2018考研英语双语阅读：昆虫大脑知你所需?

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2018考研复习进行时，考研英语阅读真题中的文章，多摘自英美主流外刊，有时候你认识所有单词、搞清全部语法还不够，还需要了解英美文化，掌握他们的表达方式，这就是阅读的潜台词。下面新东方在线考研整理《2018考研英语双语阅读精选》，速来学习吧！
    　　Insect Brain System Knows What You Want
        昆虫大脑知你所需?
    The goal for a lot of tech companies today: figure out what you, their
customer, want next, before you even ask. It’s driven by something called
similarity search.
    今天，有许多科技公司在追求这样的目标：弄清楚你，他们的消费者，接下来想要的，甚至这一切发生在你提出要求之前。这种目标背后的驱动力被称作类似搜索。
    "If you go to YouTube and you watch a video they’re going to suggest
similar videos to the one you’re watching. That’s similarity search. If you go
to Amazon and look for similar products to the one you’re going to buy, that’s
similarity search."
    “如果你上YouTube看一个视频的话，接下来它们会推荐你更多类似视频。这就是类似搜索。如果你上亚马逊找一样你要买的类似产品，那么这种情况就是类似搜索。”
    Saket Navlakha, a computer scientist at the Salk Institute. He says we do
similarity searches too, for example, when we scan faces in a crowd for the one
we know. And even fruit files do a version, related to smell:
    萨克生物研究学院电脑科学家，Saket
Navlakha说，我们也做类似搜索，例如说，你可以在人群中，扫描这些人的脸面找到你所认识的那个人。甚至是水果也有一个版本，它与气味相关：
    "So the fly is having to solve a similar problem, of kind of searching
through its database of previous experiences and previous odors it has smelled,
to determine what should be the most appropriate behavioral response to that
odor."
    “因此，蝇子就面临着解开一个类似的难题，类似这样的搜索，即通过自身先前的经历和已经闻过的气味来决定什么应该是对那种气味的最符合的行为反应。”
    But flies tag incoming odors differently from the way modern search
algorithms parse similarity. A small group of neurons makes an initial
evaluation of the smell. Then a much larger set of neurons is activated to make
a final decision about the smell. Rather than the way a computer similarity
search does it, taking something with many dimensions, and simplifying it down
to a few.
    但是，蝇子对闻过的气味做出的标记非同于现代研究算法解析类似的方式。一小组神经造成了这种气味的最初评判。然后，有更多数量的神经被激活，最终对这种气味做出判定。而并非像电脑类似搜索的做法，将一些东西分成诸多维度，再精简到几个。
    So Navlakha and his colleagues tweaked computer similarity search functions
to do it fly style. And then pitted the fly-inspired algorithms against
conventional ones. And the biologically inspired code won out, better at telling
’like’ from ’unlike’ on an image-similarity test.
    因此，Navlakha和他的同事们按照蝇子的方式对电脑搜索功能进行了轻微调整。然后针对传统的方式，对受蝇子启发的算法进行标点处理。在一场类似相片的辨别
‘相似’与‘非相似’的测试中，这种受生物启发的编码方式胜出且表现更好。
    "You know evolution figured it out, it figured out a very elegant solution
to this very important problem." The report is in the journal Science.
    刊登在《科学杂志》上的文章这样写道：“进化使它把东西分辨清楚，它对这个重要的难题指明了一条优雅的解决途径。”
    Navlakha says he and his team are looking to partner with tech companies
now, in hopes of endowing machines with the time-tested problem-solving
abilities of the brain. Even if it’s a fruit fly brain.
    Navlakha称他和他的团队现在正在与多家科技公司寻求合作，希望他们能提供一些具有大脑所具备的测试时间及解决难题能力的仪器。即使是这样一个果蝇的大脑也可以。
    来源:科学美国人