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广州番禺最好的保宫人流光明社区

2018年10月23日 18:08:28|来源:国际在线|编辑:QQ典范
Across factories in South China, millions of young Chinese spend their days churning out garments for consumers in Japan, South Korea, Europe and the US. For many of the workers, their most important piece of equipment — after the umbilical smartphone — is a sewing machine made by Juki.在中国华南地区的一座座工厂内,数百万名中国年轻人每天为日本、韩国、欧洲和美国的消费者们制造着装。对许多制衣工人来说,他们最重要的设备——除了离不开的智能手机以外——是一台Juki牌缝纫机。The Tokyo-based company, which started making sewing machines in 1947, has customers in 170 countries from China to the Vatican. While some of the big manufacturers — such as Sony — that were synonymous with the rise of Japan have lost their lustre, Juki is an example of the low-profile companies sustaining Japan’s economy.总部位于东京的Juki公司从1947年开始生产缝纫机,客户遍及从中国到梵蒂冈的170个国家。当一些与日本同步崛起的大厂商——如索尼(Sony)——失去了昔日的光,像Juki这样低调的企业撑起了日本经济。The business is the leading player in the industry, with 30 per cent of the market, and is especially popular among manufacturers that produce for multinational retailers. “It’s rather a personal preference, like choosing a car,” says Gerhard Flatz, managing director of the Chinese apparel manufacturer KTC, which uses Juki for more than 90 per cent of its machines. “But Juki machines are as reliable as a draught horse.”Juki是业内的龙头企业,拥有30%的市场份额,尤其在跨国零售商的代工商中间特别流行。中国装制造商KTC所采用的机器90%以上都是Juki的,总经理格哈德#8226;弗拉茨(Gerhard Flatz)说:“这更像是个人喜好,就像选车一样。但Juki的机器就像挽马一样可靠。”TAL, a Hong Kong apparel maker whose clients include Brooks Brothers and Burberry, says at least 80 per cent of its machines are Juki. Harry Lee, TAL chairman and a leading figure in the Hong Kong garment trade, says the Japanese group owes its success to the close relationship it builds with its customers.香港装生产商联业制衣(TAL)的客户包括布克兄弟(Brooks Brothers)和柏利(Burberry),该公司表示所用机器至少80%都是Juki。香港制衣业的领军人物、TAL董事长李乃熺(Harry Lee)表示,这家日本集团的成功要归功于其建立起了与客户之间的密切关系。Naotake Miyashita, head of Juki’s sewing machine business, who spends half his time visiting clients, also stresses the importance of relationships — sometimes nurtured over the umeshu plum wine it makes in the grounds of its factory in Tochigi prefecture north of Tokyo — and how the company is quick to respond. “When TAL has a problem, we hear from Harry Lee,” he jokes. “I have been summoned many times over our long relationship.”Juki缝纫机业务负责人宫下尚武(Naotake Miyashita)在工作中会把一半的时间花在拜访客户上,他强调了客户关系的重要性(Juki在东京以北的栃木县有间工厂,有些客户关系就是靠在该厂酿造的梅酒培养出来的),并表示该公司能够对客户需要做出迅速反应。宫下尚武开玩笑说:“当TAL遇到问题时,李乃熺便会告知我们。在我们的长期合作中,我多次受到召唤。”The Tokyo-listed company’s origins are in the second world war. When the army ran out of its most popular rifle in 1938, small manufacturers came together to form a group to produce the Type 99 guns, which are called juki in Japanese. As demand for rifles evaporated after the war, Juki switched to making domestic and industrial sewing machines. The group wanted to keep the name but wrote the word juki with different Japanese characters that meant heavy machinery instead of rifle.这家东京上市公司起源于第二次世界大战。1938年,由于日军的三八式步不够用,小型制造商聚到一起组成了一个集团,开始生产九九式步,该型号的日语名为“juki”。二战结束后随着对步需求的消失,Juki转向生产家用及工业用缝纫机。该集团希望保留juki这个名称,但更改了日文写法,原来的日文意思是“步”,更改后的意思为“重机”。While Juki also makes robots to place components on circuit boards, its sewing machine business — which generates 73 per cent of its turnover — provides a window on trends in the global textile business.虽然Juki也生产贴片机器人(将元器件贴装到电路板上的机器人),但其营业额的73%来自缝纫机业务。Juki的缝纫机业务提供了一个窗口,让人们可以看到全球纺织业的发展趋势。In 1970, the company opened its first overseas subsidiary in Hong Kong, then the centre of the global textile industry. Soon after, it followed suit in Europe, and later moved into the US.1970年Juki在香港开设了第一家海外子公司,当时香港是全球纺织业中心。不久以后,它又在欧洲开设了子公司,然后又将分扩展到了美国。Speaking at Juki’s headquarters in western Tokyo, Mr Miyashita says the company entered China in 1976 when it won a contract to supply the state-owned clothing manufacturer, which had 32 factories across the country.在Juki位于东京西边的总部里,宫下尚武介绍说,Juki于1976进入中国,当时公司争取到了一份为国有装公司供货的合同,该企业在全中国拥有32家工厂。After Deng Xiaoping launched economic reforms in 1979, Juki increased its orders — a trend that continued as Hong Kong companies moved production across the border, and accelerated following the 1997 Asian financial crisis. “Until then, even though China had started reforms, there was still a lack of capital and infrastructure,” says Mr Miyashita.1979年邓小平开启经济改革之后,Juki的订单增加了。随着香港的装公司纷纷转移到内地生产,Juki的订单越来越多,而且在1997年亚洲金融危机之后呈现加速趋势。宫下尚武说:“直到那时,尽管中国早已开始改革,但仍缺乏资金和基础设施。”Companies such as Walmart, Nike and Adidas decided China was more stable because the government had insulated the country from the currency crisis and because there was an abundance of cheap labour.沃尔玛(Walmart)、耐克(Nike)和阿迪达斯(Adidas)等公司都认为中国形势更为稳定,因为中国政府让这个国家避免了货币危机,而且中国有充足的廉价劳力。“The situation in China was nothing like today#8201;.#8201;.#8201;.#8201;when a factory advertised for 1,000 people, 10,000 people would gather outside the factory gate,” recalls the Japanese executive. As more factories moved to China, it started to account for a bigger share of Juki’s global sales, rising to 50 per cent in 2000 and staying there for much of the decade.宫下尚武说:“中国当时的情况跟今天完全不同……那时如果有家工厂招工一千人,工厂大门外会聚集起一万人。”随着迁往中国内地的工厂越来越多,中国在Juki全球销量中所占的份额也越来越大,2000年升至50%,并且在随后十年大部分时间里都保持在这个比例。Everything changed in 2005. China unpegged its currency from the US dollar and allowed it to appreciate slowly, which in turn increased manufacturing costs.2005年一切都变了,那一年人民币与美元脱钩,并开始缓慢升值,这增加了生产成本。Then, in 2008, China introduced a new labour law that ensured workers enjoyed better conditions, but dramatically raised labour costs.接着在2008年,中国出台了新的劳动法,虽然保障工人享受到更好的待遇,但大大提高了劳动成本。“Costs rose, the renminbi kept getting stronger, and profits started to fall,” says Mr Miyashita. “Retailers said China was becoming difficult and slowly started shifting orders to southeast Asia.”宫下尚武说:“成本越来越高,人民币不断走强,利润开始下降。零售商们表示在中国盈利变得越来越难,于是慢慢开始将订单往东南亚转移。”Currently, 25 per cent of Juki’s sales are in China. In recent decades, Juki has successfully expanded across the globe, leaving its main Japanese rival, Brother, in its wake.中国市场目前占Juki销量的25%。近几十年来,Juki已成功在全球各地扩张,将主要的日本竞争对手兄弟(Brother)甩在身后。Today, Juki faces a challenge from a new rival: Jack, a Chinese company that has 12 per cent of the global market.如今Juki面对着一个新对手的挑战:中国的新杰克缝纫机股份有限公司(Jack),该公司在全球市场中拥有12%的份额。Mr Miyashita recalls one trip to Bangladesh where the president of an old customer took him around the factory to show him how the sewing machines were being operated.宫下尚武回忆起一次去孟加拉的行程,当地一家老客户的总裁带着他参观工厂,向他展示缝纫机的使用情况。“He told me all its machines were Juki, but as soon as we entered the factory I realised they were Jack,” he says. “We are Juki and they are Jack with exactly the same font,” he says with a smile.宫下尚武笑着说:“他告诉我他们的缝纫机都是Juki的,但我们一进入工厂我就发现他们用的是新杰克。我们是‘Juki’,而他们是‘Jack’,字体一模一样。”On other occasions, he claims, factories have phoned to complain that their new Juki machines have aly broken down, only to be told that their equipment was actually made by a Chinese company based in Taizhou, a city in Zhejiang province where most of China’s sewing machine companies are based.宫下尚武称还有时候,一些工厂打来电话抱怨他们的Juki缝纫机才买来就出问题了,结果却被告知他们的机器是由一家总部在台州的中国公司制造的。台州位于浙江省,中国缝纫机企业大部分建在那里。The issue highlights a problem faced by many foreign companies in China: trademark copying. Mr Miyashita says: “There was a Chinese company called JUKL, but we sued them and they went away.”上述情况凸显了许多在华外企面临的一个问题:商标仿造。宫下尚武说:“有家中国公司叫JUKL,但当我们起诉他们时,他们就消失了。”Mr Miyashita, who spent more than two decades in Hong Kong and Shanghai building up Juki’s China business, says other Chinese companies are also trying to get in on the game.宫下尚武二十多年来致力在香港和上海发展Juki在华业务,他说还有别的中国公司也想从中得利。One Fujian company has created a brand called “Brosister”, which is similar to the name of rival manufacturer Brother. “They really come up with amazing names,” he says.福建一家公司推出了一个名为“兄”(Brosister)的品牌,与Juki竞争对手“兄弟”名字相似。他说:“他们在起名字方面真的很惊人。”Additional reporting by Mitsuko Matsutani and Nobuko JujiMitsuko Matsutani和Nobuko Juji补充报道 /201504/368864If you#39;re still painstakingly killing all your apps in the hopes of squeezing out some extra battery life from your iPhone, you can officially stop.如果你还在煞费苦心地通过关闭所有应用程序来为你的iPhone电池延长一点点寿命的话,那么现在你可以正式收手了。Apple#39;s iOS chief Craig Federighi has dispelled the myth that force closing your iPhone apps will help save your battery. The executive confirmed that killing apps isn#39;t necessary for your battery and said that he is not in the habit of closing his apps.苹果iOS总监克雷格·费德里吉已经澄清了关于强行关闭iPhone应用程序能够节约电池寿命的传言。费德里吉实:关闭切换的应用程序对延长你的电池寿命并无益处,同时也表示自己也没有随时关闭后台应用的习惯。Federighi, who oversees iOS and OS X, was responding to an email sent by an Apple customer to CEO Tim Cook when he made the comments. In the email, which was first published by 9to5Mac, the customer asked Cook, ;do you quit your iOS multitasking apps frequently and is this necessary of battery life?;费德里吉平常负责监督iOS和OS X开发,此前一位苹果手机用户在对产品进行反馈时向苹果公司CEO蒂姆·库克发送了一封邮件,费德里吉对这位顾客进行了回复。该邮件最先由9to5Mac网站公布,在邮件中,这位苹果用户询问库克:“你会不会经常随时关闭你的iOS的多任务应用程序,这对于提高续航是否有效?”Though the note, dated March 6, was sent to Cook, Federighi weighed in the next day with a simple answer. ;No and no,; he wrote.虽然这封邮件于3月6号发给的库克,但最后却是费德里吉在第二天代劳给予了回复。针对这位用户提出的两个问题,费德里吉的回答都是“no”。This is far from the first time this particular myth has been debunked. Apple#39;s own support page even states that ;generally, there#39;s no need to force an app to close unless it#39;s unresponsive.;这并不是苹果公司第一次澄清这个传言。苹果在自己的帮助页面甚至专门进行了声明:“一般来讲,没有必要强制关闭后台应用程序,除非手机出现卡顿等情况。”That#39;s because, as 9to5Mac and others have pointed out, most of the apps that appear in the multitasking view when you double press the home button aren#39;t actually running in the background.正如9to5Mac网站和其他媒体所言,不用关闭后台的原因在于,当你双击手机主画面按钮时,显示在屏幕列表上的大多数应用程序并没有真正运行,只是你在过去已经打开的应用程序的静态图像。Of course, it#39;s always a good idea to check your app settings every once in awhile to make sure that the apps that are using your location actually need it — as location services tend to use up the most battery. Also, disabling background refresh on apps you don#39;t use very much is a good idea. Some apps, like Facebook#39;s, may be worse offenders at sucking your battery dry than others.当然,每隔一段时间查看你的应用程序管理,以便确定正在使用定位功能的程序是否确实需要GPS这一功能倒是个不错的习惯。因为通常来讲,这些定位务会消耗手机大量的电量。此外,禁用那些不常用的后台刷新程序也是一个较好的办法。有些软件,比如Facebook这一类软件比其他软件更容易消耗你的电量。 /201603/432255

“I never forget a face,” some people like to boast. It’s a claim that looks quainter by the day as artificial intelligence research continues to advance. Some computers, it turns out, never forget 260 million faces.有些人总喜欢夸口说:“我从来不会忘记别人的长相。”在人工智能研究突飞猛进的今天,还要这么夸口就有点奇怪了。事实上,现在有些电脑能记住2.6亿张脸。Last week, a trio of Google GOOG -0.66% researchers published a paper on a new artificial intelligence system dubbed FaceNet that it claims represents the most-accurate approach yet to recognizing human faces. FaceNet achieved nearly 100-percent accuracy on a popular facial-recognition dataset called Labeled Faces in the Wild, which includes more than 13,000 pictures of faces from across the web. Trained on a massive 260-million-image dataset, FaceNet performed with better than 86 percent accuracy.上周,谷歌公司的三位研究人员发表了一篇有关全新人工智能系统的研究论文。这一系统名为FaceNet,谷歌号称它是迄今为止最精确的人脸识别技术。面对一个名为“人面数据库”(Labeled Faces in the Wild)的常用人脸识别数据库时,FaceNet识别的准确率近乎百分之百。这个数据库容纳了网上搜集的一万三千多张人脸照片。而在面对一个含有2.6亿张人脸照片的庞大数据库时,这个系统的准确率也超过86%。Researchers benchmarking their facial-recognition systems against Labeled Faces in the Wild are testing for what they call “verification.” Essentially, they’re measuring how good the algorithms are at determining whether two images are of the same person.研究人员声称,面对“人面数据库”时,他们主要测试该系统的“确认能力”。就本质而言,他们衡量的是这套算法在判断两张照片是否同属一人时到底有多准确。In December, a team of Chinese researchers also claimed better than 99 percent accuracy on the dataset. Last year, Facebook researchers published a paper boasting better than 97 percent accuracy. The Facebook FB 1.66% paper points to researchers claiming that humans analyzing images in the Labeled Faces dataset only achieve 97.5 percent accuracy.去年12月,一个中国研究团队也声称,对这套数据库的识别准确率超过99%。去年,Facebook公司的研究人员发表论文称,他们也能做到超过97%的准确率。根据这篇论文援引的一些研究人员的说法,人类对该数据库的识别准确率仅有97.5%。However, the approach Google’s researchers took goes beyond simply verifying whether two faces are the same. Its system can also put a name to a face—classic facial recognition—and even present collections of faces that look the most similar or the most distinct.不过,谷歌研究人员采用的方法绝不只是确认两张脸是否一样这么简单。这套系统还能将人名和脸匹配——经典的人脸识别技术,甚至能把看起来最像或最不像的脸归集在一起。This is all just research, but it points to a near future where the types of crime-fighting, or surveillance-enhancing, computers we often see on network television and blockbuster movies will be much more attainable. Or perhaps a world where online dating is even simpler (and shallower) than swiping left or right on Tinder.目前这还仅仅是研究而已,但它预示着,在不远的将来,我们经常在网上视频或大片里看到的那种能惩治犯罪、加强监控的电脑将更加触手可及。比起在交友应用Tinder上划来划去,它可能会使网上交友更加简单(也更停留于表面)。Have a thing for Brad Pitt circa 1998? Here are the 500 profiles that look the most like him.很喜欢1998年左右时的布拉德o皮特?这个数据库里有500张看起来很像他的脸。At first we’ll see systems like Google’s FaceNet and Facebook’s aforementioned system (dubbed “DeepFace”) make their way onto those company’s web platforms. They will make it easier, or more automatic, for users to tag photos and search for people, because the algorithms will know who’s in a picture even when they’re not labeled. These types of systems will also make it easier for web companies to analyze their users’ social networks and to assess global trends and celebrity popularity based on who’s appearing in pictures.一开始,我们会看到谷歌的FaceNet及Facebook的DeepFace系统在各自的网络平台上运行。它们会让用户更加方便地(或者说更加自动化地)给照片贴上标签,找到要找的人,因为这些算法知道照片中的这个人是谁,即使这些照片并没有姓名标记。此外,这类系统还能让网络公司更加方便地基于照片人物的身份,来分析它们的用户社交网络,评判全球流行趋势及名人的受欢迎程度。Though Google and Facebook’s advances in facial recognition are relatively new, computer systems like this can be found all around us today. They incorporate an artificial intelligence technique called deep learning, which has proven remarkably effective at so-called machine perception tasks such as recognizing objects (by some metrics, machines are now better at this than are people), recognizing voices, and understanding the content of written text.尽管谷歌和Facebook在人脸识别技术上最近才取得这类进步,但与之类似的电脑系统早就无处不在。它们都含有一种名为“深度学习”的人工智能技术。事实明,这种技术能够极其有效地完成识别物体(按照某些标准来看,机器在这方面已经比人类要强了)、识别语音及理解书面文字等机器辨别任务。Aside from Google and Facebook, companies including Microsoft MSFT 0.32% , Baidu, and Yahoo YHOO 0.63% are also investing heavily in deep learning research. The algorithms aly power everyday features such as voice control on smartphones, Skype Translate, predictive text-messaging applications, and advanced image-searching. (If you have images uploaded to a Google+ account, go ahead and search them for specific objects.) Spotify and Netflix NFLX -0.82% are investigating deep learning to power smarter media recommendations. PayPal EBAY -0.13% is using it to fight fraud.除了谷歌和Facebook外,微软、百度和雅虎也在“深度学习”研究上投入重金。这种算法已经应用在一些我们常用的功能上了,比如智能手机语音控制、Skype实时翻译、短信预测输入法及先进的图像搜索等(如果你已经将一些图片上传至Google+账户里,你就可以试试用它们来搜索特定目标)。Spotify和Netflix公司正在研究如何利用深度学习技术更智能地推荐视频。贝宝公司则将其用于打击欺诈。There are also several technology startups using deep learning to analyze medical images in real time, and to provide capabilities such as text analysis, computer vision, and voice recognition as cloud computing services. Twitter, Pinterest, Dropbox, Yahoo, and Google have all acquired deep learning startups in recent years. And IBM IBM -0.08% just bought a Denver-based startup called AlchemyAPI to help make its Watson system smarter and bolster its new Bluemix cloud platform. (The idea: Developers can easily connect mobile and web applications to cloud services and therefore build smart applications without ever studying the complex computer science that underpins artificial intelligence.)还有几家科技创业公司正将深度学习技术用于实时分析医疗图像,并提供诸如文本分析、计算机视觉及语音识别这类云计算务项目。近年来,Twitter、Pinterest,、Dropbox、雅虎和谷歌等公司都收购了一些专攻深度学习技术的创业公司。IBM公司刚刚收购了一家位于丹佛,名为AlchemyAPI的初创企业,用以提升其Watson超级计算机的智能水平,并持其全新的Bluemix云平台(该平台的理念是:开发者可以方便地将移动和网络应用与云务连接起来,借以打造一些智能应用,而无需再钻研人工智能背后复杂的计算机科学)。That’s not all. As consumer robots, driverless cars and smart homes become real, deep learning will be there, too, providing the eyes, ears, and some of the brains for our new toys. DARPA, the U.S. Department of Defense’s research agency, is also investigating how deep learning techniques might be able to help it make sense of the streams of communications crossing intelligence networks everyday.不止于此。随着消费级机器人、无人驾驶汽车及智能家居逐渐成为现实,深度学习技术也将如影随形,为我们这些新玩具提供耳目和一些头脑功能。美国国防部高级研究计划局(DARPA)也在探索如何借助深度学习技术来实时理解庞大的情报信息流。Something tells me it’s looking at Google’s FaceNet and getting pretty excited, too.我猜想,DARPA正在关注谷歌的FaceNet系统,并为之激动。 /201503/367041

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