迄今為止人類拍了多少張照片？：英語精讀講義

Hey, Vsauce.

嗨，Vsauce。

Michael here.

我是 Michael。

In 1826,

1826年，

this became the very first photograph ever taken. 文法

這成了史上第一張拍攝下來的照片。

And in 1992,

而在1992年，

this became the very first image ever uploaded to the web.

這成了史上第一張上傳到網路的圖片。

But how many photographs have we all taken altogether

但我們大家總共拍了多少張照片

throughout all of history?

——放眼整段歷史來看呢？

Well,

嗯，

1,000 Memories investigated this very question.

1,000 Memories 調查的正是這個問題。

They took a look at the number of digital cameras currently in use, 片語搭配

他們研究了目前正在使用的數位相機數量，

typical usage of a digital camera,

數位相機的一般使用情況，

as well as the amount of analog film and film developing supplies 片語搭配

以及傳統底片和底片沖洗用品的數量，

used by the industry ever since the 19th century. 文法

也就是這個產業自19世紀以來的相關用量。

Tabulated altogether,

彙整所有資料後，

they estimated that we have taken

他們估計，我們已經拍攝了

3 and 1/2 trillion photographs,

3.5兆張照片，

4 billion of which were taken this year alone. 文法

其中光是今年就拍了40億張。

We are snapping more photographs than ever before 文法

我們現在拍的照片比以往任何時候都多，

because of the proliferation of easy-to-use, 用詞

因為簡單易用、

affordable digital cameras.

價格親民的數位相機已經非常普及。

In fact,

事實上，

we take four times more pictures per day 文法

我們現在每天拍的照片數量

than we did 10 years ago.

是10年前的四倍。

Or think of it this way. 表達脈絡

也可以換個角度想。

Today,

如今，

every 2 minutes,

每過2分鐘，

humanity takes more pictures

人類拍攝的照片數量

than we took altogether in the entire 1800s.

就超過整個19世紀拍攝的照片總量。

Of course,

當然，

the 1800s were a long time ago,

19世紀已經是很久以前了，

but if we take every year from the invention of photography until today,

但如果把攝影術發明以來直到今天的每一年都算進去，

10% of all of those images,

所有這些圖片中有10%，

a 10th of every still image recorded of our world

也就是所有記錄我們世界的靜態影像的十分之一，

was taken in the last 12 months.

都是在過去12個月內拍攝的。

That's a lot.

這真的很多。

But even crazier is the fact that a fifth of these images, 文法

但更瘋狂的是，這些圖片中有五分之一，

20% of them,

也就是其中的20%，

all wind up in the same place, 片語動詞

最後全都去了同一個地方：

Facebook.

Facebook。

Facebook is huge.

Facebook 的規模非常龐大。

But to put it in perspective, 慣用語

不過，為了讓你有個具體概念，

you Vsaucers are huge.

你們這些 Vsauce 粉絲加起來也很龐大。

If all of us got together in one place and claimed independence, 講解

如果我們所有人聚在一個地方並宣布獨立，

we would become the 152nd largest country on Earth,

我們就會成為全球第152大國，

right between Guinea-Bissau and Trinidad and Tobago.

正好排在幾內亞比索與千里達及托巴哥之間。

But Facebook,

但 Facebook

with its 1 billion users,

憑藉著10億名使用者，

would be the third largest country on Earth.

將成為全球第三大國。

To take a quick, dark detour, 表達脈絡

先來個短暫而沉重的題外話：

of those 1 billion people on Facebook,

Facebook 上這10億人當中，

it's estimated that 30 million of them are now dead. 文法

據估計，有3,000萬人如今已經過世。

And in 100 years,

而100年後，

it's estimated that half a billion of the people on Facebook

據估計，Facebook 使用者中將有5億人

will be deceased. 用詞

已經離世。

Facebook Stories offers a really neat tool where you can click on a country

Facebook Stories 提供了一個很棒的工具，你可以點選某個國家，

and then see what other countries most of their Facebook friends live in.

然後看看該國使用者的大多數 Facebook 好友住在哪些其他國家。

It's fun to see what countries are most connected to which others,

看看哪些國家彼此連結最緊密很有意思，

but this whole thing brings up the question of degrees of separation. 講解

不過這也帶出了「分隔度」的問題。

If you were to take two random people on Earth, 文法

如果從地球上隨機挑選兩個人，

how many friend of a friend of a friend of a friend's

需要經過多少層「朋友的朋友的朋友的朋友」

would you need to connect those two people?

才能把這兩個人連結起來？

Well, in the real world,

嗯，在現實世界裡，

it's a little difficult to figure out because we don't know who's friends with who 片語動詞

這有點難算，因為我們不知道誰跟誰是朋友，

and there are a lot of people.

而且人數實在太多。

But luckily,

但幸運的是，

mathematics has come to our rescue. 慣用語

數學來幫我們了。

Watts and Strogatz showed that you could calculate

Watts 和 Strogatz 證明，我們可以算出

the average path between any two random people

任意兩個隨機挑選的人之間的平均路徑，

quite easily.

而且相當容易。

In this equation,

在這個方程式中，

the N stands for the total number of people in the population 片語搭配

N 代表總人口數，

and K stands for the number of friends each person has.

K 代表每個人擁有的朋友數。

If we assume that each person has,

如果我們假設每個人都有，

say, 30 friends 用詞

比方說，30個朋友，

and we assume that 10% of our population is too young to have actual friends,

再假設總人口中有10%的人年紀太小，還交不到真正的朋友，

it turns out that you can connect any two people on Earth with only 6.6 connections, 片語搭配

那麼結果是，只要6.6層連結，就能把地球上任意兩個人連結起來，

theoretically.

至少理論上如此。

Of course,

當然，

in the real world,

在現實世界中，

we don't all have the same number of friends,

我們的朋友數量並不都一樣，

we don't all have 30 friends,

也不是每個人都有30個朋友，

and isolated groups make the average much, much higher.

而彼此隔絕的群體會讓平均值高出許多許多。

Of course,

當然，

there are non-real world places where these connections are easier to follow.

在一些並非現實世界的地方，這些連結會更容易追蹤。

For instance,

例如，

Facebook.

Facebook。

Last year,

去年，

Facebook's data team released two papers showing

Facebook 的資料團隊發表了兩篇論文，結果顯示，

that amongst all Facebook users at the time, 用詞

在當時所有的 Facebook 使用者中，

the average distance between any two random users was only 4.74 friends.

任意兩名隨機使用者之間的平均距離只有4.74層好友關係。

Twitter is even tighter. 慣用語

Twitter 上的關係甚至更緊密。

It's been shown that any two random users of Twitter are connected by only 4.67 friends,

研究顯示，任意兩名隨機 Twitter 使用者之間只隔著4.67層好友關係，

though some studies have shown it to be as low as 3 and 1/2. 片語搭配

有些研究得出的數值甚至低至3.5。

Numbers like that can make impersonal crowds seem quite intimate. 文法

這樣的數字能讓互不相識的人群顯得相當親近。

But one of my favorite things about crowds is how smart they are. 文法

不過，說到人群，我最喜歡的一點就是他們有多聰明。

Wisdom of the crowds is a fascinating phenomenon where the collective knowledge or guesses or estimations of a big group of people, 文化背景

「群眾智慧」是一種迷人的現象：一大群人的集體知識、猜測或估算，

when averaged, 文法

取平均值後，

are better than one individual person working alone.

會比一個人獨自得出的結果更準確。

A good example of this is trying to guess how many jelly beans are in a jar.

一個很好的例子，就是猜罐子裡有多少顆雷根糖。

Some people will overestimate, 用詞

有些人會高估，

while others will underestimate.

另一些人則會低估。

But collectively,

但從整體來看，

each member cancels out the errors of the other 片語動詞

每個人的誤差都會抵消其他人的誤差，

and the group average estimation winds up being smarter than the sum of its parts. 講解

最後，群體的平均估計會比個體單純相加更高明。

The BBC's demonstration of this is fantastic.

BBC 對此所做的示範非常精彩。

I've linked it down in the description.

我把連結放在下方說明欄裡了。

It's worth watching. 文法

很值得一看。

They had 160 people guess the number of jelly beans in a jar. 文法

他們讓160個人猜罐子裡有多少顆雷根糖。

The guesses ranged from a few hundred to tens of thousands, 片語搭配

答案從幾百顆到幾萬顆都有，

but the average of all 160 guesses was 4,515.

但160個答案的平均值是4,515顆。

Only five beans away from the exact answer. 片語搭配

與正確答案只差5顆。

It's amazing to think that in a large enough group, 文法

想想看，在一個夠大的群體中，真的很不可思議：

the errors and shortcomings of everyone else,

其他所有人的錯誤和不足，

no matter how annoying they are individually, 文法

無論單獨看有多惱人，

actually can balance and correct our own shortcomings.

實際上都能平衡並修正我們自己的不足。

It feels good,

這讓人感覺很好，

though a little bit strange to think that in a group,

不過，一想到在一個群體中，也會覺得有點奇怪：

it's possible for nobody to be correct, 表達脈絡

可能沒有任何一個人是正確的，

but for everybody to be right.

但所有人合起來卻是對的。

And as always,

一如往常，

thanks for watching.

謝謝收看。