The brain is the ultimate computing machine, so it's no wonder researchers are keen to try and emulate it. Now, new research has taken an intriguing step in that direction - a device that's able to 'forget' memories, just like our brains do.
大脑是终极计算机器，所以研究人员热衷于尝试模仿它也就不足为奇了。现在，新的研究朝着有趣的方向迈出了一步，也就是一种能够像我们的大脑一样“忘记”事情的设备。
It's called a second-order memristor (a mix of "memory" and "resistor"). The clever design mimics a human brain synapse in the way it remembers information, then gradually loses that information if it's not accessed for an extended period of time.
它被称为二阶忆阻器（结合了“memory”（存储器）和“resistor”（电阻器）这两个词）。这种灵巧的设计模仿了人脑突触记忆信息的方式，也就是说，如果它长时间不接触信息，就会逐渐失去这些信息。
While the memristor doesn't have much practical use just now, it could eventually help scientists develop a new kind of neurocomputer – the foundation of artificial intelligence systems – that fulfils some of the same functions a brain does.
虽然忆阻器目前还没有什么实用性，但它最终可能有助于科学家开发出一种可以实现部分大脑功能的新的神经计算机，这也是人工智能系统的基础。
In a so-called analogue neurocomputer, on-chip electronic components (like the memristor) could take on the role of individual neurons and synapses. That could both reduce the computer's energy requirements and speed up computations at the same time.
在所谓的模拟神经计算机中，芯片上的电子元件（如忆阻器）可以发挥单个神经元和突触的作用。这既可以降低计算机对能量的需求，同时又可以加快计算速度。
Right now analogue neurocomputers are hypothetical, because we need to work out how electronics can mimic synaptic plasticity – the way that active brain synapses strengthen over time and inactive ones get weaker. It's why we can hang on to some memories while others fade away, scientists think.
现在模拟神经计算机只是一种假设，因为我们需要弄清楚电子设备应如何模拟突触的可塑性，即活跃的大脑突触可以随着时间的推移而增强，而不活跃的突触则会变弱。科学家们认为，这就是为什么我们可以保留部分记忆，而其他的记忆则会逐渐消失。
Previous attempts to produce memristors used nanosized conductive bridges which would then decay over time, in the same way that memories might decay in our minds.
之前尝试制造的忆阻器所使用的纳米导电桥会随着时间的推移而失效，就像记忆在我们的大脑中衰退那样。