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

admin2022-02-15  44

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.
How does the author feel about training robots?

选项 A、Rough but promising.
B、Rough and gloomy.
C、Disappointed but supportive.
D、Disappointed and annoyed.

答案A

解析 态度题。由文中的“tough to program” “hard to train” “struggles with today” “potentially impossible” “expensive and lengthy”可知作者一方面认为训练机器人是艰难的,但另一方面由“revolutionize services in a wide range of fields” “create cheaper automated machines” “a critical step”可知作者认为训练机器人的前景是美好的,故选项A正确。
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