今天小编为大家分享的是考研英语阅读短文，希望通过这篇文章的学习对你们有所帮助，下面跟随小编一起学习吧。
　　We improve ourselves by victories over ourselves. There must be contests, and we must win.
　　我们通过战胜自己来改进自我。那里一定有竞赛，我们一定要赢！
　　Going forward, we need three priorities. First, to get costs under control. The soup-to-nuts cost for an MBA at Stanford is $232,000—out of our ballpark. The five-star accommodation, gourmet cuisine and other perks on our campus are way over the top. So are some of our packages, even if we haven’t got quite as carried away as Columbia Business School, which, it was recently revealed, paid over $420,000 a year to a professor teaching three classes a year and $330,000 to untenured junior faculty.
　　展望未来，我们需要三个重点。首先，控制成本。斯坦福大学MBA的全覆盖费用是23.2万美元，一个超出我们预算的数字。我们学校五星级的住宿、美食和其他福利实在是太好了。我们的一些薪酬也是如此，尽管我们还没有像哥比亚商学院那样欣喜若狂。近有消息，哥比亚商学院每年向每位教授支付42万美元，一年教三门课，还向未获得终身职位的初级教师支付33万美元。
　　Don’t fear the Writernator
　　不要害怕机器写手
　　Computer-generated writing will never replace the human kind
　　计算机生成的文字永远不会取代人类
　　Many people will be familiar with automated writing through two features of Gmail. Smart Reply proffers brief answers to routine emails. If someone asks “Do you want to meet at 3pm”, Gmail offers one-click responses such as “Sure!” More strikingly, Smart Compose kicks in as you write, suggesting endings to your sentences. Both are not only rendered in flawless English; they often eerily seem to have guessed what you want to say. If someone sends bad news, Smart Reply might offer “Ugh.”
　　许多人将通过Gmail的两个特性来熟悉自动写作。Smart Reply 会给常规邮件提供简短的回复。如果有人问“你想下午三点见面吗”，Gmail会提供一键式的回答，如“当然!”更引人注目的是，当你写作时，Smart Compose会发挥作用，为句子提供结尾。这两个功能不仅用完美的英语呈现；还常常奇怪地似乎猜到了你想说什么。如果某人发来不好的消息，Smart Reply可能会说“呃······”
　　The New Yorker’s John Seabrook recently described a more powerful version of this technology, called GPT-2, which can ably mimic his magazine’s style. Such systems use a digital network of billions of artificial “neurons” with virtual “synapses”—the connections between neurons—that strengthen as the network “learns”, in this case from 40 gigabytes-worth of online writing. The version Mr Seabrook tested was refined with back-issues of the New Yorker.
　　《纽约客》的（特约撰稿人）约翰西布鲁克近描述了这种技术的一个更强大的版本——GPT-2，可以巧妙地模仿撰稿风格。这些系统使用了一个由数十亿人造“神经元”和虚拟“突触”（神经元之间的联系）组成的数字网络，突触随网络的“学习”而增强，这可以在相当于40千兆的网络写作中找到例子。西布鲁克先生测试的版本在《纽约客》的后刊中进行了修改。
　　The metaphor of the brain is tempting, but “neurons” and “synapses” deserve those scare-quotes. The system is merely making some—admittedly very sophisticated—statistical guesses about which words follow which in a New Yorker-style sentence. At a simple level, imagine beginning an email with “Happy…” Having looked at millions of other emails, Gmail can plausibly guess that the next word will be “birthday”. GPT-2 makes predictions of the same sort.