VOA常速英语2019--科学家教机器人利用经验以做出更好的表现（在线收听）

Scientists Teach Robots to Use Experience to Perform Better

Teaching robots to do the simplest things is both difficult and time-consuming.This video for example shows an Android attempting to fold a T-shirt relying on a special written code.As it does, it needs to take into account the size, texture and algorithm.For artificial intelligence, it’s a complex operation.But a computer science team at the University of Maryland at College Park is working to help robots perform better by using experience from their past actions.Today, many of the robots in many applications are quite slow because they do not have the ability to predict one signal on the basis of another.Now, with creating perceptual memories, the robots can use prior experience in order to do things very fast.Combining robotic perception and motor commands is an ambitious task, one that Anton Mitrokhin and his team are tackling with, the so called hyper dimensional computer theory.They say it will help different kinds of artificial intelligence perform better.For instance, they say smartphones will be able to analyze the situation and accumulate experience.There are many applications of neural networks when it comes to mobile devices.

教机器人做最简单的事是困难又耗时的。例如，这个视频展示了安卓想利用特殊书面代码来实现折叠T恤。在折叠衣服的时候，它需要考虑尺寸、纹理和算法。对于人工智能而言，这是一项复杂的操作。但是，马里兰大学帕克分校的计算机科学团队正致力于利用过去的经验帮助机器人更好地发挥作用。今天，很多应用中的机器人速度都很慢，因为它们无法在一个信号的基础上预测到下一个信号。现在，通过创造感性记忆，机器人可以使用先前的经验来快速做事。将机器人的感知和运动的指令结合起来是一项艰巨的任务，这是Anton Mitrokhin和其团队在解决的问题，也就是所谓的超维计算机理论。他们认为这有助于不同的人工智能发挥更好。比如，他们表示，智能手机能够分析情况并且积累经验。当提及移动设备时，神经网络有很多应用。

For example, you’re trying to figure out your location.You can take a picture of your surroundings and the device will tell you where you are.Drones will be able to analyze their own surroundings and won’t need to be directed by a human pilot.The University of Maryland scientists admit they’ve taken on an ambitious project and that there’s still a lot of work ahead.But Aloimonos hopes to have a big impact by creating one system that all AI developers can use.Somehow, the whole operation of trying to develop an intelligence system resembles the biblical Babel tower where you have all these people that speak different languages.Now the new framework that we introduced allows us to have one language, the language of the hyper dimensional vectors to express all the information that is there in perception, decision, cognition and motion.Another dramatic change, robots’ eyes.Scientists say, they are not just playing cameras anymore, but dynamic vision sensors that respond to movement and light.The mechanisms behind it works similarly to those of human eye sending non-stop signals to the robotic brain that gets recorded and stored, forming the equivalent of live experience.And that scientists say brings Robert a lot closer to humans.

举个例子，你想知道自己所在位置。你可以拍一下周边的环境，设备就会告诉你你所在的位置。无人机可以分析它们自己的环境，而不需要飞行员给予指挥。马里兰大学的科学家承认，他们正在他们正开展着一个伟大的项目，并且还有很多其他工作要做。但是Aloimonos希望通过建立一个所有AI开发人员都可以使用的系统，从而产生巨大的影响。不知为何，试图开发智能系统的整个过程类似于圣经中的巴别塔，那里的人说着不同的语言。现在我们引入的新框架让我们使用一种语言，这种语言是超维向量的，用于表达感知、决策、认知和运动中存在的信息。另一个巨大的的变化就是机器人的眼睛。科学家们说，他们不再仅仅靠相机了，还使用动态视觉传感器，可以对运动和光线做出反应。其背后的机制和人眼的机制类似，向机器人大脑发送不间断的信号，大脑再记录和存储信息，形成现场体验的机制。科学家们表示，这让罗伯特更像人类了。