http://www.rrdnyyy.com/post/oiXHHofQZYAzsW5B?share=enable_share
https://backchannel.com/the-ai-takeover-is-coming-lets-embrace-it-d764d61f83a#.9fe8v6hpv
The AI Takeover Is Coming. Let’s Embrace It.
Yes, millions of low-paying, low-skilled jobs are increasingly at risk. But there’s also much to gain from the coming AI revolution.
OnTuesday,the White House released achilling/'tʃɪlɪŋ/reporton AI and the economy. It began by positing that “it is to be expected that machines will continue to reach and exceed human performance on more and more tasks,” anditwarned/wɔrn/ofmassive job losses.
chilling/'tʃɪlɪŋ/
adj. 寒冷的；冷漠的；使人恐惧的；令人寒心的；呱呱叫的（等于chillin）
n. 冷却；寒冷
v. 冷却（chill的ing形式）
warned/wɔrn/of
vt. 警告，提醒；通知
vi. 发出警告，发出预告
Yet tocounter/'kaʊntɚ/this threat, the government makes a recommendation that may soundabsurd/əb'sɝd/: we have toincreaseinvestment in AI. The risk to productivity and the US’s competitive advantage is too high to do anything butdouble down on it.
counter/'kaʊntɚ/
vi. 逆向移动，对着干；反驳
absurd/əb'sɝd/:
adj. 荒谬的；可笑的
n. 荒诞；荒诞作品
double down on it
This approach not only makes sense, but also is theonlyapproach that makes sense.It’s easy — and justified — to worry about the millions of individual careers that something likeself-driving cars and truckswillretool/ˌri'tul/, but we also havechasmsof need that machine learning could help fill. Our medical system is deeplyflawed/flɔd/; intelligent agents could spread affordable, high-quality healthcare to more people in more places. Our education infrastructure is notadequately/'ædikwitli/preparing students for thelooming/'lʊmɪŋ/economicupheaval/ʌp'hivl/; here, too,AI systems couldchip inwhere teachers are spread too thin. We might gain energy independence by developing much smarter infrastructure, as Googlesubsidiarysəb'sɪdɪɛri/DeepMind did for its parent company’s power usage. The opportunities are too great to ignore.
retool/ˌri'tul/
vt. 重组；重新装备
vi. 更换工具；重新装备；更换机械设备
chasmsof/'kæzəm/
n. 峡谷；裂口；分歧；深坑
flawed/flɔd/
adj. 有缺陷的；有瑕疵的；有裂纹的
adequately/'ædikwitli/
adv. 充分地；足够地；适当地
looming/'lʊmɪŋ/
adj. 隐隐约约的；正在逼近的
upheaval/ʌp'hivl/
n. 剧变；隆起；举起
subsidiary /səb'sɪdɪɛri/
adj. 附属的；辅助的
n. 子公司；辅助者
More important, we have to think beyond narrow classes of threatened jobs, because today’s AI leaders—at Google and elsewhere—are alreadylaying the groundwork/'graʊnd'wɝk/for an even moreambitious vision,the former pipe dream that is general artificial intelligence.
groundwork/'graʊnd'wɝk/
n. 基础；地基，根基
To visit the front lines of the great AI takeover is to observe machine learning systems routinely/rʊ'tinli/drubbingˈdrʌbɪŋ/humans in narrow,circumscribed/ˌsɝkəm'sraɪb/domains. This year, many of the most visiblecontestants/kən'tɛstənt/in AI’s face-off with humanity haveemergedfrom Google. In March, the world’s top Go playerweathered a humbling/'hʌmbliŋ/defeat against DeepMind’s AlphaGo. Researchers at DeepMind also produced a system that canlip-readvideos with an accuracy thatleaves humans in the dust. A few weeks ago, Google computer scientists working with medical researchers reported an algorithm that candetect diabeticretinopathyin images of the eye as well as anophthalmologist/ˌɑfθæl'mɑlədʒɪst/can. It’s an early steptoward/tɔrd/a goalmany companies are nowchasing: to assist doctors byautomating/'ɔtəmet/the analysis of medical scans.
routinely/rʊ'tinli/例行公事地；老一套地
drubbingˈdrʌbɪŋ/
n. 殴打；彻底击败
circumscribed/ˌsɝkəm’sraɪb/
contestants/kən'tɛstənt/
n. 竞争者；争辩者
face-off 对决
humbling/'hʌmbliŋ/
adj. 令人羞辱的
v. 羞辱（humble的ing形式）；使…谦恭；使…卑贱
diabetic/ˌdaɪə'bɛtɪk/
adj. 糖尿病的，患糖尿病的
n. 糖尿病患者
retinopathy/ˌrɛtnˈɑpəθi/
n. [眼科] 视网膜病
ophthalmologist/ˌɑfθæl’mɑlədʒɪst/
n. 眼科医师
steptoward/tɔrd/朝着
Also this fall, Microsoftunveiledˌʌn'veild/a system that cantranscribe/træn'skraɪb/human speech with greater accuracy than professionalstenographers/stə'nɑɡrəfɚ/. Speech recognition is the basis of systems like Cortana,Alexa, and Siri, and matching human performance in this task has been a goal for decades. For Microsoft chief speech scientist XD Huang, “It’s personally almost like a dream come true after 30 years.”
unveiledˌ/ʌn'veild/
adj. 裸露的；公布于众的
v. 公开（unveil的过去分词）；原形毕露
transcribe/træn'skraɪb/
vt. 转录；抄写
stenographers/stə'nɑɡrəfɚ/速记员
But AI’s 2016 victories over humans are just the beginning. Emerging research suggests we will soon move from theseslim/slɪm/slivers/'slivə/of intelligence to something richer and more complex. Though a true general intelligence is at least decades away, society will still see massive change as these systems acquire anever-widening circle of mastery.That’s why the White House (well, at least while Obama’s still in office) isn’t shrinking from it.We are in the midst of developing a powerful force that will transformeverything we do.
slim/slɪm/
adj. 苗条的；修长的；微小的；差的
vt. 使…体重减轻；使…苗条
vi. 减轻体重；变细
slivers/'slivə/
n. 裂片；条状碎木片；废屑（sliver的复数）
v. 成为薄片；裂成小片（sliver的第三人称单数形式）
ever-widening不断扩大的
To ignore this trend — to not plunge headlong into understanding it, shaping it, monitoring it — might well be the biggest mistake a country could make.
The tool of choicein theaforementionedexamples of successful AIs is deep learning: the artificial intelligence technique that’s beenrivaling/'raɪvl/habanerosinblistering'blɪstərɪŋ/hotness/'hɔtnis/.Its special nature is the reason we’re on thebrink/brɪŋk/of a more general intelligence.
aforementioned/ə,fɔr’mɛnʃənd/
rival
n. 对手；竞争者
vt. 与…竞争；比得上某人
vi. 竞争
adj. 竞争的
blistering'blɪstərɪŋ/
adj. 猛烈的；极热的，极快的
n. [涂料] 起泡；发疱
v. 起水疱；起气泡；使受暴晒（blister的ing形式）
adj. 上述的；前面提及的
hotness
n. 热烈；热心；暑热
brink/brɪŋk/
n. （峭壁的）边缘
Though we’ve been able to train AIs to solve tasks for decades, experts had topainstakingly/ˈpensˌtekɪ ŋlɪ/hand-engineer manybespoke/bɪ'spok/components for every application. The years of human work needed to support an AI in recognizing objects in an image, for example, were totally useless/'jusləs/for the problem ofdeciphering/di'saifə/sounds fortranscription/træn'skrɪpʃən/. In other words, we’ve had topre-chewour AIs’ food, over and over and over again.
painstakingly/ˈpensˌtekɪ ŋlɪ/
adv. 煞费苦心地；费力地
bespoke/bɪ’spok/
adj. 定做的；预定的
vt. 预约，显示出
deciphering/di'saifə/
n. [通信] 解密
v. 破译（decipher的ing形式）；解释；辨认
transcription/træn'skrɪpʃən/.
n. 抄写；抄本；誊写
pre-chew/tʃʊ/咀嚼
The lesson of the past four years is that thistedious/'tidɪəs/pre-chewing is now, for the moment at least, largelyirrelevant/ɪ'rɛləvənt/. Instead, there’sessentially/ɪ'sɛnʃəli/one algorithm (with many minor variants) that can adjust its own structure to solve a problem, directly from whatever massively large data set you feed it. The result is not only better-performing systems, but also much fasterexperimentation/ɪk,spɛrɪmɛn'teʃən/. “Many, many problems that welabored/ˈlebəd/onfor a long time and made very, veryhalting/'hɔltɪŋ/progress on, now in six months we can basicallyplow/plaʊ/throughthem,” says Google vice president and engineering fellow/'fɛlo/Fernando Pereira.
tedious/‘tidɪəs/
adj. 沉闷的；冗长乏味的
irrelevant/ɪ’rɛləvənt/
adj. 不相干的；不切题的
experimentation/ɪk,spɛrɪmɛn'teʃən/.
essentially/ɪ'sɛnʃəli/
adv. 本质上；本来
labored/ˈlebəd/on
n. 劳动；工作；劳工；分娩
vi. 劳动；努力；苦干
vt. 详细分析；使厌烦
halting/'hɔltɪŋ/
adj. 犹豫的；蹒跚的；跛的
v. 停止；蹒跚；犹豫（halt的ing形式）
plow/plaʊ/through
vi. [农机] 犁；耕地；破浪前进；开路
vt. [农机] 犁；耕；开路
n. [农机] 犁；似犁的工具；北斗七星
Yet as impressive as human-quality speech recognition, lip reading and image tagging are, it’s not immediately obvious that they’re thecornerstones/'kɔrnɚston/of some great, all-powerful intelligence. It’s somewhat like having your kid come home with areport cardof As in subjects that include English,knitting/'nɪtɪŋ/the heels/hilz/of socks,dodgeball/'dɑdʒ'bɔl/, and calculating ahypotenuse/haɪ'pɑtənus/. You’d likely wonder if this clever kid will be able to draw connections between those areas to emerge as a critical thinker. So is deep learning really on a path to challenging true human intelligence?
cornerstones/'kɔrnɚston/
n. 基础；柱石；地基
report card
成绩单
工作报告
knitting/'nɪtɪŋ/
Knitting 编织
heels/hilz/
n. 高跟鞋（heel的复数）；脚踝；残余料
v. 紧跟；给（鞋等）装跟（heel的三单形式）
dodgeball/‘dɑdʒ'bɔl/
https://en.wikipedia.org/wiki/Dodgeball
n. 躲避球
hypotenuse/haɪ'pɑtənus/直角三角形的斜边
“The reason we’re seeing extremely narrow systems right now is because they’re extremely useful,” says Ilya Sutskever, cofounder and research director of OpenAI. “Good translation is extremely useful. Good cancer screening is extremely useful.So that’s what people are going after.”
But he adds that although today’s systems look narrow, we “are already beginning to see the seed ofgenerality/ˌdʒɛnə'ræləti/.” The reason is that the underlying techniques are all justmild/maɪld/riffson one concept. “These ideas are so combinable, it’s likeclay/kle/. You mix and match them and they can all be made to work.”
generality/ˌdʒɛnə'ræləti/.
n. 概论；普遍性；大部分
mild/maɪld/
adj. 温和的；轻微的；淡味的；文雅的；不含有害物质的的
n. （英国的一种）淡味麦芽啤酒
n. (Mild)人名；(瑞典)米尔德；(德、捷、芬)米尔德
riffs/rɪf/
n. 反复乐节；即兴重复段
n. (Riff)人名；(法、葡、匈)里夫
mild riffs温和的段子
clay/kle/.
n. [土壤] 粘土；泥土；肉体；似黏土的东西
vt. 用黏土处理
n. (Clay)人名；(英、法、西、意、葡)克莱
combinable[kəm’bainəbl]
可以化合的
组合式
可以结合的
By mixing and matching the narrow systems of today, we’llland onsomething bigger and broader — and more recognizable as intelligent—tomorrow.
land on
登陆
降落
猛烈抨击
着陆
One early, tantalizing/ˈtæntl..aɪzɪŋ/exampleof what higher intelligence might eventually look like comes from Google’s translation research. In September, Google announced anenormous/ɪ'nɔrməs/upgrade in the performance of Google Translate, using a system it’s calling Google Neural Machine Translation (GNMT). Google’s Pereira called the jump in translationquality/'kwɑləti/“something I never thought I’d see in my working life.”
tantalizing/ˈtæntl..aɪzɪŋ/
adj. 撩人的；逗引性的；干着急的
v. 惹弄；逗弄人（tantalize的ing形式）
enormous/ɪ'nɔrməs/
adj. 庞大的，巨大的；凶暴的，极恶的
quality/'kwɑləti/
n. 质量，[统计] 品质；特性；才能
adj. 优质的；高品质的；<英俚>棒极了
“We’d been making steady progress,” he added. “This is not steady progress. This isradical./'rædɪkl/”
radical./'rædɪkl/
adj. 激进的；根本的；彻底的
n. 基础；激进分子；[物化] 原子团；[数] 根数
With the new Translate nowrolling outlanguage by language, some Googlers decided to go even further. They wondered if they could build a single translation system that couldjuggle/'dʒʌɡl/many languages and potentially displaytransfer learning, ahallmark/ˈhɔlˌmɑrk/of human intelligence. Transfer learning is the ability to apply one skill, such as playing the piano, to speed up theacquisition/ˌækwɪ'zɪʃən/of another, such asconducting/kən'dʌkt/anorchestra/'ɔrkɪstrə/or learning another instrument.
rolling out
铺开；滚出
juggle/'dʒʌɡl/
vi. 玩杂耍；欺骗；歪曲
vt. 歪曲；欺骗
n. 玩戏法；欺骗
尽力对付
hallmark/ˈhɔlˌmɑrk/
n. 特点；品质证明
vt. 给…盖上品质证明印记；使具有…标志
n. (Hallmark)人名；(英)霍尔马克
conducting/kən'dʌkt/
vi. 导电；带领
vt. 管理；引导；表现
n. 进行；行为；实施
orchestra/‘ɔrkɪstrə/
n. 管弦乐队；乐队演奏处
It seems obvious to us that knowing the fundamentals of music would help apianist/'pɪənɪst/pick up theukulele/'jʊkə'leli/, but that’s not how language translation has been done. In GNMT, one deep learning system had toabsorb/əbˈsɔrb/millions of German-to-English translations, and teach itself how to take inder rote Hundand spit outthe red dog. A separate system independently learned how to translate in the other direction, from English to German. Same goes for French to English, English to French, Korean to Japanese, and so on — every pair of languages uses its owndistinct/dɪ'stɪŋkt/system, built as if the act of translation was being inventedaneweach time. To support translation between 100 languages, you might end up training almost 10,000 separate systems. That’s time consuming.
ukulele/'jʊkə'leli/,尤克里里琴（夏威夷的四弦琴，等于ukelele）
absorb/əbˈsɔrb/
vt. 吸收；吸引；承受；理解；使…全神贯注
distinct/dɪ'stɪŋkt/
adj. 明显的；独特的；清楚的；有区别的
These researchers wanted to know if they could build a single model for multiple languages that could hold its own against those one-off systems. First, it might be more efficient. And maybe something interesting would emerge from having all those words and languagesjangling/'dʒæŋɡl/aroundinside a single architecture.
jangling/'dʒæŋɡl/
n. 争吵，吵嚷；刺耳声
vt. 使发出刺耳声；使争论
vi. 刺耳响；争论，吵架
They started small, with a neural network trained on Portuguese/ˌpɔrtʃəˈɡiz/and English, and on English and Spanish. So far so good: this single multilingual/ˌmʌltɪ'lɪŋɡwəl/system did almost as well as the state-of-the-art, dedicated GNMT models in translating between English and either Spanish or Portuguese. Then they wondered: could this algorithm also translate between Portuguese and Spanish — even though it hadn’t seen a single example of Portuguese-Spanish translation?
multilingual/ˌmʌltɪ'lɪŋɡwəl/
adj. 使用多种语言的
n. 使用多种语言的人
As theyreportedin November, the result they got was “reasonably good quality” — notstaggering/'stæɡərɪŋ/in its perfection, but not bad for anewbie/'nubi/. But when they then fed it a small set of Portuguese-to-Spanish sentence pairs, sort of anamuse/ə'mjuz/bouche/bu:ʃ/ofdata, the system suddenly became just as good as a dedicated GNMT Portuguese-to-Spanish model. And it worked for other bundles of languages, too. As the Google authors write in the paper, this “is the first time to our knowledge that a form of true transfer learning has been shown to work for machine translation.”
staggering/'stæɡərɪŋ/
adj. 惊人的，令人震惊的
stagger['stæɡə]
vt. 蹒跚；使交错；使犹豫
vi. 蹒跚；犹豫
n. 蹒跚；交错安排
adj. 交错的；错开的
newbie/'nubi/.
n. 网络新手；新兵
amuse bouche
餐前点心，可口小吃
It’s easy to miss what makes this so unusual. This neural net had taught itself arudimentary/ˌrudɪ'mɛntri/new skill using indirect information. It had hardly studied Portuguese-to-Spanish translation, and yet here it was,acingthe job. Somewhere in the system’sguts/ɡʌts/, the authors seemed to see signs of a sharedessence/'ɛsns/of words,a gist/dʒɪst/ofmeaning.
rudimentary/ˌrudɪ'mɛntri/
adj. 基本的；初步的；退化的；残遗的；未发展的
guts/ɡʌts/
n. 内脏；飞碟游戏（比赛双方每组5人，相距15码，互相掷接飞碟）；狭道；贪食者（gut的复数）
v. 取出…的内脏；毁坏…的内部；贪婪地吃（gut的第三人称单数）
n. (Guts)人名；(德)古茨
n. （俚语）勇气；决心
essence/‘ɛsns/
n. 本质，实质；精华；香精
gist/dʒɪst/
n. 主旨，要点；依据
Google’s Pereira explains it this way: “The model has a common layer that has to translate from anything to anything. That common layer represents a lot of the meaning of the text, independent of language,” he says. “It’s something we’ve never seen before.”
Of course, this algorithm’s reasoning power is very limited. It doesn’t know that a penguin is a bird, or that Paris is in France. But it’s a sign of what’s to come: an emerging intelligence that can makecognitive leaps/li:p/based on an incomplete set of examples. If deep learning hasn’t yet defeated you at a skill you care about, just wait. It will.
leaps/li:p/
vi. 跳，跳跃
n. 飞跃；跳跃
vt. 跳跃，跳过；使跃过
n. (Leap)人名；(法)莱亚
Training one systemto do many things is exactly what it takes to develop a general intelligence, andjuicing upthat process is now a core focus of AI boosters. Earlier this month OpenAI, the researchconsortium/kən'sɔrtɪəm/dreamed upby Elon Musk and Sam Altman, unveiledUniverse, an environment for training systems that are not just accomplished at a single task, but that canhop/hɑp/around andbecomeadept atvarious activities.
juicing up
使…活跃；使…有精神；使…更动人
consortium/kən'sɔrtɪəm/. 财团；联合；合伙
hop/hɑp/around跳来跳去
v. 单足跳跃〔跳行〕
vt. 搭乘
vi. 双足或齐足跳行
n. 蹦跳,跳跃；跳舞；一次飞行的距离
As cofounder Sustkever puts it, “If you try to look forward and see what it is exactly we mean by “intelligence,” it definitely involves not just solving one problem, but a large number of problems. But what does it mean for a general agent to be good, to be intelligent? These are not completely obvious questions.”
So he and his team designed Universe as a way to help others measure the general problem-solving abilities of AI agents. It includes about a thousand Atari games, Flash games, and browser tasks. If you were to enter whatever AI you’re building into the training ring that is Universe, it would beequipped withthe same tools a human uses to manipulate a computer: a screen on which to observe the action, and a virtual keyboard and mouse.
The intent is for an AI to learn how to navigate one Universe environment, such asWing Commander III, then apply that experience to quickly get up to speed in the next environment, which could be another game, such asWorld of Goo, or something as different as Wolfram Mathematica. A successful AI agent would display some transfer learning, with adegree/dɪ'ɡri/ofagility/əˈdʒɪlɪti/andreasoning.
agility/əˈdʒɪlɪti/
n. 敏捷；灵活；机敏
degree/dɪ'ɡri/
n. 程度，等级；度；学位；阶层
This approach is not withoutprecedent/'prɛsɪdənt/. In 2013, DeepMindrevealed/rɪ'vil/a single deep learning-based algorithm that discovered, on its own, how to play six out of seven Atari games on which it was tested. For three of those games —Breakout,Enduro, andPong— itoutperformeda human expert player. Universe is a sort of scaled-up version of that DeepMind success story.
precedent/'prɛsɪdənt/.
n. 先例；前例
adj. 在前的；在先的
revealed/rɪ'vil/
v. 透露（reveal的过去式）；显示
As Universe grows, AItrainees/trei'ni:/can start learninginnumerable/ɪ'nʊmərəbl/useful computer-related skills. After all, it is essentially aportal/'pɔrtl/into the world of anycontemporary/kən'tɛmpərɛri/deskjockey/'dʒɑki/. Thediversity/daɪ'vɝsəti/of Universe environments might even allow AI agents to pick up somebroadworld knowledge that otherwise would betough/tʌf/to collect.
trainees/trei'ni:/
n. [经管] 实习生；[劳经] 受训人员（trainee的复数）；训练中的动物
innumerable/ɪ'nʊmərəbl/
adj. 无数的，数不清的
portal/'pɔrtl/
n. 大门，入口
n. (Portal)人名；(法、西、葡)波塔尔；(英)波特尔
jockey/'dʒɑki/
vt. 驾驶；欺骗；移动
n. 操作工；驾驶员；赛马的骑师
vi. 当赛马的骑师；耍手段图谋；搞欺骗
contemporary/kən'tɛmpərɛri/
n. 同时代的人；同时期的东西
adj. 当代的；同时代的；属于同一时期的
tough/tʌf/
adj. 艰苦的，困难的；坚强的，不屈不挠的；坚韧的，牢固的；强壮的，结实的
n. 恶棍
vt. 坚持；忍受，忍耐
adv. 强硬地，顽强地
n. (Tough)人名；(英)图赫
It’s a bit of aleap/lip/from a Flash-and-Atarichampion/'tʃæmpɪən/to an agent that improves the quality of healthcare, but that’s because our intelligent systems are still in kindergarten.For many years, AI hadn’t made it even this far. Now it is on the path to first grade, middle school, and eventually, advanced degrees.
leap/lip/
vi. 跳，跳跃
n. 飞跃；跳跃
vt. 跳跃，跳过；使跃过
n. (Leap)人名；(法)莱亚
champion/‘tʃæmpɪən/
n. 冠军；拥护者；战士
vt. 支持；拥护
adj. 优胜的；第一流的
n. (Champion)人名；(英)钱皮恩；(法)尚皮翁
Yes, the outcome is uncertain. Yes, it’s totally scary. But we have a choice now.We can try to shut down thismurky/'mɝki/future that we can neither fully control nor predict, and run the risk that the technologyseeps/sip/outunbidden/ʌn'bɪdn/,potentially/pə'tɛnʃəli/triggering/'trɪgɚ/massivedisplacement/dɪs'plesmənt/. Or we can actively/'æktivli/try to guide it to the paths of greatest social gain, and encourage/ɪn'kɝɪdʒ/the future we want to see.
murky/'mɝki/future
adj. 黑暗的；朦胧的；阴郁的
seeps out
vi. 漏；渗出
n. 小泉；水陆两用的吉普车
unbidden/ʌn'bɪdn/
adj. 未受邀请的；未受指使的；自愿的
actively/'æktivli/
adv. 积极地；活跃地
encourage/ɪn’kɝɪdʒ/
vt. 鼓励，怂恿；激励；支持
I’m with the White House on this one. A deep learning-powered world is coming, and we might as well rush right into it.
Creative Art Direction:Redindhi Studio
Illustration by:Laurent Hrybyk
【time】
6:16 - 6:58 am 42m
6:58-7:12am14m
9:26-10：54pm1.29m
[sentence]
This approach not only makes sense, but also is the only approach that makes sense.
It’s personally almost like a dream come true after 30 years.
We are in the midst of developing a powerful force that will transform everything we do.
Its special nature is the reason we’re on the brink /brɪŋk/ of a more general intelligence.
So that’s what people are going after.
something I never thought I’d see in my working life.
an environment for training systems that are not just accomplished at a single task, but that can hop/hɑp/ around and become adept at various activities.
Yes, the outcome is uncertain. Yes, it’s totally scary. But we have a choice now.
I’m with the White House on this one. A deep learning-powered world is coming, and we might as well rush right into it.