Introduction

How clever is artificial intelligence? It currently helps us in many ways from car satnavs to detecting cancer cells but it's yet to be cleverer than us humans.?We still need to train AI to do things but should we fear that it eventually learns too much?

This week's question

In terms of brain cell count, what level of intelligence is AI currently working at? Is AI as smart as:

a) a frog

b) an earthworm

c) a bumblebee

Transcript

Note: This is not a word for word transcript?

Neil

Hello. This is 6 Minute English from BBC Learning English. I’m Neil.

Sam

And I’m Sam.

Neil

Do you like cooking, Sam? There’s a new recipe I’ve been trying out - it’s for ‘frosted oysters’.

Sam

Frosted oysters?! Sounds… unusual. How do you make it?

Neil

Well, take a pound of chicken, then some cubed pork and half a crushed garlic.

Sam

Eh? I thought you said it was for ‘frosted oysters’, whatever they are.

Neil

Yes, that’s right. Now heat it up until boiling and serve with custard.

Sam

Ugh, that sounds disgusting! Who on earth told you that recipe?

Neil

It’s not ‘who’ told me, Sam, but ‘what’. In fact, that recipe was made by computers using artificial intelligence, or AI, which is the topic of today’s programme. In real life, AI is making huge progress - from car satnavs to detecting cancer cells. But as you can see from that revolting recipe, things don’t always go according to plan.

Sam

So, just how intelligent?is artificial intelligence? I mean, it definitely needs some cooking lessons!

Neil

Right. AI is not as intelligent as we tend to think. AI programmes use artificial brain cells to roughly imitate real brain cell activity, but they’re still a long way behind human levels of intelligence. And that’s my quiz question – in terms of brain cell count, what level of intelligence is AI currently working at? Is AI as smart as:

a)????a frog

b)????an earthworm

c)?????a bumblebee

Sam

Well, I don’t think anyof?those?are good cooks either, to be honest. I’ll say c) a bumblebee, because at least they can make honey!

Neil

Nice guess, Sam. We’ll find out the answer later. But first let’s find out more about how AI misunderstandings like the oyster recipe can happen. Janelle Shane is the author of ‘You Look Like a Thing and I Love You’ in which she tells her amusing experiences and bizarre experiments with AI.

Sam

You Look Like a Thing and I Love You – that’s a strange title for a book, Neil.

Neil

Yes. It’s another example of AI miscommunication. The book title is what a AI produced when asked to write?chat-up lines?– remarks men and women make to start up a conversation with someone they don’t know but find attractive.

Here she is talking to the BBC World Service programme More or Less:

Janelle Shane

‘Machine learning’ is what most programmers mean when they say ‘AI’. In the programme that we’re used to, if you want to have a computer programme solve a problem you have to have a human?programmer?write down exhaustive step-by-step instructions on how to do everything. But with ‘machine learning’ you just give it the goal, and then the programme figures out via?trial and error?how it’s going to solve that problem.

Sam

So even though we’re talking about machines learning for themselves, there still need to be humans involved at the start of the journey. This human teaching is done by?computer programmers?– people who write, or code, the computer programmes used by AI.

Neil

Right. These programmers write?algorithms?– a set of rules or procedures to be followed in problem-solving exercises. So, for example, the AI that wrote that oyster recipe read thousands of other recipes before coming up with its own version.

Sam

In other words, Artificial intelligence uses a process of?trial and error?– repeating the same task over and over until finding the most successful way. Only in the case of the oyster recipe, there was more ‘error’ than ‘trial’!

Neil

Well, according to Janelle Shane, we can learn a lot about something by seeing how it goes wrong. Here she is, talking about an AI which had been told to solve maths problems:

Janelle Shane

It seemed to be that it was getting scored on how many wrong answers it got, and it was supposed to be?minimising?the number of wrong answers, and just by?a stroke of luck?as part of its trial and error flailing around, one of the flails it did accidentally deleted the solutions list, and then it and everybody else got a perfect score.

Sam

So, AIs learn by?minimising?their errors – reducing them as much as possible. And sometimes, these algorithms only discover the right answer by?a stroke of luck?– when something unexpected happens by good luck or chance. It seems to me that they’re not so intelligent after all!

Neil

Well, let’s settle it once and for all by answering today’s quiz question. Remember I asked you how intelligent AI was in terms of brain cell count and you said, as intelligent as…

Sam

I said c) a bumblebee.

Neil

Well, here’s Janelle again with the answer…

Janelle Shane

If you’re looking at rough computing power, the algorithms we’re working with are probably somewhere around the level of an earthworm.

Sam

So, the correct answer was b) as clever as an earthworm! No wonder AIs can’t cook!

Neil

Or take a maths test without cheating! In this programme we’ve been looking at artificial intelligence, or AI, and seeing how?programmers?– that’s people who write instructions for computers to follow create?algorithms?– sets of rules used in problem-solving.

Sam

AI learns through?trial and error?– repeating the same activity again and again until discovering the best way, and?minimising?– reducing as much as possible, the number of errors it makes.

Neil

And success can be the result of?a stroke of luck,?when something unexpected happens purely by chance, although so far that hasn’t helped AIs to write good?chat-up lines?– the flattering remarks people make to get to know someone they find attractive.

Sam

And AIs don’t know much about cooking oysters either!

Neil

That’s all from us from this programme. Be sure to join us again for more topical discussion and vocabulary at 6?Minute English for BBC Learning English. Bye for now!

Sam

Bye.

Vocabulary

chat-up lines

remarks men and women make to start up a romantic conversation with someone they don’t know but find attractive

computer programmers

people who write, or code, computer programmes

algorithms

a set of rules or procedures to be followed by computers in problem-solving exercises

trial and error

repeating the same task over and over until finding the most successful way

minimising

reducing as much as possible

a stroke of luck

when something unexpected happens by good luck or chance

雙語(yǔ)版Transcript

Neil

Hello. This is 6 Minute English from BBC Learning English. I’m Neil.

大家好，這里是BBC教學(xué)英語(yǔ)的六分鐘英語(yǔ)，我是尼爾。

Sam

And I’m Sam.

我是山姆。

Neil

Do you like cooking, Sam? There’s a new recipe I’ve been trying out - it’s for ‘frosted oysters’.

你喜歡做飯嗎？我正在嘗試一種新食譜- “凍牡蠣”

Sam

Frosted oysters?! Sounds… unusual. How do you make it?

凍牡蠣？聽起來……不尋常。你怎么做的？

Neil

Well, take a pound of chicken, then some cubed pork and half a crushed garlic.

好吧，取一磅雞肉，然后放一些豬肉塊和半個(gè)碎大蒜。

Sam

Eh? I thought you said it was for ‘frosted oysters’, whatever they are.

??？我以為你說的是“凍牡蠣”

Neil

Yes, that’s right. Now heat it up until boiling and serve with custard.

是的，沒錯(cuò)?，F(xiàn)在將其加熱至沸騰，然后與卡仕達(dá)一起食用。

Sam

Ugh, that sounds disgusting! Who on earth told you that recipe?

聽起來真惡心！到底是誰(shuí)告訴你那個(gè)食譜？

Neil

It’s not ‘who’ told me, Sam, but ‘what’. In fact, that recipe was made by computers using artificial intelligence, or AI, which is the topic of today’s programme. In real life, AI is making huge progress - from?car sat navs?to detecting cancer cells. But as you can see from that revolting recipe, things don’t always?go according to plan.

不是“誰(shuí)”，而是“什么”。實(shí)際上，該配方是使用人工智能的計(jì)算機(jī)完成的，這是今天節(jié)目的主題。在現(xiàn)實(shí)生活中，人工智能正在取得巨大進(jìn)步-從汽車衛(wèi)星導(dǎo)航到檢測(cè)癌細(xì)胞。但是，從令人反感的食譜中可以看出，事情并非總是按計(jì)劃進(jìn)行。

Sam

So, just how intelligent is artificial intelligence? I mean, it definitely needs some cooking lessons!

人工智能有多智能？我的意思是，它肯定需要一些烹飪課程！

Neil

Right. AI is not as intelligent as we tend to think. AI programmes use artificial brain cells to roughly?imitate?real brain cell activity, but they’re still a long way behind human levels of intelligence. And that’s my quiz question – in terms of brain cell count, what level of intelligence is AI currently working at? Is AI as smart as:

a) a frog

b) an earthworm

c) a bumblebee

對(duì)。人工智能并不像我們認(rèn)為的那樣聰明。人工智能程序使用人工腦細(xì)胞粗略地模仿真實(shí)腦細(xì)胞活動(dòng)，但距離人類的智力水平還有很長(zhǎng)的路要走。這是我的測(cè)試問題–就腦細(xì)胞數(shù)量而言，人工智能目前正在哪種智能水平？人工智能像

a）青蛙

b）蚯蚓

c）大黃蜂

Sam

Well, I don’t think any of those are good cooks either, to be honest. I’ll say c) a bumblebee, because at least they can make honey!

好吧，老實(shí)說，我也不認(rèn)為這些都是好廚師。我會(huì)說c）大黃蜂，因?yàn)橹辽偎鼈兛梢葬勗旆涿郏?/span>

Neil

Nice guess, Sam. We’ll find out the answer later. But first let’s find out more about how AI misunderstandings like the oyster recipe can happen. Janelle Shane is the author of ‘You Look Like a Thing and I Love You’ in which she tells her amusing experiences and bizarre experiments with AI.

猜的好。我們稍后會(huì)找到答案。但是首先讓我們更多地了解AI如何發(fā)生像牡蠣食譜這樣的誤解。Janelle Shane是《You Look Like a Thing and I Love You》的作者，在書中講述了她的有趣經(jīng)歷和AI的奇異實(shí)驗(yàn)。

Sam

You Look Like a Thing and I Love You – that’s a strange title for a book, Neil.

你看起來像個(gè)東西，我愛你-這本書的標(biāo)題很奇怪。

Neil

Yes. It’s another example of AI miscommunication. The book title is what a AI produced when asked to write chat-up lines – remarks men and women make to start up a conversation with someone they don’t know but find attractive.Here she is talking to the BBC World Service programme More or Less:

是的，這是AI錯(cuò)誤溝通的另一個(gè)例子。本書標(biāo)題是AI被要求編寫聊天記錄時(shí)產(chǎn)生的–男女之間與有魅力的陌生人開始交流時(shí)的言論。這是她在BBC More or Less節(jié)目的談話：

Janelle Shane

‘Machine learning’ is what most programmers mean when they say ‘AI’. In the programme that we’re used to, if you want to have a computer programme solve a problem you have to have a human programmer write down exhaustive step-by-step instructions on how to do everything. But with ‘machine learning’ you just give it the goal, and then the programme figures out via trial and error how it’s going to solve that problem.

“機(jī)器學(xué)習(xí)”是大多數(shù)程序員說“ AI”時(shí)的意思。在我們慣用的程序中，如果要使用計(jì)算機(jī)程序來解決問題，則必須讓人類程序員寫下詳盡的逐步的指令，說明如何進(jìn)行所有操作。但是通過“機(jī)器學(xué)習(xí)”，你只需給它一個(gè)目標(biāo)，然后程序就會(huì)通過反復(fù)試驗(yàn)弄清楚它將如何解決該問題。

Sam

So even though we’re talking about machines learning for themselves, there still need to be humans involved at the start of the journey. This human teaching is done by computer programmers – people who write, or code, the computer programmes used by AI.

即使我們正在談?wù)摰臋C(jī)器學(xué)習(xí)是機(jī)器的，在旅程的開始仍需要人類參與。這種人工教學(xué)是由computer programmers計(jì)算機(jī)程序員完成的，他們編寫AI使用的計(jì)算機(jī)程序。

Neil

Right. These programmers write algorithms – a set of rules or procedures to be followed in problem-solving exercises. So, for example, the AI that wrote that oyster recipe read thousands of other recipes before coming up with its own version.

這些程序員編寫algorithms算法 -解決問題練習(xí)中要遵循的一組規(guī)則或過程。因此，例如，編寫牡蠣食譜的AI讀取數(shù)千種其他食譜之后提出自己的版本。

Sam

In other words, Artificial intelligence uses a process of trial and error – repeating the same task over and over until finding the most successful way. Only in the case of the oyster recipe, there was more ‘error’ than ‘trial’!

換句話說，人工智能使用trial and error試驗(yàn)和犯錯(cuò) -一遍又一遍地重復(fù)相同的任務(wù)，直到找到最成功的方式。只是在牡蠣食譜的情況下，“錯(cuò)誤”多于“試驗(yàn)”！

Neil

Well, according to Janelle Shane, we can learn a lot about something by seeing how it goes wrong. Here she is, talking about an AI which had been told to solve maths problems:

根據(jù)Janelle Shane的說法，我們可以通過觀察問題出在哪里，從而學(xué)到很多東西。在這里，她談?wù)摻鉀Q數(shù)學(xué)問題的AI。

Janelle Shane

It seemed to be that it was getting scored on how many wrong answers it got, and it was supposed to be minimising the number of wrong answers, and just by a stroke of luck as part of its trial and error flailing around, one of the flails it did accidentally deleted the solutions list, and then it and everybody else got a perfect score.

似乎正在對(duì)它得到多少錯(cuò)誤答案進(jìn)行評(píng)分，并且應(yīng)該將錯(cuò)誤答案的數(shù)量減至最少，而在實(shí)驗(yàn)和錯(cuò)誤的過程中，碰巧走運(yùn)，偶然刪除了方案列表，然后它和其他所有人得到了滿分。

Sam

So, AIs learn by?minimising their errors?– reducing them as much as possible. And sometimes, these algorithms only discover the right answer by a stroke of luck – when something unexpected happens by good luck or chance. It seems to me that they’re not so intelligent after all!

人工智能通過minimising最小化錯(cuò)誤來學(xué)習(xí)- 盡可能減少錯(cuò)誤。有時(shí)，這些算法只能通過a stroke of luck運(yùn)氣來找到正確的答案-因好運(yùn)或偶然發(fā)生意外事情時(shí)。在我看來，他們畢竟不是那么聰明！

Neil

Well, let’s settle it once and for all by answering today’s quiz question. Remember I asked you how intelligent AI was in terms of brain cell count and you said, as intelligent as…

我們通過回答今天的測(cè)驗(yàn)問題一次性解決它。還記得我問過你在腦細(xì)胞數(shù)量方面AI的智能程度如何，你說過，像...一樣聰明。

Sam

I said c) a bumblebee.

我說過c）大黃蜂。

Neil

Well, here’s Janelle again with the answer…

再聽聽Janelle的答案

Janelle Shane

If you’re looking at rough computing power, the algorithms we’re working with are probably somewhere around the level of an earthworm.

如果你考慮粗略的計(jì)算能力，那么我們正在使用的算法可能大約處于蚯蚓的水平。

Sam

So, the correct answer was b) as clever as an earthworm! No wonder AIs can’t cook!

所以，正確答案為B）像蚯蚓一樣聰明！難怪AI不會(huì)做飯！

Neil

Or take a maths test without cheating! In this programme we’ve been looking at artificial intelligence, or AI, and seeing how programmers – that’s people who write instructions for computers to follow ,create algorithms – sets of rules used in problem-solving.

參加數(shù)學(xué)考試而不作弊！在本期節(jié)目中，我們一直在研究人工智能即AI，并觀察programmers程序員-為計(jì)算機(jī)編寫遵循的指令。創(chuàng)造algorithms算法-解決問題的系列規(guī)則。

Sam

AI learns through trial and error – repeating the same activity again and again until discovering the best way, and minimising – reducing as much as possible, the number of errors it makes.

AI學(xué)習(xí)是通過trial and error試驗(yàn)犯錯(cuò)-一次又一次地重復(fù)相同的活動(dòng)，直到找到最好的方法為止，并且minimising最小化 - 盡可能地減少犯錯(cuò)數(shù)量。

Neil

And success can be the result of a stroke of luck, when something unexpected happens purely by chance, although so far that hasn’t helped AIs to write good chat-up lines – the flattering remarks people make to get to know someone they find attractive.

成功可能是a stroke of luck碰運(yùn)氣的結(jié)果，這是純粹因偶然而發(fā)生的意外事件，盡管到目前為止，這還沒有幫助AI編寫良好的chat-up lines聊天記錄 –人們用討喜的話來結(jié)識(shí)有魅力的人。

Sam

And AIs don’t know much about cooking oysters either!

AI也不了解牡蠣的烹飪知識(shí)！

Neil

That’s all from us from this programme. Be sure to join us again for more topical discussion and vocabulary at 6 Minute English for BBC Learning English. Bye for now!

這就是本期節(jié)目的全部?jī)?nèi)容了！下次再見！