Learning, fast and deep

快速深度学习

New schemes aim to teach anyone to use AI

一批新项目想教所有人编写AI

Over the past five years researchers in artificial intelligence have become the rock stars of the technology world. A branch of ai known as deep learning, which uses neural networks to churn through large volumes of data looking for patterns, has proven so useful that skilled practitioners can command high six-figure salaries to build software for Amazon, Apple, Facebook and Google. The top names can earn over $1m a year.

过去五年里，人工智能（以下简称AI）的研究人员已然成了科技界的摇滚明星。AI技术的一个分支、运用神经网络处理大量数据并从中寻找模式的“深度学习”被证明非常有用，亚马逊、苹果、Facebook和谷歌愿意开出六位数高薪，聘请熟练的专业人员编写软件。顶级专家更是年薪过百万美元。

The standard route into these jobs has been a PhD in computer science from one of America’s elite universities. Earning one takes years and requires a disposition suited to academia, which is rare among more normal folk. Graduate students are regularly lured away from their studies by lucrative jobs.

要从事这类工作，标准路径一般是在美国的某所顶尖大学取得计算机科学的博士学位。一个人要为此付出多年时间，性情也得适合做学术研究，普通人能有如此耐性的不多。面对高薪工作的诱惑，研究生往往会放弃研究生涯。

That is changing. Last month fast.ai, an education non-profit based in San Francisco, kicked off the third year of its course in deep learning. Since its inception it has attracted more than 100,000 students, scattered around the globe from India to Nigeria. The course and others like it come with a simple proposition: there is no need to spend years obtaining a PhD in order to practise deep learning. Creating software that learns can be taught as a craft, not as a high intellectual pursuit to be undertaken only in an ivory tower. Fast.ai’s course can be completed in just seven weeks.

但事情正在发生变化。上月，位于旧金山的非营利性教育机构fast.ai进入了它开办深度学习课程的第三年。自推出以来，这门课吸引了从印度到尼日利亚的全球各地十多万名学生。这类课程都有一个简单的主张：要从事深度学习方面的工作，没必要花几年时间拿博士学位。打造会学习的软件可以当一门手艺来教，而不是一种只能在象牙塔里传授的高级智力探索。Fast.ai的课程短短七周就可学完。

Demystifying the subject, to make it accessible to anyone who wants to learn how to build AI software, is the aim of Jeremy Howard, who founded fast.ai with Rachel Thomas, a mathematician. He says school mathematics is sufficient. “No. Greek. Letters,” Mr Howard intones, thumping the table for punctuation.

让深度学习不再神秘是杰里米·霍华德（Jeremy Howard）的目标，为此，他和数学家雷切尔·托马斯（Rachel Thomas）一起创立了fast.ai，让任何想学习编写AI软件的人都能学习这门技术。霍华德说有中学数学知识就足够了。“没有，希腊，字母。”他在桌上敲着拍子，一字一顿地说道。

It is working. A graduate from fast.ai’s first year, Sara Hooker, was hired into Google’s highly competitive AI residency programme after finishing the course, having never worked on deep learning before. She is now a founding member of Google’s new AI research office in Accra, Ghana, the firm’s first in Africa. In Bangalore, some 2,400 people are members of AI Saturdays, which follows the course together as a gigantic study group. Andrei Karpathy, one of deep learning’s foremost practitioners, recommends the course.

效果已经开始显现。莎拉·霍克（Sara Hooker）是fast.ai第一年的毕业生，毫无深度学习工作经验的她在修完课程后便被谷歌竞争非常激烈的AI实习项目录用。她现在是谷歌在加纳首都阿克拉新建的AI研究中心（谷歌在非洲的首个AI研究机构）的创始成员。在班加罗尔，巨型学习小组“AI星期六”（AI Saturdays）的2400名成员一起修读该课程。深度学习的权威专家安德烈·卡尔帕西（Andrei Karpathy）也推荐了这门课。

Fast.ai’s is not the only alternative AI programme. AI4ALL, another non-profit venture, works to bring AI education to schoolchildren in the United States that would otherwise not have access to it. Andrew Ng, another well-known figure in the field, has started his own online course, deeplearning.ai.

Fast.ai的课程并非攻读博士以外的唯一选择。AI4ALL是另一家非营利性机构，为无法获得AI教育的美国学童提供这方面的培训。该领域另一位知名人物吴恩达则已启动了自己的在线课程deeplearning.ai。

Mr Howard’s ambitions run deeper than loosening the AI labour market. His aim is to spread deep learning into many hands, so that it may be applied in as diverse a set of fields by as diverse a group of people as possible. So far, it has been controlled by a small number of mostly young white men, almost all of whom have been employed by the tech giants. The ambition, says Mr Howard, is for AI training software to become as easy to use and ubiquitous as sending an email on a smartphone.

霍华德的雄心壮志远不止于缓解AI行业人才短缺的问题。他的目标是向更广泛的人群传播深度学习技术，以让尽可能多样化的人群将它应用于尽可能多样化的领域。到目前为止，AI技术一直由几乎全部受雇于科技巨头的少数人掌握，这些人大部分是年轻白人男性。霍华德表示，他的志向是让AI训练软件变得像在智能手机上发送电子邮件那样易用而普遍。

Some experts worry that this will serve only to create a flood of dodgy AI systems which will be useless at best and dangerous at worst. An analogy may allay those concerns. In the earliest days of the internet, only a select few nerds with specific skills could build applications. Not many people used them. Then the invention of the world wide web led to an explosion of web pages, both good and bad. But it was only by opening up to all that the internet gave birth to online shopping, instant global communications and search. If Mr Howard and others have their way, making the development of AIsoftware easier will bring forth a new crop of fruit of a different kind.

一些专家担心这只会造就大量劣质的AI系统，它们至多毫无用处，最糟的情况下还会构成危险。一个类比也许能打消这种疑虑。在互联网早期，只有少数有特定技能的书呆子才会编写应用。没有多少人使用它们。然后万维网问世了，网页呈爆炸式增长，品质良莠不齐。但是，正是因为互联网向所有人开放了，才出现了在线购物、即时全球通信和网络搜索。如果霍华德和其他人如愿以偿，那么让AI软件开发变得更容易将会催生出一批新的不同的果实。