is at the mercy of a rising technology,

享受著科技帶來的便利

yet few actually understand what it is.

但其實很少人知道這背後到底是哪些科技在支撐著他們的生活

Artificial intelligence. You know, HAL 9000

人工智慧。你知道的，就是 HAL 9000

and Marvin the Paranoid Android?

以及疑心病很重的那個人型機器人 Ｍarvin？

Thanks to books and movies,

多虧了每個世代的書和電影

each generation has formed

各自想像描述了屬於他們

its own fantasy of a world ruled

自己由機器人所統治的

-- or at leased served -- by robots.

或者說至少是由機器人提供服務的世界

We've been conditioned to expect flying cars

我們已經被制約去期待一個飛行汽車出現的

that steer clear of traffic

一個不會塞車的世界

and robotic maids whipping up our weekday dinner.

以及機器人侍者在我們週間用晚餐時清潔打掃

But if the age of AI is here,

但是如果 AI 時代到來時

why don't our lives look more like the Jetson's?

為什麼看起來不會更像是 Jetson 過的生活那個樣貌？

Well, for starters, that's a cartoon.

這個麻，對於初次接觸的人來說，是一部卡通的概念

And really, if you've ever browsed Netflix movie suggestions

而實際上，你若有瀏覽過 Netflix 電影建議清單

or told Alexa to order a pizza,

或者曾經叫過 Alexz 去幫你訂披薩

you're probably interacting with artificial intelligence

你與人工智慧互動的程度

more than you realize.

大概比你認知到的還要多更多

And that's kind of the point.

而這就是重點所在

AI is designed so you don't realize

AI 本來就是應該設計得讓你無法察覺

there's a computer calling the shots.

背後其實是有電腦在決定這個動作的

But that also makes understanding what AI is,

但是也讓我們能夠理解到底什麼是 AI

and what it's not, a little complicated.

什麼又不是，這其中其實有點複雜

In basic terms, AI is a broad area of computer science

但基本上來說，AI 就是一個非常大的電腦科學領域

that makes machines seem

能夠讓機器看起來

like they have human intelligence.

好像擁有人類的智力

So it's not only programming a computer to drive a car

所以這不僅僅是寫一個程式讓電腦能夠遵守交通號誌來駕駛汽車

by obeying traffic signals, but it's when that program

也是一個能夠

also learns to exhibit signs of human-like road rage.

學習模仿人類在駕車時產生的「路怒」的能力

As intimidating as it may seem,

看起來好像很嚇人

this technology isn't new.

但這個並不是新科技了

Actually, for the past half-a-century,

事實上，大概半個世紀前就有了

it's been an idea ahead of its time.

所以這個是相當前衛的一個點子

The term "artificial intelligence" was first coined back in

「人工智慧」一詞在1956年時

1956 by Dartmouth professor John McCarthy.

由 Dartmouth 的教授 John McCarthy 所創造

He called together a group of computer scientists and mathematicians

他召集了一群電腦和數學科學家

to see if machines could learn like a young child does,

來測試看看電腦是否能夠擁有像是小孩子的學習能力

using trial and error to develop formal reasoning.

藉由嘗試錯誤來發展一個合乎正常的推理能力

The project proposal says they'll figure out how to make machines

這個案子的企劃寫說他們會探究出如何讓機器：「具有語言能力、

"use language, form abstractions and concepts,

具備抽象及概念性思考

solve kinds of problems now reserved for humans,

以及現今人類面臨的眾多不同的問題

and improve themselves."

並且機器能夠自我改進。」等等能力

That was more than 60 years ago.

這已經是超過 60 年之前了

Since then, AI has remained for the most part

至從那時起，AI 就在眾多的大學課堂中及超級機密實驗室中

in university classrooms and super secret labs ...

被廣泛的研究

But that's changing.

但這已經改變了

Like all exponential curves, it's hard to tell when a line

就跟所有的指數函數曲線，是很難判斷一條數學關係曲線

that's slowly ticking upwards is going to skyrocket.

從起初慢慢遞增的狀態，突然竄升的時機點在什麼時候

But during the past few years, a couple of factors

但在過去幾年當中，其中的一些因素

have led to AI becoming the next "big" thing:

導致 AI 成為下一個新顯學

First, huge amounts of data are being

首先，每分鐘被創造出來的數據

created every minute. In fact, 90% of the world's data

急速增加。事實上，世界上百分之九十的資料

has been generated in the past two years.

是過去兩年以內產生的

And now thanks to advances in processing speeds,

而現在多虧了在運算處理能力的進步

computers can actually make sense

電腦能夠更睏素且確實地理解

of all this information more quickly.

所有接收到的資訊

Because of this, tech giants and venture capitalists

因為這樣，科技巨人及創投資本家

have bought into AI and are infusing the market

都進入了 AI 市場並且將資金和新的應用融合

with cash and new applications.

到市場當中

Very soon, AI will become a little less artificial,

很快地，AI 將會變成比較不「人工」

and a lot more intelligent.

而且會更加「智慧」

Now the question is: Should you brace yourself for yet

現在問題變成是：你應該該要接受

another Terminator movie, live on your city streets?

你所生活的城市街上上演電影「魔鬼終結者」嗎？

Not exactly. In fact, stop thinking of robots.

不完全是。事實上，不要朝著機器人的方面去思考

When it comes to AI, a robot is nothing more than

當我們談到 AI 時，機器人往往只是

the shell concealing what's actually used

真正推動這項科技的

to power the technology.

外殼罷了

That means AI can manifest itself in many

也就是說 AI 能夠把他自己實現在

different ways. Let's break down the options.

不同的地方。我們來解析看看有哪些選項

First, you have your bots. They're text-based and

第一，你會有屬於自己的機器人。他們是以文字輸入作為基礎並且

incredibly powerful, but they have limitations.

功能不可思議的強大，但是還是有極限

Ask a weather bot for the forecast, and it will tell you

詢問一個天氣機器人幫你做天氣預報，它會告訴你

it's partly cloudy with a high of 57.

今天天氣是局部多雲，高溫華氏 57 度

But ask that same bot what time it is in Tokyo,

但問同一個機器人現在東京的時間是多少

and it'll get a little confused.

它可能會有點混淆不清你的意思是什麼

That's because the bot's creator only programmed it to

這是因為這個機器人的創造者只將他設定成

give you the weather by pulling from a specific data source.

有能力去存取特定的資料來源以便能告訴你天氣的狀況而已

Natural language processing makes these bots

自然語言處理讓這些機器人

a bit more sophisticated.

變得更有智慧一些

When you ask Siri or Cortana

當你問 Siri 或者 Cortana

where the closest gas station is,

最近的加油站在哪的時後

it's really just translating your voice into text,

它們真的就只是將你的聲音化為文字

feeding it to a search engine,

輸入搜尋引擎而已

and reading the answer back in human syntax.

並且把答案讀取出來用人類的語氣回答你

So in other words, you don't have to speak in code.

所以換句話說，你不用說出「程式語言碼」就可以達到跟電腦溝通的目的

At the far end of the spectrum is machine learning,

在 AI 能力的功能的光譜上的最終端就是機器學習

and honestly, it's one of the most exciting areas of AI.

而說實話，這是 AI 讓人最興奮的領域之一

Like a human, a machine retains information

像一個人類一般，一個機器獲取訊息

and becomes smarter over time.

並且隨時間變得更加聰明

But unlike a human, it's not susceptible to things like

但是跟人不同的地方，它不是非常容易發生像是

short-term memory loss, information overload,

短期記憶的流失、資訊量過載

sleep deprivation, and distractions.

睡眠剝奪以及受到分心

But how do these machines actually learn?

但是這些機器到底是如何進行學習的？

Well, while it may be easy for a human to know

這個麻，人們很容易能夠知道

the difference between a cat and a dog,

一隻狗和一隻貓的不同點

for a computer, not so much.

但對一部電腦來說，不是這麼容易的

You see, when you're only considering

你看，當你只考慮到

physical appearance, the difference between

形體的外表，這些在貓和狗之間

cats and dogs can be a little gray.

的差異就會有點模糊

You can say cats have pointed ears

你可以說一隻貓有尖尖的耳朵

and dogs have floppy ears,

而狗狗有軟趴趴耳朵

but those rules aren't universal.

但是這些規則並非普遍一致適用

Between tail length, fur texture, and color,

在以八的長度、毛的質地，和顏色

there are a lot of options,

有非常多的選擇

and that means a lot of tedious rules someone would

這代表很多生澀難解的規則

have to program manually to help a computer

會需要被寫進電腦程式中幫助電腦

spot the difference.

去判斷它們這之間的差異

But remember -- machine learning is about making

但切記，機器學習是關於

machines learn like humans. And like any toddler,

如何讓機器像人一樣去學習。而像每個寶寶一樣

that means they have to learn by experience.

代表它們需要透過經驗來學習

With machine learning, programs analyze

關於機器學習，電腦程式會分析

thousands of examples to build an algorithm.

上千筆的案例來建立一組演算法

It then tweaks the algorithm

然後它會根據它是否達成目標

based on if it achieves its goal.

來調整演算法

Over time, the program actually gets smarter.

隨著時間，程式的確會變得更聰明

That's how machines like IBM's Watson can

這是像 IBM 的華生電腦一樣的機器如何能夠

diagnose cancer, compose classical symphonies,

診斷癌症、譜出古典樂曲

or crush Ken Jennings at Jeopardy.

或者在 Jeopardy 上擊潰 Ken Jennings 的原因

Some programs even mimic the way

某些程式甚至會模仿人類

the human brain is structured,

大腦的組成方式

complete with neural networks that help humans --

以神經網路姿態出現來幫助人類

and now machines -- solve problems.

以及現今的機器來解決問題

Generations have long imagined the ramifications of AI,

幾個世代以來人類長期一直想像 AI 可能的各種發展

visualizing a society where machines seek revenge

描繪一個機器對人類復仇的社會狀況

and wreak havoc on human society.

導致人類社會的毀滅

However, the more logical and pressing question is:

然而，更符合邏輯的問題將是：

How will AI affect your job?

AI 對你的工作會產生什麼影響？

Will it make your work obsolete?

它將會讓你的工作被取代掉嗎？

Just like the Industrial Revolution,

就如工業革命一樣

it's not human versus machine.

這並不是人類對上機器

It's human and machine versus problem.

而是人類和機器一同面對問題

The point is that artificial intelligence

重點在人工智慧

helps you accomplish more in less time,

會幫助你以更少的時間完成更多的事情

taking on the repetitive tasks of your job

把你工作中重複性的部分分擔掉

while you master the strategy and relationships.

而讓你精於處理事情的策略和人際關係的經營

That way, humans can do what they do best … be human.

如此一來，人類便可以去做他們最擅長的事情...當一個真正的人類