風蕭蕭_Frank
以文會友
美國為何會輸掉與中國的科技戰
題目這句話，並不是有理哥盲目樂觀，而是來自7月23日美國克萊爾蒙特研究所（Claremont Institute）高級研究員古德曼（David P Goldman），在美國《國家利益》雜誌（National Interest）網站撰寫的一篇文章，題目是：《美國正在輸掉與中國的科技戰，為什麽》。
古德曼認為，美國現在想要通過封鎖和限製措施，在科技戰中壓製中國，已經太晚了，美國需要真正有助於第四次工業革命的產業政策，需要在提升自身研發和生產能力上投入。看來，除了那些狂熱的反華政客，美國還是有真知灼見的專家仍然保持清醒頭腦！古德曼提及的中美科技戰，毋庸置疑，就發生在眼前。從5G到芯片再到人工智能，應當說，美國已經在科技領域對中國發動全手段封鎖和限製措施，可謂無所不用其極。明爭暗鬥：科技戰早已拉開帷幕從奧巴馬第二個任期開始，美國政府打壓、圍堵中國科技發展的政策圖謀就已經醞釀形成，並在特朗普任期得到強化，全麵打壓中國華為。拜登上台後繼續沿襲這一立場，對中國“芯片”、半導體進行全麵“掃蕩”。
2022年8月9日，美國總統拜登簽署《2022年芯片和科學法案》（以下簡稱《芯片法案》），其中規定，禁止獲得聯邦資金的公司在中國大幅增產先進製程芯片，期限為10年。2022年10月7日，美國商務部出台“對中國實施先進計算和半導體製造的出口管製”新規，進一步禁止將使用美國設備製造的先進芯片銷售給中國。
近日，“美國之陰”、“彭博社”等報道稱，拜登計劃在下周簽署行政命令，限製美國對中國在半導體和人工智能(AI)等關鍵技術方麵的投資，禁止英偉達和其他芯片製造商在未獲得許可證的情況下，向中國和其他關注國家的客戶出口芯片。這是米粒國在打壓中國“芯”的最新罪證。當然，除了美國窮盡招數打擊中國科技，其他盟友也不閑著，不管是自願的還是被迫的，紛紛上陣，助老大哥一臂之力。2022年，美國、韓國、日本等組成“芯片四方聯盟”，以牽製中國，在全球供應鏈中對華形成包圍圈。今年1月，在老美的主導下，美、日、荷達成協議，將共同限製阿斯麥、東京電子、尼康等企業向中國出口先進芯片製造機器。
今年3月，日本政府宣布對23種半導體製造設備限製出口，新規定將於7月23日正式生效，限製包括中國在內的160個國家。今年6月，荷蘭政府宣布針對先進半導體設備出口的新規，要求該國生產先進芯片製造設備的公司在出口先進光刻機時需要申請許可證，新規將於9月1日正式生效。現在，美國糾結一幫小弟，對中國的國產芯片業進行全方位圍堵。中國“芯”路麵臨的局勢將從原來的老美單邊阻攔變為多邊圍堵，真可謂是“黑雲壓城城欲摧”。這場科技戰，怎麽贏？
四處漏風：美戰略失策必然付諸東流越是花裏胡哨的招數，越是沒有卵用。西方有句話，叫條條大路通羅馬，這也完美地體現到中美科技戰中。現在，美國專注在先進芯片上打擊中國，但美國忽略的一個事實是，市場需求最大、最有盈利空間的，其實是傳統芯片，所以當美國集中打壓中國先進芯片的發展時，中國看清市場需求，在發展先進芯片的同時，更專注於傳統芯片的發展。美國彭博社（Bloomberg）7月31日曾發布報道稱，盡管美國出台各種政策，減緩了中國先進芯片製造能力的進步，但基本沒有影響中國使用14納米以上技術的能力。這使得中國企業建造新廠的速度比世界其他地方都快。根據國際半導體產業協會（SEMI）的預測，到2026年，中國將建造26座使用200毫米和300毫米晶圓的工廠，相比之下，美國屆時隻有16家晶圓廠。從數據上看，2018年之前，中國的芯片自給率僅為5%；2022年快速增長到17%左右；2023年，中國的芯片自給率有望提高到25%。中國能自主生產的芯片主要由傳統芯片組成，這意味著中國不僅可以有效反製美國芯片戰，美國對華出口的傳統芯片市場也在急劇縮小，對美國造成打擊。
可能有人會問，先進芯片搞不出來，整一堆傳統芯片有啥用，不還是落後？傳統芯片並不是毫無價值。古德曼也提到，美國決策者沒搞懂芯片與生產之間的關係，以為最先進的芯片才是有用的，但實際上傳統芯片單獨或並行工作，可處理大多數商業化人工智能業務。他還稱，中國無法進口7納米以下芯片及其製造設備，但可以用更昂貴的工藝自己製造7納米芯片，或者通過將舊芯片堆疊接近最快芯片的性能，或者通過巧妙的係統架構臨時組裝舊芯片以接近新芯片性能。簡單說就是，先進的咱沒有，那我把傳統的好好利用一下，也能賽過先進芯片。古德曼舉一例來說明，目前中芯國際可以生產7納米芯片，雖然成本高、效率低，但肯定能滿足中國軍方對7納米芯片的需求，因為現有的軍事係統絕大多數使用傳統芯片，這類需求本就很小。這樣看，用好傳統芯片，在當前客觀條件下，是十分必要的。除了中國自身在努力破局，美國那邊，願意投入到對華科技戰的企業也不多，有多個美國內半導體巨頭不聽白宮“招呼”，甚至出現“逼宮”行為。
去年，中國芯片進口額大幅降低，相比前年減少了470億美元。這下，美國的半導體巨頭公司坐不住了，要知道，英特爾、高通和英偉達等企業，每年超過20%的營收來自中國市場。來看看業績，今年一季度，英特爾公司淨虧損達28億美元，業績同比下跌134%；AMD 2023年一季度淨虧損達1.39億美元，較上年同期下滑118%；美光科技公司在2023財年第二季度虧損達23.1億美元，為20年來最大虧損季。這與中國市場也存在一定關係。現在，為了利益，英特爾、高通和英偉達嚐試繞過白宮禁令，謀求與中國合作。英偉達公司調整其AI芯片規格，確保在符合白宮限製要求的情況下，繼續向中國出口，其還為中國市場量身打造名為A800的AI芯片版本，以取代被限製出口的 A100，二者大部分關鍵技術規格都是相同的，唯一的差別是傳輸速度。同時，英特爾公司還準備在深圳建立新的芯片創新中心，以加深與中國的聯係。而另一家半導體公司AMD，也在考慮效仿英偉達的做法。
或許，這就是西方版的“上有政策下有對策”吧。不僅如此，7月17日，英特爾、高通和英偉達三家公司的高管，還專程前往華盛頓“逼宮”，遊說了包括布林肯、雷蒙多、布雷納德和沙利文在內的一眾政府高層，希望能阻止拜登政府擴大對中國出售芯片和半導體製造設備的限製。同日，美國半導體行業協會（SIA）發布聲明，呼籲白宮要避免進一步升級對華半導體出口限製，稱這可能會削弱美國半導體行業的競爭力，破壞供應鏈，損害政府在美國國內芯片製造領域的大量新增投資。
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古德曼在文章中，也表達了這一觀點，即美國對中國技術出口的限製，反而減少了美國公司的收入並危及其研發預算。大洋彼岸，美國陣營已然軍心渙散，各有打算，這仗，還怎麽打？前車之鑒：華為就是中美科技戰最好縮影古德曼以華為為例，解釋為何對華采取科技限製措施會失敗。2020年，特朗普政府禁止向華為銷售美國高端半導體後，西方媒體預測中國5G建設將陷入停滯，但結果恰恰相反，中國5G基站數量在2021年翻了一番，達到143萬個，到2022年增至231萬個，而全球總數為300萬個。華為用28納米而非遭美國封鎖的7納米芯片建造5G基站，其能耗高於最佳水平，但係統正常運行沒有問題。這也印證了前文我們講到，傳統芯片具有替代先進芯片的重要作用。由於無法獲得更新的芯片，華為手機業務一度大幅萎縮，但如今，華為可以設計自己的高端芯片並在中國製造。最新報告顯示，華為將在2023年下半年重新進入5G手機市場。
反觀美國，對華為的打壓，並沒有幫助美國發展5G。在美國等西方國家，5G一直被作為一項消費技術看待，美國5G網絡的下載速度隻有中國的一半，某些美國5G網絡的延遲時間比4G網絡還長，這使得它們對於自動駕駛汽車等應用的用處有限。這也充分說明，打壓別人，並不能幫助自己進步。最後，還是談談幾點看法吧。古德曼這篇文章，雖然預言美國對華科技戰注定失敗，但我們仍不可掉以輕心、盲目樂觀，以為敲鑼打鼓就能取得最終的勝利。中國之所以能夠以驚人速度實現科技發展、經濟增長和社會進步，從本質上來看，是我們擁有雄厚的科研能力和人才儲備，有全球門類最健全的製造業產業鏈，有製度優勢，社會主義市場經濟體製建設進入更成熟階段。而美國失敗的原因，是對實力衰落的現實選擇視而不見、聽而不聞，不能正視這是價值規律作用下市場選擇的必然結果，注定了美國必將被市場和價值規律所拋棄。未來，美國還會出更多四麵漏風的招數，我們應當做的，就是正視困難，保持戰略定力，充分利用市場、價值規律的力量，擊破美西方的“限製牢籠”。正如比爾·蓋茨在評價美國芯片禁令時所說，這隻會迫使中國花時間和金錢來製造自己的芯片，美國永遠無法阻止中國擁有強大的芯片。對於美國想將中國阻止在“第四次工業革命”大門之外企圖，有理哥免費送老美四個字：癡心妄想！
Why America Is Losing the Tech War with China
https://nationalinterest.org/blog/techland/why-america-losing-tech-war-china-206664
It is simply too late to try to suppress China. The United States must either spend seriously on research and development, along with industrial policy, or it will lose the race for twenty-first-century technological supremacy.
Western media, for the most part, has ignored a remarkable array of Chinese pilot products in industrial automation, executed primarily by Huawei, the world’s largest maker of telecommunications infrastructure and the target of a global suppression campaign by the United States. Fully automated factories, mines, ports, and warehouses already are in operation, and the first commercial autonomous taxi service is starting up in Beijing. Huawei officials say the company has 10,000 contracts for private 5G networks in China, including 6,000 in factories. Huawei’s cloud division has just launched a software platform designed to help Chinese businesses build proprietary AI systems using their own data.
There’s no indication that the Biden administration’s restrictions on high-end chips and the software and machines that make them have slowed China’s drive for dominance in the so-called Fourth Industrial Revolution—the application of AI to manufacturing, mining, farming, and logistics. Although the fog of tech war makes it hard to evaluate China’s progress with precision, available information points to surprisingly rapid progress in China’s efforts to work around technology restrictions.
The Three Potential Outcomes
China’s single-minded goal is to lead the next wave of industrial technology. Former World Bank Chief Economist Justin Yifu Lin, now a professor at Peking University and a councilor of China’s State Council, wrote in a 2021 book:
China’s 5G technology has become the world leader in the new industrial revolution. In the past few years, the US has repeated its old tricks and suppressed Chinese companies with groundless accusations, using all of its national resources. If the US succeeds in suppressing China by means of a blockade in the new industrial revolution, China will not be able to achieve its second centennial goal. How can China break through the US blockade? It can only do this by working hard to lead the new industrial revolution.
China is leading in the application of AI and high-speed broadband to business productivity. This can have one of three outcomes:
1. The United States and its allies make a concerted effort to leapfrog China and reclaim technological leadership in industry;
2. America and Europe adopt Chinese industrial technology and become followers, as China was a follower of developed markets a generation ago;
3. America continues to lose market share in industry and increases its import dependency, following the United Kingdom’s path of industrial decline.
The first option would require an industrial policy of some kind. America has turned towards such through the CHIPS Act, which has motivated $200 billion in projected investment in semiconductor production, according to the Semiconductor Industry Association. How effective the research and development (R&D) component of the CHIPS Act will be remains to be seen. Whatever the merits and flaws of the legislation, building chip fabs in the United States is justifiable on national security grounds but does not necessarily contribute to the productivity of other industries. On the contrary: the same quality (and even better) chips can be imported at a lower cost from Taiwan and South Korea; TSMC reportedly will sell chips made in the United States at a price 30 percent higher than the same product made in Taiwan. And beyond chips, the United States has not begun to consider a broader industrial policy, let alone begin to put such a policy into place.
To some extent, the second option—adopting Chinese technology—already is taking hold in increments. As noted below, only American companies that already have large-scale manufacturing operations in China have adopted AI/5G applications, entirely in the auto and related sectors.
The third alternative, continued deindustrialization, is unacceptable.
China’s Chip Dominance and the Failure of U.S. Tech Controls
Western analysts have overestimated the impact of technology controls on China, and underestimated China’s ability to work around them. There is a great deal of confusion about the importance of the latest generation of computer chips, whose narrow gate width allows more transistors to be packed into a single chip. The newest iPhones run on chips with 13 billion transistors; for reference, the computer that took the Apollo capsule to the moon in 1969 had about 64,000. The faster speed and energy efficiency of the newest chips are indispensable for 5G handsets. The graphics processing units (GPUs) produced by Nvidia and AMD make tractable the enormous datasets required for large language models (LLMs), like ChatGPT. But older chips, alone or working in parallel, can handle most business AI applications. More important than raw chip speed is the availability of the right data, the ability to transmit it quickly and conveniently, and the overall system architecture.
After the Trump administration banned sales of high-end U.S. semiconductors to Huawei in 2020, Western media predicted that China’s 5G rollout would grind to a halt. The Nikkei Asian Review wrote, for example: “Huawei Technologies and ZTE, China’s two largest telecoms equipment providers, have slowed down their 5G base station installation in the country, the Nikkei Asian Review has learned, a sign that Washington’s escalating efforts to curb Beijing's tech ambitions are having an effect.”
On the contrary: the number of 5G base stations in China doubled in 2021 to 1.43 million, and rose to 2.31 million in 2022, out of a world total of 3 million. Huawei simply built the 5G base stations with mature chips (with a 28-nanometer gate width rather than the 7-nanometer chips banned by Washington). Energy consumption was higher than optimal, but the system worked. Without access to the newer chips, Huawei’s handset business, the world’s largest in the second quarter of 2020, shrank drastically, because 5G handsets need powerful, energy-efficient processors.
Now it appears that Huawei can design its own high-end chips and manufacture them in China. Chinese research firms report that Huawei will reenter the 5G handset market in the second half of 2023. Reuters reported on July 12 that, “Huawei should be able to procure 5G chips domestically using its own advances in semiconductor design tools along with chipmaking from Semiconductor Manufacturing International Co (SMIC), three third-party technology research firms covering China’s smartphone sector told Reuters.” Caixin Global Daily reported in March that Huawei had co-developed Electronic Design Automation software with local firms for older 14-nanometer chips. It isn't clear whether SMIC can make enough 7-nanometer chips to meet Huawei's requirements, or whether the reported new 5G chips use another technology, for example, “stacking” two 14-nanometer chips in a “chiplet” to achieve 7-nanometer performance.
Consumer technology like handsets, though, is a subplot. The decisive issue is business productivity. Huawei and other Chinese companies now offer cloud-based AI services along with training and consulting to propagate the new technology to thousands of firms.
Huawei Cloud CEO Zhang Pingan July 7 rolled out a business-centered AI system before the 6th World Artificial Intelligence Conference in Shanghai, with a dismissive nod to ChatGPT: “The Pangu model does not compose poetry, nor does it have time to compose poetry, because its job is to go deep into all walks of life, and help AI add value to all walks of life.” Unlike OpenAI’s LLM, Huawei’s entry will train AI systems for customers in manufacturing, pharmaceutical R&D, mining, railways, finance, and other industries, Zhang said. The platform is powered by Huawei’s own Kunpeng and Ascend AI accelerator chips. Like the American LLMs, Pangu writes computer code, according to Huawei. But “it was designed for industry, and will be dedicated to industry,” Zhang added.
Most of these are embryonic, but with the Pangu system, Huawei Cloud offers its customers “large-scale industry development kits. Through secondary training on customer-owned data, customers can have their own exclusive industry large models,” the company said.
Zhang Pingan added that Huawei has built an AI cloud platform based on its own Kunpeng and Ascend processors, supporting a suite of AI software. Although “Nvidia’s V100 and A100 GPUs remain the most popular GPUs for training Chinese large-scale models,” a recent study notes, “Huawei used its own Ascend 910 processors” to train the Pangu model. Second, China appears able to produce proprietary AI chips like Ascend, although U.S. sanctions continue to prevent it from fabricating its Kirin smartphone chipset in Taiwan. Chinese chipmakers are keeping their cards close to their vests about fabrication capability.
The overriding issue is that industrial systems rarely require the complexity and computing power that ChatGPT applies to composing school essays and Valentine’s Day poems. China can’t import the fastest and most efficient chips with gateways of 7 nanometers or less, let alone the equipment to manufacture them. But it can make 7-nanometer chips with a costlier process, or approximate the performance of the fastest chip by stacking older chips into so-called chiplets, or jerry-rig older chips to approximate the performance of newer ones through clever system architecture.
Think of the railroad in the nineteenth century, which made it profitable to grow large crops far from water transport. This unleashed ripple effects that made the U.S. economy the world’s largest. Whether the train traveled at 40 or 80 miles an hour made a small difference to its impact on the broader economy—what mattered is that the distance could be crossed. The combination of AI and high-speed broadband creates a data highway that will transform the way most businesses run.
China Is Pushing Ahead on Tech, and It Shows
The United States and China approach AI differently. The trillion-dollar valuations of the great American technology companies mainly come from consumer entertainment. China, as Huawei’s Zhang said, has no time for poetry. Rather than guess when the machines will become sentient or when AI will replace human beings, China has focused on the automation of drudge work: inspecting parts on a factory conveyor belt, checking the bins near the coal face for foreign objects, detecting anomalies in machines, picking containers out of ships and placing them on autonomous trucks, and so forth.
China’s plan to assert leadership in the Fourth Industrial Revolution—the application of AI to production, logistics, and services—appears to be on track.
Except for large manufacturers who already maintain large-scale operations in China, American manufacturers have shown little commitment to Fourth Industrial Revolution technology. To my knowledge, the only U.S. manufacturing firms that have installed private 5G networks to support factory automation are General Motors (which made 2.3 million cars in China in 2022), Ford (which made 500,000 cars in China in 2022), and John Deere (which rolled its 70,000th Chinese-made tractor in February). These firms have joint ventures with Chinese manufacturers and can be considered auxiliaries of Chinese industry.
The trouble is that what is left of American manufacturing after the great decline of the 2000s often does not have the scale to realize the benefits of AI applications. The installation of private 5G networks does not coincide completely with AI applications; wifi and fiber optic cables can transmit information just as well in certain factory environments. But 5G has obvious advantages over cable-based communications in environments with fast-moving heavy machinery, especially in robot-intensive manufacturing, mines, ports, and warehouses.
According to a count by the European 5G Observatory, about sixty factories, ports, and airports have built private 5G networks, prominently including automakers like Volkswagen, Porsche, Saab, and Toyota. Again, most of the manufacturing and transport firms applying this Industry 4.0 technology have a major presence in China.
As a Western consumer technology, 5G has been a disappointment. As the Wall Street Journal headlined a January 2023 report: “It’s Not Just You: 5G is a Big Letdown.” With download speeds of about 150 mbps per second, moreover, American 5G networks are half as fast as China’s. And some U.S. 5G networks have higher latency than the 4G networks that preceded them, making them less useful for applications like autonomous vehicles. Reduced spending on 5G infrastructure pushed Ericsson into a loss during the second quarter of 2023.
China, by contrast, views 5G as an industrial technology, and expects 5G2B (5G to business) to drive sales. The relative stock price performance of Western vs. Chinese companies contains some forward-looking information. Huawei, the largest provider of telecom infrastructure, is a private (employee-owned company) and has no listed stock price, so no insight can be gleaned there. But China’s number two telecom company, ZTE, provides a rough proxy for Huawei. Its stock price has doubled over the past five years, while the second and third-ranked global firms, Ericsson and Nokia, have lost about 30 percent of their market value (price performance calculated in U.S. dollars). That is noteworthy considering that the broad European market rose 23 percent between July 2018 and July 2023 while the Chinese market (CSI 300) is almost unchanged. American pressure has excluded the Chinese firms from the U.S. market and many European markets as well, but the Chinese firms dominate their home market and most of the Global South.
China thus has a distinct advantage in 5G broadband, a critical element in business automation. Transmitting large amounts of data (for example, thousands of photos of a factory conveyor belt per minute or real-time video of underground mining operations) is more of a bottleneck than chip speed. Last month, China was the first country to allocate spectrum in the 6GHZ band to 5G and 6G services, to promote “global or regional division of 5G/6G spectrum resources” and provide the groundwork to “promote mobile communications and industrial developments at home.”
U.S. spectrum allocation favors wifi over mobile broadband, allocating virtually all of the 6GHz band to “unlicensed use,” that is, Wi-Fi. As the industry website Lightreading observed, “the ruling represented a win for the cable industry and other Wi-Fi proponents ranging from Apple to Cisco. But for 5G network operators – which continue to argue they don’t have enough spectrum for high-bandwidth services like fixed wireless – the FCC’s ruling came as a setback.”
In other words, U.S. policies continue to favor consumer-oriented Big Tech over industry applications.
Telecom infrastructure and related applications have also buoyed China’s exports to the Global South, which have risen 50 percent since 2019 in ASEAN, nearly 100 percent in Brazil, and 250 percent in Turkey. Broadband has a transformational impact on countries with a high proportion of informal employment. It puts payment systems onto smartphones and opens banking and credit to previously marginalized people, and provides information and sales opportunities to entrepreneurs. It reduces the cost of delivery of services, including education and healthcare, and fosters new industries.
Because of all of these efforts, China in 2023 became the world’s leader in the largest manufacturing industry, automobiles, with $3 billion in global sales. High-tech manufacturing and economies of scale are likely to increase China’s edge. In 1908, Henry Ford defined an era of mass ownership of personal cars by pricing the Model T at $800, then America’s per capita GDP. China now produces electric vehicles with adequate range and power at around $11,000, just below China’s per capita GDP. China’s cheap but full-featured electric cars may dominate the low end of Europe’s auto market. Once China’s best-selling brand, Volkswagen’s market share has fallen, with annual sales down to 3.2 million units in 2022 from 4.2 million before the coronavirus pandemic. The benefits of 5G2B and artificial intelligence are thus tangible and visible: Cheaper industrial products, more efficient ports, deployment of automated vehicles, and so forth.
Meanwhile, in the West, how LLMs will drive profitability is less clear. Generative AI may find more lucrative uses in the future, especially in the automation of software, but how the existing technology justifies the trillions of dollars of additional equity valuation inspired by ChatGPT remains something of a mystery. OpenAI’s ChatGPT model meanwhile appears to have peaked as an object of popular curiosity, with a 10 percent decline in website visits in June.
As for present usage and estimates, the picture is sanguine. An Asia Times study noted that replacing every help desk employee in the United States with a chatbot would save a mere $1.6 billion a year, while replacing the bottom 25 percent of computer programmers by earnings would save just $2.5 billion.
Why Have U.S. Tech Sanctions Failed?
For several reasons, U.S. sanctions are ineffective in constraining AI development in China.
First, as noted, China’s home designs are competitive in industry applications, which typically require less computing power than LLMs and may already offer performance equivalent to the Nvidia and AMD offerings
Second, China’s SMIC can produce 7-nanometer chips, albeit with much higher costs and lower efficiency. It can certainly meet the requirements of China's military for 7-nanometer chips. These are probably quite small; existing military systems overwhelmingly use older chips, which are more robust and easier to harden, as the RAND Corporation explained in a 2022 study.
Third, Nvidia’s fastest AI chips are readily available in China through third-party sellers although at higher prices. Slower versions designed by Nvidia to stay within U.S. guidelines are still sold to China, although Washington reportedly may ban these as well.
Stopping Chinese firms from using American AI computing power via cloud services won’t accomplish much, according to US industry leaders. Amazon CEO Andy Jassy was asked by CNBC July 6: “One of the things the administration has floated is the idea that Chinese companies wouldn’t have access to kind of AI-grade cloud computing resources through hyper scalers, through cloud providers, like Amazon. Do you have a sense of how that would affect Amazon if Chinese companies couldn’t access AI scale computing on [Amazon Web Services]?” Jassy replied: “Well, the reality is that there are some very strong cloud providers who are Chinese cloud providers in China. So Chinese companies in China are going to have access to AI capabilities, whether they come from U.S. companies, European companies, or Chinese companies.”
Compete Seriously or Perish
U.S. limits on technology exports to China do not appear to have stopped or even slowed the rollout of the AI applications that have the greatest strategic impact. At the same time, restrictions on sales to China reduce the revenues of U.S. semiconductor companies and endanger their R&D budgets. In December 2019, the Defense Department vetoed a Trump administration plan to ban the export of high-end chips to Huawei on the grounds that the loss of Huawei as a customer would impinge on chipmakers’ ability to sustain R&D. President Donald Trump initially backed the Pentagon position, but reversed this later in 2020 after the coronavirus epidemic hit with full force.
The semiconductor industry is unique in the scale of its R&D requirements. It budgeted $200 billion for R&D on $600 billion in 2021 sales (the actual total will be $160 billion or less due to market softness). No other industry devotes a third of revenue to R&D. The world’s largest industry, automobiles, spends about one-fourteenth of its revenue in R&D. For companies like Qualcomm, which earns a third of its revenue in China, or Nvidia, which earns one-fifth of revenue, the support available under the CHIPS act will not compensate for revenues lost due to federal regulation. These companies are lobbying the Biden administration to relax controls on China, and they have a good case—in fact, the same case the Pentagon made in December 2019.
Restrictions on technology exports to China at best are a stopgap. Eventually, China, which graduates more engineers each year than the rest of the world combined, will develop its own substitutes, as ASML, the world’s premier maker of chip lithography equipment, avers. Even as a stopgap, though, the controls are failing. They impose high costs on China in several ways but have not impeded the Fourth Industrial Revolution. On the contrary: the limited adoption of Fourth Industrial Revolution technologies by American industry is concentrated in firms that have major commitments to China.
Whatever its merits, the CHIPS Act is not a substitute for the kind of effort the United States made under the Apollo program, or during the late 1970s and early 1980s, when DARPA funded the invention of the digital economy. In 1983 the United States devoted 1.2 percent of GDP and 5 percent of the U.S. budget to federal R&D. Today we spend only 0.6 percent of GDP on federal R&D and barely 2 percent of the federal budget.
To maintain a technological edge over China, we will have to spend an additional several hundred billions of dollars, train a highly-skilled workforce, educate or import more scientists and engineers, and provide broader incentives to manufacturing. It is simply too late to try to suppress China. That is no longer within our power. What remains within our power is to restore American pre-eminence.
David P. Goldman is Deputy Editor of Asia Times and a Washington Fellow of the Claremont Institute. He is the author of You Will Be Assimilated: China’s Plan to Sino-Form the World, How America Can Lose the Fourth Industrial Revolution, and Restoring American Manufacturing: A Practical Guide.
