How many of you had to fill out a web form where you've been asked to read a distorted sequence of characters like this? How many of you found it really annoying?
有多少人在填写网页表格时 需要识别像这样扭曲的词语? 有多少人觉得很烦人? 哇,不少呢。我就是发明这个的人。
(Laughter)
OK, outstanding. So I invented that.
(笑声)
(Laughter)
或者说我是其中之一
Or I was one of the people who did it. That thing is called a CAPTCHA. And it is there to make sure you, the entity filling out the form, are a human and not a computer program that was written to submit the form millions of times. The reason it works is because humans, at least non-visually-impaired humans, have no trouble reading these distorted characters, whereas programs can't do it as well yet. In the case of Ticketmaster, the reason you have to type these characters is to prevent scalpers from writing a program that can buy millions of tickets, two at a time.
这个称作验证码 其理由是保证填写表格的是一个真人 而不是什么电脑程序在操作 可以不停地填写表格 这是因为人类 至少是没有视力问题的人 可以识别这些扭曲的文字 而机器做不到 比如说在票务大全网站上 你输入这些扭曲字符的原因 是防止黄牛写一个电脑程序 一次购买上万张票
CAPTCHAs are used all over the Internet. And since they're used so often, a lot of times the sequence of random characters shown to the user is not so fortunate. So this is an example from the Yahoo registration page. The random characters that happened to be shown to the user were W, A, I, T, which, of course, spell a word. But the best part is the message that the Yahoo help desk got about 20 minutes later.
验证码在网络上普遍应用 因其普遍性 很多时候使用者就会看到一些 异常搭配的文字排序 这个例子来自雅虎注册网页 使用者看到的这几个随机字母 W,A,I, T,正好组成了“等” 最有意思的是 这是20分钟后的帮助页面
[Help! I've been waiting for over 20 minutes and nothing happens.]
文字:“帮忙!我已经等了二十多分钟,没有任何变化。”
(Laughter)
(笑声)
This person thought they needed to wait. This, of course, is not as bad as this poor person.
这人以为网站让他等着 当然还有更倒霉的
(Laughter)
(笑声)
CAPTCHA Project is something that we did at Carnegie Melllon over 10 years ago, and it's been used everywhere. Let me now tell you about a project that we did a few years later, which is sort of the next evolution of CAPTCHA. This is a project that we call reCAPTCHA, which is something that we started here at Carnegie Mellon, then we turned it into a start-up company. And then about a year and a half ago, Google actually acquired this company.
验证码计划是我们十多年前在卡内基梅隆大学做起来的 并被广泛应用 现在谈谈几年后我们做的一个项目 算是验证码的新生代版本 这个计划我们称之“reCAPTCHA” 这个计划是从卡内基梅隆大学起步 成为我们的启动公司 一年半前 谷歌收购了这个公司
Let me tell you what this project started. This project started from the following realization: It turns out that approximately 200 million CAPTCHAs are typed everyday by people around the world. When I first heard this, I was quite proud of myself. I thought, look at the impact my research has had. But then I started feeling bad. Here's the thing: each time you type a CAPTCHA, essentially, you waste 10 seconds of your time. And if you multiply that by 200 million, you get that humanity is wasting about 500,000 hours every day typing these annoying CAPTCHAs.
现在我来说说这个项目的初始 这个项目是出于以下认识: 每天全球范围内有大约2亿次 验证码输入 我头次听到的时候还挺自豪 我想 我们的研究影响力不小啊 接着我就感觉很难受 因为每次你输入一个验证码 你就浪费了10秒钟 这个乘以2亿 全人类每天就浪费了50万个小时 来输入烦人的验证码
(Laughter)
我就很难受了
So then I started feeling bad.
(笑声)
(Laughter)
我开始思考 既然不能放弃验证码
And then I started thinking, of course, we can't just get rid of CAPTCHAs, because the security of the web depends on them. But then I started thinking, can we use this effort for something that is good for humanity? So see, here's the thing. While you're typing a CAPTCHA, during those 10 seconds, your brain is doing something amazing. Your brain is doing something that computers cannot yet do. So can we get you to do useful work for those 10 seconds? Is there some humongous problem that we cannot yet get computers to solve, yet we can split into tiny 10-second chunks such that each time somebody solves a CAPTCHA, they solve a little bit of this problem? And the answer to that is "yes," and this is what we're doing now.
因为网页安全依赖于此 那么有什么方法可以利用它 来做点好事呢? 关键在于 当你在10秒钟内输入验证码的时候 你的大脑在做了不起的工作 这是电脑目前尚无法做到的 那么能不能让这10秒钟的工作变得有意义呢? 也就是说 有没有什么目前电脑无法解决的难题 但是可以分割成10秒的单位小块 这样每个人通过验证码 解决这个问题的一个小单位? 答案是肯定的话 这就是我们目前在做的
Nowadays, while you're typing a CAPTCHA, not only are you authenticating yourself as a human, but in addition you're helping us to digitize books. Let me explain how this works. There's a lot of projects trying to digitize books. Google has one. The Internet Archive has one. Amazon, with the Kindle, is trying to digitize books. Basically, the way this works is you start with an old book. You've seen those things, right? Like a book?
也许你不知道 如今当你输入一个验证码 不仅仅是在证明你是真人 也是在把书电子化 我来解释一下 目前有很多书籍电子化的项目 谷歌有一个。 “互联网档案”有一个 现亚马逊的Kindle也有一个 方法就是 从一本旧书开始 你见过书对吧?一本书? (笑声)
(Laughter)
首先扫描一本书
So you start with a book and then you scan it.
扫描就是
Now, scanning a book is like taking a digital photograph of every page. It gives you an image for every page. This is an image with text for every page of the book. The next step in the process is that the computer needs to be able to decipher the words in this image. That's using a technology called OCR, for optical character recognition, which takes a picture of text and tries to figure out what text is in there. Now, the problem is that OCR is not perfect. Especially for older books where the ink has faded and the pages have turned yellow, OCR cannot recognize a lot of the words. For things that were written more than 50 years ago, the computer cannot recognize about 30 percent of the words. So now we're taking all of the words that the computer cannot recognize and we're getting people to read them for us while they're typing a CAPTCHA on the Internet.
相当于把每一页照一张数码照片 你就有了这本书每一页的照片 这是一本书每一页文字内容的照片 下一步就是 电脑得解读这些照片上的每一个字 这涉及到一个叫做OCR的技术 也就是光学字符识别 拍下一段文字的照片 然后识别出文字内容 问题是光学字符识别的技术并不能解决所有问题 特别对于旧书 墨水褪色,书页泛黄 很多字OCR无法识别 比如,五十多年前的书 有百分之三十的单词电脑无法识别 我们做的就是 摘录出电脑无法识别的单词 通过真人在网上输入验证码时 阅读识别出来
So the next time you type a CAPTCHA, these words that you're typing are actually words from books that are being digitized that the computer could not recognize. The reason we have two words nowadays instead of one is because one of the words is a word that the system just got out of a book, it didn't know what it was and it's going to present it to you. But since it doesn't know the answer, it cannot grade it. So we give you another word, for which the system does know the answer. We don't tell you which one's which and we say, please type both. And if you type the correct word for the one for which the system knows the answer, it assumes you are human and it also gets some confidence that you typed the other word correctly. And if we repeat this process to 10 different people and they agree on what the new word is, then we get one more word digitized accurately.
下次当你输入一个验证码时,你输入的那个单词 实际是我们电子化书籍里 电脑无法识别的单词 现在我们使用两个而非一个单词的理由是 其中一个词是 系统把一个电脑无法识别的单词 提供给你 因为系统不认识这个单词 所以无法判断你的答案 我们就加入另一个单词 一个系统已经认识的单词 不告诉你哪个是已知的,哪个是未知的 请你将两者都输入 如果你能拼写正确 系统已认知的那个单词 就判断你为真人 这样对你输入的另一个单词就有所把握 我们把这个过程让十个人重复进行 如果他们对不识别单词的答案一致 我们就得到了一个准确电子化的新单词
So this is how the system works. And since we released it about three or four years ago, a lot of websites have started switching from the old CAPTCHA, where people wasted their time, to the new CAPTCHA where people are helping to digitize books. So every time you buy tickets on Ticketmaster, you help to digitize a book. Facebook: Every time you add a friend or poke somebody, you help to digitize a book. Twitter and about 350,000 other sites are all using reCAPTCHA. And the number of sites that are using reCAPTCHA is so high that the number of words we're digitizing per day is really large. It's about 100 million a day, which is the equivalent of about two and a half million books a year. And this is all being done one word at a time by just people typing CAPTCHAs on the Internet.
这就是这个系统的工作原理 大约三四年前我们导入这个系统 许多网站已经从旧的验证码 换成新的来帮助书籍电子化 而不是浪费人们的时间 比如“票务大全” 每次你在它的网站上购票 就在帮助把书籍电子化 脸书:每次你加好友或者打招呼 你就帮忙在把书籍电子化 推特和其他350,000个网站都在用reCAPTCHA 现在使用reCAPTCHA的网站是如此之多 每天我们电子化的单词数量惊人 大概是每天一亿 这就是每年大概250万本书 而这一切仅仅都是通过人们在网上 输入验证码来做到的 (掌声)
(Applause)
当然
Now, of course, since we're doing so many words per day, funny things can happen. This is especially true because now we're giving people two randomly chosen English words next to each other. So funny things can happen. For example, we presented this word. It's the word "Christians"; there's nothing wrong with it. But if you present it along with another randomly chosen word, bad things can happen. So we get this.
因为每天处理的词是如此之多 难免有搞笑的状况 特别是现在我们给出的单词是 两个随机组合的英语单词 就出现了有意思的事 比如 我们给出了这个词 “基督徒” 这没什么问题 问题是另外一个随机抽取的词 就把事情搞糟了 比如这个 (恶基督徒)
[bad Christians]
更糟的是 出现这个的网站
But it's even worse, because the website where we showed this actually happened to be called The Embassy of the Kingdom of God.
正好是“神之国度大使馆” (笑声)
(Laughter)
糟了
Oops.
(笑声)
(Laughter)
这儿还有一个
Here's another really bad one. JohnEdwards.com
JohnEdwards.com (该死的自由主义者)
[Damn liberal]
(Laughter)
(笑声)
So we keep on insulting people left and right everyday. Of course, we're not just insulting people. Here's the thing. Since we're presenting two randomly chosen words, interesting things can happen. So this actually has given rise to a really big Internet meme that tens of thousands of people have participated in, which is called CAPTCHA art. I'm sure some of you have heard about it. Here's how it works. Imagine you're using the Internet and you see a CAPTCHA that you think is somewhat peculiar, like this CAPTCHA.
我们就这么每天不停地羞辱别人 当然 不仅是人 其他东西也难逃厄运 因为我们是随机选取的单词 就有了很有趣的结果 这个正在成为 互联网上一个流行趋势 无数的人参与这个 所谓的验证码艺术 肯定有人听说过 是这样 假设你在上网看到一个验证码 你觉得很特别 比如这个 (隐形的烤面包机)
[invisible toaster]
你要做的就是截图
What you're supposed to do is you take a screenshot of it. Then of course, you fill out the CAPTCHA because you help us digitize a book. But first you take a screenshot and then you draw something that is related to it.
然后当然就是输入验证码 因为你在帮我们电子化书籍 接下来 你截了图 就画出与它相关的图像
(Laughter)
(笑声)
That's how it works.
就是这样
(Laughter)
这样作品大概有一万个
There are tens of thousands of these. Some of them are very cute.
有些很可爱 (握紧它)
[clenched it]
(笑声)
(Laughter)
有些很好玩
Some of them are funnier.
(大醉的创始人)
[stoned Founders]
(Laughter)
(笑声)
And some of them, like paleontological shvisle ...
还有一些
(Laughter)
比如 “古生物学的史维凿”
they contain Snoop Dogg.
说不定那儿有史诺谱・道格(美国说唱歌手)
(Laughter)
(笑声)
OK, so this is my favorite number of reCAPTCHA. So this is the favorite thing that I like about this whole project. This is the number of distinct people that have helped us digitize at least one word out of a book through reCAPTCHA: 750 million, a little over 10 percent of the world's population, has helped us digitize human knowledge. And it is numbers like these that motivate my research agenda. So the question that motivates my research is the following: If you look at humanity's large-scale achievements, these really big things that humanity has gotten together and done historically -- like, for example, building the pyramids of Egypt or the Panama Canal or putting a man on the Moon -- there is a curious fact about them, and it is that they were all done with about the same number of people. It's weird; they were all done with about 100,000 people. And the reason for that is because, before the Internet, coordinating more than 100,000 people, let alone paying them, was essentially impossible. But now with the Internet, I've just shown you a project where we've gotten 750 million people to help us digitize human knowledge. So the question that motivates my research is, if we can put a man on the Moon with 100,000, what can we do with 100 million?
这是我最喜欢的reCAPTCHA数字 这是我最喜欢的这个项目的部分 这个数字是 通过reCAPTCHA帮助我们电子化书籍中单词的人数 7.5亿 多于世界总人口的十分之一的人们 帮助我们电子化人类的知识 正是这样的数字激励我的研究进程 那激励我研究进程的问题如下: 试想人类的大型成就 人类共同 创造的那些大型历史性事物- 比如 建造埃及金字塔 开凿巴拿马运河 或者把人类送上月球- 这些工程都有个奇怪的事实 就是它们基本都是由一样数量的人们完成的 这很奇怪 这些工程都是由大概十万人完成 因为在互联网出现之前 整合十万人 这十万人的巨大酬劳基本上是无法支付的 但是有了互联网 刚刚展示的这个项目 就找到了7.5亿人 来帮助我们电子化人类知识 那么 激励我的研究的问题就是 如果十万人能把一个人送上月球 一亿人能做到什么呢?
So based on this question, we've had a lot of different projects that we've been working on. Let me tell you about one that I'm most excited about. This is something that we've been semiquietly working on for the last year and a half or so. It hasn't yet been launched. It's called Duolingo. Since it hasn't been launched, shhh!
基于这个问题 我们有很多项目在进行中 下面介绍一个最令我兴奋的项目 这是过去一年半里 我们低调进行的一个项目 还没有真正投入使用 它叫做Duolingo 因为我们还没有投入使用 嘘!
(Laughter)
(笑声)
Yeah, I can trust you'll do that. So this is the project. Here's how it started. It started with me posing a question to my graduate student, Severin Hacker. OK, that's Severin Hacker. So I posed the question to my graduate student. By the way, you did hear me correctly; his last name is Hacker.
我相信你们都会保密的 这个项目是这样开始的 它始于我向我的一名研究生提的问题 塞韦林・骇客 这就是他 我向他提了一个问题 另外你确实没听错 他姓骇客
(Laughter)
我向他提了个问题:
So I posed this question to him: How can we get 100 million people translating the web into every major language for free? There's a lot of things to say about this question. First of all, translating the web. Right now, the web is partitioned into multiple languages. A large fraction of it is in English. If you don't know English, you can't access it. But there's large fractions in other different languages, and if you don't know them, you can't access it. So I would like to translate all of the web, or at least most of it, into every major language. That's what I would like to do.
怎么才能找到一亿人 把互联网上的内容免费翻译成所有的主要语言? 这个问题有好几个方面 首先是翻译网页 现在的网页内容主要分为几大语言 其中一个大的分支是英语 如果你不会英语就无法使用 但是还有其他几种不同的语言 如果你不会那几种也无法使用 我打算把所有网页 大部分网页 翻译成主要语言 这是我想做的
Now, some of you may say, why can't we use computers to translate? Machine translation is starting to translate some sentences here and there. Why can't we use it to translate the web? The problem with that is it's not yet good enough and it probably won't be for the next 15 to 20 years. It makes a lot of mistakes. Even when it doesn't, since it makes so many mistakes, you don't know whether to trust it or not.
也许有人会说 怎么不用电脑翻译? 为什么我们不用机器翻译? 机器翻译已经在应用中 为什么不用它来翻译所有网页呢? 问题就是机器翻译还不够好 也许将来的15到20年内都不行 机器翻译有很多错误 甚至就算它翻对的时候 因为它的错误率太高 你也不敢相信它
So let me show you an example of something that was translated with a machine. Actually, it was a forum post. It was somebody who was trying to ask a question about JavaScript. It was translated from Japanese into English. So I'll just let you read. This person starts apologizing for the fact that it's translated with a computer. So the next sentence is going to be the preamble to the question. So he's just explaining something. Remember, it's a question about JavaScript.
比如这个例子 是由机器翻译的 这是个论坛帖子 有人提了关于Java语言的一个问题 是从日语翻译成英语 你可以读一下 他首先道歉 这是机器翻译的内容 下一个句子开始涉及问题 他开始说明 记住 这个问题是关于Java语言的
[At often, the goat-time install a error is vomit.]
(文字:常常,山羊时间启动错误被吐出来)
(Laughter)
(笑声)
Then comes the first part of the question.
接下来是问题的第一部分
[How many times like the wind, a pole, and the dragon?]
(文字:有多少次像风,像杆子,像龙?)
(Laughter)
(笑声)
Then comes my favorite part of the question.
接下来是最好玩的部分
[This insult to father's stones?]
(文字:这是对父亲的石头的侮辱?)
(Laughter)
(笑声)
And then comes the ending, which is my favorite part of the whole thing.
接下来是结尾 我最喜欢的部分 (文字:请为你的愚蠢道歉,很多谢谢)
[Please apologize for your stupidity. There are a many thank you.]
(笑声)
(Laughter)
可见 机器翻译 还不够好
OK, so computer translation, not yet good enough. So back to the question. So we need people to translate the whole web. So now the next question you may have is, well, why can't we just pay people to do this? We could pay professional translators to translate the whole web. We could do that. Unfortunately, it would be extremely expensive. For example, translating a tiny fraction of the whole web, Wikipedia, into one other language, Spanish. OK? Wikipedia exists in Spanish, but it's very small compared to the size of English. It's about 20 percent of the size of English. If we wanted to translate the other 80 percent into Spanish, it would cost at least 50 million dollars -- and this is even at the most exploited, outsourcing country out there. So it would be very expensive. So what we want to do is, we want to get 100 million people translating the web into every major language for free.
回到问题上去 我们需要人来翻译所有网页 下一个问题是 为什么不付钱找人做呢? 我们可以找专业翻译人员来翻译整个网页 可以这么做 但是 这会无比昂贵 比如 翻译互联网很小很小的一个部分 维基百科 英语翻译成西班牙语 维基百科有西班牙语 但是相比英语部分小多了 大概是英语内容的百分之二十 如果我们把剩下的百分之八十翻译成英语 就得至少五千万美元- 这还是在最便宜的服务外包国家 所以这个方法很昂贵 我们要的是一亿人 免费把网页内容翻译成 所有主要语言
If this is what you want to do, you quickly realize you're going to run into two big hurdles, two big obstacles. The first one is a lack of bilinguals. So I don't even know if there exists 100 million people out there using the web who are bilingual enough to help us translate. That's a big problem. The other problem you're going to run into is a lack of motivation. How are we going to motivate people to actually translate the web for free? Normally, you have to pay people to do this. So how are we going to motivate them to do it for free? When we were starting to think about this, we were blocked by these two things. But then we realized, there's a way to solve both these problems with the same solution. To kill two birds with one stone. And that is to transform language translation into something that millions of people want to do and that also helps with the problem of lack of bilinguals, and that is language education.
如果你要这么做的话 就会意识到面临两个非常 巨大的障碍 首先是缺乏掌握双语的人 我甚至不知道 是否有一亿个互联网使用者 掌握双语来进行翻译 这是个大问题 另一个问题是缺少鼓励机制 怎么才能让人们 甘愿免费翻译网页? 通常你得付钱请人干活儿 那么怎么才能让他们无偿劳动呢? 当我们着手考虑这个项目的时候这是拦在面前的两大问题 后来我们意识到 有一个方法可以一举解决这两个问题 一箭双雕 这就是把翻译转化成 无数人想做的事情 同时解决双语人员人手不够的问题 这就是语言学习
So it turns out that today, there are over 1.2 billion people learning a foreign language. People really want to learn a foreign language. And it's not just because they're being forced to do so in school. In the US alone, there are over five million people who have paid over $500 for software to learn a new language. So people really want to learn a new language. So what we've been working on for the last year and a half is a new website -- it's called Duolingo -- where the basic idea is people learn a new language for free while simultaneously translating the web. And so basically, they're learning by doing.
当今 有超过12亿人口在学习外语 人们迫切得想学习外语 而且这不是学校里不得不做的功课 比如在美国 有超过五百万的人在为外语学习软件 每人支付超过五百美元 所有人们非常想学外语 过去一年半里我们建立的新网站 叫做Duolingo- 就是基于这个让人们免费学习外语 同时翻译网页的想法 就是让他们学以致用
So the way this works is whenever you're a just a beginner, we give you very simple sentences. There's a lot of very simple sentences on the web. We give you very simple sentences along with what each word means. And as you translate them and as you see how other people translate them, you start learning the language. And as you get more advanced, we give you more complex sentences to translate. But at all times, you're learning by doing.
使用方法是这样 如果你是个新手 我们会给出非常非常简单的句子 网页上有很多简单的句子 我们给出非常简单的句子 以及句中单词释义 然后你翻译一下 并且可以看到别人是如何翻译的 这样学习外语 当你级别提高后 我们会给出越来越复杂的句子让你翻译 这整个过程 你都是边学边用 这个方法令人疯狂之处
Now, the crazy thing about this method is that it actually really works. People are really learning a language. We're mostly done building it and now we're testing it. People really can learn a language with it. And they learn it about as well as the leading language learning software. So people really do learn a language. And not only do they learn it as well, but actually it's more interesting. Because with Duolingo, people are learning with real content. As opposed to learning with made-up sentences, people are learning with real content, which is inherently interesting. So people really do learn a language.
是它居然确实有效 首先 人们可以通过它学外语 我们建完了网站,它现正在测试中 人们可以用它学习外语 完全可以跟外语学习软件媲美 所以用它确实可以学外语 不仅可以学好 而且更有趣味性 因为通过Duolingo人们学的是真正的语言使用内容 而不是编造的句子 通过学习真正的文本内容,趣味性大大提高 这样人们就实实在在学习外语
But perhaps more surprisingly, the translations that we get from people using the site, even though they're just beginners, the translations that we get are as accurate as those of professional language translators, which is very surprising. So let me show you one example. This is a sentence that was translated from German into English. The top is the German. The middle is an English translation that was done by a professional translator who we paid 20 cents a word for this translation. And the bottom is a translation by users of Duolingo, none of whom knew any German before they started using the site. If you can see, it's pretty much perfect. Of course, we play a trick here to make the translations as good as professional language translators. We combine the translations of multiple beginners to get the quality of a single professional translator.
最令人惊讶的是 网站使用者的翻译 甚至是初学者的翻译 和专业的翻译人员几乎不相上下 这很让人惊讶 让我给你们看一个例子 这是一个从德语翻译成英语的例子 上面是德语 中间是一名专业英语翻译人员 翻译的句子 一个词二十美分的价钱 下面是Duolingo使用者的翻译 他们在使用该网站前 不会任何德语 可以看到 几乎很完美 当然 为了让翻译达到专业水准 我们也想了个办法 我们把多名翻译者的翻译结合起来 得到专业人员的水准
Now, even though we're combining the translations, the site actually can translate pretty fast. So let me show you, this is our estimates of how fast we could translate Wikipedia from English into Spanish. Remember, this is 50 million dollars' worth of value. So if we wanted to translate Wikipedia into Spanish, we could do it in five weeks with 100,000 active users. And we could do it in about 80 hours with a million active users. Since all the projects my group has worked on so far have gotten millions of users, we're hopeful that we'll be able to translate extremely fast.
即使我们要结合翻译 这个网站仍然可以迅速翻译 让我展示一下 这是我们对维基百科翻译工程的预计 从英语翻译成西班牙语 要记住 这可是价值五千万美元的工程 如果要把维基百科从英文翻译成西班牙语 十万名活跃用户可以在五周内完成 一百万活跃用户可以在八十小时内完成 现在我们的项目小组已经有了上百万使用者 我们希望可以以极快的速度 进行这个翻译工程
Now, the thing that I'm most excited about with Duolingo is I think this provides a fair business model for language education. So here's the thing: The current business model for language education is the student pays, and in particular, the student pays Rosetta Stone 500 dollars.
现在我对Duolingo最兴奋的就是 它为外语教育创造了一个公平的商业模式 是这样: 目前外语教育的商业模式是 学生付钱 主要就是学生购买罗赛塔石碑五百美元的软件
(Laughter)
(笑声)
That's the current business model. The problem with this business model is that 95 percent of the world's population doesn't have 500 dollars. So it's extremely unfair towards the poor. This is totally biased towards the rich. Now, see, in Duolingo, because while you learn, you're actually creating value, you're translating stuff -- which, for example, we could charge somebody for translations, so this is how we could monetize this. Since people are creating value while they're learning, they don't have to pay with their money, they pay with their time. But the magical thing here is that is time that would have had to have been spent anyways learning the language. So the nice thing about Duolingo is, I think, it provides a fair business model -- one that doesn't discriminate against poor people.
这是目前的商业模式 这个模式的问题是 世界人口的百分之九十五没有五百美元 所以这个模式对穷人极度不公平 这是个面向富人的模式 而Duolingo 因为你学习的时候 也创造价值,你在翻译东西- 因为比如我们得付钱给人翻译东西 这样你的学习过程就货币化了 因为人们学习的时候同时创造价值 他们就不用付钱 而是付出时间 最妙的是 虽然人们得付出时间 但这个时间是他们学习外语无论如何 都会付出的那部分时间 所以Duolingo做的好事就是提供了一个公平的商业模式- 这个模式对穷人一样敞开机会 这就是这个网站 谢谢
So here's the site. Thank you.
(掌声)
(Applause)
这个网站
We haven't yet launched, but if you go there, you can sign up to be part of our private beta, which is probably going to start in three or four weeks. We haven't yet launched it.
我们还没有投入应用 但是如果你去我们的页面的话可以注册 也许三四周后就可以开始了 我们还没有投入使用Duolingo
By the way, I'm the one talking here, but Duolingo is the work of a really awesome team,
另外 虽然是我在这里介绍Duolingo 但这个网站是一个优秀的团队的成果 这是其中一些人
some of whom are here. So thank you.
谢谢你们
(Applause)
(掌声)