中国日报网6月3日电 据美国《连线》月刊近2日报道，谷歌母公司“字母表”公司（Alphabet）的执行总裁埃里克•施密特日前在中国乌镇向人们描述了他所谓的“智能时代”。但他所谈论的并不是人的智慧，而指的是人工智能。他鼓吹了深度神经网络和其他技术的兴起——该技术通过在大量数据中寻找模式或自身试错的方法使机器能够主要依靠自身来学会执行任务。
在谷歌，工程师们利用一个名为“TensorFlow”的软件库，已经建立起深度学习系统。这些系统能够识别照片中的面孔和物体，识别智能手机的语音指令，并将一种语言翻译成另一种语言。施密特将之称为自己一生中最大的技术变革。
接着他提到中国的三大互联网公司：百度、腾讯和阿里巴巴。他说，这三家公司都可以从谷歌大约18个月前开放源代码、与全世界共享的“TensorFlow”中广泛受益。
施密特在谈到这些中国互联网巨头时说：“它们如果使用‘TensorFlow’，境况都会更好。”他表示，该软件可以预测人们想要购买什么，帮助确定广告受众，甚至决定谁应该获得信用额度。“它们可以利用‘TensorFlow’研究自己的商业模式，并用这项技术为客户提供更快捷的服务。”
报道称，施密特是在中国棋手柯洁对战人工智能程序“阿尔法围棋”的比赛期间发表这番讲话的，因而并非言过其实。深度学习及其相关技术正从根本上改变谷歌的工作方式。在未来几年内，它们也将改变其他许多公司甚至是整个产业。不过，对于这些技术在谷歌公司之外已经发展到何种程度，施密特轻描淡写。智能时代的发展速度远比他所承认的更快，特别是在中国。
施密特的话准确描述了现代人工神经网络的巨大威力，也表明谷歌公司在这方面的进展和雄心。但是，如果揣摩字里行间的意思，这些话也显示了谷歌野心中的局限——中国正是它的软肋。尽管西方许多人把深刻的学习革命描绘成一个由美国大互联网公司推动的现象，但中国几乎并未落后多远。
报道称，百度、腾讯和阿里巴巴等中国企业已经在使用同美国的脸书、微软和亚马逊等巨头一样的技术。谷歌捷足先登，主要是因为它得到了很多关键人才。但不少公司也都在很大程度上涉足了深度学习领域，包括中国几家最大的互联网公司。目前负责百度硅谷人工智能实验室的人工智能专家亚当•科茨说：“人们很容易陷入旧有成见，认为中国只会模仿，认为中国远远落后，一切都靠进口。但这种看法已经过时了。”
早在2013年，百度就开设了一个名为深度学习研究院的内部研究实验室，显示出极大的野心。现在，它还经营着其他几个实验室，包括设在硅谷的拥有200人的研发基地。该公司共雇用了1800人从事人工智能研究，内容包括无人驾驶汽车和其他机器人技术，以及许多在线服务。从百度的搜索引擎到图像和语音识别服务，该公司的所有领域都受到了深度学习技术的驱动。这家大型中国公司曾透露，它利用人工神经网络帮助确定在线广告服务对象。
报道称，腾讯最近开设了自己在美国的人工智能实验室。像阿里巴巴和百度一样，该公司如今对人工智能研究的发展起着重要的作用。
与此同时，这些技术不再被大公司所垄断，中国其他企业也加入其中。一家名叫Skymind的旧金山深度学习创业公司在中国设立了子公司，为这个新兴市场服务。Skymind创始人亚当•吉布森现在身在亚洲，他在谈到深度学习技术时说：“中国正在尽可能地锁定一切。”
显然，谷歌公司看到了这个巨大市场中的机会。施密特上周与该公司负责机器学习的几个关键人物一起访华也正是出于这个原因。多年前，谷歌从中国撤出，但是现在，它需要回来，并把人工智能看作可以利用的途径。
（编辑：沈洋 党超峰）
GOOGLE IS ALREADY LATE TO CHINA'S AI REVOLUTION
SITTING ON A stage in Wuzhen, China, a historic city up the river from Shanghai, Google chairman Eric Schmidt described what he called "the age of intelligence."
But he wasn't talking about human intelligence. He meant machine intelligence. He trumpeted the rise of deep neural networks and other techniques that allow machines to learn tasks largely on their own, either by finding patterns in vast amounts of data or through their own trial and error.
At Google, using a sweeping software tool called TensorFlow, engineers have built deep learning systems that can identify faces and objects in photos, recognize commands spoken into smartphones, and translate one language into another. Schmidt called this the biggest technological change of his lifetime.
Then he mentioned China's three largest internet companies: Baidu, Tencent, and Alibaba. All three, he said, could benefit from TensorFlow, which Google open sourced about 18 months ago, sharing it with the world at large. "All of them would be better off if they used TensorFlow," Schmidt said of the Chinese internet giants. He said the software could predict what people want to purchase, help target ads, and even decide who should a get line of credit. "They can use TensorFlow to study the patterns of their business. They can use this technology to serve their customers faster."
Delivered amidst the week-long Go match between Chinese grandmaster Ke Jie and AlphaGo, a seminal machine created by Google's DeepMind artificial intelligence lab, Schmidt's words were not hyperbole. Deep learning and related technologies are fundamentally changing the way Google works, and they will change so many other companies—even entire industries—over the next several years. The trouble is that Schmidt undersells how far these technologies have already spread beyond the walls of Google. The age of intelligence has moved ahead much farther than he admits—especially in China.
Schmidt's words accurately described the enormous power of modern neural networks. And they showed the enormity of Google's progress and ambition in this area. But if you read between the lines, they also showed the limits of the company's ambitions—namely: China. Though many in the West paint the deep learning revolution as a phenomenon driven by the big US internet companies, China is hardly far behind.
AI—Not Just American
Chinese companies like Baidu, Tencent, and Alibaba are already using these same technologies, as are US giants like Facebook, Microsoft, and Amazon. Google took an early lead, mainly because it bought up so much of the key talent. But many others have embraced deep learning in big ways, including the largest internet companies in China. "It's easy to fall into the old stereotype—the copy-to-China stereotype, that China is so far behind and they're just importing everything—but that's out of date," says Adam Coates, the American-born AI researcher who now oversees Baidu's Silicon Valley AI lab.
As far back as 2013, Baidu started an internal research lab it called The Institute of Deep Learning, showing its own extreme ambitions. Now it runs several other labs, including the 200-person outpost in Silicon Valley. All told, the company employs more than 1,800 researchers and engineers who work on AI, including driverless cars and other robotics as well as many online services. Deep learning technology is already driving everything from the Baidu search engine to the company's image and speech recognition services. More than 18 months ago, the Chinese giant publicly revealed it was using neural networks to help target online ads—one of the particular tasks Schmidt said TensorFlow could help them with.
Tencent recently opened a stateside AI lab of its own. And like Alibaba and Baidu, it's now a regular part of the international AI conference circuit that plays such an important role in the progress of AI research in academia and across the industry. (Beijing hosted the International Conference on Machine Learning in 2015.)
Meanwhile, these technologies are spreading beyond the big players and across the rest of the China. A San Francisco deep learning startup called Skymind recently created a subsidiary in mainland China to serve this burgeoning market. "China is latching on to everything it can," says Skymind founder Adam Gibson, who is now based in Asia, referring to deep learning technologies.
Opportunities and Costs
Clearly, Google sees the opportunities available across this enormous market—just as it sees opportunities for its AI technologies in so many other parts of the world. That's why Schmidt was in China last week alongside several of the key players in the company's push toward machine learning. These included Jeff Dean, the head of the Google Brain AI lab, and Jia Li, who helps oversees artificial intelligence across the company's increasingly important cloud computing services. Google withdrew its online services from China more than seven years ago, unhappy with government censorship laws and apparent state-sponsored hacking operations. But now it wants back in, and it sees AI as the available path. The Go match—a reprise of the historic match AlphaGo played in Korea last year—was an ideal starting point.
But although Google has taken a worldwide lead in machine learning, it's clearly a long way from really applying this expertise in China. Google's online services are still blocked in the country, and though the company collaborated with local authorities in organizing the event in Wuzhen last week, this collaboration has its limits. Two days before the event, state TV pulled out, and half-an-hour into the first Go game, all online broadcasts went dark. Media outlets covered the event with news stories but they avoided the name Google, apparently under instructions from the government.
The event still took place, but it seemed to betray Google's inability to win hearts and minds in the country. Even Americans were struck by the way Schmidt talked down to Baidu, Alibaba, and Tencent, when he should have done the opposite. "Some of the major Chinese companies are some of the most sophisticated deep learning and data companies in the world," says Skymind founder and CEO Chris Nicholson. "Google has misread China in the past, and I think that Eric Schmidt's speech is evidence it will continue to misread China and lose out on one of the biggest markets on earth."
Schmidt may have pushed TensorFlow for a reason. It's the sole means of using its new TPU chip, a processor specifically designed for running deep neural networks that will soon be available via Google's cloud computing services. In many ways, Google sees cloud computing, where it rents raw computing resources to businesses and coders over the internet, as the future of the company. That future would be much, much bigger if can get Chinese businesses on its cloud. But that reality is a long way off—at best.
Like the company's other online services, the Google cloud isn't available in China. And despite what Schmidt implied, Chinese companies like Baidu and Tencent are already starting to offer machine learning tools atop its own cloud computing services. It is indeed the age of intelligence—but the whole world already knows it.
