2024考研英语：《经济学人》中英读译Day159

英语阅读能力依靠什么？必然是词汇的积累，但，仅仅是词汇的积累是不够了，更应该了解英语句式，不同句型所表达意义。如何培养自己的阅读语感呢？那么就跟着聚创考研网小编每天学一点英语，一起为考研筑起坚实的地基。阅读是需要积累的，就像我们需要经常和人沟通才会促进我们的表达能力一样~小伙伴跟着小编一起，每天坚持打卡，培养英语阅读能力及语感，了解文章一些经典词汇的用法。

经济学人:新的联想学习模型与其对人工智能的影响(下)

Looking at things this way deals with two things that have always bugged the old model.One is sensitivity to timescale.The other is computational tractability.The timescale problem is that cause and effect may be separated by milliseconds (switching on a light bulb and experiencing illumination), minutes (having a drink and feeling tipsy) or even hours (eating something bad and getting food poisoning).Looking backward, Dr.Namboodiri explains, permits investigation of an arbitrarily long list of possible causes.Looking forward, without always knowing in advance how far to look, is much trickier.This leads to the second problem.

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以这种模型看待问题解决了两个旧模型无法解释的问题。一是时间上的敏感性。二是计算上的可操纵性。时间方面的问题在于，因果可能以毫秒（打开灯泡并感受到照明）、分钟（喝饮料并感到醉意）甚至小时（吃坏肚子并食物中毒）为单位出现。南博迪里博士解释说，回顾过去，可以分析很多可能造成某个结果的原因。但展望未来，不总是能够知道要等待什么时候发生的什么结果，分析起来要困难得多。这就导致了第二个问题。

Sensory experience is rich, and everything therein could potentially predict an outcome.Making predictions based on every single possible cue would be somewhere between difficult and impossible.It is far simpler, when a meaningful event happens, to look backwards through other potentially meaningful events for a cause.In practice, however, it is hard to distinguish experimentally between the two models.And that is especially true if you do not even bother to look - which, until now, people have not.Dr. Jeong and Dr. Namboodiri have done so.They devised and conducted 11 experiments involving mice, buzzers and drops of sugar solution that were designed specifically for the purpose.During these they measured, in real time, the amount of dopamine being released by the nucleus accumbens, a region of the brain in which dopamine is implicated in learning and addiction.

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感官体验是十分丰富的，其中一切都有可能是结果的预测。根据可能的单一线索进行预测十分困难，甚至不可能实现。而如果发生了一件有意义的事，据此回顾其它潜在的、有意义的事来寻找原因要简单得多。然而现实是，很难在实验中区分这两种模型。如果你甚至懒得费心去看，那就更是如此——到目前为止，还没有人做过这样的事。而郑博士和南博迪里博士做到了这一点。他们设计并进行了11项实验，实验用到了小鼠和专门为实验设计的蜂鸣器和糖液。伏隔核是大脑中与学习和成瘾有关的区域，在实验过程中，研究人员对伏隔核释放的多巴胺含量进行了实时测量。

 

All of the experiments came down in favour of the new model.The 180° turnabout in thinking - from prospective to retrospective - that is implied by these experiments is causing quite a stir in the world of neuroscience.It is "thought-provoking and represents a stimulating new direction," says Ilana Witten, a neuroscientist at Princeton University uninvolved with the paper.More experiments will be needed to confirm the new findings.But if confirmation comes, it will have ramifications beyond neuroscience.It will suggest that the way AI works does not, as currently argued, have even a tenuous link with how brains operate, but was actually a lucky guess.But it might also suggest better ways of doing AI.Dr. Namboodiri thinks so, and is exploring the possibilities.Evolution has had hundreds of millions of years to optimize the process of learning.So learning from nature is rarely a bad idea.

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所有的实验结果都支持新的模型假设。这些实验所暗示的思维180度大转变——从前瞻性思维到回顾性思维——在神经科学界引起了不小的轰动。没有参与这篇论文的普林斯顿大学的神经学家伊兰那·维登说，这篇论文“发人深省，代表了一个鼓舞人心的新方向”。还需要更多的实验来证实新的发现。但如果该发现的真实性得到证实，它产生的影响将不仅限于神经科学。它表明，人工智能的工作方式并不像目前人们所说的那样，与大脑的运作方式有着微妙的联系，而实际上是幸运的猜测。但它也可能为人工智能学习提供更好的方法。南博迪里博士就是这样认为的，并正在探索新的可能性。数亿年的进化在不断优化学习的过程。因此，向大自然学习不失为一个好主意。