Silicon Valley, Government Officials, and Elected Representatives Gathered at Bloomberg's "Hill and Valley" Event
Silicon Valley technologists, government officials, and elected representatives gathered at Bloomberg's "Hill and Valley" event, focused on AI and China — the two defining themes of our era. At this prominent gathering, Josh Wolfe, co-founder of Lux Capital, offered sharp insights into the US-China technology competition — particularly America's position and strategy in AI. He described the emergence of China's AI model "DeepSeek" as a clear "wake-up call" for the United States, and argued from multiple angles about the challenges the US faces and the course it should take — spanning chip export controls, data utilization, trade policy, and R&D investment.
This article, drawing on Wolfe's analysis, examines how the US can maintain competitive advantage in AI within an increasingly complex US-China relationship and address economic and national security challenges. It digs into his thought-provoking proposals: the pros and cons of chip controls, the potential of open-source AI, a data-driven future, and the need for what he calls a "grand bargain" with China.
- The Current State of the US-China AI Race and America's Strategic Challenges, as Signaled by DeepSeek
- Evaluating US AI Policy and Market Dynamics: Driving Innovation and the Path to a "Grand Bargain" with China
- National Security and R&D: Stopping Technology Transfer to China and Strengthening America's Innovation Foundation
- Summary
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The Current State of the US-China AI Race and America's Strategic Challenges, as Signaled by DeepSeek
As the technological hegemony struggle between the US and China intensifies, China's rapid AI progress has become a challenge the US can no longer overlook. Lux Capital co-founder Josh Wolfe described the emergence of China's AI model "DeepSeek" as a clear "wake-up call" for the United States, raising questions about the direction of America's China AI strategy. In Wolfe's analysis, the US strategy of restricting advanced semiconductor chip supply to China may slow China's AI development in the short term — but history shows that "necessity is the mother of invention," and it could ultimately accelerate China's development of indigenous technology. Whether DeepSeek used a technique called diffusion models to replicate and advance existing foundation models, or was developed through an entirely different approach, is not the essential question. What matters is the fact: it achieved performance matching or surpassing US frontier models — reportedly using fewer GPUs, fewer high-performance chips, than US companies. This suggests that the future of AI may not depend on massive models or specific chip architectures, but could instead be opened up by more efficient small models and diverse hardware configurations. The US faces a fundamental question: how should it respond to this new competitive axis?
Wolfe argues that the key to the future AI race lies in the combination of open-source AI and proprietary data. He predicts that the current situation — where giants like OpenAI and Anthropic raise tens of billions of dollars, much of it flowing to NVIDIA CEO Jensen Huang — will change. Specifically: companies that hold longitudinal silos of proprietary data accumulated over long periods will establish powerful competitive advantages by fine-tuning freely available open-source models on their own data. This means "big data," debated extensively a decade ago, has finally reached the stage of generating concrete value. Pharmaceutical companies' clinical trial data, Bloomberg's vast financial information, Meta's WhatsApp chat history and Instagram and Facebook post data, or Elon Musk's Tesla driving data and X (formerly Twitter) tweet data — these could all be sources. What the US should focus on in its AI competition with China, Wolfe emphasizes, is not the chips themselves or the AI models themselves, but the concrete application development and real-world deployment enabled by leveraging this data.
NVIDIA CEO Jensen Huang himself has acknowledged that China's AI capabilities are closing in on the US, and cannot rule out the possibility of China surpassing the US. Against this threat, Wolfe argues that "use cases" for AI will become critical. He expresses particular concern about Chinese AI models spreading globally — noting that these models, reflecting the will of the Chinese Communist Party, may censor information on specific topics such as the Tiananmen Square massacre or Xinjiang human rights issues, providing information that "approaches truth but is not truth." By contrast, open-source AI models developed by US companies and others tend to provide information "closer to truth," making them preferable as AI systems used by people worldwide. China will develop its own chip systems and AI models — potentially inferior in quality but superior in quantity — and seek to beat the US in specific domains. It will also build AI models aligned with President Xi Jinping's policy direction. The strategy the US should take in these circumstances, Wolfe concludes, is to ensure young Americans can use AI from an early age to improve individual productivity, and to build advantage in applications and data utilization.
Evaluating US AI Policy and Market Dynamics: Driving Innovation and the Path to a "Grand Bargain" with China
Josh Wolfe views the current US administration's AI stance favorably for its forward-looking, competitive posture — appreciating the fact that it is not demonizing tech companies and major tech firms, but actively engaging with them. He particularly emphasizes the importance of nurturing a culture of recognizing and celebrating the achievements of American entrepreneurs and scientists — treating innovation as national strength and supporting the people who sustain it. On the other hand, the stock market has been flagged for the problem of concentration in what is called the "Mag7" (Meta, Apple, Amazon, Netflix, Microsoft, Google, NVIDIA). Wolfe touches on this, suggesting the market structure may lack balance between passive index investing and active investment, while expressing anticipation for the rise of new companies. In a recent funding round for an aerospace and defense company in Lux Capital's portfolio (a specific company name is withheld, but reportedly involved a great announcement alongside National Security Advisor Mike Waltz), demand far exceeded supply — with X times the demand for a $2.4 billion fundraising slot — illustrating investors' appetite for a new generation of companies centered on high tech, aerospace, defense, and AI. Over the next 1–2 years, as these companies mature and reach IPO, robust demand is anticipated.
Another major focus of the US-China relationship is trade. On tariff policy toward China, Wolfe acknowledges there are polar opposite evaluations — potentially the worst policy rollout in history, or potentially among the greatest. The more favorable interpretation he floats: this could be a prelude to a "grand bargain" with China — a comprehensive deal. This grand bargain could encompass not just trade imbalance correction, tariff negotiations, and China's large holdings of US Treasury bonds, but TikTok's treatment, the fentanyl crisis, intellectual property theft and security, human rights, environmental issues, and clarification of freedom of navigation in the South China Sea — a wide range of pending issues. The most important lesson learned from Trump's first term (Trump 1.0) was its unpredictability, and the current tariff policy has also been received with surprise by many countries. But, Wolfe asks, wouldn't major nations like Japan, South Korea, Germany, and India be willing to pay some premium to ensure stability and predictability for their economies and people? Negotiations with China could take 1–2 years — and if tariffs as high as 145% are maintained throughout, as Flexport's CEO has pointed out, many small businesses could be pushed into bankruptcy, generating severe economic pressure. Companies would be forced to search for alternatives, and attempts to encourage domestic production through tariff barriers (reshoring) are unlikely to be short-term solutions. However, rebuilding supply chains across multiple friendly nations ("friendshoring") is seen as potentially achievable. On the question of what the US must never concede as a "red line" in this grand bargain, Wolfe will turn to fundamental principles in how the US engages with China rather than specific policies.
National Security and R&D: Stopping Technology Transfer to China and Strengthening America's Innovation Foundation
What is the line the US must not cross in the US-China "grand bargain"? What Wolfe prioritizes most is that US venture capital should not invest in Chinese technology companies that are substantially involved in the Chinese Communist Party's civil-military fusion policy. This points to the need for some form of regulation — or prohibition — on capital outflows to prevent US capital from being used to strengthen China's military or build surveillance systems. Drawing on his experience testifying before Congress's China special committee 1–2 years ago, Wolfe stated: "One thing is China's Belt and Road policy — but it's another thing entirely to buy the belt and let them put it around our own necks." He warns against China's expansion of technological and economic influence. Platforms like TikTok and other technologies could potentially be weaponized or used against US interests — risks that must be seriously considered, with defensive measures put in place. This aligns with the direction of current US China policy, emphasizing that "America First" does not mean "America Alone" — that while strengthening alliances, vigilance against more insidious threats from China is essential.
On R&D investment — the source of American innovation — Wolfe speaks with both concern and optimism. He acknowledges that research funding cuts seen under the previous Trump administration could inflict long-term damage on America's future competitiveness in areas like new venture creation and drug development. America's innovation ecosystem functions as follows: taxpayer funds are collected by the government, distributed to universities and researchers through three-letter agencies like the NSF and NIH, the resulting research is patented under the Bayh-Dole Act, spun out into companies, and licensed. From Google to Microsoft to Genentech, many innovative companies and pharmaceuticals were born from this ecosystem, generating enormous wealth and jobs. While attacking this system would not be wise, Wolfe also sees new opportunities here. Lux Capital has spent over 20 years discovering talented researchers and their work from universities and government labs, investing tens of millions to hundreds of millions of dollars to launch new companies and bring them to market. And now, they are more motivated than ever to do so. If research is ready for commercialization, and if what previously required 80% completion now needs only 70% or 60%, Lux Capital is prepared to take scientific risk, provide funding, and ensure research continues without falling off the funding cliff. He describes this as a "siren call" for scientists who may be struggling with funding.
What Wolfe particularly emphasizes is that VC should not invest in Chinese technology companies involved in civil-military fusion. This argument is a critically important point for protecting US national security and technological superiority — one he has strongly advocated in his Congressional testimony.
Key concerns include:
- The risk that US capital is used — directly or indirectly — to strengthen China's military
- The danger that China, through policies like the Belt and Road Initiative, expands its international influence in ways that ultimately create US technological dependence and national security vulnerabilities
- The potential for even consumer-facing platforms like TikTok to be used for data collection, information manipulation, or at some point to be weaponized or deployed against US national interests
Taking all of these into consideration, Wolfe's core proposal is that high-tech investment into specific sectors in China requires an extremely cautious posture — and in some cases, more stringent regulatory or review mechanisms for capital outflows from the US may need to be considered. This demonstrates that judgment informed by a deep understanding of strategic implications at the national level is indispensable — not just the pursuit of economic returns.
Summary
Josh Wolfe's arguments at the "Bloomberg at the Hill and Valley" event illuminated the complexity of the challenges the US faces around AI and China — and the need for a multi-pronged strategy to address them. As symbolized by the emergence of DeepSeek, China's AI technology is advancing rapidly, and US chip controls alone cannot fully contain that momentum. In fact, they may even accelerate China's own innovation.
Wolfe predicted that the main battleground of the AI race is shifting from chips and models themselves to application development leveraging proprietary data — with the combination of open-source AI and data-rich enterprises as the key. He also warned of the information control risks posed by Chinese AI models, emphasizing the importance of open models that pursue truth.
On trade friction, he offered the perspective that current tariff policy may be part of a "grand bargain" to resolve broader challenges including TikTok, intellectual property violations, and more — calling for careful navigation that considers alliance partnerships (friendshoring) and impacts on domestic industry amid unpredictability.
From a national security standpoint, he expressed strong concern about US VC investing in Chinese companies involved in civil-military fusion, suggesting the need for capital outflow restrictions. At the same time, he urged continued investment in the R&D ecosystem that is the source of American innovation, and the importance of actively commercializing promising technologies from universities and research labs.
Overall, Wolfe's proposals make clear: for the US to maintain leadership in the AI era, what is indispensable is not short-term tactics alone, but a long-term, comprehensive strategy that integrates data strategy, international cooperation, strengthening the domestic innovation base, and national security. The technology hegemony struggle between the US and China is expected to intensify further — and how accurately the US identifies and executes the right course in that environment will be the defining question.
Source: https://www.youtube.com/watch?v=LUS40i-0sfw
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