高質(zhì)量英語演講&專訪視頻哪里看？
請(qǐng)您點(diǎn)擊上方“精彩英語演講”，選擇“設(shè)為星標(biāo)”
全網(wǎng)最新鮮，熱門的英語演講第一時(shí)間為您奉上！
近日，人形機(jī)器人Ameca在美國(guó)CES國(guó)際消費(fèi)電子展上和人們互動(dòng)的視頻在網(wǎng)絡(luò)上引起熱議。視頻中Ameca不但會(huì)回答各種問題，還會(huì)開玩笑...她隨便說的一句玩笑話，更是讓和她對(duì)話的小哥啞口無言...你覺得這個(gè)智能程度如何？
視頻里，能看到一個(gè)有著灰色頭部、機(jī)械身體的機(jī)器人，在滿是機(jī)器人零件的實(shí)驗(yàn)室里打盹。
有人對(duì)它打了個(gè)響指，它醒來了，有點(diǎn)受到驚嚇的樣子，眨巴著惺忪的眼睛。
接著，它好像意識(shí)到自己的身體與眾不同，好奇地看著自己的手臂。機(jī)器人終于注意到面前有人，它嚇了一跳，身體下意識(shí)地向后傾。
看這自然的表情，流暢的動(dòng)作，這是某個(gè)科幻電影的片段吧？視頻里的機(jī)器人，肯定是用CG做出來的吧？
很多人一開始確實(shí)是這么想的，他們?cè)谠u(píng)論區(qū)里安慰眾人，這肯定是CG動(dòng)畫，沒必要驚慌。
但很快，英國(guó)科技公司“工程藝術(shù)”（Enginnered Arts）就出來認(rèn)領(lǐng)了，說這是他們?cè)谌ツ?2月上傳的視頻，片中的一切是真實(shí)發(fā)生的，那只驚訝的機(jī)器人名叫Ameca。工程藝術(shù)說，這是世界上最先進(jìn)的仿真機(jī)器人。
Ameca：the humanoid robot in its FIRST public demo00:0025:1216:14
AI Robots Date HumansBeyond Atlas And Ameca.↓↓↓ 上下滑動(dòng)，查看解說稿 ↓↓↓
Ameca’s incredible expressions and interactions are part of a major leap for AI and robots.
They can now see the world and react to it, which means they’re starting to replace human workers.
Robot muscle and AI’s creating immense wealth and removing millions of jobs, but the upsides are stunning.
I’ll also explain all this.
People often mistake this for a real dolphin - but it’s a robot designed to set dolphins free, by replacing them in marine parks.
Thousands of dolphins are locked up in parks, but closing the parks would cut off the millions they raise for conservation.
They’re working on a new version to perform entirely by itself - and that could be the point where they can impress the crowds and replace the dolphins.
And to help reduce the plastic that ends up in the ocean, recycling can now be sorted by robots like this.
It can see different types of plastic, pick them up and throw them into bins.
The things we order online are also being handled by increasingly advanced robots.
Stretch, from Boston Dynamics, can work alongside its friend Spot.
It can deal with large volumes of boxes, and of course, it can dance.
A lot of the food we eat is also moved by robots, or made by them.
And humanoid robots are entering warehouses.
Starting in back rooms, once they’re considered safe, they’ll work alongside humans.
And it’s hard to compete with robots that can work 24 hours a day, without pay - particularly at Amazon, which is infamous for pushing its workers to their limits.
“My work day feels like a nine hour intense workout, every day, and they track our every move.” Amazon workers were twice as likely to be seriously injured as workers at other companies.
One thing that’s preventing robots from taking over entirely, according to an amazon executive, is that humans are good at quickly recognising and sorting products.
And robots are rapidly developing this kind of skill.
Digit sees the world through lidar and depth sensors.
Most of its energy isn’t used for movement, it’s used for computing.
The company expects its robots to go on to help you around the home.
Robot hands are becoming impressively dextrous.
They can use tweezers, scissors and hold tricky objects.
And robot bodies are starting to capture more natural human movement.
Ameca is being used to test and develop AI, so it’s going to get smarter.
And robots are rapidly learning new skills through simulations.
Here’s a simple example, where an AI learns to jump over an increasingly tall barrier.
It also learned to fight, and to master an obstacle course.
And robots have learned incredible dexterity from simulations, including rubik’s cube skills.
We create thousands of different simulated environments.
This means like thousands of years of experience that this neural network has had in simulation.
Everytime the algorithm has gotten good at the task, we make the task harder.
This ability to generalise to new environments feels like a very core piece of intelligence.
Here, AI solves an incredible 55x55 cube.
This machine learned to play table tennis in just 90 minutes, returning 98% of balls: And some AI’s have outsmarted their creators - like this spider which was asked to minimise the time its feet touched the ground.
When it reported that it had leant to move without its feet ever touching the ground, its creators were shocked to find that it had turned itself over.
And when AI’s learned to master hide and seek, one of them found that it could use a ramp to jump outside the game walls.
The rapid progress of AI is giving robots incredible skills.
And it could enable new machines like this bird-like evtol, designed to land in difficult terrain in Africa, carrying medical supplies.
It’s an ambitious project, but the team has some character.
It was designed to blend in with the surrounding landscape.
Unlike most other drones which don't actually fly around, they're just so ugly, the earth repels them from the ground.
Some robots can already walk and fly.
And a flying humanoid robot is in development.
Designed to help search for survivors in disaster zones.
Creative new designs keep emerging, like this one that can accelerate rapidly like a car, walk a dog, or stand up like a human.
It can carry things pretty much anywhere.
Of course, carrying humans at high speed requires a higher level of safety.
You can always think of tesla as like, the world’s biggest robot company, um, or, semi-sentient robot company.
We’re effectively creating the most advanced, practical AI.
It would be tempting to write it off as hype, but they’ve created some incredible technology.
The AI behind autopilot will also power the Tesla bot.
What I find kind of fascinating about this, is that we are effectively building a synthetic animal, from the ground up.
It moves around, it senses the environment, and acts autonomously and intelligently.
We are building the synthetic visual cortex.
So the processing starts when light hits out artificial retina and we are going to process this information with neural networks” The cars also work together.
Here different cars driving the same route combine their data to build a more detailed image of the environment.
Cars also shared ten thousand clips of wind and snow, to learn to identify things from all angles, but also to remember that they’re still there, even if they’re covered up.
The cars have a big advantage over us.
While humans focus on a small area at once - a problem exploited by magicians You were focused on your hand, that's why you were distracted.
While you were watching this I couldn't quite get your watch off, it was difficult.
Yet you had something inside your front pocket, do you remember what it was? Money? Check your pocket, see if it’s still there.
Is it still there? You’re human you’re not slow” AI can see everything in its field of view at all times, and pick out what’s important.
Tesla also uses an impressive simulation, to train its AI.
Notice the road is cracked and patched up.
They create unusual situations, like this couple and their dog running on the road.
Musk believes we all live in a simulation.
Simulation theory shows that if the sims continue to improve, even at a slow pace, eventually they’ll become indistinguishable from reality.
And there will be many of them, so the chances that we’re living in the one reality is very small.
Virtual characters are getting spookily realistic.
Is this the real Keanu Reeves? The choices we make, the worlds we build, they also confront us with questions, about why we want to choose this over that.
Or is this him? It was important for me to ask people, how do we know what is real? You can probably tell, but it’s getting harder.
In just 35 years, we’ve gone from this, to this.
Who knows what we’ll have in a thousand years.
And what would reality mean, when a world we can build feels as real as our own? And Tesla’s building an impressive matrix.
It’s cars have been trained on 300 million images.
In just one training project, 10 billion labels were applied to 2 million clips, using 20,000 CPU cores.
And Tesla has built its own incredibly powerful training matrix.
It’s designed to be the world’s fastest AI training machine and the most powerful computer.
This new chip is more powerful than most computers, and there are 25 of them in this AI training tile.
I can’t believe i’m holding nine petaflops out here.
They’re connecting 120 tiles in one computer - 3000 chips in total.
Straight after announcing this, Tesla revealed plans to build the Tesla bot.
Neural nets, recognising the world, understanding how to navigate through the world.
Uh it kind of makes sense to put that onto a humanoid form.
It’s intended to be friendly, of course um, and navigate through a world built for humans and eliminate, dangerous, repetitive and boring tasks.
Most of the one million warehouse jobs in the US, and millions more in other sectors.
Musk is straightforward about the impact of this.
What happens when there is, er, you know, no shortage of labour, um.
This is why I think long term that there will have to be universal basic income” The robots have a screen for a face, which could show information or expressions.
It’s powered by the same computer used for autonomous driving, the same cameras - with two sets of eyes - and will learn via simulation, in their supercomputer.
The robots will generate incredible wealth.
It obviously has profound implications for the economy because, given that the economy at its foundational level is labour, I mean, is there any actual limit to the economy? Maybe not.
Robot workers have already made Musk the world’s richest man, and he could be the first trillionaire.
It’s made him a target, in a country where many struggle to pay the rent, and half a million are homeless.
Please don’t call the manager on me, Senator Karen.
She struck first, obviously.
Yeah, she did.
She called me a freeloader, and a drifter who doesn’t pay taxes basically, and I’m literally paying the most tax that any individual in history has ever paid this year, ever, uh and she doesn’t pay taxes, basically at all, and her salary is paid for by the taxpayer.
If you could die by irony she would be, she would be dead.
Whatever you think of all this, the wealth gap is growing.
So what happens when billionaires start building humanoid robot workforces? Countries with higher wealth gaps have more crime, more health problems, and lower levels of satisfaction and happiness.
They also have lower economic growth when money goes to luxuries like super-yachts instead of workers.
Researchers are experimenting with a solution that could help everyone, but first, let’s have a look at personal robots.
It could be actually a very good companion.
It could develop, like a personality over time that is, that is like, unique, and the, suttle perfections of the personality of the robot, could actually make an incredible, buddy basically.
In that way.
Like R2D2 or like C3PO sort of thing you know.
Where are you taking these prisoners? These are prisoners? Yes, where are you taking them? I am taking them, to imprison them, in prison.
He is taking us to.
Quiet! Can you spot the boston dynamics robot used in this star wars TV series? Humanoid robots could help with a big global problem that might surprise you.
The birth rate has been declining for decades.
I think the biggest problem people will face in 20 years is population collapse.
It’s very easy to see what the world will look like in 20 years, because humans have a 20 year boot sequence, so like you say, okay well, who was born last year? Okay now you know what the world will look like in 20 years, it’s that easy.
I absolutely agree with that, the speed of population decreasing is going to speed up.
Now you call it collapse, I agree with that.
Accelerating collapse.
Accelerating collapse.
The big problem is that there won't be enough young people, enough workers.
Japan’s already struggling with too few young people, to support its ageing population.
It’s former prime minister called for more rapid development of robots, to help overcome the problem.
People in Japan are already dating AI and robots.
That might be a symptom of isolation, but AI conversations are getting more interesting.
GPT-3 learned to talk by reading hundreds of billions of words on the web.
What do you think is organic? And what do you think is artificial? Good question, I think everything that was ever made somehow stems from organic, even if it was processed to the point most of us like to call it artificial, how about you? I think that's true, in times past, things felt more organic because people used handcrafting to make everything.
Now everything is programmed and let's face it, if we go way back in history, you couldn't even make a wooden spoon, nevermind a skyscraper without a machine.
The AI was initially thought too dangerous to release, in case it wrote huge volumes of fake news, but thousands of developers are now working on it.
One man tailored the AI to sound like his fiance, who died ten year ago, and OpenAI removed his access.
Robots are now learning to track our eyes and move theirs more naturally.
Even for humans it’s a tricky skill, which can have a big impact on a first date.
Hi, how are you? Good, Drew.
Aleisha.
Nice to meet you.
Here their gaze is all over the place, and it was really awkward.
She got on better with this guy, and their gaze was more calm and direct.
Eye tracking has been used to bring characters to life in VR and in experimental robots like this.
And now with Ameca, it’s eyes, face and its body all react to what it’s seeing.
Look at the way it leans back.
Artificial muscles will create even more realistic movements.
Just look at the range of motion in this hand.
It’s incredibly strong - the weight is 7 kg, and here it lifts 26 kg.
It’s powered by water pressure, with half as many muscles as a human hand, and sensors in each joint.
There are 42 muscles in the human face.
Once they’re recreated in a robot, AI can apply infinite expressions.
At the moment, pre-programmed and remote controlled robots get a lot of attention, like boston dynamics dancing robots and this robot dog facing off with a cheetah at Sydney zoo.
It’s an experiment to see if the robot could be used to control the Cheetahs if they got into a dangerous situation.
But the real revolution is going on behind robots’ eyes.
So, the lightsabers.
Apart from a bit of fun, it shows two kinds of robots.
Atlas is incredibly impressive, but it’s best moves are pre-programmed, and it’s largely independent.
It has one life.
With Tesla bot, they’re working towards a robot that can teach itself to perform many tasks.
It will be part of a huge AI network.
The robot itself is less important, and if the AI wanted to survive, it would be very hard to kill.
Hello again.
AI doesn't have to be evil to destroy humanity.
If AI has a goal and humanity just happens to be in the way, it’ll destroy humanity as a matter of course, without even thinking about it, no hard feelings.
It’s just like if we’re building a road, and an anthill happens to be in the way, we don’t hate ants, we’re just building a road, and so goodbye anthill.
For now, it’s taking jobs.
Up to half of all US jobs are expected to disappear over the next ten years I think long term that there will have to be universal basic income.
A Stanford study of several UBI projects found some interesting results.
People who received money regularly didn’t work less.
They did spend more time in education, with higher school attendance.
Their health improved, and rates of disease dropped.
Basic income also allows people to take risks, like this guy, who’s doing amazing things with robotics.
Most of the world’s 40 million amputees can’t afford prosthetics - particularly children who grow out of them.
To bring the cost down, these arms are 3D printed.
I have never, experienced the sensation of having fingers that move like that on this side of my body.
I wonder if I can just.
I just got this open, I have never done that, in my life, what I just did.
Some of the world’s poorest people are now receiving a basic income through a charity called give directly.
08:58
雙語 | 機(jī)器人會(huì)導(dǎo)致我們失業(yè)？↓↓↓ 上下滑動(dòng)，查看雙語全文 ↓↓↓
The world is widely considered to be on the cusp of a fourth industrial revolution – one where machines will be able to do many of the jobs currently performed by humans, and perhaps even do them better. It is a future that promises greater efficiency and cheaper services, but one that also could herald widespread job losses.
人們普遍認(rèn)為，世界正處于第四次工業(yè)革命的風(fēng)口浪尖——機(jī)器將能夠承擔(dān)人類目前所做的許多工作，甚至比人類做得更好。未來的社會(huì)會(huì)更加高效，服務(wù)也更加廉價(jià)，但這也可能預(yù)示著大范圍的失業(yè)。
It raises a troubling question for all of us – when will a machine be able to do my job?
一個(gè)令所有人不安的問題應(yīng)運(yùn)而生了——機(jī)器何時(shí)能替代我的工作？
There are no certain answers, but some of the world’s top artificial intelligence researchers are trying to find out.
這個(gè)問題并沒有確切的答案，但一些世界頂級(jí)的人工智能研究員正試圖找出答案。
Katja Grace, a research associate at the University of Oxford’s Future of Humanity Institute, and her colleagues from the AI Impacts project and the Machine Intelligence Research Institute, have surveyed 352 scientists and compiled their answers into predictions about how long it may take for machines to outperform humans on various tasks.
凱特亞·格蕾絲是牛津大學(xué)人類未來研究所的助理研究員，她與來自人工智能影響項(xiàng)目和機(jī)器智能研究所的同事，對(duì)352名科研人員進(jìn)行了調(diào)研并匯總了結(jié)果，以此來預(yù)測(cè)機(jī)器在不同的工作中超越人類所需的時(shí)間。
人工智能在工作上的表現(xiàn)何時(shí)會(huì)超越人類？
When will AI outperform humans at work?
Many of the world’s leading experts on machine learning were among those they contacted, including Yann LeCun, director of AI research at Facebook, Mustafa Suleyman from Google’s DeepMind and Zoubin Ghahramani, director of Uber’s AI labs.
在調(diào)研中，他們接觸到了許多世界領(lǐng)先的機(jī)器學(xué)習(xí)專家，其中包括臉書人工智能研究主管揚(yáng)·勒丘恩，谷歌DeepMind創(chuàng)始人穆斯塔法·蘇萊曼以及優(yōu)步人工智能實(shí)驗(yàn)室主管Zoubin Ghahramani。
The good news is that many of us will probably be safe in our jobs for some time to come. The researchers predict there is a 50% chance that machines will be capable of taking over all human jobs in 120 years.
好消息是，我們中的大部分人暫時(shí)都不會(huì)丟飯碗。研究人員預(yù)測(cè)，在未來120年內(nèi)，機(jī)器有50%的可能性會(huì)取代人類所有工作。
So what does this mean for the coming years and decades?
所以，對(duì)于未來幾年甚至幾十年，這意味著什么呢？
Increasing unemployment?
增加失業(yè)？
The survey suggests machines could also be folding laundry by 2021. So, if you work at a laundromat, is it time to throw in the towel? Perhaps not.
調(diào)查顯示，到2021年機(jī)器就可以疊盥洗的衣物，這樣的話，如果你在自助洗衣店工作，到時(shí)候會(huì)不會(huì)甘拜下風(fēng)呢？或許并不會(huì)。
Machines that can fold clothes do already exist: roboticists at the University of California, Berkeley, have already developed a robot that can neatly fold towels, jeans and T-shirts.
其實(shí)會(huì)疊衣服的機(jī)器已經(jīng)問世。加州大學(xué)機(jī)器人學(xué)家伯克利研發(fā)出了一款能夠?qū)⒚怼⑴Ｗ醒澓蚑恤疊得十分整齊的機(jī)器人。
Admittedly, it took the robot nearly 19 minutes to pick up, inspect and fold a single towel in 2010, but by 2012, it could fold a pair of jeans in five minutes and a T-shirt in a little over six minutes. Perhaps most excitingly, though, the robot can even take on the tedious task of pairing socks.
雖然2010年時(shí)機(jī)器人拿起一條毛巾，審視一遍然后將其疊好需要花費(fèi)19分鐘，可是到了2012年，它用5分鐘就能疊好一條牛仔褲，疊好一件T恤的時(shí)間也就6分鐘多一點(diǎn)兒。也許最讓人振奮的是，機(jī)器人甚至能勝任給襪子配對(duì)的乏味工作。
But despite this progress, it could be some time before robots like this are able to replace humans.
盡管取得了如此進(jìn)展，這樣的機(jī)器人要想取代人類仍需時(shí)日。
“I am a bit skeptical of some of the timelines given for tasks that involve physical manipulation, says Jeremy Wyatt, professor of robotics and artificial intelligence at the University of Birmingham.
伯明翰大學(xué)機(jī)器人學(xué)和人工智能教授杰里米·懷亞特表示：“我對(duì)機(jī)器取代人工的有些時(shí)間節(jié)點(diǎn)略表懷疑。”
“It is one thing doing it in the lab, and quite another having a robot that can do a job reliably in the real world better than a human.”
“在實(shí)驗(yàn)室里操作是一回事，研制出能在現(xiàn)實(shí)世界靠譜地做一項(xiàng)工作并超越人類的機(jī)器人完全是另外一回事。”
Manipulating physical objects in the real world – figuring out what to manipulate, and how, in a random, changing environment – is an incredibly complex job for a machine. Tasks that don’t involve physical manipulation are easier to teach.
在隨機(jī)多變的現(xiàn)實(shí)環(huán)境下操作實(shí)體對(duì)象，確定操作的內(nèi)容和方式，對(duì)機(jī)器來說著實(shí)復(fù)雜。不需要物理操作的任務(wù)更容易訓(xùn)練。
Robot mobility – things like self-driving cars and autonomous deliveries – are probably at the stage the internet was in the early 1990s, Wyatt says. “Moving things around in the world is probably 10 years further behind that.”
機(jī)器人的機(jī)動(dòng)性，比如自動(dòng)駕駛汽車和自動(dòng)配送等，所處的水平可能只相當(dāng)于上世紀(jì)90年代初的互聯(lián)網(wǎng)。懷亞特說：“要在全世界實(shí)現(xiàn)自動(dòng)移動(dòng)技術(shù)可能還要再晚10年。”
Your friendly robot assistant
友好的機(jī)器人助手
While towel folders are safe for now, perhaps there is reason for truck drivers and retailers to consider their roles over the coming two decades. The researchers predict that AI could be driving trucks by 2027 and doing retail jobs by 2031.
既然會(huì)疊毛巾的機(jī)器目前來看問題不大，或許卡車司機(jī)和零售從業(yè)者該想想他們?cè)诮酉聛?0年的出路了。研究人員預(yù)測(cè)到2017年人工智能將能夠駕駛卡車，到2031年可以從事零售工作。
The stereotypical retail assistant job – a friendly human to help you find a pair of jeans in a shop, and tell you how they look – is a role that requires complex physical and communication skills, and is probably safe for the moment.
傳統(tǒng)的零售輔助工作是一個(gè)友好的銷售員在店里幫你找到一條牛仔褲，為你講解它穿在身上是什么樣子。這種工作需要復(fù)雜的物理和溝通技巧，可能暫時(shí)不會(huì)受到威脅。
But as more people shop online, AI in the form of bots and algorithms may be replacing other roles in retail far earlier than we might think, says Wyatt. “Look at how many transactions we now do online that are largely automated – it is a significant proportion. And they are already using a reasonable amount of AI.”
懷亞特表示，隨著越來越多的人進(jìn)行網(wǎng)購(gòu)，以機(jī)器人和算法形式出現(xiàn)的人工智能或許會(huì)取代零售環(huán)節(jié)的其他角色，而且遠(yuǎn)早于我們所認(rèn)為的時(shí)間。“看看現(xiàn)在我們?cè)诰W(wǎng)上進(jìn)行的交易有多少基本上是自動(dòng)完成的，顯然大部分都是，人工智能在其中得到了大量應(yīng)用。”
Fear not, fellow humans
不要害怕，人類同胞
Perhaps the hardest jobs for machines to perform are those that take years of training for humans to excel at. These often involve intuitive decision making, complex physical environments or abstract thinking – all things computers struggle with.
可能對(duì)于機(jī)器來說，最難掌握的往往是人類經(jīng)由長(zhǎng)年的訓(xùn)練所精通的技能。這些技能常常包括直覺決策，復(fù)雜的現(xiàn)實(shí)環(huán)境或抽象思維，這些都是計(jì)算機(jī)所不擅長(zhǎng)的。
The experts predict robots will not be taking over as surgeons until around 2053, while it could take 43 years before machines are competing with mathematicians for space in top academic journals.
據(jù)專家估計(jì)，機(jī)器人將在2053年左右取代外科醫(yī)生，而與數(shù)學(xué)家匹敵，在頂級(jí)學(xué)術(shù)期刊上占有一席之地則需要43年的時(shí)間。
They also predict AI computers could be churning out New York Times bestselling novels by 2049.
專家還預(yù)測(cè)，到2049年，人工智能計(jì)算機(jī)還能大量創(chuàng)作出《紐約時(shí)報(bào)》最佳暢銷小說。
In reality, machines are already dipping their digital fingers into this field too.
在現(xiàn)實(shí)中，機(jī)器也已經(jīng)在數(shù)字科技方面涉足到這些領(lǐng)域。
Google has been training its AI on romantic novels and news articles in an attempt to help it write more creatively, and an AI bot called Benjamin can write short sci-fi film scripts – even if they don’t entirely make sense. Then there is the work of Automated Insights, which has created algorithms that churn out millions of personalised news, finance and sports articles for companies like Reuters and the Associated Press.
一直以來，谷歌都在訓(xùn)練人工智能寫言情小說和新聞報(bào)道，以助于寫出最有創(chuàng)意的內(nèi)容。一個(gè)名叫本杰明的人工智能機(jī)器人已經(jīng)寫出了一篇短篇科幻電影劇本，雖然有點(diǎn)前言不搭后語。此外，Automated Insights公司（譯者注：一家由美聯(lián)社及其他投資者提供融資的科技公司）也已經(jīng)發(fā)明了一種算法，為路透社和美聯(lián)社等公司提供數(shù)百萬篇個(gè)性化新聞、金融和體育報(bào)道。
Adam Smith, chief operating officer at Automated Insights, says this technology is intended to complement, rather than replace, human expertise. “Automated journalism is creating content that would not have existed before, but humans still need to add context to those stories.”
Automated Insights公司首席運(yùn)營(yíng)官亞當(dāng)·斯密表示，這項(xiàng)技術(shù)旨在對(duì)人工技能加以輔助，而不是取代人類的專業(yè)技能。“自動(dòng)化的新聞報(bào)道創(chuàng)造了以前不存在的內(nèi)容，但是人類仍然需要對(duì)這些內(nèi)容加以豐富。”
These stories, however, are produced according to a formula, where information is pulled out of large data sets and plugged in to templates. Producing bestselling fiction – rich in word play and with compelling twists in narrative – is still probably three decades away. Attempts by to use machines to play with language in creative ways usually result in nonsense.
但是，人工智能機(jī)器人創(chuàng)作的小說是根據(jù)一個(gè)公式而生成的，在這個(gè)公式中，信息從大數(shù)據(jù)集中提取出來并插入到模板中去。但人工智能創(chuàng)作出語言豐富且故事情節(jié)引人入勝的暢銷小說，可能還需要三年的時(shí)間。而利用機(jī)器寫出創(chuàng)造性語言的這種方式，往往會(huì)導(dǎo)致毫無意義的結(jié)果。
The challenge will be getting AI to produce material that is acceptable to our human tastes, says Wyatt. says “We find anything that is even slightly below human-level performance to be unacceptable. Take chatbots – they are not that far from human level performance… but we are so sensitive to any imperfections that they often seem laughably bad.”
對(duì)此，懷亞特表示，人工智能面臨的挑戰(zhàn)將是讓機(jī)器人生產(chǎn)出符合人類口味的產(chǎn)品。他還表示，“我們發(fā)現(xiàn)，人們對(duì)于任何稍微低于人類水平的性能都難以接受。”比如聊天機(jī)器人，它離人類的水平其實(shí)已經(jīng)非常接近了…但是我們卻常常對(duì)一些不完美之處吹毛求疵，顯得它們的性能很差。
Grace believes the survey should serve as a reminder that the world is on the cusp of radical change: “I don’t think there are any tasks humans can do that AI will be technically unable to carry out.”
格蕾絲認(rèn)為，這項(xiàng)調(diào)查應(yīng)該讓人們認(rèn)識(shí)到，世界正處在巨大變革的風(fēng)口浪尖。她表示，“我不覺得人類有任何技能是人工智能在技術(shù)上實(shí)現(xiàn)不了的。”
But she believes some roles may never be replaced by machines. A minister in a church, for example, might never be replaced by a robot if the churchgoers want a person to be in the role.
但她也相信人工智能不能完全取代人類的所有工作。比如教堂里的牧師，如果做禮拜的人需要人來承擔(dān)這個(gè)角色，牧師就永遠(yuǎn)不會(huì)被機(jī)器人取代。
“There will still be tasks that can only be conducted by a human because we will care that they are,” she says.
“有些事情只能由人類來做，因?yàn)槲覀冎幌胱屓祟悂碜鲞@些事。”她說。
