第十五章现代计算机奠基者阿兰·图灵-Alan Turing

翻译内容

Hi, I'm Carrie Anne and welcome to Crash Course computer science.
(｡･∀･)ﾉﾞ嗨，我是 Carrie Anne，欢迎收看计算机科学速成课！

Over the past a few episodes,
前几集我们聊了基础，比如函数，算法和数据结构

we've been building up our understanding of computer science fundamentals,
前几集我们聊了基础，比如函数，算法和数据结构

such as functions, algorithms and data structures.
前几集我们聊了基础，比如函数，算法和数据结构

Today, we're going to take a step back and look at the person
今天，我们来看一位对计算机理论 贡献巨大的人

who formulated many of the theoretical concepts that underline modern computation.
今天，我们来看一位对计算机理论 贡献巨大的人

The father of computer science
计算机科学之父

and not quite Benedict Cumberbatch lookalike, Alan Turing.
长得不怎么像 本尼 的 阿兰·图灵

Alan Mathison Turing was born in London in 1912
阿兰·马蒂森·图灵 于 1921 年出生在伦敦，\N 从小就表现出惊人数学和科学能力

and showed an incredible aptitude for maths and science throughout his early education.
阿兰·马蒂森·图灵 于 1921 年出生在伦敦，\N 从小就表现出惊人数学和科学能力

His first brush of what we now call computer science came in 1935
他对计算机科学的建树始于 1935 年

while he was a master student at King's College in Cambridge.
当时他是剑桥国王学院的硕士生

He set out to solve a problem posed by German Mathematician David Hilbert
他开始解决德国数学家 大卫·希尔伯特 提出的问题

known as the Entscheidungsproblem
叫 Entscheidungsproblem （德语）

or decision problem,
即"可判定性问题":

which asked the following:
即"可判定性问题":

is there an algorithm that takes, as input, a statement written in formal logic,
是否存在一种算法，输入正式逻辑语句 \N 输出准确的"是"或"否"答案？

and produces a "yes" or "no" answer that's always accurate?
是否存在一种算法，输入正式逻辑语句 \N 输出准确的"是"或"否"答案？

If such an algorithm existed,
如果这样的算法存在， \N 可以回答比如 "是否有一个数大于所有数"

we could use it to answer questions like, "Is there a number bigger than all numbers?"
如果这样的算法存在， \N 可以回答比如 "是否有一个数大于所有数"

No, there's not. We know the answer to that one,
不, 没有. 我们知道答案

but there are many other questions in mathematics that we'd like to know the answer too.
但有很多其他数学问题，我们想知道答案

So if this algorithm existed, we'd want to know it.
所以如果这种算法存在, 我们想知道

The American mathematician Alonzo Church first presented a solution to this problem in 1935.
美国数学家 阿隆佐·丘奇 \N 于 1935年 首先提出解决方法

He developed a system of mathematical expressions called Lambda Calculus
开发了一个叫"Lambda 算子"的数学表达系统

and demonstrated that no such universal algorithm could exist.
证明了这样的算法不存在

Although Lambda Calculus was capable of representing any computation,
虽然"Lambda 算子"能表示任何计算

the mathematical technique was difficult to apply and understand.
但它使用的数学技巧 难以理解和使用

At pretty much the same time on the other side of the Atlantic,
同时在大西洋另一边

Alan Turing came up with his own approach to solve the decision problem.
阿兰·图灵 想出了自己的办法来解决"可判定性问题"

He proposed a hypothetical computing machine, which we now call a Turing Machine.
提出了一种假想的计算机，现在叫"图灵机"

Turing Machines provided a simple, yet powerful
图灵机提供了简单又强大的数学计算模型

mathematical model of computation.
图灵机提供了简单又强大的数学计算模型

Although using totally different mathematics,
虽然用的数学不一样

they were functionally equivalent to lambda calculus in terms of their computational power.
但图灵机的计算能力和 Lambda 算子一样

However their relative simplicity made them much more popular
同时因为图灵机更简单，所以在新兴的计算机领域更受欢迎

in the burgeoning field of computer science.
同时因为图灵机更简单，所以在新兴的计算机领域更受欢迎

In fact, they're simple enough that I'm going to explain it right now.
因为它如此简单，我现在就给你解释

A Turing Machine is a theoretical computing device
图灵机是一台理论计算设备

There's also a state variable in which we can hold a piece of information
还有一个状态变量，保存当前状态

about the current state of the machine.
还有一个状态变量，保存当前状态

And a set of rules that describes what the machine does.
还有一组规则，描述机器做什么

Given a state and the current symbol the head is reading,
规则是根据 当前状态+读写头看到的符号，决定机器做什么

the rule can be to write a symbol on the tape,
结果可能是在纸带写入一个符号

change the state of the machine, move the read/write head to the left or right by one spot
或改变状态，或把读写头移动一格

or any combination of these actions.
或执行这些动作的组合

To make this concrete, let's work through a simple example:
为了更好理解，讲个简单例子：

a Turing Machine that reads a string of ones ending in a zero
让图灵机读一个以零结尾的字符串

and computes whether there is an even number of ones.
并计算 1 的出现次数 是不是偶数

If that's true,
如果是, 在纸带上写一个 1

the machine will write a one to the tape
如果是, 在纸带上写一个 1

and if it's false, it'll write a zero.
如果不是，在纸带上写一个 0

First we need to define our Turing machine rules.
首先要定义"图灵机"的规则

If the state is even and the current symbol of the tape is one,
如果当前状态是"偶数", 当前符号是1

then we update the machine state to odd and move the head to the right.
那么把状态更新为"奇数"，把读写头向右移动

On the other hand if the state is even and the current symbol is zero,
如果当前状态为偶数，当前符号是 0

which means we've reached the end of the string of ones,
意味着到了字符串结尾

then we write one to the tape and change the state to halt,
那么在纸带上写一个 1，并且把状态改成 停机(halt)

as in we're finished and the Turing machine has completed the computation.
状态改为"停机" 是因为图灵机已完成计算

We also need rules for when the Turing machine is in an odd state,
但我们还需要 2 条规则，来处理状态为奇数的情况

one rule for the symbol on the tape is a zero and another for when it is one.
一条处理 奇数 + 纸带是 0 的情况 \N 一条处理 奇数 + 纸带是 1 的情况

Lastly we need to define a Starting state, which we'll set to be even.
最后，要决定机器的初始状态，这里定成"偶数"

Now we've defined the rules in the starting state of our Turing machine,
定义好了 起始状态+规则

which is comparable to a computer program, we can run it on some example input.
就像写好了程序，现在可以输入了

Let's say we store 1 1 0 onto tape.
假设把"1 1 0"放在纸带上，有两个 1，是偶数

That's two ones, which means there is an even number of ones,
假设把"1 1 0"放在纸带上，有两个 1，是偶数

and if that's news to you,
如果"偶数"对你是新知识 \N 也许我们该开一门【十分钟速成课：数学】

We should probably get working on crash course Math.
如果"偶数"对你是新知识 \N 也许我们该开一门【十分钟速成课：数学】

Notice that our rules only ever move their head to the right
注意，规则只让 读写头 向右移动

so the rest of the tape is irrelevant.
其他部分无关紧要，为了简单所以留空

We'll leave it blank for simplicity.
其他部分无关紧要，为了简单所以留空

Our Turing machine is all ready to go so let's start it.
"图灵机"准备好了，开始吧

Our state is even and the first number we see is one.
机器起始状态为"偶数"，看到的第一个数是 1

That matches our topmost rule and so we execute the effect,
符合最上面那条规则，所以执行对应的步骤

which is to update the state to odd and move the read/write head to the right by one spot.
把状态更新到"奇数"， 读写头向右移动一格

Okay, now we see another one on the tape, But this time our state is odd
然后又看到 1, 但机器状态是"奇数"，所以执行第三条规则

and so we execute our third rule
然后又看到 1, 但机器状态是"奇数"，所以执行第三条规则

which sets the state back to even and moves the head to the right.
使机器状态变回"偶数"，读写头向右移动一格

Now we see a 0 and our current state is even
现在看到 0，并且机器状态是 偶数，所以执行第二条规则

so we execute our second rule
现在看到 0，并且机器状态是 偶数，所以执行第二条规则

which is to write a 1 to the tape signifying that yes, it's true,
在纸带上写 1，表示"真" 的确有偶数个 1

there is an even number of ones,
在纸带上写 1，表示"真" 的确有偶数个 1

and finally the machine halts.
然后机器停机

That's how Turing machines work.
这就是图灵机的原理，很简单对吧？

Pretty simple, right?
这就是图灵机的原理，很简单对吧？

so you might be wondering why there's such a big deal.
你可能想知道 有什么大不了的

Well, Turing shows that this simple hypothetical machine
图灵证明了这个简单假想机器

can perform any computation if given enough time and memory.
如果有足够时间和内存，可以执行任何计算

It's a general-purpose computer.
它是一台通用计算机

Our program was a simple example.
刚才的程序就是个简单例子

But with enough rules, states and tape,
只要有足够的规则，状态和纸带 可以创造任何东西

you could build anything
只要有足够的规则，状态和纸带 可以创造任何东西

• a web browser, world of warcraft, whatever!
  浏览器, 魔兽世界 任何东西！

Of course it would be ridiculously inefficient, but it is theoretically possible.
当然 这样做效率很低，但理论上可行.

And that's why, as a model of computing,
所以图灵机是很强大的计算模型

it's such a powerful idea.
所以图灵机是很强大的计算模型

In fact, in terms of what it can and cannot compute
事实上，就可计算和不可计算而言

there's no computer more powerful than a turing machine.
没有计算机比图灵机更强大

A computer that is as powerful is called Turing complete.
和图灵机一样强大的，叫 "图灵完备"

Every modern computing system, your laptop, your smartphone
每个现代计算系统 比如笔记本电脑，智能手机

and even the little computer inside your microwave and thermostat
甚至微波炉和恒温器内部的小电脑

are all Turing Complete.
都是"图灵完备"的

To answer Hilbert's decision problem,
为了回答可判定性问题

Turing applied these new Turing machines to an intriguing computational puzzle:
他把图灵机用于一个有趣计算问题：

the halting problem.
"停机问题"

Put simply this asks
简单说就是

"Is there an algorithm that can determine,
"给定图灵机描述和输入纸带，是否有算法可以确定

given a description of a turing machine and the input from its tape,
"给定图灵机描述和输入纸带，是否有算法可以确定

whether the Machine will run forever or halt?"
机器会永远算下去还是到某一点会停机？

For example we know our Turing machine will halt when given the input 1 1 0
我们知道输入 1 1 0，图灵机会停机

Because we literally walk through the example until it halted,
因为刚做过这个例子，它最后停机了

but what about a more complex problem?
但如果是更复杂的问题呢？

Is there a way to figure out if the program will halt without executing it?
有没有办法在不执行的情况，弄清会不会停机？

Some programs might take years to run
一些程序可能要运行好几年

so it would be useful to know before we run it
所以在运行前知道 会不会出结果很有用

and wait and wait and wait and then start getting worried and wonder
否则就要一直等啊等，忧虑到底会不会出结果

and then decades later when you're old and gray control-alt-delete.
当几十年后变老了，再按强制结束

So much sadness!
好悲伤！

Unfortunately, Turing came up with a proof that shows the halting problem was in fact unsolvable,
图灵通过一个巧妙逻辑矛盾 \N 证明了停机问题是无法解决的

through a clever logical contradiction.
图灵通过一个巧妙逻辑矛盾 \N 证明了停机问题是无法解决的

Let's follow his reasoning.
我们来看看他的推理

Imagine we have a hypothetical Turing machine that takes a description of a program
想象有一个假想图灵机，\N 输入：问题的描述 + 纸带的数据

and some input for his tape
想象有一个假想图灵机，\N 输入：问题的描述 + 纸带的数据

and always outputs either Yes, it halts, or no, it doesn't.
输出 Yes 代表会"停机"，输出 No 代表不会

And I'm going to give this machine a fun name
我要给这台机器一个有趣的名字叫 H， \N 来自"停机"的第一个字母

H for Halts.
我要给这台机器一个有趣的名字叫 H， \N 来自"停机"的第一个字母

Don't worry about how it works.
不用担心它具体怎么工作

Let's just assume such a machine exists.
假设这样的机器存在就好 毕竟重点是推论

We're talking theory here.
假设这样的机器存在就好 毕竟重点是推论

Turing reasons if there existed a program whose halting behavior was not decidable by H,
图灵推理说： 如果有个程序， H 无法判断是否会"停机"

it would mean the halting problem is unsolvable.
意味着"停机问题"无法解决

To find one, Turing designed another Turing machine that built on top of H.
为了找到这样的程序，图灵用 H 设计了另一个图灵机

If H says the program halts,
如果 H 说程序会"停机"，那么新机器会永远运行（即不会停机）

then we'll make our new machine loop forever.
如果 H 说程序会"停机"，那么新机器会永远运行（即不会停机）

If the answer is no, it doesn't the halt.
如果 H 的结果为 No，代表不会停机

That will have the new machine output no and halt.
那么让新机器输出 No，然后"停机"

In essence, we're building a machine that does the opposite of what H says.
实质上是一台和 H 输出相反的机器

Halt if the program doesn't halt
如果程序不停机，就停机

and run forever if the program halts.
如果程序停机，就永远运行下去

So this argument will also need to add a splitter to the front of our new machine.
我们还需要在机器前面加一个分离器

So it accepts only one input and passes that as both the program and input into H.
让机器只接收一个输入，\N 这个输入既是程序，也是输入

Let's call this new Machine Bizzaro.
我们把这台新机器叫 异魔

So far this seems like a plausible machine right.
目前为止，这个机器不难理解

Now it's going to get pretty complicated.
但接下来马上会变复杂，会有点难懂

But bear with me for a second.
但接下来马上会变复杂，会有点难懂

Look what happens when you pass bizzaro a description of itself as the input.
如果把 异魔 的描述，作为本身的输入会怎样

This means We're asking h what bizzaro will do when asked to evaluate itself.
意味着在问 H ，当异魔的输入是自己时会怎样

But if H says Bizzaro halts,
但如果 H 说异魔会停机

then Bizzaro enters its infinite loop and thus doesn't halt.
那么异魔会进入无限循环，因此不会停机

And if H says the Bizzaro doesn't halt, then Bizzaro outputs no and halt.
如果 H 说异魔不会停机，那么异魔会输出 No 然后停机

So H can't possibly decide the halting problem correctly
所以 H 不能正确判定 停机问题

because there is no answer.
因为没有答案

It's a paradox.
这是一个悖论

And this paradox means that the halting problem cannot be solved with Turing machines.
意味着"停机问题"不能用图灵机解决

Remember Turing proves that Turing machines could implement any computation.
还记得刚刚说： 图灵证明了图灵机可以实现任何计算

So this solution to the halting problem proves
"停机问题"证明了，不是所有问题都能用计算解决

that not all problems can be solved by computation.
"停机问题"证明了，不是所有问题都能用计算解决

Wow, that's some heavy stuff.
哇，好难理解

I might have to watch that again myself.
我都可能要再看一遍

Long story short, Church and Turing showed there were limits to the ability of computers.
长话短说，丘奇和图灵证明了计算机的能力有极限

No matter how much time or memory you have,
无论有多少时间或内存，有些问题是计算机无法解决的

there are just some problems that cannot be solved ever.
无论有多少时间或内存，有些问题是计算机无法解决的

The concurrent efforts by Church and Turing to determine the limits of computation,
丘奇和图灵证明了计算是有极限的，

and in general, formalize computability, are now called the Church-Turing Thesis.
起步了可计算性理论，现在叫"丘奇-图灵论题"

At this point in 1936, Turing was only 24 years old
当时是1936年，图灵只有24岁

and really only just beginning his career.
他的职业生涯才刚刚开始

From 1936 through 1938,
从1936年到1938年 \N 在丘奇指导下，他在普林斯顿拿到博士学位

he completed a PhD at Princeton University under the guidance of Church
从1936年到1938年 \N 在丘奇指导下，他在普林斯顿拿到博士学位

then after graduating he returned to Cambridge.
毕业后回到剑桥

Shortly after in 1939, Britain became embroiled in World War II.
1939年后不久，英国卷入第二次世界大战

Turing's genius was quickly applied for the war effort.
图灵的才能很快被投入战争

In fact, a year before the war started,
事实上，在战争开始前一年

he was already working part-time at the UK's government Code and Cypher school,
他已经在英国政府的 密码破译学校兼职

which was the British code breaking group based out of Bletchley Park.
位于"布莱切利园"的一个密码破译组织

One of his main efforts was figuring out how to decrypt German communications.
他的工作内容之一是破解德国的通信加密

Especially those that use the Enigma Machine.
特别是"英格玛机"加密的信息

In short, these machines scrambled text
简单说，英格玛机会加密明文

like you type the letters H-E-L-L-O
如果输入字母 H-E-L-L-O

and the letters X-W-D-B-J would come out.
机器输出 X-W-D-B-J

This process is called Encryption.
这个过程叫"加密"

The scrambling wasn't random.
文字不是随便打乱的

The behavior was defined by a series of real world rotors on the top of the enigma machine.
加密由"英格玛机"顶部的齿轮组合决定

Each were 26 possible rotational positions.
每个齿轮有26个可能位置

There was also a plug board at the front of the machine that allow pairs of letters to be swapped.
机器前面还有插板，可以将两个字母互换

In total, there were billions of possible settings.
总共有上十亿种可能

If you had your only enigma machine and you knew the correct rotor and plug board settings,
如果你有"英格玛机"，并且知道正确的齿轮和插头设置

you could type in X-W-D-B-J and "hello" would come out.
输入X-W-D-B-J，机器会输出 hello

In other words, you decrypted the message.
解密了这条消息

Of course, the German military wasn't sharing their enigma settings on Social Media.
当然，德军不会把机器设置发到微博上

So the allies had to break the code.
盟军必须自己破译密码

With billions of Rotor and plug board combinations,
有数十亿种组合，根本没法手工尝试所有组合

there was no way to check them all by hand.
有数十亿种组合，根本没法手工尝试所有组合

Fortunately for Turing, Enigma Machines and the people who operated them were not perfect.
幸运的是，英格玛机和操作员不是完美的

Like one key flaw was that a letter would never be encoded as itself,
一个大缺陷是：字母加密后绝不会是自己

as in an H was never encrypted as an H.
H 加密后绝对不是 H

Turing building on earlier work by Polish code breakers
图灵接着之前波兰破译专家的成果继续工作

designed a special-purpose electro-mechanical computer called the bombe
设计了一个机电计算机，叫 Bombe

that took advantages of this flaw.
利用了这个缺陷，它对加密消息尝试多种组合

It tried lots and lots of combinations of enigma settings for a given encrypted message.
利用了这个缺陷，它对加密消息尝试多种组合

If the bombe found a setting that led to a letter being encoded as itself
如果发现字母解密后和原先一样

which we know no enigma machines could do.
我们知道英格玛机决不会这么做

That combination was discarded then the machine moved on to try another combination.
这个组合会被跳过，接着试另一个组合

So bombe was used to greatly narrow the number of Possible enigma settings.
Bombe 大幅减少了搜索量

This allowed human code breakers to hone their efforts on the most probable solutions,
让破译人员把精力花在更有可能的组合

looking for things like common german words in fragments of decoded text.
比如在解码文本中找常见的德语单词

Periodically, the Germans would suspect someone was decoding their communications
德国人时不时会怀疑有人在破解，然后升级英格玛机

and upgrade the enigma machine,
德国人时不时会怀疑有人在破解，然后升级英格玛机

like they'd add another rotor creating many more combinations.
比如加一个齿轮，创造更多可能组合

They even built entirely new encryption machines.
他们甚至还做了全新的加密机

Throughout the war, Turing and his colleagues at Bletchley Park
整个战争期间，图灵和同事在布莱切利园努力破解加密

worked tirelessly to defeat these mechanisms.
整个战争期间，图灵和同事在布莱切利园努力破解加密

And overall, the intelligence gained from decrypted German communications
解密得到的德国情报，为盟军赢得了很多优势

gave the allies an edge in many theaters
解密得到的德国情报，为盟军赢得了很多优势

with some historians arguing is shortened the war by years.
有些史学家认为他们把战争减短了好几年

After the war, Turing return to academia
战后，图灵回到学术界 \N 为许多早期计算机工作做出贡献

and contributed to many early electronic computing efforts
战后，图灵回到学术界 \N 为许多早期计算机工作做出贡献

like the Manchester Mark 1, which was an early and influential stored-program computer.
比如曼彻斯特 1 号，一个早期有影响力的存储程序计算机

But his most famous post-war contribution was the Artificial Intelligence.
但他最有名的战后贡献是"人工智能"

A field's so new that it didn't get that name until 1956.
这个领域很新，直到1956年才有名字

It's a huge topic. So we'll get to it again in future episodes.
这个话题很大，以后再谈（第34集）

In 1950, Turing could envision a future where computers
1950 年，图灵设想了未来的计算机

were powerful enough to exhibit intelligence equivalent to
拥有和人类一样的智力，或至少难以区分

or at least indistinguishable from that of a human.
拥有和人类一样的智力，或至少难以区分

Turing postulated that a computer would deserve to be called intelligent
图灵提出 \N 如果计算机能欺骗人类相信它是人类，才算是智能

if it could deceive a human into believing that it was human.
图灵提出 \N 如果计算机能欺骗人类相信它是人类，才算是智能

This became the basis of a simple test, now called the Turing test.
这成了智能测试的基础，如今叫"图灵测试"

Imagine that you are having a conversation with two different people
想像你在和两个人沟通 \N 不用嘴或面对面，而是来回发消息

not by voice or in person, but by sending type notes back and forth,
想像你在和两个人沟通 \N 不用嘴或面对面，而是来回发消息

you can ask any questions you want and you get replies.
可以问任何问题，然后会收到回答

But one of those two people is actually a computer.
但其中一个是计算机

If you can't tell which one is human and which one is a computer,
如果你分不出哪个是人类，哪个是计算机

then the computer passes the test.
那么计算机就通过了图灵测试

There's a modern version of this test called
这个测试的现代版叫

a completely automated public turing test to tell computers and humans apart
"公开全自动图灵测试，用于区分计算机和人类"

or Captcha for short.
简称"验证码"

These are frequently used on the internet to prevent automated systems
防止机器人发垃圾信息等

from doing things like posting spam on websites.
防止机器人发垃圾信息等

I'll admit sometimes I can't read what those squiggly things say.
我承认 有时我都认不出那些扭曲的东西是什么字

Does that mean I'm a computer?
这难道意味着我是计算机？

Normally in this series, we don't delve into the personal lives of these historical figures.
通常这个系列我们不会深入历史人物的个人生活

But in Turing's case his name has been inextricably tied to tragedy
但图灵与悲剧密不可分

so his story is worth mentioning.
所以他的故事值得一提

Turing was gained a time when homosexuality was illegal in the United Kingdom and much of the world.
图灵那个时代，同性恋是违法的，英国和大部分国家都是

And an investigation into a 1952 Burglary at his home
1952 年调查他家的入室盗窃案时，向当局暴露了他的性取向

revealed his sexual orientation to the authorities,
1952 年调查他家的入室盗窃案时，向当局暴露了他的性取向

who charged him with gross indecency.
被起诉 "行为严重不检点"

Turing was convicted and given a choice between imprisonment,
图灵被定罪，有2个选择： \N 1. 入狱 2. 接受激素来压制性欲

or probation with hormonal treatments to suppress his sexuality.
图灵被定罪，有2个选择： \N 1. 入狱 2. 接受激素来压制性欲

He chose the latter in part to continue his academic work,
他选了后者，部分原因是为了继续学术工作

but it altered his mood and personality.
但药物改变了他的情绪和性格

Although the exact circumstances will never be known,
虽然确切情况永远无法得知

it's most widely accepted that Alan Turing took his own life by poison in 1954.
图灵于1954年服毒自尽，年仅41岁

He was only 41.
图灵于1954年服毒自尽，年仅41岁

Many things have been named in recognition of Turing's contributions to theoretical computer science
由于图灵对计算机科学贡献巨大，许多东西以他命名

But perhaps the most prestigious among them is the Turing award
其中最出名的是"图灵奖"

the highest distinction in the field of computer science.
计算机领域的最高奖项

Equivalent to a Nobel prize in Physics, chemistry or other sciences.
相当于物理, 化学等其它领域的诺贝尔奖

Despite a life cut short, Alan inspire the first generation of computer scientists
虽然英年早逝，但图灵激励了第一代计算机科学家

and lead key groundwork that enabled a digital era that we get to enjoy today.
而且为如今便利的数字时代 做出了重要基石性工作

I'll see you next week.
我们下周见