风萧萧_Frank
以文会友
美国为何会输掉与中国的科技战
题目这句话，并不是有理哥盲目乐观，而是来自7月23日美国克莱尔蒙特研究所（Claremont Institute）高级研究员古德曼（David P Goldman），在美国《国家利益》杂志（National Interest）网站撰写的一篇文章，题目是：《美国正在输掉与中国的科技战，为什么》。
古德曼认为，美国现在想要通过封锁和限制措施，在科技战中压制中国，已经太晚了，美国需要真正有助于第四次工业革命的产业政策，需要在提升自身研发和生产能力上投入。看来，除了那些狂热的反华政客，美国还是有真知灼见的专家仍然保持清醒头脑！古德曼提及的中美科技战，毋庸置疑，就发生在眼前。从5G到芯片再到人工智能，应当说，美国已经在科技领域对中国发动全手段封锁和限制措施，可谓无所不用其极。明争暗斗：科技战早已拉开帷幕从奥巴马第二个任期开始，美国政府打压、围堵中国科技发展的政策图谋就已经酝酿形成，并在特朗普任期得到强化，全面打压中国华为。拜登上台后继续沿袭这一立场，对中国“芯片”、半导体进行全面“扫荡”。
2022年8月9日，美国总统拜登签署《2022年芯片和科学法案》（以下简称《芯片法案》），其中规定，禁止获得联邦资金的公司在中国大幅增产先进制程芯片，期限为10年。2022年10月7日，美国商务部出台“对中国实施先进计算和半导体制造的出口管制”新规，进一步禁止将使用美国设备制造的先进芯片销售给中国。
近日，“美国之阴”、“彭博社”等报道称，拜登计划在下周签署行政命令，限制美国对中国在半导体和人工智能(AI)等关键技术方面的投资，禁止英伟达和其他芯片制造商在未获得许可证的情况下，向中国和其他关注国家的客户出口芯片。这是米粒国在打压中国“芯”的最新罪证。当然，除了美国穷尽招数打击中国科技，其他盟友也不闲着，不管是自愿的还是被迫的，纷纷上阵，助老大哥一臂之力。2022年，美国、韩国、日本等组成“芯片四方联盟”，以牵制中国，在全球供应链中对华形成包围圈。今年1月，在老美的主导下，美、日、荷达成协议，将共同限制阿斯麦、东京电子、尼康等企业向中国出口先进芯片制造机器。
今年3月，日本政府宣布对23种半导体制造设备限制出口，新规定将于7月23日正式生效，限制包括中国在内的160个国家。今年6月，荷兰政府宣布针对先进半导体设备出口的新规，要求该国生产先进芯片制造设备的公司在出口先进光刻机时需要申请许可证，新规将于9月1日正式生效。现在，美国纠结一帮小弟，对中国的国产芯片业进行全方位围堵。中国“芯”路面临的局势将从原来的老美单边阻拦变为多边围堵，真可谓是“黑云压城城欲摧”。这场科技战，怎么赢？
四处漏风：美战略失策必然付诸东流越是花里胡哨的招数，越是没有卵用。西方有句话，叫条条大路通罗马，这也完美地体现到中美科技战中。现在，美国专注在先进芯片上打击中国，但美国忽略的一个事实是，市场需求最大、最有盈利空间的，其实是传统芯片，所以当美国集中打压中国先进芯片的发展时，中国看清市场需求，在发展先进芯片的同时，更专注于传统芯片的发展。美国彭博社（Bloomberg）7月31日曾发布报道称，尽管美国出台各种政策，减缓了中国先进芯片制造能力的进步，但基本没有影响中国使用14纳米以上技术的能力。这使得中国企业建造新厂的速度比世界其他地方都快。根据国际半导体产业协会（SEMI）的预测，到2026年，中国将建造26座使用200毫米和300毫米晶圆的工厂，相比之下，美国届时只有16家晶圆厂。从数据上看，2018年之前，中国的芯片自给率仅为5%；2022年快速增长到17%左右；2023年，中国的芯片自给率有望提高到25%。中国能自主生产的芯片主要由传统芯片组成，这意味着中国不仅可以有效反制美国芯片战，美国对华出口的传统芯片市场也在急剧缩小，对美国造成打击。
可能有人会问，先进芯片搞不出来，整一堆传统芯片有啥用，不还是落后？传统芯片并不是毫无价值。古德曼也提到，美国决策者没搞懂芯片与生产之间的关系，以为最先进的芯片才是有用的，但实际上传统芯片单独或并行工作，可处理大多数商业化人工智能业务。他还称，中国无法进口7纳米以下芯片及其制造设备，但可以用更昂贵的工艺自己制造7纳米芯片，或者通过将旧芯片堆叠接近最快芯片的性能，或者通过巧妙的系统架构临时组装旧芯片以接近新芯片性能。简单说就是，先进的咱没有，那我把传统的好好利用一下，也能赛过先进芯片。古德曼举一例来说明，目前中芯国际可以生产7纳米芯片，虽然成本高、效率低，但肯定能满足中国军方对7纳米芯片的需求，因为现有的军事系统绝大多数使用传统芯片，这类需求本就很小。这样看，用好传统芯片，在当前客观条件下，是十分必要的。除了中国自身在努力破局，美国那边，愿意投入到对华科技战的企业也不多，有多个美国内半导体巨头不听白宫“招呼”，甚至出现“逼宫”行为。
去年，中国芯片进口额大幅降低，相比前年减少了470亿美元。这下，美国的半导体巨头公司坐不住了，要知道，英特尔、高通和英伟达等企业，每年超过20%的营收来自中国市场。来看看业绩，今年一季度，英特尔公司净亏损达28亿美元，业绩同比下跌134%；AMD 2023年一季度净亏损达1.39亿美元，较上年同期下滑118%；美光科技公司在2023财年第二季度亏损达23.1亿美元，为20年来最大亏损季。这与中国市场也存在一定关系。现在，为了利益，英特尔、高通和英伟达尝试绕过白宫禁令，谋求与中国合作。英伟达公司调整其AI芯片规格，确保在符合白宫限制要求的情况下，继续向中国出口，其还为中国市场量身打造名为A800的AI芯片版本，以取代被限制出口的 A100，二者大部分关键技术规格都是相同的，唯一的差别是传输速度。同时，英特尔公司还准备在深圳建立新的芯片创新中心，以加深与中国的联系。而另一家半导体公司AMD，也在考虑效仿英伟达的做法。
或许，这就是西方版的“上有政策下有对策”吧。不仅如此，7月17日，英特尔、高通和英伟达三家公司的高管，还专程前往华盛顿“逼宫”，游说了包括布林肯、雷蒙多、布雷纳德和沙利文在内的一众政府高层，希望能阻止拜登政府扩大对中国出售芯片和半导体制造设备的限制。同日，美国半导体行业协会（SIA）发布声明，呼吁白宫要避免进一步升级对华半导体出口限制，称这可能会削弱美国半导体行业的竞争力，破坏供应链，损害政府在美国国内芯片制造领域的大量新增投资。
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古德曼在文章中，也表达了这一观点，即美国对中国技术出口的限制，反而减少了美国公司的收入并危及其研发预算。大洋彼岸，美国阵营已然军心涣散，各有打算，这仗，还怎么打？前车之鉴：华为就是中美科技战最好缩影古德曼以华为为例，解释为何对华采取科技限制措施会失败。2020年，特朗普政府禁止向华为销售美国高端半导体后，西方媒体预测中国5G建设将陷入停滞，但结果恰恰相反，中国5G基站数量在2021年翻了一番，达到143万个，到2022年增至231万个，而全球总数为300万个。华为用28纳米而非遭美国封锁的7纳米芯片建造5G基站，其能耗高于最佳水平，但系统正常运行没有问题。这也印证了前文我们讲到，传统芯片具有替代先进芯片的重要作用。由于无法获得更新的芯片，华为手机业务一度大幅萎缩，但如今，华为可以设计自己的高端芯片并在中国制造。最新报告显示，华为将在2023年下半年重新进入5G手机市场。
反观美国，对华为的打压，并没有帮助美国发展5G。在美国等西方国家，5G一直被作为一项消费技术看待，美国5G网络的下载速度只有中国的一半，某些美国5G网络的延迟时间比4G网络还长，这使得它们对于自动驾驶汽车等应用的用处有限。这也充分说明，打压别人，并不能帮助自己进步。最后，还是谈谈几点看法吧。古德曼这篇文章，虽然预言美国对华科技战注定失败，但我们仍不可掉以轻心、盲目乐观，以为敲锣打鼓就能取得最终的胜利。中国之所以能够以惊人速度实现科技发展、经济增长和社会进步，从本质上来看，是我们拥有雄厚的科研能力和人才储备，有全球门类最健全的制造业产业链，有制度优势，社会主义市场经济体制建设进入更成熟阶段。而美国失败的原因，是对实力衰落的现实选择视而不见、听而不闻，不能正视这是价值规律作用下市场选择的必然结果，注定了美国必将被市场和价值规律所抛弃。未来，美国还会出更多四面漏风的招数，我们应当做的，就是正视困难，保持战略定力，充分利用市场、价值规律的力量，击破美西方的“限制牢笼”。正如比尔·盖茨在评价美国芯片禁令时所说，这只会迫使中国花时间和金钱来制造自己的芯片，美国永远无法阻止中国拥有强大的芯片。对于美国想将中国阻止在“第四次工业革命”大门之外企图，有理哥免费送老美四个字：痴心妄想！
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.
