VOA常速英语2019--AI可通过知觉记忆快速完成任务（在线收听）

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.

教机器人做哪怕最简单的事情也有难度，而且耗费时间。比如，这个视频里，一个安卓系统的机器人正试图通过特殊编写的代码来折叠一件衬衫。在折叠衬衫的过程中，机器人需要考虑衬衫的大小、质地、算法。对人工智能来说，这样的操作算是复杂操作了。不过，有一个来自马里兰大学帕克分校的计算机科学团队正在努力帮助机器人表现得更好，方法就是借鉴过去行为的经验。如今，很多应用领域的很多机器人完成任务的速度都很慢，因为它们不具备根据某一信号来预测其他信号的能力。现在，有了知觉记忆之后，机器人就能通过之前的经验来快速完成任务了。将机器人的感知跟运动指令结合在一起是野心不小的任务，目前，安东和他的团队正在完成这项任务——所谓的超维计算机理论。他们认为，这样做将可以帮助不同类型的人工智能表现得更好。比如，他们说智能手机将可以分析当前情况并积累经验。在移动设备上，神经网络可以用广泛应用。

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 robot a lot closer to humans.

比如，当一个人弄清自己所在的位置时，可以给周围环境拍一张照片，然后设备就会告诉你方位。无人机也将可以分析周围的环境，从而不再需要人类飞行员的指示。马里兰大学的科学家承认，他们已经开始着手于一个颇有雄心的项目，未来还有很多任务有待完成。不过，Aloimonos希望能通过创建一个所有人工智能开发人员都能用的系统，从而产生重大的影响。从某种角度来说，试图研发人工智能系统的这项任务就很像圣经中的巴别塔，在巴别塔中，所有人都说着不同的语言。现在，我们引入的这个新框架让我们可以拥有同一种语言，一种超维向量的语言，可以表达所有信息，只要机器人感知到的、决定的、认知到的、移动的信息，这些都可以。还有一项重大改变——机器人的眼睛。科学家表示，机器人不只依靠摄像头了，还会凭借 动态视觉传感器，可以对移动和光做出反应。其背后的机制与人类眼睛发出不间断信号给机器人大脑的原理是类似的，信息都可以得到记录和储存，就像曾真实体验过一样。这种功能的实现让机器人离人类更近了。