中國科技巨擘競逐人工智能

As the quest to master artificial intelligence intensifies, China’s tech trio of Baidu, Alibaba and Tencent have a distinct advantage over their Silicon Valley rivals — data.

在各方對人工智能(AI)的探索日益白熱化之際，中國科技三巨頭百度(Baidu)、阿里巴巴(Alibaba)和騰訊(Tencent)比硅谷競爭對手擁有一項明顯優勢——數據。

As Robin Li, chairman and chief executive of Baidu, says: “Baidu knows you better than you know yourself.”

正如百度董事長兼首席執行官李彥宏(Robin Li)所說的那樣：“百度（比你自己）更懂你。”

Baidu, Alibaba and Tencent, have embraced AI with alacrity: setting up specialist labs at home and overseas and hiring top engineers. Much like their US peers such as Google, they are using machine learning to push into newer fields of autonomous driving, medical diagnosis, facial recognition for payments and AI-enabled hardware that can be operated by voice.

百度、阿里巴巴和騰訊均已欣然接受AI：在國內和海外建立專家實驗室，聘請頂級工程師。和谷歌(Google)等美國同行一樣，他們利用機器學習進入了一些較新的領域，包括自主駕駛、醫療診斷、用於支付驗證的面部識別，以及可用語音操作的AI功能硬件。

“We regarded AI as one of our top priorities last year and treat it as a strategic focus,” says Mark Ren, Tencent’s chief operating officer last month.

“去年我們把AI視爲我們的優先項目之一，把它當作一個戰略重點，”騰訊首席運營官任宇昕(Mark Ren)上月表示。

Alibaba takes a similar view, saying AI permeates “every aspect of our business?.?.?.?we don’t see it as a separate business unit.”

阿里巴巴持有類似觀點，稱AI滲透進了“我們業務的方方面面……我們不把它看作獨立的業務部門。”

The difference now, says Xiaofeng Wang, senior analyst at Forrester, the consultants, is the scale of the data companies have and the speed with which machines are able to process it. “You can easily do personalisation for a group of customers, but if its millions it’s very hard, and it’s about how fast you can provide that,” she says.

諮詢機構Forrester高級分析師王小峯（音）表示，如今的差別在於企業所掌握的數據規模以及機器處理數據的速度。“你可以輕鬆地對一羣顧客進行個性化分析，但如果要分析數百萬顧客就會非常難，這裏的關鍵在於你可能多快得出結果，”他表示。

Alibaba began highlighting its AI-powered improvements in this year’s earnings report. Jeff Zhang, chief technology officer, told analysts earlier this year that the biggest change was the scope of data — which now tops 1,000 PBs, equivalent to about 580bn books — it is able to process.

阿里巴巴在今年的盈利報表中開始介紹AI推動的改進。首席技術官張建鋒(Jeff Zhang)今年早些時候向分析師們表示，最大的變化是該公司如今能夠處理的數據規模（1000PB），相當於大約5800億冊書。

“We are generating and collecting all different kinds of data,” he says. “We want to leverage this to enable personalisation, to power search, security, customer service in all of these areas we are providing support through our data products.”

“我們產生並收集所有不同類型的數據，”他稱，“我們希望利用這些數據來實現個性化，通過我們的數據產品在我們提供支持的所有領域推動搜索、安全、客戶服務。”

Some of that was in evidence on Singles Day, when Alibaba used AI to generate 400m customised banner advertisements in the month leading up to the shopping day. It also used chatbots, to answer 3.5m simple queries a day over the presale period, such as “Where’s my package?”

11月11日的“光棍節”展現了AI的一部分威力，阿里巴巴在這個購物節之前的一個月利用AI製作了4億個定製橫幅廣告。在預售期，該公司還利用聊天機器人每天回答350萬個簡單詢問，比如“我的包裹在哪？”

All of this was possible previously, through the use of microphones and cameras, but not on the massive scale and at the split-second speeds afforded by AI technologies.

這一切在過去也可以通過麥克風和攝像頭實現，但是達不到如此龐大的規模以及AI技術帶來的高速度。

Edouard de Mezerac, head of data and analytics for Asia-Pacific at Oliver Wyman, the consultancy, highlights another change under way on Taobao, Alibaba’s third-party ecommerce platform. It allows users to search by image using deep learning, a technique designed to emulate the way a human brain works, to find a matching or similar item. This enables shoppers, for example, to source a dress worn by a celebrity. “That does not exist on Amazon today,” he says.

奧緯諮詢(Oliver Wyman)亞太區數據和分析主管愛德華?德梅澤拉克(Edouard de Mezerac)介紹了阿里巴巴的第三方電商平臺淘寶網(Taobao)正在經歷的另一個變化。它允許用戶通過圖片進行搜索，利用深度學習（一種旨在模擬人類大腦運作方式的技術）找到相同或類似的商品。比如，這可以讓購物者搜索某個名人穿的裙子。“現在這種技術在亞馬遜(Amazon)的平臺上還不存在，”他表示。

It is still early days for the industry but applications such as these hint at how the country could take the global lead, say analysts, especially as companies ramp up how they use the technology.

分析師們表示，該行業在利用AI方面仍處於起步階段，但是這類應用暗示了中國如何可能居於全球領先地位，特別是隨着企業加快利用相關技術。

Anand Swaminathan, a senior partner at consultants McKinsey, highlights two further factors that set China apart from Silicon Valley. “Their consumer testing ground is bigger than anywhere in the world,” he says. “Here they are testing with 1bn-plus people so for that reason the US is automatically handicapped. And the pace and scale of investment is fundamentally higher.”

諮詢公司麥肯錫(McKinsey)高級合夥人阿南德?斯瓦米納坦(Anand Swaminathan)列舉了讓中國跑贏硅谷的另外兩個因素。“他們的消費者測試場比世界上其他任何地方都大，”他表示，“他們在這裏能夠藉助10億以上人口進行測試，因此美國在這方面先天不足。而且中國的投資速度和規模從根本上高於美國。”

The Chinese also generate far more data that is far more accessible. While Apple and Google have sought to fortify user data against governments, most notably last year when it thwarted the FBI’s attempt to unlock the San Bernardino shooter’s iPhone. Chinese companies are less coy.

中國還產生在規模和易於獲取程度上遠超其他地區的數據。蘋果(Apple)和谷歌都試圖頂住政府的壓力來保護用戶數據，最突出的例子是去年蘋果拒絕幫助美國聯邦調查局(FBI)解鎖聖貝納迪諾(San Bernardino)槍擊者的iPhone。中國企業沒那麼不配合。

Delegates at this month’s Fortune Global Conference in Guangzhou enjoyed unusual access to Google, Facebook and Twitter, services that are normally blocked in China. “I spoke to a number of folks here who said, ‘How nice of them to provide free WiFi so I can access everything’,” says Mr Swaminathan. “But that means [the companies] can access everything of yours.”

本月在廣州參加《財富》全球論壇的代表們，不同尋常地得以訪問谷歌、Facebook和Twitter這些正常情況下在中國被屏蔽的服務。“我在這裏聽到很多人說，‘他們提供免費WiFi多好啊，這樣我能訪問一切服務’，”斯瓦米納坦表示，“但是這意味着（這些公司）可以獲得你所有的信息。”

A hint of what could be coming from China’s tech giants is how they might use AI in communications and healthcare.

至於中國科技巨頭未來可能推出什麼新穎產品和服務，從他們在通信和醫療行業可能如何利用AI可見一斑。

Alibaba is taking the voice-activated personal assistant concept a step further than Apple’s Siri or Amazon’s Alexa, with a plan to deploy ticket dispensing machines in subway stations that can cancel out background noise and focus purely on the person ordering the tickets.

阿里巴巴目前採用的語音激活個人助手概念比蘋果的Siri和亞馬遜的Alexa領先一步，該公司計劃在地鐵站推出可以過濾掉背景雜音、只聽訂票者說話的售票機。

The technology itself — essentially combining microphones and cameras to identify the speaker — has “a long history in research”, says Zhijie Yan, who heads up the speech interaction research at Alibaba.

阿里巴巴語音交互研究主管鄢志傑表示，該技術本身——本質上是結合麥克風和攝像頭來識別說話人——“的研發歷史很長”。

What is new, he says, is its application into a real product, helped by improving technology, which means personal assistants can move to public arenas: airports, train stations, restaurants and reception desks.

他表示，新穎之處在於，在不斷改進的技術的幫助下，把它應用於實際產品，這意味着個人助手可能進入公共場所：機場、火車站、餐廳和前臺。

Smarter AI and bigger data caches apply to medical applications too. Tencent is among those looking to corral the technology into detecting lung cancer at an early stage.

智能程度更高的AI和更龐大的數據規模也適用於醫療應用場合。騰訊是打算把該技術應用於檢測早期肺癌的公司之一。

Helping on that score are cross-border collaborations, led by university researchers, such as a project enabling researchers in Hong Kong to access American databases so computers can learn to recognise the features of malignant nodules.

推動這方面進展的是由高校研究員牽頭的跨境合作，比如某個項目讓香港的研究員能夠訪問美國數據庫，以便讓計算機可以學習惡性結節的特徵。

David Lam, assistant professor and specialist in respiratory medicine at the University of Hong Kong, says it will be five years before early results from projects materialise.

香港大學(University of Hong Kong)助理教授、呼吸內科專家大衛?林(David Lam)表示，項目得出初步結果將需要5年時間。

One reason is that data sharing is complicated by the fact different ethnicities have different characteristics. Lung cancer affords one example: in the US, UK and much of the world, the main cause is smoking. That is not the case in Hong Kong, Taiwan and South China, where there is also far more prevalence among women.

其中一個原因是，由於不同民族有不同的特徵，數據共享比較複雜。肺癌就是這方面的一個例子：在美國、英國以及世界大部分地區，肺癌的主要病因是吸菸。但在香港、臺灣以及中國南方不是這樣，這些地區女性的發病率高得多。

Other early stage efforts that have come in for criticism over concerns that they have little real-world application include programmes that beat world champions of chess and Go.

一些早期努力因爲缺乏實用性而招致批評，包括打敗圍棋和國際象棋世界冠軍的程序。

But Si Chen, senior strategy manager at Tencent’s AI lab, says the requisite perception and decision-making learning to beat those games will resonate.

但是騰訊AI實驗室的高級戰略經理陳思（音）表示，贏得這些遊戲所必需的感知和決策學習將具有借鑑價值。

“In the real world that is the same as self-driving,” she says. “Based on your sensors or what you can see, you have an understanding of the environment and from that be able to make decisions and take an action, which could be to turn the steering wheel left or brake.”

“在現實世界中，這就跟自動駕駛一樣，”她表示，“基於你的傳感器或者你能看見的情況，你對環境有一個瞭解，據此可以作決定和採取行動，比如向左打方向盤或是剎車。”