翻译三级笔译实务模拟72Section 1 English-Chinese TranslationTranslate the following passage into Chinese.1. Para（江南博哥）. 1 During the summer before the presidential election, John Seymour and Philip Tully, two researchers with ZeroFOX, a security company in Baltimore, unveiled a new kind of Twitter bot. By analyzing patterns of activity on the social network, the bot learned to fool users into clicking on links in tweets that led to potentially hazardous sites. Para. 2 The bot, called SNAP_R, was an automated phishing system, capable of homing in on the whims of specific individuals and coaxing them toward that moment when they would inadvertently download spyware onto their machines. Archaeologists believe theyve found the tomb of Alexander the Great is in the U.S. for the first time, the bot tweeted at one unsuspecting user. Para. 3 Even with the odd grammatical misstep, SNAP_R succeeded in eliciting a click as often as 66 percent of the time, on par with human hackers who craft phishing messages by hand. Para. 4 The bot was unarmed, merely a proof of concept. But in the wake of the election and the wave of concern over political hacking, fake news and the dark side of social networking, it illustrated why the landscape of fakery will only darken further. Para. 5 The two researchers built what is called a neural network, a complex mathematical system that can learn tasks by analyzing vast amounts of data. Para. 6 A neural network can learn to recognize a dog by gleaning patterns from thousands of dog photos. It can learn to identify spoken words by sifting through old tech-support calls. Para. 7 And, as the two researchers showed, a neural network can learn to write phishing messages by inspecting tweets, Reddit posts, and previous online hacks. Para. 8 Today, the same mathematical technique is infusing machines with a wide range of humanlike powers, from speech recognition to language translation. In many cases, this new breed of artificial intelligence is also an ideal means of deceiving large numbers of people over the internet. Mass manipulation is about to get a whole lot easier. Para. 9 It would be very surprising if things dont go this way, said Shahar Avin, a researcher at the University of Cambridge. All the trends point in that direction. Para. 10 Many technology observers have expressed concerns at the rise of A.I. that generates Deepfakesfake images that look like the real thing. What began as a way of putting anyones head onto the shoulders of a porn star has evolved into a tool for seamlessly putting any image or audio into any video. Para. 11 The threat will only expand as researchers develop systems that can metabolize and learn from increasingly large collections of data. Neural networks can generate believable sounds as well as images. This is what enables digital assistants such as Apple Siri to sound more human than they did in years past. Para. 12 Ideally, artificial intelligence could also provide ways of identifying and stopping this kind of mass manipulation. Mark Zuckerberg likes to talk about the possibilities. But for the foreseeable future, we face a machine-learning arms race. 正确答案：第一段 在总统大选前的那个夏天，巴尔的摩(Baltimore)安全公司零狐(ZeroFOX)和两名研究员约翰西摩(John Seymour)和利普塔利(Philip Tully)发布了一个新型推特机器人程序。该程序通过分析社交网络上的活动模式，学会诱骗用户点击推特链接，跳转到存在潜在危险的网站。 第二段 这款名为SNAP_R(全称Social Network Automated Phishing with Reconnaissance，意为“带有侦查功能的社交媒体自动钓鱼程序”)的机器人程序是一个自动化钓鱼系统，能够追踪特定目标的想法，设法诱使他们在不经意间将间谍软件下栽到电脑或手机里。“考古学家相信他们在美国首次发现了亚历山大大帝(Alexander the Great)的陵墓。”这就是该钓鱼程序向一位不知情用户发送的推文。 第三段 该程序虽然偶尔会出现语法错误，但66%的情况下能够成功诱导用户进行点击操作，与那些手动编写钓鱼信息的黑客不相上下。 第四段 这个程序实际上并没有携带间谍软件和危险网站，它仅仅是对自动化钓鱼可行性的一个证明。但随着大选临近以及人们对政治性黑客活动、虚假新闻和社交网络阴暗面的担忧日益高涨，这个程序说明了为什么欺诈事态只会愈演愈烈。 第五段 这两位研究人员搭建起一个类神经网络，这是一个可以通过分析海量数据来进行任务学习的复杂数学系统。 第六段 类神经网络可以逐步从成千上万张狗的照片中提取模型，从而学会识别狗。它同样可以通过筛查先前的技术支持通话，学会识别口头语言。 第七段 而且，正如两位研究员所展示的，类神经网络可以通过研究推特、红迪网(Reddit)帖子以及之前的网络黑客行为来学习编写钓鱼信息。 第八段 今天，从语音识别到翻译，同样的数学技术赋予了机器各种各样类人类的能力。在很多情况下，这种新型的人工智能同样也是在网络上欺骗大量网民的理想手段。大规模欺诈将越来越容易操作。 第九段 剑桥大学的研究人员沙哈阿温(Shahar Avin)说，“如果事情不按照这个趋势发展的话那就很奇怪了。所有的趋势都指向这一方向。” 第十段 人工智能不断兴起，发展出深度伪造(Deepfakes)技术，许多科技观察人士对此表示担忧。深度伪造的图片虽是伪造，看起来却很像是真的。这种技术一开始只是可以将任何人的头移在色情明星肩膀上，到现在演变成能够完美地将任一图片或音频插入到视频中。 第十一段 随着研发人员开发出可以不断更新变化、可以从不断增加的数据中学习的系统，这个威胁只会不断加剧。类神经网络可以生成让人信以为真的声音和图像。现在像苹果西丽(Siri)这样的智能语音助手听起来比以前更像人类了，原因就在于此。 第十二段 理想情况下，人工智能也有方法识别和阻止这种大规模欺诈的操纵。马克扎克伯格(Mark Zuckerberg)就喜欢谈论这些可能性。但在可预见的未来，我们将面对的是一场机器学习的军备竞赛。解析 1第一段句较长，句中with ZeroFOX, a security company in Baltimore是插入成分，旨在说明和两名研究员合怍的机构，即“位于巴尔的摩的安全公司零狐”。在翻译时可以根据句子逻辑关系将其前置。 2第二段句home in on是固定搭配，意思是“集中注意力解决特定问题”“瞄准，对准”。根据原文语境，该机器人程序能够从海量的用户数据中进行任务学习，了解用户的社交活动模式，以提高钓鱼成功概率，因此选第二个义项，homing in on the whims of specific individuals译为“瞄准特定目标突发的念头”，这里可以稍加转换，译为“追踪特定目标的想法”。 3第二段句the bot tweeted at one unsuspecting users，直译为“该钓鱼程序向一位不知情用户发送推文”，但与前文“考古学家相信他们在美国首次发现了亚历山大大帝(Alexander the Great)的陵墓”这一