The opposite state will be called generalized focus.

与之相反的状态叫做泛化专注。

And this allows it to generalize.

样 AI 就可以泛化。

Generalized Focus is broadly distributed attention.

泛化专注即宽广分散的注意力。

One interesting notion is that of stimulus generalization.

一个有趣的概念是刺激泛化。

So, there's this tendency towards generalisation.

因此，种泛化的趋势。

It will enter into a state of generalized focus, determine an imminent threat, and begin saving people or evacuating.

让机入泛化专注状态，测定迫近威胁并开始救或撤离。

During this period of generalized focus, the Robo3000 has to prioritize the stimuli it detects in its environment and act accordingly.

泛化关注阶段，机 3000 必须优先探测其周围环境的变数，并随之应变。

Here's an example of an operating system: for every 30 seconds the Robo3000 spends in a state of directed focus, it must spend 5 seconds in a state of generalized focus.

机 3000 每行 30 秒定向专注，就必须花 5 秒行泛化关注。

How does it decide how much time to spend in a state of directed focus producing boxes and how much time to spend in a state of generalized focus analyzing its environment?

它怎样才能决定，花多少时间定向专注状态下生产箱子，又花多少时间泛化专注状态下去分析环境情况呢？

And stimulus generalization is the topic of one of your articles in The Norton Reader, the one by Watson, John Watson, the famous behaviorist, who reported a bizarre experiment with a baby known as Little Albert.

刺激泛化是您《诺顿读者》中的一篇文章的主题， 那篇文章作者是华生，约翰华生，著名的行为主义者， 他报道了一个用一个名叫小阿尔伯特的婴儿行的奇怪实验。

In a state of generalized focus, our AI will do things such as analyzing if any one needs serious help, if there are any imminent threats, and communicate with the Robo5000 to see if an update is worth getting.

泛化专注下，我们的工智能会行诸如分析是否有迫切需要帮忙，是否有迫眉睫的危险情况，以及与机 5000 通信看是否值得行更新。