導語：Eye on A.I.是由紐約時報資深記者 Craig S. Smith 主持的一檔雙週部落格節目。每一期節目，Craig 都將與這一領域有影響力的人物進行交流，推進廣義環境中的機器智慧新發展，思考技術發展新蘊意。
機器之心為此係列對話的中文合作方。以下為此係列內容的第四篇，Craig Smith 與李開復先生展開的對話。
Hi, this is Craig Smith with a new podcast about artificial intelligence. I’m a former New York Times correspondent now focused on AI. I have been talking to the people who are making a difference in the space and am bringing the most interesting of those conversations to you. This week, I talk to Kaifu Lee, a thought leader on AI in China who just published the book, AI Superpowers: China, Silicon Valley, and the New World Order just came out. Kaifu, who did his PhD in speech recognition AI at Carnegie Mellon founded both Microsoft Research and Google in China. He now runs Sinovation Ventures, a venture capital fund in Beijing. We talked about the premise of the book, which is that China has already caught up with the US in the field of AI and is poised to surpass it. I hope you find Kaifu as interesting as I did.
大家好，我是 Craig Smith，這是一個有關人工智慧的新播客。我之前是《紐約時報》的記者，現在專注於 AI，我將與致力於該領域的人對話並呈現最有趣的內容。這周與我對話的是李開復先生，他是中國 AI領域的一位思想領袖，最近剛發表了新書《AI Superpowers: China, Silicon Valley, and the New World Order（人工智慧超級力量：中國、矽谷和新世界秩序）》。李開復先生，博士畢業於卡內基梅隆大學，研究方向為語音識別 AI。他曾創立了微軟研究院和谷歌在中國的分支機構。他現在北京經營一家風險投資公司“創新工場”。我們談到了這本書的前提，即中國已經在 AI領域趕上了美國，並終將超過美國。
CRAIG: Going through the book it looks like you're talking less about national competition than about national competency. Which are very different things because competition implies that one country will dominate another at the end of the day. But what you're talking about really is China developing an AI competency that's equal to or ahead of that of the United States. Can you talk a little bit about that?
Craig：通讀這本書，感覺你談到了更多有關國家競爭力的內容，而較少有關國家競爭的內容。國家競爭力和國家競爭是非常不同的，因為國家競爭意味著一個國家想要主宰另一個國家，而你實際上談到的是中國正在發展自己的 AI競爭力，以期望達到或超過美國的水平。你能談談這方面嗎？
KAIFU: I think the two are very correlated. If you have extremely strong competency you will become the leader in the world. So, China has a number of unique advantages, the greatest of which is the huge amount of data. And then the great engineers, companies, entrepreneurs, who are using it to find holes in its sometimes backward traditional economy. And when the economy's backwards you can have a late mover advantage and reinvent retail schools communications, health care, and so on.
李開復：我認為這兩者非常相關。如果你有極其強大的競爭力，你就將成為世界的領導者。所以，中國具有很多特有的優勢，其中最大的優勢是擁有巨量資料。而且還有很多出色的工程師、公司和企業家在使用這些資料來尋找其有時有些落後的傳統經濟中的漏洞。當傳統經濟有些落後時，你就能擁有一些後發優勢，然後重塑零售、教育、通訊、醫療等行業。
Also, I think the government has taken a very techno utilitarian approach which is really to let technologies to be tried before going to regulation. And not working out the kinks before getting the technology to launch. And these factors will propel China forward. While the U.S. does have much deeper research bench, China is rapidly catching up and developing a young cadre of very smart AI engineers who arguably matter more than having a small number of AI superstars because we're now in the age of implementation.
另外，我認為中國政府已經採納了一條非常技術實用主義的道路，也就是讓技術在得到法規管理之前先進行嘗試。而不是在技術釋出之前就先設定好條條框框。這些因素會推動中國向前發展。儘管美國確實有更深度的研究環境，但中國正在快速追趕並正在培養一個由非常聰明的年輕 AI工程師構成的核心群體，很多人認為這樣一個群體比擁有少量 AI超級明星更重要，因為我們現在正處於“實現”時代。
In the age of discovery the US brilliant researchers clearly have an edge. Geoff Hinton, Andrew Ng and so on. The research ruled. But now it's really more about landing the technology in a real business and making money with it. And for that the Chinese make up in AI companies is much more formidable, much more scalable, combining fearless hardworking tenacious entrepreneurs with hard working AI engineers - not writing so many papers but just getting things done, getting problems solved, improving efficiency, profits for banking, reducing costs for factories. It's happening everywhere around us. So, these are the conditions that make up an AI superpower in a very different way than, you know, when you think about national competition. It's more who can build more nuclear warheads, but here we have a very different set of competencies that makes China way ahead in some areas and still way behind in others. But the ones that really matter for the foreseeable future are the elements in which China is strong.
在“發現”時代，美國的傑出研究者顯然掌控了前沿——Geoff Hinton、吳恩達等等。他們的研究優勢是壓倒性的。但現在實際上更多的是將這項技術落地成真正的業務，並用它賺錢。而在這方面，由中國人組成的 AI公司要強大得多且更具可擴充套件性，更何況還有無所畏懼的勤奮頑強的企業家和盡職盡責的 AI工程師——他們不會寫那麼多的論文，但會把事情做成，把問題解決；他們能幫銀行提升效率和利潤，還能幫工廠降低成本。這樣的事情發生在我們周遭各個地方。所以，這就是構成一個 AI超級力量的條件，非常不同於我們對國家競爭的看法。國家競爭更多的是看誰能製造更多核彈頭，但這裡我們看到的是一組非常不同的競爭條件——這些條件會讓中國在某些領域領先，而在其它方面仍然可能更落後。但在可預見的未來裡，那些真正重要的條件正是中國的強項。
CRAIG: To date the developments in AI are largely confined to their respective markets. The Chinese are developing technology for implementation in China. The U.S. is developing new technology for implementation primarily in the English-speaking world. Or at least the American and European worlds. Can you say that China is ahead if its implementations are restricted to its own market. And one of the things that I've been waiting to see: When are these technological super companies in China going to succeed outside of China. And that's something we really haven't seen.
Craig：到目前為止，AI的發展主要侷限於它們各自的市場。中國人開發的技術是為了在中國的實現。美國開發的新技術的實現主要針對的是說英語的世界，或者說是美洲和歐洲。如果中國的實現都限於自己的市場，你能說中國領先嗎？而且我還一直在等著看：中國的科技巨頭何時才能在中國之外取得成功？這樣的事情還從未發生過。
KAIFU: I have a two-part answer to that but I really think it's not the right way to look at the problem. People think of China as one of the hundreds of markets so you only have one market. What good is that. But my answer is that China is larger and more important and more valuable than the rest of the world combined. And so yes, it's not the whole world. But it may be half the world. So why is it half the world? Well if we look at all the mobile payments that are gathered, which form the strongest basis for AI learning, China has more than the rest of the world combined. If you look at computer vision, gathering of images, face recognition and so on, China has more than the rest of the world combined.
李開復：對那個問題，我有一個包含兩部分的答案，但我實際上認為這並不是看待這個問題的正確方式。人們認為中國是數百個市場中的一個，所以那些公司僅有一個市場。所以那有什麼好的？但我的答案是中國市場比世界其它地方加起來更大更重要更有價值。確實如此，這並不是整個世界。但卻可能是半個世界。所以為什麼這是半個世界呢？如果我們看看所有的移動支付發生的位置，可以看到中國的佔比超過世界其它地方的總和，這為 AI學習構建了最強大的基礎。再看看計算機視覺、影像收集和人臉識別等等，中國也超過了世界其它地方的總和。
I think the evidence is that the Chinese computer vision companies are worth ten billion dollars. The American ones are worth hardly one billion. So I think to position it as China has only one of the markets and what about the rest of the world, is missing the very facts in front of us, which says China has so much more data and so many more ways of gathering data - and that includes a larger market and more advanced digital collection system, putting sensors and inputs from everything from retail to airports, gathering information from payment activity, this amount of data is phenomenal. And I would argue, if China companies were restricted to stay in China for the next 10 years the total capitalization of Chinese AI companies will still be larger than the rest of the world combined. So that's the first half of my answer.
我認為有證據表明中國的計算機視覺公司價值數百億美元。美國的計算機視覺公司價值幾乎達不到十億美元。所以我認為說中國只有一個市場而沒有世界的其它市場是忽視了我們眼前的事實，也就是中國有遠遠更多資料，而且還有遠遠更多的收集資料的方式——其中包括一個更大的市場和更先進的數字收集系統。中國將感測器和輸入端放進了從零售店到機場的各個地方，從支付活動中收集資訊，這樣的資料量很是驚人。而且我也相信，就算中國公司在未來十年中仍侷限在中國市場內，中國 AI公司的總資本量仍將超過世界其它地方的總和。這是我答案的上半部分。
The second half is that the Chinese companies are looking to go abroad, but they're going abroad in a very different way and arguably a smarter way than the Facebooks in Googles. History of tech colonialism is such that America dominated the world. So, Windows and Intel took over the world and had a 100 percent and demanded adoption whether their products were well localized or not. And China was one of the technically colonized countries in the sense of using PC hardware and software. However, in the age of mobile Internet that's not the case anymore. The American technologies are reaching less and less of the world. Chinese technology is actually reaching more and more of the world but not in the same way.
下半部分答案是中國公司正在積極出海，但它們出海的方式非常不同，可能也比 Facebook和谷歌等所採用的方式更聰明。在技術殖民主義的歷史中，一直是美國主宰世界。所以，Windows和英特爾幾乎掌控了全世界的計算機，它們的產品會得到 100%的採用，不管它們的產品本地化做得好不好。而且在 PC的硬體和軟體方面，中國也是一個被技術殖民的國家。但是，在移動網際網路時代，情況已然改變。美國技術觸及世界的範圍越來越小。中國技術實際上已經越來越多地走向世界，但方式卻不一樣。
You don't see anyone using DiDi in Indonesia. However, DiDi is very cleverly partnering with all the locals so as to form an alliance of the insurgents against the American hegemony. Uber is trying to dominate the world using one brand, one platform, one world. That's the typical American way. Windows, Microsoft, Intel and then going on to attempts by Yahoo, Google, Amazon, with less success but still decent success. But that method is not going to be good enough anymore because technologies now touch physical aspects of our world. Putting Uber in Brazil is not a trivial matter. There's government relations, there's usage patterns, there's taxi coalitions. So, it requires a local to be successful. So, the Chinese AI company approach is 'Let's partner with the locals.' So, Didi has partnered with locals in Southeast Asia, South America and is greatly expanding its footprint against Uber. And it doesn't own the local partners. It owns maybe 20 percent, 30 percent, maybe with Softbank, maybe by themselves. And is forming a very powerful alliance where the local companies now feel they have a chance at building products for their own country.
在印度尼西亞，你不會看到任何人使用滴滴。但是，滴滴非常聰明地與所有當地公司建立了合作關係，形成了一個針對美國霸權的反抗聯盟。Uber試圖使用一個品牌、一個平臺、一個世界來主導這個世界。這是典型的美國做法。Windows、微軟和英特爾都成功了，雅虎、谷歌和亞馬遜也一直在這樣做，雖然沒有那麼成功，但成績也很不錯。但這一方法再也不會那樣有效了，因為現在的技術已經觸及到了我們的物理世界。把 Uber投放到巴西不再簡單輕鬆。會有政府監管，會有使用模式，還有計程車聯盟的問題。所以，這需要一家本地公司才能取得成功。所以，這家中國 AI公司的方法是“讓我們與當地公司合作吧”。滴滴已經在東南亞和南美與當地公司建立了合作關係，針對 Uber極大地擴充套件著自己的足跡。而且滴滴並不擁有當地合作伙伴。它可能擁有 20%或 30%，也許和軟銀一起，也許只靠自己。它們正在構建一個非常強大的聯盟，當地公司現在覺得他們有機會為他們自己的公司開發產品了。
So, China has been through the technical colonialism. So, it's empathetic to other countries and develops ways to work with them to give them money, business, knowhow, experience and perhaps even AI technology and maybe sharing of data parameters at the end of the day. Tencent and Alibaba are among the largest investors in tech in the world. So, it's just the method is different. See the American companies really want one brand, one technology, one platform, own it all. But I think the days of that may be over.
中國經歷過技術殖民主義。所以，它對其它國家抱有同情，會發展與它們合作的方法，為它們帶來資金、業務、方法、經驗，甚至還可能共享自己的 AI技術以及資料引數。騰訊和阿里巴巴是全球科技領域最大的投資者之二。所以，中國科技公司只是方法不同。可以看到，美國公司非常想要單一品牌、單一技術、單一平臺，並擁有一切。但我認為那可能就要結束了。
CRAIG: We're talking about corporate AI not national or military. And increasingly these companies do not have a particular national identity. I mean, they may be based in one country or another. Google's a good example. It owns Deep Brain and Geoffrey Hinton works for Google in Canada. Is that happening with China as well? Is that what you're suggesting. That these Chinese giants are first of all private companies or at least quasi private companies and their influence or their profile is becoming increasingly multinational?
Craig：我們談的是企業 AI，而不是國家或軍用的 AI。而且這些公司漸漸地不再具有單一的國家身份，雖然它們的總部可能在某個特定國家。谷歌就是個很好的例子。該公司擁有 DeepBrain，Geoffrey Hinton 在加拿大為谷歌工作。中國也有這樣的情況嗎？你說的就是這個嗎？那些中國巨頭是私營公司或者準私營公司嗎，它們是否正在具備越來越大的國際影響力？
KAIFU: Clearly, Baidu, Tencent and Alibaba all have Silicon Valley offices in which they each employee hundreds if PhDs. So, there is certainly a desire to take talent from all over the world. They do have plans to go into other markets. So, yes, they want to become global companies in both senses of that.
李開復：很顯然，百度、騰訊和阿里巴巴全都有矽谷辦公室，它們各自都聘用了數百位博士生。所以，從全世界搶奪人才的需求肯定是存在的。它們確實也有進入其它國家的計劃。所以，是的，它們希望在這兩個意義上都成為全球性公司。
CRAIG: Again, in terms of the framework of your book, AI Superpowers, are the superpowers the companies or the superpowers the nation states.
Craig：回到你的書《AI Superpowers》，其中的超級力量是指公司還是國家？
KAIFU: The collection of companies in each country. Yeah, I was not making a case of a nationalism or military. I was not going into that. That's not my expertise. I have no visibility into either U.S. or China, NSA or you know People's Liberation Army efforts. So, I don't cover that.
李開復：每個國家的公司的集合。是的，我沒有提國家或軍事的案例。我當時也沒打算那樣做。我沒有那方面的專業知識。我沒法瞭解美國或中國的計劃，也不知道美國國家安全域性或中國人民解放軍在做什麼。所以我沒有談及那方面。
CRAIG: No certainly. But what I'm saying is that as long as it's not a government-owned effort, as long as it's within the sphere of private enterprise, increasingly they are not national efforts. They're multinational efforts. Geoff Hinton is a good example, I mean he's a Briton, I think he may now have Canadian citizenship, but he was educated in the United States and worked for a long time in the United States and is now living in Canada. You know that's not American AI, the things that he's developing. It's very international and even with the Chinese PhDs, they study in the U.S., they do research in the U.S., they go back to China. They work in China or they come back to the U.S. and work. It just seems like it's becoming very fluid. And it is going to be increasingly difficult to talk about national strategies other than at the level of education.
Craig：當然。但我的意思是，只要這不是政府在做，只要這還在私營企業的範圍內，它們漸漸地都會模糊國家的界線。這是跨國性的工作。Geoff Hinton就是個很好的例子。他是個英國人，我想他現在可能有加拿大國籍，但他是在美國接受教育的，並且曾為美國工作過很長時間，現在住在加拿大。你知道他開發的東西並不是美國 AI。這是非常國際化的，甚至有些中國人博士也是在美國學習的，然後在美國做研究，或回到了中國。他們也可能在中國工作之後又回到美國工作。看起來有很強的流動性。而且除了教育水平方面，談論國家戰略將越來越困難。
KAIFU: Yes I agree with all the points you made and I think that all these things you mention will expand. But at the same time, you know China as well as Canada have had fairly effective national policies that build up national infrastructure for investment, advancement, education, training, improved roads for autonomous testing, help with the VC funding of AI companies. So, each country is rightfully trying to create more tax paying AI companies that will bolster the country's competitiveness. So, I think that's not directly in conflict with the globalization effort you talk about.
李開復：是的，我認同你所有這些觀點，我認為你提到的這些還會繼續延展。但與此同時，你知道中國和加拿大都有相當高效的國家政策，能為投資、發展、教育、培訓等構建國家基礎設施，能為自動駕駛汽車測試改善道路，幫助 AI公司獲得風險投資。因此，每個國家都在努力創造更多會交稅的 AI公司，這能提升其所在國家的競爭力。所以，我認為這與你談到的全球化方面的事情並沒有直接衝突。
CRAIG: To me that is where the idea of national AI strategy has its greatest impact, is in the economy. So, it's not that China is competing with the U.S. to become some sort of a master of AI or that the U.S. is competing with China to dominate in AI. It's that the implementations and the basic research that's coming out of each country will have an impact on each country's economy and in the Internet age and with repositories like arxiv, the developments in research on one side of the world are disseminated at lightning speed all over the world. So, it's very difficult to have an edge in one country or another. So, what you're talking about really is the entrepreneurial ecosystem that drives unique implementations, not so much about developing algorithms or systems that are unique to one country or the other.
Craig：在我看來，國家 AI戰略思想影響最大的地方是在經濟方面。所以，中國與美國競爭並不是為了變成 AI的主人或美國與中國競爭是為了主宰 AI。而是說各個國家的 AI實現和基礎研究將會影響每個國家的經濟狀況。在網際網路時代，有了 arXiv這樣的儲存庫，在世界一端的研究進展能以閃電般的速度傳播到整個世界。所以一個或另一個國家很難佔據前沿。你說的實際上是推動特有實現的企業生態系統，而不是開發對某個國家特定的演算法或系統。
KAIFU: Yes, I think the academic parts of the AI community is very naturally transparent, helpful, honest, use the common data set with the experiments being replicable. So, it's quite different from other sciences where it's not always easy to replicate say a clinical trial. Because of AI's digital nature allows it to be validated, tested and therefore people are basically standing on the shoulders of giants who are eagerly publishing in order to get academic credit but not extending any sort of, you know, national edge, which may or may not be wanted by the government. But if it did want it, it's very hard to actually consummate that.
李開復：是的，我認為 AI社群的學術界部分自然是非常透明的、互助的、誠實的，他們會使用常用的資料集來進行實驗，使得實驗可復現。這一點不同於其它某些科學，比如臨床試驗的成果並不總是容易復現。因為 AI的本質是數字的，使得它可以輕鬆得到驗證、測試，因此人們基本上都是站在巨人的肩膀上。他們都急於發表自己的研究成果，以提升自己的學術影響力，而不會延展成任何形式的國家優勢。有的政府希望有這樣的優勢，有的則不然。但如果政府確實想要這個優勢，實際上卻會變得很難實現它。
Having said that, there are some possibilities where the U.S. or any other country could take significant leadership. For example, you know, a lot of the world's best AI people are in Google. And if they make a breakthrough and choose not to publish, well they as a company will have a leadership position to build products others may not be able to replicate. And that would be indirectly a national advantage, should that happen.
話雖如此，美國或任何其它國家都有可能取得顯著的領導地位。比如你也知道，谷歌擁有大量世界頂尖的 AI人才。如果他們做出了一項重大突破而選擇不發表出來，那麼他們作為一家公司就將佔據領導地位，進而開發出其他人可能無法複製的產品。如果發生這種事，也會是一個間接的國家優勢。
CRAIG: Again, I'm not sure whether it's a national advantage or a corporate advantage. In your book you talk about the risk of hermetically sealed corporate environments. Already just going to conferences I can see there is some grumbling about papers being presented, being awarded prizes, that do not give enough of the code to be reproducible.
Craig：同樣，我不確定這是國家優勢還是企業優勢。你在書中談到封閉的企業環境具有風險。現在的學術會議上，我也看到有些人在抱怨人們提交和獲獎的論文中很多都沒有提供足夠的程式碼來複現。
KAIFU: So even when the original publisher doesn't want to give away source code other people can build it. Because machine learning code is not very large or complex, the replication once the algorithm is known is not an extremely time intensive kind of thing.
李開復：即使原始作者不想提供原始碼，其他人也能構建。因為機器學習程式碼規模並不非常大和複雜，只要知道了演算法，復現它其實並不會耗費太多時間。
CRAIG: The three elements of successful AI are the code, the algorithms, the data, but also the computing power. The computing power in the United States or in the West is really controlled by large corporate interests. Is that the same in China or is there a government aspect to that that helps individual companies.
Craig：成功的AI有三個要素：程式碼和演算法、資料、算力。美國和西方國家的算力實際上是受大型企業的利益控制的。中國也是如此嗎？政府方面會幫助各個公司嗎？
KAIFU: There is no government subsidy for computing per se, but obviously if you receive some subsidy you can use it on computing if you want. But for a lot of the common big data types of AI, you really don't need that much computing. What we generally talk about are the most complex forms of computing.
李開復：政府並不會補貼計算本身，但很顯然，如果你收到了某些補貼，你也可以將其用在計算上。但對於很多常見的大資料型別的 AI而言，其實並不需要那麼多的計算。我們一般談到的是最複雜形式的計算。
If you have a powerful single server with a couple of GPUs that will take care of most computer loads for anything up to video computer vision types of applications.
如果你有一個強大的單個伺服器，再加幾塊 GPU，就能應對大部分計算機負載了，包括影片型別的計算機視覺應用。
CRAIG: You talk about data, certainly that's one place China has a clear advantage. Partly, as you note because of the different privacy environments, but also because Chinese society is so interconnected that there's a lot of data being collected all the time. Is that something, again, that you think is giving China an advantage globally? Or is that only in its own market? Or is that allowing them to develop implementations that they can take outside.
Craig：你談到了資料，很顯然中國在這方面具有顯著優勢。部分原因是中國有不同的隱私環境，同時也因為中國社會有很多互相關聯，總是會有大量資料可供收集。你認為這能為中國提供全球性的優勢嗎？還是隻有在自身市場的優勢？還是說他們基於這些資料開發的實現能夠推廣到中國之外？
KAIFU: China's approach going globally is largely through partnerships. So, for example DiDi's partner in Indonesia, Singapore or India will apply local privacy data restrictions and policies.
李開復：中國走向全球的方法很大程度上是透過合作。比如，滴滴在印度尼西亞、新加坡或印度的合作伙伴會應用當地的隱私資料限制和政策。
So it's not up to Chinese companies to decide. Just like when U.S. companies go to Europe they have to follow GDPR now. So is it very much controlled at each country and given Chinese AI companies approach to going abroad, it is not doing so by itself, partnering locally, it will get taken care of by the local partners.
所以這不是由中國的公司決定的。就像現在美國公司進入歐洲都必須遵守 GDPR一樣。因此這方面基本上是由各個國家控制的，鑑於中國 AI公司出海的方法，它們不會自己去做這些事，而是會與當地公司合作，這些事情也會由當地合作伙伴處理。
CRAIG: I meant more that in developing implementations, there's tremendous data available and it's much easier to get your hands on in China than it is in the U.S. For example in medical implementations, it's a problem because medical data is so tied up in privacy laws. But in China I've been told that there's a lot more opportunity because a lot of the medical data is more readily available to developers.
Craig：在開發實現時，在中國會有巨量資料可用，獲取這些資料也比在美國更容易。比如在醫療實現方面，醫療資料和隱私法律關係密切，因此會存在問題。但在中國，有人告訴我機會要大得多，因為很多醫療資料都已經準備好給開發者使用了。
KAIFU: That is a possibility. The issue is also it has to be quality data. So, because the quality of healthcare is significantly lower in China compared to the U.S., China's data quality is not at the U.S. level. So, we'll have to see how this plays out with potentially much larger group of lower quality data. Whether that's good enough to build systems or not, I think that remains to be seen. But the theoretical relative openness to data sharing is certainly an advantage for Chinese AI companies.
李開復：有這個可能性。問題是資料必須要高質量。因為相比於美國，中國的醫療質量顯著更差，因此中國的資料質量達不到美國的水平。所以，我們必須要先看看使用可能遠遠更多的低質量資料能做成什麼。其質量是否足以用於構建系統？我認為這一點還有待觀察。但理論上對資料共享相對開放的態度對中國 AI公司而言肯定也是一個優勢。
We should also clarify that it's not like Chinese users don't care about privacy. It's just that there is a greater degree of openness to using some data if there is a clear benefit to the user, such as better treatment, safety, or convenience or monetary savings. There is a greater willingness to do that. Companies generally do have to disclose to users that they're collecting data. More users may say Okay. And also, the Chinese laws prohibiting sale or transfer of private data to other companies. So, taking to Facebook-Cambridge Analytica example, people would actually potentially be put in jail for doing what they did. So, it's not like the laws are loose and people are copying data everywhere. I think people get that impression.
我們應該澄清，並不是說中國使用者並不在乎隱私。只是說如果使用某些資料對使用者而言有明顯的好處，比如更好的治療、安全、便利或省錢，他們對此的態度就會更加開放。中國使用者分享資料的意願更高。一般來說，公司都必須向使用者說明它們正在收集資料。大部分使用者可能都會“同意”。另外，中國法律禁止將私人資料銷售或轉移給其它公司。所以，如果中國出現類似 Facebook和 Cambridge Analytica 那種事，相關責任人實際上是有可能進監獄的。因此，並不是說法律寬鬆，人們到處複製資料。我認為人們有這樣的看法。
CRAIG: When you talk about superpowers, you're talking about China as a nation or Chinese companies as a superpower. But there is an economic impact to the development and implementation of AI. Do you think that that impact or that effect on the Chinese economy is going to help China close the economic gap with the United States.
Craig：當你談到超級力量時，你談到了中國或中國的公司是一大超級力量。但經濟也會影響 AI的開發和實現。你認為 AI對中國經濟的影響和效果能幫助中國拉近與美國的經濟差距嗎？
KAIFU: Well given both countries are superpowers, it's hard to predict how the numbers will go. I think it's probably safer to say that U.S. and China will increase their gap with the rest of the world.
李開復：鑑於這兩個國家都是超級力量，所以很難預測資料的走向。我認為也許可以合理地說美國和中國會拉大與世界其它地方的差距。
CRAIG: The other advantage that the U.S. has is in being an anglophone nation and so much of education in science and technology is in English. But in terms of being a power globally, is that a restriction do you think?
Craig：美國的另一個優勢是美國是一個英語國家，而很多科學和技術領域的教育都使用英語。就全球力量而言，你認為這會帶來影響嗎？
KAIFU: I do think there is a big advantage for the U.S. What you describe in the language is a part of that. But I think, really, it's the U.S. research and university system that draws the world's smartest people to study in the U.S., many of whom stay in the U.S. afterwards. And that ability to really bring in the world's smartest people helps the US, despite its much smaller population to China, to actually end up with a larger technology elite class than China. And that has been the U.S. advantage going back decades, if not centuries. And that advantage will continue for the US.
李開復：我確實認為這對美國而言是一個巨大的優勢。你描述的語言方面只是其中一部分。但我認為，實際上是美國的科研和大學系統吸引了全世界最聰明的人去美國求學，之後也有很多人就留在了美國。正是這種匯聚全世界最聰明人才的能力幫助了美國，儘管美國的人口遠少於中國，但其實際上擁有比中國更大規模的技術精英階層。過去幾十年甚至數世紀以來，這一直都是美國的優勢。而且美國的這一優勢還會持續。
CRAIG: Is there a way for China to balance that, because you're talking about, you know, this age of implementation. But that's very different than, as you called it, the deep bench research that is happening in the United States. Will that eventually happen in China? Is there a move toward building that sort of capability?
Craig：中國有辦法平衡這個問題嗎？因為你也談到了，現在是實現時代。但這非常不同於美國的那種深度基礎性研究。這樣的研究最終會在中國出現嗎？是否已有構建這種能力的舉措？
KAIFU: The Chinese central government would love to dramatically improve universities and research and in fact they have improved a lot over the last 20 to 30 years.
李開復：中國中央政府希望能極大提升大學水平和科研能力，事實上過去 20到 30年裡已經提升了很多。
But it takes maybe a century for any country to elevate its universities to be best in the world. It took America that long. So, this isn't something that can be quick-fixed. We see small efforts, such as allowing universities to pay more to bring in really smart international talent in AI and setting up research institutes and things like that. But these are all just Band-Aids not the ultimate solution. The ultimate solution is, you have to make teaching and research a very respected and well-paid job. And also, you have to divert people from going to Alibaba, Tencent and startups and stay at universities and you have to make that job career interesting and pay competitive. And then there's also, on top of that, the problem of attracting global students to study, whether that would happen some day or not. So, I just think it's 50 years of slow progress kind of thing because you just don't see any country elevate its education system and research capacity that fast.
但對任何國家來說，要讓自己的大學成為世界頂級大學都可能要花費一個世紀的時間。美國就用了那麼久。所以，這並不是能一蹴而就的事情。我們看到了一些較小的努力，比如允許大學支付更多錢來引進 AI領域的真正聰明的國際人才，以及設立研究院等等。但這都只是“創口貼”，而不是最終解決方案。最終解決方案是必須讓教育和研究成為一個受人尊敬和高薪的工作。另外，也必須讓人們不被阿里巴巴、騰訊和創業公司挖走，而是讓他們呆在大學裡；你必須讓他們對這些工作有興趣，並且支付有競爭力的薪資。然後，在此基礎上，還要吸引全球的學生前來學習。這未來某天可能會發生，也可能不會。我只是認為這是一個需要 50年緩慢發展的事情，因為我們看到沒有任何國家能快速提升其教育系統和科研能力。
CRAIG: When you talk about China catching up or surpassing the U.S., you're talking about implementation. One of the reasons China has been able to build up corporate entities that now are strong on their own is because they were operating in a closed market. I mean that may be less important now than it was but certainly Baidu - you know this better than anybody - would probably not have been able to compete with Google had Google been able to operate in an unrestricted way in China. Tencent may not have developed WeChat had Facebook or Twitter been able to operate in an unrestricted way in China. Do you think that sort of national protection is still important? And do you see that changing at all?
Craig：當你談到中國趕超美國時，你說的是實現方面。中國能夠自己建立當前的強大企業實體的一個原因是它們在一個封閉的市場中運作。也許這個問題現在已經沒有那麼重要 了，但過去確實很重要，比如很顯然，你實際上知道得比任何人都清楚，如果谷歌能夠不受限制地在中國運營，百度很可能無法與谷歌競爭。如果 Facebook或 Twitter 能在中國不受限制的運營，騰訊也可能無法開發出微信。你認為那種形式的國家保護仍然很重要嗎？你認為這會改變嗎？
KAIFU: I think at this point and probably for the last five or 10 years it's really a non-issue. That is, China has developed into a parallel universe as I described in my book.
李開復：我認為目前，或許加上之前五年或十年時間，這實際上並不是一個問題。正如我在我的書中描述的那樣，中國已經發展成了一個平行宇宙。
So take a U.S. company and say, let's have you do a China version completely unencumbered. They will almost certainly fail. Because the entire building blocks are different. The users are different. Their habits are different. And they're working against incumbents that have massive brand, technology, user loyalty as well as local knowledge and the huge amount of data that it takes to build AI and then the large data gives the local companies better AI and better products. And all of which, really, I think make it very difficult for a U.S. company to come in at this point. I would also add the reverse is also true because in a parallel universe it's going to be just as hard for a Chinese company to do something in the US as well.
所以假設有一家美國公司，我們讓它完全不受阻礙地做一箇中國版本。他們幾乎肯定會失敗。因為整個建構模組都不一樣。使用者不一樣。他們的習慣不一樣。而且要與那些有大品牌、技術、使用者忠誠度以及本地知識和巨量資料的本地巨頭競爭，這些巨頭可以使用它們的資料來構建 AI，而大資料又會給這些本土公司提供更好的 AI和更好的產品。綜合這些因素，我認為美國公司現在已經很難進入中國了。我覺得反過來也是一樣，因為在平行宇宙裡，中國公司進入美國也會一樣困難.