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機(jī)器人終結(jié)真人對(duì)話(huà)?

所屬教程:金融時(shí)報(bào)原文閱讀

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2020年08月23日

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機(jī)器人終結(jié)真人對(duì)話(huà)?

或許過(guò)不了多久,我們將不再與真人對(duì)話(huà),而開(kāi)始與機(jī)器和“機(jī)器人”交談,或者,我們談話(huà)的對(duì)象可能是假扮成人的機(jī)器人。

測(cè)試中可能遇到的詞匯和知識(shí):

fad 時(shí)尚[f?d]

permutation 置換;組合[p??mj?'te??(?)n]

govern 管理;支配['g?v(?)n]

render 實(shí)施;著色;以…回報(bào)['rend?]

obsolete 淘汰;廢棄['?bs?li?t]

wayward 任性的;不規(guī)則的['we?w?d]

adolescent 青春期的;未成熟的[?d?'les(?)nt]

rogue 流氓;小淘氣[r??g]

閱讀馬上開(kāi)始,建議您計(jì)算一下閱讀整篇文章所用的時(shí)間,對(duì)照下方的參考值就可以評(píng)估出您的英文閱讀水平。

如果您讀完全文用時(shí)為: 那么,您的閱讀速度相當(dāng)于 每分鐘閱讀的英文單詞數(shù)

3分12秒 母語(yǔ)為英語(yǔ)者的朗讀速度 140

2分28秒 母語(yǔ)為英語(yǔ)的中學(xué)生的閱讀速度 250

1分28秒 母語(yǔ)為英語(yǔ)的大學(xué)生的閱讀速度 350

0分52秒 母語(yǔ)為英語(yǔ)的速讀高手 1000

Fear of bots replacing human contact may prove misplaced(521words)

By Richard Waters

-----------------------------------------------------

Whatever happened to the human touch? If you believe the latest fad from the tech world, it won’t be long before we give up talking to real people and start talking instead to machines — or “bots”. Or it might be machines pretending to be people, or people pretending to be machines. The permutations of human and artificial intelligence are about to become interesting.

But if it works as advertised, we will move one step further beyond a world of direct human interaction towards a future when screens — and new ways of engaging with computer intelligence — govern much of our lives. For sheer convenience, it will be hard to resist. Less obvious is what might be lost in the process.

Facebook has just given this trend its biggest lift with the release this week of a way for companies to plug their bots into Messenger, its chat system. Want to know the weather? Ask a question and an intelligent agent will answer. Interested in buying something? Bots on hand will show you the latest offers and guide you through to the checkout.

If people take to the idea, entire call centres could be rendered obsolete. Why hold on waiting for a human when you can get an immediate response from a bot on your smartphone? The call-centre reps are operating from scripts anyway and these are interactions that could be programmed into a piece of software.

Whether the bots catch on will depend on not stretching the technology beyond its limits. Microsoft’s wayward chatbot Tay, the algorithm pretending to be an adolescent girl that started spouting racist comments on Twitter, is Exhibit A for what can go wrong. Most artificial intelligence is not very intelligent and when the main technique for training the new systems involves something called machine learning, it turns out that machines can be taught bad behaviour as well as good.

Not that the chatbots on Facebook are about to have a mind of their own and turn rogue. Most take a very limited approach to AI, using machine learning to “understand” the questions being put to them and returning largely pre-scripted answers. They try to identify a need, then draw you down a chain of conversation to a result.

Deeper levels of intelligence will also be on tap. But it is as likely to involve a human brain as one made from silicon. M, another Facebook chat service, relies on real people sitting in the background, returning answers, though to the user, it is not at all clear whether information is being generated by a person or a computer. As the machines become smarter they will take over more of the responses, eventually pushing human workers out of the loop altogether.

The prospect of another layer of human interaction being lost to technology is bound to bring a pang of regret, not to mention a wave of concern about the impact on jobs. But then, who would want to give up ATMs and go back to queueing up for a bank teller? Most people won’t mind at all when the days of call-centre queueing have receded into history.

請(qǐng)根據(jù)你所讀到的文章內(nèi)容,完成以下自測(cè)題目:

1. What is the Messenger as mentioned?

A. Facebook’s subsidiary

B. a chat system

C. an advertisement system

D. a talking machine

2. What could be rendered obsolete if people take to the idea?

A. entire call centres

B. shopping malls

C. true friends

D. bank counter

3. Who did chatbot Tay pretend to be in the plan?

A. an adolescent boy

B. a mature woman

C. an adolescent girl

D. an old teacher

4. How to learn to “understand” the questions for most chatbots?

A. have a mind naturally

B. programming system

C. take a chance

D. machine learning

[1] 答案 B. a chat system

解釋?zhuān)篗essenger是Facebook開(kāi)發(fā)的聊天系統(tǒng)。

[2] 答案 A. entire call centres

解釋?zhuān)喝绻祟?lèi)接受這一理念,所有電話(huà)服務(wù)中心將被淘汰。

[3] 答案 C. an adolescent girl

解釋?zhuān)何④?Microsoft)任性的聊天機(jī)器人Tay就展現(xiàn)了機(jī)器人可能出現(xiàn)怎樣的錯(cuò)誤,這個(gè)扮成一名青春期少女的算法程序已開(kāi)始在Twitter上散布種族主義言論。

[4] 答案 D. machine learning

解釋?zhuān)核鼈兝脵C(jī)器學(xué)習(xí)來(lái)“理解”接收到的問(wèn)題,并主要反饋預(yù)設(shè)的答案。


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