America’s R&D Reckoning

How to kill a golden goose

What’s happening to America’s science and technology ecosystem? How is China interpreting the current state of US research, and how is it working to build its own science and technology base in response? And what can we learn from China's war mobilization exercises?

To explore these questions, we're joined by Divyansh Kaushik and Alex Rubin, who both work at Beacon Global Strategies. Divyansh holds an AI PhD from Carnegie Mellon, and Alex spent the past decade at CIA focusing on China and emerging technologies.

We discuss…

• The historical origins of the US R&D model, and the division of labor between universities, government, and industry,

• How budget cuts will impact the NSF, NIH, NIST, and DoD basic research,

• Why and how China attempts to emulate US research institutions,

• What a leaked wargame exercise from Guangdong province can tell us about China’s grand strategy,

• How institutions like ChinaTalk complement the IC with fresh, independent research.

Listen now on iTunes, Spotify, or your favorite podcast app.

Bell Labs researchers Donald Herriot, Ali Javan, and William Bennett with one of the first lasers, circa 1961. Source.

How America Has Won With R&D

Jordan Schneider: Let’s do a 101 on the broader American research ecosystem. What does the interaction between universities, government funding, and corporations look like in the 2000s?

Divyansh Kaushik: To better understand today’s landscape, we need to trace our steps back about 70 years and examine how the American research ecosystem was conceptualized. The original model positioned universities to conduct curiosity-driven research funded by the federal government, while American industry focused on transforming that research into applications.

There were certain industrial monopolies created by the government that also conducted basic research, which Alex can address more comprehensively. However, the overwhelming majority of basic research happened in academia — universities created as land-grant institutions or those existing before the war. This system served us remarkably well, as basic research developments from the 1950s, 60s, and 70s bore fruit 10, 20, 30, or 40 years later. The nature of basic research doesn’t necessarily have an immediate application, but applications may emerge years down the line.

Consider this example: During the 1970s and 80s AI winter, when nobody was funding neural networks research because it was viewed as a dead end without viable applications, the National Science Foundation — created to fund basic research through the federal government — was funding Geoffrey Hinton’s work on neural networks, being the only entity supporting this research at the time. Fast forward 40-50 years, that work has fundamentally shaped how we view AI today. It’s the foundational technology behind all the large language models currently in use.

NSF also funded Andrew Barto’s entire PhD. Barto, together with Richard Sutton, established the field of reinforcement learning at a time when there were few practical applications. Today, reinforcement learning is a critical component behind LLMs, AlphaFold, and similar technologies.

This exemplifies how America has pursued basic research. Currently, there’s considerable criticism about research projects like "shrimp on a treadmill" or "fish on cocaine," questioning why such studies receive funding. While these projects have legitimate scientific purposes, to the general public they appear to be wasteful uses of federal research dollars.

Agencies like the National Institutes of Health fund more applied research on medicines and can point to tangible outcomes — specific drugs developed with NIH funding. The NSF, conversely, funds basic research that may not demonstrate tangible benefits for decades, as happened with neural networks.

We’re now engaged in a deeper conversation about what constitutes waste or abuse of federal research dollars and how to allocate those funds more effectively. Is industry-funded research the optimal approach? Does the federal government have — or should it have — a role in the R&D ecosystem? What about public-private partnerships, which were a cornerstone of the CHIPS and Science Act in creating the Technology Innovations and Partnerships Directorate at the National Science Foundation?

This significant conversation emerged particularly this year, as the National Science Foundation, Department of Energy, Department of Defense, and National Institutes of Health find themselves at the center of questions regarding the appropriate allocation of federal dollars toward research.

Jordan Schneider: Let’s explore more of this history, because I think we can’t ignore the broader defense community’s role in funding R&D over the past 75 years. Alex, would you like to address that?

Alex Rubin: This is best illustrated through an interesting case study. We’re currently focused on the semiconductor industry due to its substantial economic and strategic implications. The foundation of the semiconductor industry can be traced directly back to funding from the Air Force and NASA for both the Apollo program and ICBMs.

One interesting example demonstrating the federal government’s role involves what we call the "Valley of Death" — the challenge of bringing novel research from the laboratory to market. The federal government, particularly the defense procurement establishment, has excelled at intervening at this crucial stage in the R&D cycle by providing customers and markets for these technologies. This allows companies to expand production, build scale, and reduce costs, making it feasible for them to enter commercial markets.

The modern semiconductor industry wouldn’t exist as it does today without those initial purchases from the Air Force, NASA, and other government entities. It’s extraordinarily difficult to transition from the lab to the market, especially when costs are high. Finding consumers willing to purchase these products when they’re expensive is challenging, which is where government plays a particularly important role in advancing that cycle.

When discussing the federal government’s role in early-stage basic research, there are instances where industry has undertaken this responsibility. The AT&T system — the Bell system — during the 20th century provides a classic example of industry conducting exactly the type of research we’re discussing. However, certain unique characteristics made this possible for the Bell system.

Throughout the 20th century, the Bell system comprised several key units: corporate headquarters in New York, its manufacturing arm (Western Electric) producing equipment for telecom networks, the regional Bell operating companies that eventually became companies like T-Mobile and Verizon providing local phone service, long-distance service, and crucially, Bell Labs.

Extensive literature documents Bell Labs’ history and impact. Innovations including the transistor, discovery of cosmic microwave background radiation, and cell networks all emerged from Bell Labs. The list of remarkable technologies and innovations originating there is extensive.

Bell Labs could invest in both basic and applied research because of their consistent funding stream from what was essentially a government-regulated monopoly. In the 1910s, the government granted AT&T monopoly status over the telecom industry with certain conditions, including a requirement to license any inventions outside the telecom industry under generous terms or without fees.

Bell Labs operated with a consistent revenue stream from their telecom service monopoly, maintained a direct relationship with manufacturers allowing them to troubleshoot as products moved to manufacturing, and had direct connections to customers through their operating companies, enabling them to identify market demands.

Most importantly, they had long-term consistent funding — precisely what makes federal research dollars so crucial for basic research. This consistent funding allows investment in projects that might not yield deliverables for 10, 15, or 20 years. This differs dramatically from typical corporate investments seeking returns within a couple of years.

Companies justifiably need to demonstrate return on investment, which becomes incredibly difficult without consistent market support. Industry can indeed support basic research, but it requires specific enabling characteristics similar to those that enable basic research funding from the public sector.

Jordan Schneider: Divyansh, could you address the university’s role in this ecosystem?

Divyansh Kaushik: Universities today aren’t limited to basic research — they conduct significant applied and industry-funded research as well. However, an often overlooked aspect of universities’ contribution is their role in creating talent pipelines. The researchers going into industry are those who received federal funding at universities.

These individuals enter graduate programs where they develop intellectual curiosity through curiosity-driven research and by solving interesting problems without immediate pressure to generate revenue. They cultivate this intellectual curiosity and bring it with them when they join industry, ultimately driving the industrial innovation we witness.

Universities play a crucial role in regional innovation and economic growth. The spillover effects include startups and jobs created as a result of research funding. Numerous economic studies demonstrate multiple dollars returned for every dollar of federal R&D spending at universities.

Universities also advance national security objectives. Carnegie Mellon University, my alma mater, works with the Department of Defense on several projects directly impacting warfighters. Universities host Federally Funded Research and Development Centers (FFRDCs) and integrate DoD personnel into their research programs.

Universities therefore have a broader ecosystem-driving role, not just a narrow focus on quarterly profits. Both approaches are valid — they’re complementary rather than substitutive. While most companies don’t conduct basic research, some do. Microsoft, for instance, spent nearly ten years developing the Majorana chip for quantum computing, made possible by consistent funding.

If we reduce consistent funding for universities, we’ll see fewer PhD students enrolling, fewer PhDs granted, fewer qualified individuals joining companies like Microsoft, and ultimately fewer innovations like the Majorana chip. This affects the entire ecosystem.

Jordan Schneider: Alex, can you discuss how envious the rest of the world is of the ecosystem America has built?

Alex Rubin: A couple of decades ago, China looked at the U.S. R&D ecosystem and essentially said, “We want that,” and began working to replicate it. They’ve invested considerable resources — money, time, and high-level attention. President Xi Jinping regularly emphasizes the importance of basic research, improving China’s STEM education system, and developing talent as key enablers of China’s technological development and growth as an economic and global power.

China recognizes that the U.S. model is incredibly effective at generating innovations, bringing them to market, and establishing dominance and first-mover advantages in critical new technologies. China’s approach to its R&D ecosystem and education system focuses on three main categories, emphasizing generational investment.

Jordan Schneider: Let me provide some context with numbers. The U.S. spends approximately $50 billion annually on basic R&D, with another $50 billion coming from universities and businesses — totaling around $100 billion yearly.

American firms represent 80% of the world’s global technology market capitalization. Additionally, 80% of science Nobel Prizes over the past 50 years have included winners with U.S. affiliations. These three factors are interconnected.

This ecosystem produces the most advanced companies, which then provide cutting-edge technologies to the national security establishment. It’s a beautiful, self-reinforcing system. The best scientists work at American universities, attracting the best students worldwide. Despite providing only 25% of global basic funding, the U.S. spends it so effectively that the greatest minds globally want to come here and work on these topics.

Alex Rubin: This is indeed a generational investment. It’s no coincidence that U.S. companies initially led in the semiconductor industry, then in personal computers and other computing applications, and now in AI. These advantages build upon each other.

If you establish early leadership in one industry and continue making long-term investments, it naturally positions you advantageously for the next generation of technology. Conversely, if we make decisions now that underinvest in research or otherwise hinder the development of these talent ecosystems, the real impact might not become apparent for 10-15 years.

Unfortunately, once those impacts become visible, it’s often too late. Recovering lost ground requires significant time. The research investments and decisions we make now — whether regarding grants or graduate programs — will show their consequences a decade or more from now.

Jordan Schneider: That concludes our cheerleading session for the American R&D ecosystem. Divyansh, what has been happening over the past 100 days that concerns all three of us — developments that may risk the world-historical R&D golden goose America has built since Vannevar Bush wrote to FDR, envisioning a glorious future made possible by the collaborative efforts of corporations, research universities, and the U.S. government?

Divyansh Kaushik: I would actually broaden the timeframe to consider the last year or so. During this period, we saw the NSF budget cut by approximately 8% from the previous year, the NIST budget cut by about 13%, and the DoD basic research budget reduced by roughly 4%.

Early in the administration, NIH changed its policy on Facilities and Administrative (F&A) benefits, unilaterally reducing them to 15% — a decision that faced legal challenges. This was followed by layoffs at several federal funding agencies.

More recently, DoD and DOE followed NIH’s approach by capping F&A at 15%, which merits separate discussion. Additionally, NSF terminated approximately 400 previously awarded grants. We also witnessed the resignation of the NSF director amid rumors of potential additional layoffs at the agency.

Jordan Schneider: A former Trump appointee, mind you.

Divyansh Kaushik: Correct, and unanimously confirmed by the Senate. Further concerning developments included leaked information about the President’s budget request, suggesting NSF could face approximately 55% budget cuts, with NIH potentially facing similar reductions.

These issues are foremost in the minds of both academic and industry researchers. Brad Smith recently wrote a blog post about quantum computing where he emphasized the importance of basic science funding for workforce development. This concern is widespread.

Several former national security leaders, including former Trump appointees such as his former Homeland Security advisor and others, signed a letter to Congress highlighting the importance of funding basic science research at this critical juncture. As Alex mentioned, China has increased its basic R&D spending by 10% year-over-year for the past seven years.

The CHIPS and Science Act established a vision to double our federal basic R&D spending over the next decade. Instead, we’ve failed to meet this moment. Approximately $50 billion of authorized funding from the CHIPS and Science Act remains unappropriated for the science component.

Regarding talent, certain universities received letters terminating visas for some PhD students — a decision the administration later reversed. This situation weighs on the minds of universities and researchers, raising questions about broader implications on the global stage.

France, Australia, and China have attempted to capitalize on this uncertainty by establishing specific programs to attract U.S. researchers, offering long-term stability, funding, and residency benefits.

Jordan Schneider: You missed one aspect, Divyansh. We’re also seeing targeted actions against specific universities, with significant conflicts involving Columbia and Harvard. Beyond the 400 NSF grants canceled due to DEI considerations, research is being canceled simply because researchers happen to be PhD students or professors at Harvard.

Divyansh Kaushik: That certainly occurred. Interestingly, as we record this, President Trump just announced he’s naming Secretary of State Marco Rubio as interim National Security Advisor and nominating NSA Mike Waltz for UN Ambassador. Developments are unfolding rapidly.

Jordan Schneider: Wow, really? That’s the best possible outcome. I was preparing for the Laura Loomer National Security Advisor era.

Divyansh Kaushik: I mention this because the National Security Council plays a crucial role in this conversation by emphasizing the national security importance of federal R&D. Alex understands this well from his previous position, particularly regarding the critical benefits it provides.

Jordan Schneider: Wait, we need to focus on this for a moment. We haven’t seen this dual role since Kissinger. Is that right, Alex? Has there ever been another person serving in both capacities simultaneously?

Alex Rubin: No, I believe Kissinger was the only one.

Jordan Schneider: This is remarkable. There’s been considerable discussion about NSC reform, as it’s not a fixed organization. I wonder if this presents an opportunity for such reforms, though Rubio’s State Department reforms appear less developed than anticipated or discussed.

I recognize we’re speculating beyond our expertise, but this breaking news deserves attention. There’s a certain Nixon-era quality to these developments. From my perspective, this appointment represents a positive direction — the situation could have been significantly worse than Marco Rubio.

Alex Rubin: Regarding technology policy, Rubio has been at the forefront on issues concerning investments in technology and its centrality to competition with China. During his Senate tenure, his team produced a report examining Made in China 2025. Technology represents the key battleground in this competition. Extending that metaphor, researchers, scientists, and engineers serve as the frontline contributors to American power in this space.

Jordan Schneider: This is astonishing. Earlier today, New York Times articles suggested Waltz had been dismissed — likely someone attempting to shape that narrative. Rubio presents an interesting case, given the contrast between his decade-plus Senate career and his more recent MAGA-aligned positioning. JD Vance seems to embody that perspective more naturally than Rubio. We’ll have to observe how this develops.

Returning to science and technology — before discussing positive aspects, Divyansh, we should address the challenges facing the university ecosystem regarding talent and funding. International students constitute a crucial funding component since most pay full tuition. Government funding represents another vital revenue stream.

Only about 10-15 universities possess multibillion-dollar endowments that would enable them to withstand major external shocks such as losing international students or significant funding cuts without drastic measures like closure or acquisition by private equity firms.

You briefly mentioned immigration concerns, but the situation created genuine alarm among many students who feared leaving the country. Although courts have temporarily reversed certain policies, I worry these uncertainties will linger in the minds of parents worldwide and PhD students considering where to establish their careers.

Divyansh Kaushik: We’ll soon see how this affects enrollment as universities release their yield data. With May 1st approaching and April 15th being the deadline for students to accept or decline offers, that information will become available shortly.

We’ve already observed an 11% decrease in international student enrollment between March 2024 and March 2025, mirroring a similar trend between March 2016 and March 2017. We must monitor this data closely.

Regarding the importance of this population, people often overlook that international students comprise 60% of Computer Science and AI PhDs, and approximately 50% of all STEM PhDs and Masters students. Replacing this talent with domestic students would require considerable time and concerted effort.

Notably, the number of domestic computer science undergraduates pursuing graduate degrees has remained unchanged since approximately 1990-1995. China, with four times the U.S. population, produces twice as many STEM PhDs, twice as many STEM Masters, and four times as many STEM Bachelors graduates.

We can no longer credibly claim that their STEM education or research quality is inferior — they excel in both quality and quantity. Based purely on numbers, our only viable competitive strategy involves recruiting talent globally. China has substantially more human resources to dedicate to complex problems than we do, a critical factor in this discussion.

Jordan Schneider: Let’s return to your "On the plus side" perspective, Divyansh.

Divyansh Kaushik: Consider Michael Kratsios’ remarks at the Endless Frontier retreat approximately 16-17 days ago, on April 14. He described an emerging golden age for America, speaking of "the early light of this new golden age," "American hope," and "the possibility of progress through science and technology."

He emphasized that this golden age will materialize only if we actively choose it, then outlined his approach. He discussed how ours was the atomic age and how we must fight to restore that inheritance. He proposed rethinking federal R&D spending through smarter methodologies.

The Biden administration implemented numerous pilot programs in this direction, but making those approaches the primary R&D strategy would represent a significant achievement for the current administration. New experimentation and prize competitions would be particularly beneficial. We must consider how to optimize every dollar spent on R&D.

Grazio emphasized that beyond a protective agenda to maintain American dominance, we need a promotional agenda. We must create a funding environment that clearly articulates our national priorities, enables scientists to develop new theories, and empowers engineers to implement them. Using advanced market commitments would multiply the impact of government-funded research.

His address contained numerous positive elements that create opportunities for the administration to scale these efforts. Now is the ideal time for those with bold ideas to advance them.

Jordan Schneider: We observed the DOGE approach during the first hundred days — not implementing reforms to unlock a better version of government, but simply making cuts. As the DOGE era concludes, we recognize you can’t forcibly impose creative meta-science reforms, though these organizations do need restructuring.

The current energy, insight, and understanding acknowledge that conditions aren’t ideal. Breakthroughs have become less frequent and more expensive relative to expenditures compared to the 1950s-70s. This presents an opportune moment to experiment with new approaches. However, these efforts become significantly more challenging with half the funding and without international talent — risks created by the budgetary constraints, visa restrictions, and confrontational stance toward universities we’ve witnessed in recent months.

Alex Rubin: Yes.

Divyansh Kaushik: My friend Caleb Watney offers a valuable perspective: viewing federal R&D through a venture capital lens, given the substantial VC presence in government. We should measure performance by return on investment rather than by minimizing expenditure. The critical question is how to maximize outcomes from our investments.

Regarding reforming and restructuring agencies, these institutions are generally receptive to change. The National Science Foundation created the Technology, Innovation, and Partnerships (TIP) Directorate before Congress even passed the CHIPS and Science Act, despite some quiet resistance from other directorates. The agencies welcome innovation.

Consider how Department of Energy national laboratories are experimenting with OpenAI’s models as scientific peers for brainstorming. These represent fascinating initiatives by research agencies to reinvent their approaches to research and funding. If the administration pursues this direction, they’ll likely find substantial support from within the agencies themselves, as well as from universities and industry.

Jordan Schneider: We should campaign for Irwin as NSF Director!

To conclude our discussion on America’s research ecosystem, my assessment is that the Vannevar Bush “Endless Frontier” model has, over the past 75 years, delivered some of humanity’s greatest benefits. Setting aside national power considerations — which should be self-evident given that this system helped overcome the Soviet Union and created history’s wealthiest nation — this ecosystem could benefit from reforms. However, it represents the quintessential golden goose that we’ve managed to develop through work, consistency, and some fortunate circumstances.

This represents a national treasure, and what disturbs me most is the risk of crossing thresholds we cannot reverse. Ecosystems like this, when supported, demonstrate remarkable resilience. However, they contain inherent vulnerabilities related to institutions, funding streams, and talent that require continuous replenishment to maintain previous levels of success.

We’ve covered this extensively over the past eight years, following the excitement surrounding and ultimate passage of the CHIPS and Science Act — a period when bipartisan consensus seemed to favor increased investment in basic research. Watching immigration restrictions, culture war issues, and DOGE priorities converge to create perhaps the greatest threat this ecosystem has faced in decades is deeply concerning and something we’ll monitor closely in the coming months and years.

Divyansh Kaushik: American R&D is globally envied, and we should intensify our commitment to it. Universities serve as powerhouses in this system. Simultaneously, they aren’t blameless in many respects and need to engage in introspection regarding why our commitment to academia and universities faces questioning today. I hope many institutions will undertake this self-reflection and emerge stronger.

Alex Rubin: I’d like to add that while we’ve focused extensively on laboratories and academia and higher education, the R&D ecosystem extends beyond these components. It encompasses community colleges, vocational schools, and technical training programs that produce technicians who operate equipment in these laboratories — an absolutely crucial function.

Many major technology companies, particularly those with significant manufacturing operations, primarily employ community college graduates or individuals with technical training rather than PhDs. The semiconductor industry, for instance, has a substantial veteran population, recruiting former mechanics with relevant skills to maintain equipment. These aren’t PhDs, but they possess essential skills for equipment maintenance.

The final component, which speaks to generational investment, is K-12 education. Truly enhancing the quantity and quality of graduates from PhD and master’s programs begins at these early stages. We’ll discuss China’s approach in this area later, but the foundation lies in K-12 education, gradually building technical literacy so that by the undergraduate or graduate level, students’ mathematics and science skills match global standards.

Divyansh Kaushik: The administration recognizes this priority, evidenced by the recent AI in K-12 executive order, which aims to integrate AI education throughout K-12 curriculum to develop an AI-ready workforce in the coming years. Alex’s observation is entirely accurate, which further supports my optimism regarding future opportunities.

Monitoring Chinese Innovation

Jordan Schneider: Let’s discuss China. Alex, when fundraising for the ChinaTalk Institute, which has enabled me to hire exceptional talent tracking China’s developments in AI and biotech, several funders questioned the necessity of such an organization. They assumed the U.S. government adequately monitors China’s commercial technology through open-source intelligence. As someone who has spent the past decade primarily following Chinese science and technology in the commercial sector, how would you respond to that assumption?

Alex Rubin: My response is that it’s fundamentally a team sport. Different organizations — the intelligence community, other government agencies — have comparative advantages in what they monitor. However, when discussing commercial technology and areas where the primary actors aren’t governments but companies, universities, and laboratories, many strategically significant developments emerge from industry rumors and corporate insights.

Effectively monitoring these developments can’t be limited to individuals like myself in my previous role, working in secured environments to examine these issues. It requires a comprehensive approach that incorporates companies and universities.

The space for organizations like ChinaTalk involves engaging the general public. During the Cold War, nobody questioned why developments within the Soviet Union mattered — there was an inherent understanding of their connection to the American economy, jobs, and security. We need to establish similar connections today, explaining why developments like Huawei creating an advanced GPU matter to average Americans.

This is precisely where podcasts like ChinaTalk and similar outlets contribute value — bringing perspectives well-understood in Washington and disseminating them throughout the country.

Jordan Schneider: It’s interesting how you frame this through tactical, operational, and strategic perspectives when analyzing these questions. The flexibility available in think tanks, academia, or whatever category ChinaTalk occupies allows for different approaches.

Alex, what are the Chinese government’s long-term strategic intentions regarding science and technology?

Alex Rubin: I’ve settled on what I believe is the most accurate characterization, paraphrasing Matt Damon in “The Martian” — Xi Jinping plans to “science the hell out of China.” That’s his fundamental approach — an all-in bet on science and technology.

Whether examining the economy, military, or internal stability, technology permeates everything. Looking at the economy, Xi’s new catchphrase is "new quality productive forces" — a reinterpretation of classic Marxist-Leninist productive forces theory that essentially asks how technology can improve economic performance.

Key components include upgrading traditional manufacturing through robotics and AI automation. Another focus involves eliminating technological choke points by making China more self-sufficient through innovation and R&D investments, enabling Chinese companies to develop domestic alternatives to technologies they currently source from foreign providers. A classic example is photolithography, where significant investment is directed toward Chinese companies like SMEE to reduce dependence on lithography systems from the Netherlands.

The third component focuses on future industries. Last year, China identified six broad categories and numerous specific technologies for targeted support in their Future Industries Development Action Plan. Some might seem far-fetched, including humanoid robots, quantum technologies, artificial general intelligence, and brain-computer interfaces.

They’re absolutely serious about leveraging these technologies for economic benefits. China recognizes that the United States, through its R&D ecosystem, positioned itself to dominate high-revenue sectors of the modern economy. China aims to dominate these sectors moving forward and is investing accordingly.

Regarding social concerns, Chinese leadership prioritizes issues like social stability that could potentially undermine the Party’s control. Their solution involves technology — AI-based tools to enhance surveillance through facial recognition, gait recognition, voice recognition, and predictive analysis. These technology-based solutions monitor and control the population.

Throughout Chinese history, food security has represented the leading cause of revolutions and rebellions. For 22 consecutive years, the first document issued annually by the State Council and CCP Central Committee has addressed rural policy and agriculture — reflecting their significant concern about food security partly due to limited arable land and pollution. Again, their solution involves technology-based approaches to improve agricultural output.

Examining China’s strategy from the reform and opening period to the present reveals consistent prioritization of scientific and technological investment, seeking to leverage these advancements across multiple objectives. So yes, the aim is to “science the shit out of China.”

Divyansh Kaushik: To add to what Alex was saying, China has openly stated in many documents how they want to copy the US system. I was testifying last year to Senate Energy and Natural Resources on this topic. The Chinese 13th Five Year Plan explicitly identifies Argonne, Los Alamos, and Lawrence Berkeley national labs as crown jewels of US innovation. China aims to mimic the US national laboratory system to focus on national goals, strategic needs, and target international technological frontiers — all the points that Alex highlighted.

Jordan Schneider: Alex, could you tie that to the basic research ecosystem?

Alex Rubin: Everything I’m discussing and everything China is attempting to do is fundamentally based in the basic research ecosystem and the talent flowing into it. Xi Jinping himself has talked about how basic research is the foundation of China’s technological progress and how talent is the key enabling factor for their development.

There’s a recognition within senior leadership circles in China that to succeed in dominating future industries and technologies, they must start with investments in basic research. They’re facing challenges in shifting their investments away from applied research toward basic research, given their long-standing investments in applied areas. However, there is broad recognition that to be competitive as a global technology leader, you must invest in early-stage research, basic research, and crucially, train people to staff those facilities.

Xi visits a seed innovation lab in Sanya, 2022. Source.

When we discuss basic research, we often focus on building infrastructure — whether purchasing GPUs or constructing data centers to train models. However, you can build the best infrastructure in the world, fill it with the best equipment, and provide unlimited funding, but if you lack people who know how to use that equipment and what to do with it, it accomplishes nothing. It inevitably comes down to having the right people working together with the appropriate training, experience, and connections to advance science and technology.

Jordan Schneider: Alex, what’s your take on the argument that China is looking for "good enough" technology as opposed to Nobel Prizes and truly frontier research?

Alex Rubin: China is essentially pursuing both approaches. China has a different interpretation of what it means to be a technology leader than the US does. The US defines technology leadership as having the most advanced technology and leading cutting-edge research. China defines it as that plus dominating markets and owning most of the world’s markets for key technology products.

For that second part of their definition, you don’t necessarily need the most advanced technology. What you need is technology that achieves perhaps 80% of the capability at 80% of the cost. When you’re looking at dominating markets, you’re considering Sub-Saharan Africa, Southeast Asia, Latin America — places that aren’t necessarily capable of affording the most advanced technology but still want the benefits advanced technology can provide.

A classic example is Huawei circa 2019. For a very long time, from its early stages, Huawei wasn’t seeking to be the world leader in telecommunication equipment. Instead, it developed technology that was "just good enough" and offered it to countries that couldn’t afford the best American options. Eventually, once the US exited the telecom equipment market, Huawei competed with European offerings by providing discounted prices and generous financial incentives — possible because of government funding, subsidies, and state support.

If you track the rollout of telecom networks through the 2000s and 2010s, from 2G networks to 3G and 4G networks, Huawei’s secret sauce was entering emerging markets in the Global South, offering technology that was perhaps not as good but cheaper, thereby gaining a foothold in these network buildouts. This strategy gave them significant revenue and market share, which they reinvested in research and development.

By 2019, they not only owned most of the world’s 4G network infrastructure but had leveraged their profits from markets like Sub-Saharan Africa to invest in 5G technology, which at the time was both better and cheaper than competitors’ offerings. This put the US in a difficult position because, arguably for the first time in modern history, it faced a major critical infrastructure buildout without a US company in the running, confronted by a Chinese company offering equally good technology at a lower price.

When we talk about "good enough" technology, it’s about broadening our definition of what it means to be a global technology leader. It emphasizes that leadership isn’t just about cutting-edge innovation but also about scale and presence in markets worldwide.

Jordan Schneider: Eva Dou, who wrote the excellent The House of Huawei, is on maternity leave, but we’ll get her on ChinaTalk at some point. One of the fascinating lessons from the Huawei story is that even though the government was pushing firms to do more R&D, the decision to spend an absurdly high percentage of revenue on R&D was Ren Zhengfei’s decision, not a government mandate. This made Huawei an outlier compared to rivals in China like ZTE, which invested only 5-7%. It demonstrates the interaction between government support, domestic scale, and visionary founders who see the long game. These founders understand that to build the most advanced technology company on the planet, you need to do the work yourself — you can’t just steal it.

Alex Rubin: You can steal your way to parity, but you can’t steal your way to leadership.

Jordan Schneider: Totally.

Alex Rubin: Another key point we mentioned earlier is the interconnection between research, customers, and manufacturing. That’s exactly what Huawei built for itself after studying success stories in the US and elsewhere. Huawei functions as both manufacturer and designer with a secure domestic market, where government support was particularly crucial in its early days. This creates an interplay that makes for a very successful, efficient model for advancing R&D.

The concerning part is that we’re seeing these same dynamics play out across multiple sectors today. If we’re not careful, we could find ourselves in the same position later this year or within two years, where critical infrastructure sectors are either reliant on Chinese technology or forced to choose between a Chinese supplier or paying more to be less competitive by going elsewhere.

Jordan Schneider: The broader American media and political ecosystem is only starting to process that China will be ahead in major commercial technologies over the next five years. We’ve already seen it in drones, telecom, and electric vehicles. Regardless of where the Chinese macroeconomic environment or American science funding goes in the coming years, we’re entering a new dynamic.

The trade-offs of keeping these technologies out of the US — which is broadly what we’ve decided to do for drones, telecom, and cars — creates a strange situation. Another important part of the China story was export discipline and the fact that many of these firms, at least in their early days, really had to compete to achieve scale domestically, both with other firms from different provinces and against companies like Apple and Tesla.

From a policy perspective, we need to remember that just because we don’t see these cars here doesn’t mean they don’t exist. They’re getting better, winning in third markets, and forcing GM, Ford, and Tesla to improve.

A DJI drone factory. Source.

Alex Rubin: Even if what a Chinese company offers right now isn’t as good or is more expensive than what a US company offers, they’ve consistently shown they can leverage legacy technology to eventually move up the stack and position themselves to achieve world-leading technology. Focusing solely on where they are right now and the current quality of their offerings misses the future risks of their ability to leverage "good enough" technology to eventually generate world-leading technology, whether through theft or innovation.

Jordan Schneider: Divyansh, do you want to say anything about this?

Divyansh Kaushik: Look at where Huawei is now compared to where it was in 2019, as Alex pointed out. It’s expanding everywhere — building data centers, producing cell phones and laptops, operating undersea cables, and investing in EVs. It’s no longer just a telecom company. The same pattern is true for many other Chinese companies.

Alex’s point about projecting forward rather than just looking at a static moment in time is extremely critical, especially as we try to implement more "protect and promote" actions. We should consider where these companies want to be. They’ve laid it all out openly. Made in China 2025 was not a hypothetical document — they met every objective. The AI 2030 plan was not hypothetical either — they’re on track for their 2025 goals.

We’re sometimes overconfident about how significant our lead is. We have an uncanny ability to underestimate China’s capacity to out-hustle everybody. This is something people should be careful about.

Jordan Schneider: When I was fundraising for the ChinaTalk Institute, which now exists and is still taking donations — we’re doing great work around Chinese AI, biotech, and strategic competition — a number of funders asked if the Intelligence Community already has all this China technology information covered. What would you say about what the IC can and can’t do, and the utility of people writing about these topics independently from the government and publicly?

Alex Rubin: Fundamentally, we’re talking about commercial technologies and commercial entities — companies and academia. Many of these industries are relatively small where key players know each other. There’s an inherent need for platforms like ChinaTalk and a key role for industry participants.

Many key insights that might be technological in nature but have significant strategic implications are rumors circulating within industry or insights that companies gain from talking to customers or partners, whether in China or elsewhere. There’s significant value in that information.

Unlike analyzing the Chinese military or leadership, which is a very different challenge, the targets and developments you’re looking at here are fundamentally different. There must be a role for entities that monitor the open-source ecosystem. Otherwise, you risk missing significant trends and developments.

Last point — while we spend a lot of time discussing how China is different and how Chinese companies operate differently, they still have profit motivation, even if somewhat reduced or circumventable when needed. Many of these companies actively publicize their developments in industry press and within their ecosystem because they want visibility. They want to broadcast their technological advancement and development.

There’s so much available in open sources — small technological developments with massive strategic implications. Something like China making progress toward more advanced semiconductor manufacturing is highly technical but has enormous strategic implications for U.S. export controls and AI policy.

Jordan Schneider: I think my answer is that if you’re comparing military to commercial intelligence, maybe it’s 80/20 or 90/10 on the military side — the interesting information requires hunting and digging in an intelligence community way. On the commercial side, it’s the inverse, where 90-95% of what you need — maybe not in a specific tactical way, but at a larger strategic level of what it means for America, industrial policy, or science and technology policy — you can get by just reading publicly available information.

The relative openness of the Chinese media ecosystem when discussing commercial technologies versus operational military plans is completely different because companies need to win domestic market share, hire people, get workers excited about their companies, and raise money from investors. All of that happens under a journalism ecosystem which is, for the most part, fairly free. It’s valuable to surface this information if you have the language skills and context to process it and share it with an English-speaking audience.

Alex Rubin: China’s war plan for tech is essentially their industrial policies, which they release constantly. Made in China 2025 was a very specific tech dominance plan that detailed their goals down to controlling specific percentages of industries or producing certain percentages of components. You can’t get more detailed than that.

Jordan Schneider: Before this episode, Alex, I asked if there was one document you wanted to discuss, and you pointed me to this mobilization war plan. We’ll link it in the show notes, but could you give listeners some context on why you think it’s interesting and important?

Alex Rubin: The document is from May 2022 — it’s a leaked transcript from a tabletop exercise, a war mobilization simulation in Guangdong province. What makes it interesting is that it includes representatives from the party, military, and government, all brought together in one room.

The scenario presented is essentially: "We’ve decided to invade Taiwan. What does the province do?" The focus isn’t necessarily on military movements like positioning naval vessels, but rather on how to mobilize the population and economy. In very detailed fashion, it discusses converting civilian manufacturing industries to wartime production, specifically calling out the shipbuilding sector, drone manufacturing, and other high-tech industries.

This provides a fascinating example of China preparing for potential major conflict with the US, not at the national level, but at the provincial level. They’re thinking through how to leverage their economy in wartime. If this sounds familiar, it’s basically similar to the US approach to war mobilization during World War II — that’s the scale and framework they’re considering.

They’re planning to leverage the benefits of China’s decades-long investment in expanding manufacturing capacity to essentially outproduce the US in the event of a conflict. The transcript is surprisingly detailed and covers all their considerations, from mobilizing reserves and recruiting people to converting maritime industries, aerospace repair yards, and organizing militias — everything is covered.

Jordan Schneider: When I read this, I thought it might be somewhat performative — Americans do nuclear war games for entertainment, after all. There’s something about the history of the Chinese Communist Party where national mobilization is portrayed as the most exciting time to be alive. But your sense is that I shouldn’t dismiss this entirely. Convince me otherwise, Alex.

Alex Rubin: You can find evidence of these activities in local Chinese press — I found examples just by using ChatGPT to search for relevant articles. There are numerous instances at county and prefectural levels, as well as provincial levels, of similar exercises being conducted. These are part of a comprehensive national system called the National Defense Mobilization system, which establishes cross-party government-military committees at national, provincial, county, and prefectural levels.

For example, in November 2020 in Chongqing Municipality, they conducted a mobilization exercise where civilian manufacturing companies temporarily switched their production lines to make ATVs. While not particularly advanced technology, it demonstrates them testing their capabilities.

To put this in a US context, these county and prefectural level exercises would be equivalent to officials in Fairfax County or New York City planning how they would mobilize to support a national-level conflict in the Pacific. It shows the scale and depth of their preparation and system-building.

Jordan Schneider: For our next episode on ChinaTalk, we’ll Twitch stream America’s national mobilization war plan.

Mood Music—Divyansh’s request as the song capturing the essence of China’s S&T strategy