所以, 現在, 在這個世界上
05:27
we think about data數據 as being存在 this curse詛咒.
126
312000
3000
我們說到數據的時候常常提到這個詛咒,
05:30
We talk about the curse詛咒 of information信息 overload超載.
127
315000
3000
我們會提到資訊爆炸,
05:33
We talk about drowning溺死 in data數據.
128
318000
3000
我們會提到淹沒在資料中。
05:36
What if we can actually其實 turn that upside上邊 down
129
321000
2000
如果我們能夠顛覆這些想法,
05:38
and turn the web捲筒紙 upside上邊 down,
130
323000
2000
顛覆網路世界,
05:40
so that instead代替 of navigating導航 from one thing to the next下一個,
131
325000
3000
相對於一個東西連接到另一個東西,
05:43
we get used to the habit習慣 of being存在 able能夠 to go from many許多 things to many許多 things,
132
328000
3000
讓我們開始來習慣從多樣向多樣的轉換,
05:46
and then being存在 able能夠 to see the patterns模式
133
331000
2000
然後能夠看到
05:48
that were otherwise除此以外 hidden?
134
333000
2000
隱藏其中的規律。
05:50
If we can do that, then instead代替 of being存在 trapped被困 in data數據,
135
335000
5000
如果我們能做到,那麼,我們將不再被困於大量的資料,
05:55
we might威力 actually其實 extract提取 information信息.
136
340000
3000
我們或許可以真的從中萃取出有用的資訊。
05:58
And, instead代替 of dealing交易 just with information信息,
137
343000
2000
而,除了單純地處理資訊,
06:00
we can tease out knowledge知識.
138
345000
2000
我們可以獲取知識。
06:02
And if we get the knowledge知識, then maybe even there's wisdom智慧 to be found發現.
139
347000
3000
而如果我們得到了知識, 也許我們就會找到智慧。
06:05
So with that, I thank you.
140
350000
2000
這就是我的總結, 謝謝大家。
06:07
(Applause掌聲)
141
352000
8000
(掌聲)
Translated by Jenny Yang
Reviewed by Bill Hsiung

▲Back to top

ABOUT THE SPEAKER
Gary Flake - Technologist
Gary Flake is a Technical Fellow at Microsoft, and the founder and director of Live Labs.

Why you should listen

Gary Flake is a Technical Fellow at Microsoft, where he focuses on Internet products and technologies including search, advertising, content, portals, community and application development. In this capacity, he helps define and evolve Microsoft's product vision, technical architecture and business strategy for online services. He is also the founder and director of Live Labs, a skunkworks that bridges research and development, and is widely recognized for inventing new best practices for catalyzing and managing innovation.

Prior to joining Microsoft, Flake founded Yahoo! Research Labs, ran Yahoo!'s corporate R&D activities and company-wide innovation effort, and was the Chief Science Officer of Overture, the company that invented the paid search business model. Flake also wrote the award-winning book The Computational Beauty of Nature, which is used in college courses worldwide.

More profile about the speaker
Gary Flake | Speaker | TED.com