Question

Learning, Fast and Deep

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(神经的) networks to scan 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 standard route into these jobs has been a PhD in computer science from one of America’s top universities. Earning one takes years and requires a personality suited to academia, which is rare among more normal folk.

That is changing.

Last month fast.ai, a non-profit education organization based in San Francisco, kicked off the third year of its course in deep learning. Since its foundation it has attracted more than 100,000 students around the globe from India to Nigeria. The course and others like it, come with a simple idea: 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.

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, pounding the table with his fist for punctuation.

Some experts worry that this will serve only to create a flood of unreliable AI systems which will be useless at best and dangerous at worst. In the earliest days of the Internet, only a select few nerds, namely computerholics 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 AI software easier will bring forth a new crop of fruit of a different kind.

1.What can we learn about deep learning?

A.It replaces artificial intelligence.

B.It attracts rock stars to practice.

C.It scans patterns for large companies.

D.It helps technicians to create software.

2.Fast.ai is an organization that __________________.

A.ensures one to obtain a PhD B.teaches craft in ivory tower

C.offers a course in deep learning D.requires weeks to apply

3.The underlined words “No. Greek. Letters”in Paragraph 5 means doing fast.ai course is _______.

A.easy B.difficult

C.interesting D.boring

4.It can be inferred from the last paragraph that _______.

A.it is quite reliable for anyone to grasp artificial intelligence

B.the Internet has brought forth a flood of useless AI systems

C.opening up to all leads to instant global search and online shopping

D.simplifying software development may result in unexpected outcomes

Answer

1.D

2.C

3.A

4.D

【解析】

这是一篇说明文。人工智能的深度学习被证明很有用，霍华德和数学家托马斯一起创办的非营利性教育机构fast.ai致力于让深度学习变得简单。

1.细节理解题。根据第一段A branch of AI known as deep learning, which uses neural networks to scan through large volumes of data looking for patterns…build software for Amazon, Apple, Facebook and Google.可知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。这说明深度学习能帮助编写软件，故选D项。

2.细节理解题。根据第三段的Last month fast.ai, a non-profit education organization based in San Francisco, kicked off the third year of its course in deep learning.可知。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。也就是说fast.ai是一个提供深度学习课程的组织，故选C项。

3.推理判断题。根据前文To make it accessible to anyone who wants to learn …He says school mathematics is sufficient.可知让深度学习不再神秘是杰里米·霍华德的目标，为此，他和数学家雷切尔·托马斯一起创立了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。这说明fast.ai的课程很简单，仅需要中学数学知识。因此霍华德说“No. Greek. Letters（没有，希腊，字母）是想说fast, ai的深度学习课程很简单。故选A项。

4.推理判断题。根据最后一段If Mr Howard and others have their way, making the development of AI software easier will bring forth a new crop of fruit of a different kind.

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。由此推断简化软件开发可能会导致意料之外的结果。故选D项。