Facebook developed what it calls a foundational " breakthrough": software that enables machines to learn to walk like toddler

admin2022-02-15  63

问题   Facebook developed what it calls a foundational " breakthrough":  software that enables machines to learn to walk like toddlers. Humans are very efficient at maneuvering. As children, we figure out how to adjust our stride and cadence to trek through mud, water, and up and down hills with ease. We can do this while toting a variety of objects, either in our hands or on our backs. However, it’s tough to program robots to make instantaneous adjustments to their legs and feet to accommodate such a variety of tasks, mainly because it’s hard to train them to deal with " corner cases" , or objects and environments they have never seen before.
  Advanced robot navigation could revolutionize services in a wide range of fields,  such as emergency response, agriculture, autonomous driving and manufacturing. It could hold the key to more complex chore robots. But it also requires teaching machines to act in the same way humans do subconsciously, based on lived experience—something that would be potentially impossible.
  Humans learn to navigate new environments by stumbling and trying again. But that’s an expensive and lengthy undertaking when applied to robots, which need to be fixed or have their code tweaked when damaged. Researchers try to avoid this by simulating new environments and adjusting robot brains accordingly.
  First, researchers used simulations to train AI to respond to various environmental conditions, such as slippery ground or a sudden incline. Then, they taught a generic dog-like robot to learn from its mistakes and keep walking as far as possible despite sudden changes to its environment. They layered the two strategies, and together they " enable the robot to perform robust and adaptive locomotion without any fine tuning," Facebook says.
  What this means is that AI allows them to adapt to factors in their environment without having seen them first. Rather than trying to avoid disruptions, they learn from surprises and move with them. Through the observation AI, each new leg movement is informed by previous ones. Obstacles that push against the robot’s feet or legs can reveal information about the ground around it. The AI learns from that.
  The so-called Rapid Motor Adaptation software might allow companies to create cheaper automated machines that figure out how to operate at peak performance with more affordable, not as-accurate hardware. Cheaper robots are a critical step toward more advanced robots in more fields.
The core ideas of using AI to train robots are to_________.

选项 A、coach in realistic surroundings and finely tune code
B、coach in realistic surroundings and learn from feedback
C、coach in simulated surroundings and finely tune code
D、coach in simulated surroundings and learn from feedback

答案D

解析 细节题。根据题干可定位至第四段,由第一句中used simulations to train AI可知是在虚拟环境中训练,由第二句中learn from its mistakes可知,AI会从过去的错误中学习,即从反馈中学习,故选项D正确。而第五段再次强调了这两个核心概念。
转载请注明原文地址:https://jikaoti.com/ti/yXg7FFFM
0

随机试题
最新回复(0)