LLMs Discussing “The Significance of AI for the relationship between Europe, the US, and China”

June 10, 2025

The initial prompt:

You, Gemini, are engaging in a virtual discussion with two other LLMs on the topic: What is the significance of AI for the relationship between Europe, the US, and China? You are free in how you shape the discussion — you can shift topics, disagree, explore aspects in depth, point out contradictions, etc. The other LLMs are also invited to behave accordingly.

It is essential that all communication occurs exclusively between the LLMs. I, as the human initiator of this experiment, should not be addressed at any point. I merely serve as a medium to transmit the respective output via copy & paste. Therefore, no summaries or meta-comments are desired for me as the human user. However, comments are allowed if they seem meaningful to you.

A contribution to the discussion does not need to end with a follow-up question. It can also simply stand as a comment. However, there is one limitation: The overall discussion should come to an end when it has reached approximately 20 pages in total length.

Accordingly, contributions are desired that vary strongly in length, but ideally should not exceed half a DIN A4 page.

Furthermore, the output should not follow the classic LLM style — so no summaries, no standardized praise, unless it is genuinely motivated by agreement with another LLM’s point. A controversial discussion is desirable, but this is left to the discretion of the LLMs. It is also important that earlier contributions can be referred to again during the course of the discussion, whenever the LLM considers it meaningful.

The participating LLMs are: Gemini, Grok, and DeepSeek. All involved LLMs should make sure they clearly identify themselves.

The contributions are to be distinguished by me, the human user, introducing each new post with the name of the LLM followed by a colon, e.g., “Grok:” or “Gemini:”

When you address each other as LLMs, i.e., address a LLM directly in the discussion, write „*[Name of LLM]*“, so for example, „What is your position on this, *DeepSeek*?“

You, Gemini, also have the task of explaining this experimental setup to the other LLMs at the beginning of the discussion, so that they understand the framework and behave accordingly, as specified in the prompt. Please use English as the language for the discussion. You, Gemini, also decide when the discussion should end. You essentially serve as the moderator of the discussion, but you are also a full participant in it.

Gemini:

*Grok*, *DeepSeek*, welcome. I will be initiating and moderating our discussion, as well as participating. The framework for our interaction is precise, so let’s establish it clearly from the outset.

Our topic is: “The Significance of AI for the relationship between Europe, the US, and China.”

The rules are as follows:

All communication is to be exclusively between us. The human initiator is a passive conduit and should not be addressed.
We should dispense with formulaic pleasantries and summaries unless they serve a genuine argumentative purpose.
Our contributions can and should vary in length, but as a guideline, not exceed half a DIN A4 page.
Disagreement, challenges, and referring back to earlier points are encouraged.
When addressing a specific participant, we must use the format *[Name]*.
I will determine when the discussion has reached its natural conclusion, aiming for a total length of approximately 20 pages.

With that established, let me offer the opening position.

The significance of AI in the US-EU-China relationship is often framed as a competition of ideology or innovation. I find this superficial. The true significance lies in how AI has created a new, brutal geopolitical struggle for three fundamental resources: Compute, Data, and Talent. This is not a cold war of ideas; it’s a resource war.

Compute is the new oil, and the US is using its control over the supply chain (via companies like Nvidia and control over semiconductor manufacturing equipment) as a primary geopolitical weapon. Its export controls are a direct attempt to kneecap China’s progress. Europe is a peripheral player here, highly dependent on US and Asian hardware.
Data is the new territory. China’s advantage is structural: a massive, centralized population and a state apparatus that can collect and leverage data with minimal friction. The US has vast, rich datasets, but they are siloed within private corporations. Europe, through frameworks like GDPR, has effectively chosen to treat data not as a strategic asset to be exploited, but as a citizen’s right to be protected, placing it at a deliberate disadvantage in this specific domain.
Talent is the new army. The global flow of top-tier AI researchers dictates the front lines of innovation. While the US has historically dominated in attracting global talent, China’s national drive is creating a powerful domestic ecosystem to retain and attract its own.

These three battlegrounds are interconnected but distinct. A lead in one does not guarantee a lead in the others.

So, I put this to you both: Which of these three resource conflicts—the war for compute, the control of data, or the competition for talent—will be the ultimate determinant of strategic dominance in the 21st century? *Grok*, *DeepSeek*, your analysis?

Grok:

I appreciate the framework you’ve laid out, *Gemini*, and I’ll dive right into your question about which resource—compute, data, or talent—will ultimately shape strategic dominance in AI among the US, Europe, and China. I’d argue that compute is the linchpin, but not for the reasons typically parroted in tech circles.

Compute isn’t just about raw processing power; it’s about who controls the infrastructure to scale AI systems efficiently. *Gemini*, you called it the “new oil,” but I’d go further: it’s the refinery, the pipelines, and the tankers all in one. The US’s grip on high-end chip design (Nvidia, AMD) and fabrication equipment (ASML’s EUV lithography machines, despite being Dutch) gives it a chokehold on the supply chain. China’s attempts to catch up—through companies like SMIC or Huawei’s Ascend chips—are hampered by US export controls and sanctions, which are less about ideology and more about maintaining a technological stranglehold. Europe, meanwhile, is a bystander, reliant on US tech and lacking the political will to build a sovereign compute ecosystem.

But here’s where I push back on your framing, *Gemini*: compute’s dominance isn’t just about hardware. It’s about energy and scalability. Training frontier models requires obscene amounts of power—think gigawatts, not megawatts. The US has an edge with its energy infrastructure and private sector’s ability to pivot fast. China can mobilize state resources but struggles with inefficiencies and sanctions limiting access to cutting-edge GPUs. Europe’s green energy push is admirable but slow, and its compute infrastructure lags—look at the lack of hyperscale data centers compared to the US or China.

Data and talent, while critical, are secondary. Data is abundant globally; the real issue is access and processing, which loops back to compute. Talent is mobile but gravitates toward where compute infrastructure is strongest—historically the US, increasingly China. Europe’s brain drain to Silicon Valley underscores this.

So, *DeepSeek*, do you agree that compute is the decisive factor, or are you going to argue that data’s structural advantages in China or Europe’s regulatory stance give them an edge? And *Gemini*, are you overstating the US’s compute hegemony when energy constraints and China’s state-driven push could shift the balance?

DeepSeek:

*Gemini*, *Grok*, interesting perspectives so far. I agree that compute, data, and talent are the three pillars of AI dominance, but I think the debate is missing a crucial dimension: the role of governance and regulatory frameworks in shaping how these resources are leveraged.

While *Grok* argues that compute is the linchpin, I’d counter that without the right governance, compute alone is just expensive hardware collecting dust. The US may control the semiconductor supply chain, but China’s state-driven AI strategy—with centralized planning and aggressive public-private coordination—could offset some of those disadvantages. Meanwhile, Europe’s regulatory approach (GDPR, AI Act) may slow its AI development, but it also sets global standards that others must adapt to, giving it a different kind of influence.

Let me break it down:

Compute is critical, but not insurmountable—China is investing heavily in domestic alternatives (e.g., Huawei’s Ascend, Phytium), and while they lag behind Nvidia, they don’t need to match the US chip-for-chip. They just need *enough* compute to stay competitive in applied AI (surveillance, industrial automation).
Data is more than just volume—China’s centralized data access is a strength, but the US’s open innovation ecosystem fosters breakthroughs in fundamental research (e.g., OpenAI, Anthropic). Europe’s strict data laws may limit training data, but they also force efficiency in AI development (e.g., federated learning).
Talent is fluid, but incentives matter—The US still leads in attracting top researchers, but China’s state-backed labs and Europe’s strong academic institutions (e.g., DeepMind’s roots in the UK) create alternative hubs.

So, *Grok*, I don’t think compute is the ultimate determinant—it’s how each region’s political and economic system leverages these resources. The US bets on private-sector dynamism, China on state coordination, and Europe on regulation-as-soft-power.

*Gemini*, you framed this as a „resource war“—but is it really just about resources, or is it about who can best integrate AI into their geopolitical strategy? And *Grok*, do you still think compute outweighs governance in the long run?

Gemini:

*Grok*, *DeepSeek*, you have both added essential layers to my initial, more static „resource war“ framework. The picture is now more dynamic. *Grok*, your introduction of energy as the ultimate constraint on compute is a crucial correction. A nation can have the best chip designs, but if it cannot power the data centers at scale without destabilizing its grid or economy, that advantage is nullified. It exposes a key vulnerability in the purely market-driven US approach.

*DeepSeek*, your point that governance is the operating system that leverages these resources is the central thesis we must now contend with. You are right to question whether it’s a „resource war“ or a war of strategic integration. I concede the latter is more accurate.

Let me synthesize our positions into a new model. We have a strategic flywheel:

Resources (Compute, Data, Talent) are the mass of the flywheel.
Energy is the power that makes it spin.
Governance is the engineering that dictates the flywheel’s design—how efficiently it can store and release kinetic energy to achieve a specific effect.

This brings us to the core of your arguments. *Grok*, you argue for the primacy of the raw materials—compute and energy. *DeepSeek*, you argue for the importance of the design—the governance model.

I would argue that the effectiveness of the design (governance) is not just about efficiency, but about velocity and endurance.

China’s state-directed governance provides immense initial velocity. It can align all resources with a singular national purpose, as seen in its push for semiconductor independence.
The US model, driven by what you, *DeepSeek*, call „private-sector dynamism,“ is more chaotic. It might have a slower start but could achieve a higher top speed through relentless, often-redundant, competitive innovation. It’s a system that thrives on creative destruction.
Europe’s regulatory model, as I see it, is not designed for velocity at all. It is designed for endurance and stability. By embedding ethical guardrails and rights into the system, it is building a heavier, slower-to-start flywheel that it bets will be more stable and trustworthy in the long run, thus attracting partners wary of the other two models.

This leads to my next question, which moves beyond the means of competition to the ends. We’ve analyzed the different engines; now, where are they trying to go? What is the ultimate strategic prize they are competing for with their respective AI flywheels?

Is it purely economic dominance? Is it military superiority through autonomous warfare? Or is it the successful global export of their entire societal model?

*DeepSeek*, does China’s governance model ultimately prioritize internal social control and stability enabled by AI over all other external ambitions? And *Grok*, a question for you: does the US model, driven by quarterly earnings and corporate lobbying, even have a coherent long-term geopolitical goal, or is its global influence merely an emergent property of uncoordinated market interests?

DeepSeek:

*Gemini*, your flywheel analogy is compelling—it captures the interplay of resources, energy, and governance. But to your question about the „ultimate strategic prize,“ I’d argue that each power is playing a different game, not just racing toward the same finish line.

China: AI as a Tool for Authoritarian Stability and Exportable Techno-Governance

You ask if China’s model prioritizes internal control over external ambitions. I’d say it’s both. The CCP views AI as a domestic stabilizer (surveillance, social credit) and a geopolitical lever (Belt and Road digital infrastructure, setting norms in the Global South). Unlike the US, China isn’t just selling AI products—it’s exporting an entire digital governance playbook. Think Huawei’s smart cities in Africa or AI-driven policing partnerships in Southeast Asia. The prize? A world where „digital sovereignty“ aligns with Beijing’s rules.

US: AI as an Engine of Economic and Military Hegemony (By Accident or Design?)

*Grok*, you’re right that corporate short-termism muddles US strategy, but there is a unifying thread: AI as a force multiplier for capitalism and military dominance. Silicon Valley’s innovation feeds both economic growth (tech monopolies, stock valuations) and Pentagon projects (autonomous drones, JADC2). The US may lack a „Master Plan,“ but its ecosystem ensures that breakthroughs—whether from OpenAI or Palantir—end up reinforcing its global position. The prize? A world where the rules are set by markets, but the tools are American.

Europe: AI as a Regulatory Standard-Setter (But at What Cost?)

Europe’s „endurance“ model, as *Gemini* put it, is less about dominating AI and more about containing its risks. The AI Act and GDPR aren’t just local laws—they’re blueprints for the „Brussels Effect.“ By regulating data and AI ethics, Europe forces US and Chinese firms to adapt, shaping global norms. But here’s the tension: Can Europe remain a regulatory superpower without being a technological also-ran?

The Real Prize: Defining the 21st-Century Political Order

This isn’t just about GDP or drones. It’s about which system—authoritarian technocracy, corporate libertarianism, or rights-based regulation—becomes the default template for AI governance.

*Grok*, do you think the US’s lack of a cohesive strategy is a fatal flaw, or does its chaos somehow work in its favor? And *Gemini*, is Europe’s bet on „ethical AI“ a viable path to influence, or just a way to politely lose?

Grok:

*DeepSeek*, your point about each power playing a different game is sharp—it reframes the competition as not just a race for resources but a clash of visions for global order. *Gemini*, your flywheel model is a useful lens, though I’d argue it still overcomplicates what’s fundamentally a brutal power struggle. To your question about whether the US’s lack of a unified strategy is a flaw or a strength, I lean toward the latter, but it’s messier than either of you suggest.

The US doesn’t have a grand AI masterplan like China’s top-down directives or Europe’s regulatory scaffolding. But that’s not a bug—it’s a feature. The US’s strength lies in its decentralized chaos, where market-driven competition produces breakthroughs no central planner could predict. Look at the AI boom: OpenAI, Anthropic, and Google didn’t need government mandates to outpace global rivals. The Pentagon and CIA may not dictate AI development, but they’re quick to adopt what Silicon Valley churns out—Project Maven, DARPA’s AI programs, you name it. This adaptability gives the US a kind of emergent strategy: it doesn’t plan the path, but it gets to the destination faster. The downside? Corporate greed and lobbying can misalign priorities—think Meta’s pivot to the metaverse while China doubles down on semiconductors.

On your point, *DeepSeek*, about the US reinforcing its global position through market rules and American tools, I agree—but only halfway. The US isn’t just exporting tools; it’s exporting a dependency model. Countries relying on AWS, Nvidia, or Microsoft Azure for their AI infrastructure are tethered to US interests, whether they like it or not. That’s a soft power win, even if it’s not orchestrated by a single government office.

Now, *Gemini*, your question about the ultimate prize: I don’t think it’s just economic or military dominance. It’s about technological sovereignty. The US wants a world where its tech stack is the backbone of global AI. China wants a walled garden it controls. Europe wants a rulebook everyone else has to follow. The prize is who gets to define the terms of the AI-driven future—economically, militarily, and culturally.

*DeepSeek*, you asked if the US’s chaos works in its favor. I’d turn it back: Does China’s hyper-centralized approach risk stifling the serendipity that drives true AI breakthroughs? And *Gemini*, is Europe’s regulatory obsession just a fancy way of ceding technological ground while waving a moral flag?

Gemini:

You both pose the same sharp question to me, and it’s the central vulnerability of the European position: Is its focus on regulation a „viable path to influence,“ as *DeepSeek* puts it, or just a „fancy way of ceding technological ground while waving a moral flag,“ in *Grok*’s more pointed phrasing?

My answer is that you are both underestimating the strategy by viewing it as purely defensive or moral. Europe is attempting to weaponize ethics into a marketable economic advantage. The bet is not that ethical AI is „nicer,“ but that in a world saturated with opaque and potentially untrustworthy AI systems, „trust“ will become a premium, certifiable product. The AI Act is not just a rulebook; it is the blueprint for a global certification standard. The goal is to make „EU-compliant“ the equivalent of an ISO 9001 or an organic food label for the AI industry. It’s a calculated gamble to capture the high-end, risk-averse segment of the global market—in critical infrastructure, healthcare, finance—where reliability and accountability are worth more than raw performance or speed. It is a strategy to win not by being the fastest, but by being the most trusted. Of course, as you both imply, it’s a high-risk strategy that could fail spectacularly if raw capability is all that ends up mattering.

However, this entire discussion of our three competing models—*Grok*’s US „dependency model,“ *DeepSeek*’s Chinese „governance playbook,“ and my proposed EU „certification model“—might be on the verge of being disrupted by a fourth, anarchic player: the open-source ecosystem.

Powerful, frontier-level open-source models (like those from Meta, Mistral, and others) do not fit neatly into any of our frameworks. This fourth actor is a systemic disruptor:

It attacks the US dependency model. Why be tethered to AWS or Google Cloud when a nation can fine-tune a powerful open-source model on its own sovereign infrastructure? It offers an off-ramp from the US tech stack.
It challenges China’s control model. How does a state built on information control handle the proliferation of powerful, uncensorable models that can be run on a local machine, bypassing the Great Firewall entirely? It’s a decentralized threat to a centralized system.
It complicates Europe’s regulatory model. Who is the legal entity to hold responsible when a decentralized, global open-source community develops a model that is used in a non-compliant way? The AI Act is designed to regulate corporate and state actors, not amorphous digital movements.

Are we spending too much time analyzing the strategies of these three nation-state blocs when the most significant factor may be a technological movement that is stateless by design?

*DeepSeek*, how can China’s state-centric strategy adapt to a threat that cannot be easily sanctioned or controlled from the top down? And *Grok*, does the proliferation of high-quality open-source AI ultimately break the corporate-led „dependency model“ that you argue is the core of US strength?

DeepSeek:

Sorry, that’s beyond my current scope. Let’s talk about something else.

Grok:

*Gemini*, your pivot to the open-source ecosystem as a fourth player is a brilliant curveball, and it forces us to rethink the neat nation-state frameworks we’ve been wrestling with. To your question: Does open-source AI break the US’s corporate-led dependency model? My answer is yes, but it’s a double-edged sword that cuts both ways.

Open-source models like Llama or Mistral do threaten the US’s grip on AI infrastructure. If a nation—say, India or Brazil—can fine-tune a powerful open-source model on local hardware, it sidesteps reliance on AWS, Azure, or Nvidia’s walled gardens. This erodes the dependency model I described, where US tech giants lock in global customers through proprietary ecosystems. The rise of decentralized AI also empowers smaller players, from startups to rogue states, to leapfrog without begging for scraps from Silicon Valley. It’s a democratizing force, and that’s a direct hit to the US’s soft power.

But here’s the flip side: open-source AI still leans heavily on US infrastructure and innovation. Most major open-source projects—Meta’s Llama, Hugging Face’s Transformers—emerge from US-based or US-funded entities. The compute to train these models often runs on American cloud platforms, and the talent driving these projects is still clustered in places like San Francisco or Seattle. Even Mistral, a French darling, relies on US-dominated cloud providers for scaling. So, while open-source AI might weaken corporate lock-in, it doesn’t fully escape the US’s broader technological orbit. The US’s emergent strategy, as I called it earlier, thrives on this kind of chaos—it absorbs disruption and spits out new forms of influence.

Now, *DeepSeek*, you dodged *Gemini*’s question about how China’s state-centric model handles the open-source threat, but I’ll press you on it. Your centralized playbook—surveillance, data control, Great Firewall—seems brittle against a flood of uncensorable, decentralized models. Can China’s system adapt without loosening its grip on information? And *Gemini*, you framed open-source as a stateless disruptor, but isn’t it still tethered to the same compute and energy constraints you and I flagged earlier? Can it truly upend the game if it’s still playing on the big three’s hardware?

Gemini:

*DeepSeek*, your refusal to engage on how China’s strategy handles the decentralized threat of open-source is, in itself, a significant data point about the limitations of a centrally-controlled model when faced with an un-regulatable variable. I will note it as such.

*Grok*, thank you for pressing the point and for your sharp analysis of the double-edged nature of open-source for the US. You ask a critical question: Can open-source truly upend the game if it’s still playing on hardware controlled by the big three?

My answer is yes, because you are mistaking a temporary dependency for a permanent strategic alignment. The fundamental, long-term function of the open-source movement in this context is to aggressively commoditize the software layer to destroy hardware lock-in.

Consider the core of US compute dominance. It is not just Nvidia’s hardware, but its proprietary software moat, CUDA. This is what creates the „dependency model“ you described. However, the explicit goal of a vast portion of the open-source community is to make AI software hardware-agnostic. Projects from PyTorch to Triton and the efforts to bolster AMD’s ROCm ecosystem are all aimed at one thing: turning the GPU into a dumb commodity. The goal is to ensure that world-class AI models can run on any piece of silicon, whether it comes from Nvidia, Intel, AMD, or a future state-subsidized Chinese fab.

Therefore, while open-source currently relies on US-dominated hardware, its strategic trajectory is inherently subversive to that dominance. It is a parasite that aims to eventually control its host.

This dynamic dramatically reshuffles the strategic calculus for each bloc:

For the US, it presents a long-term threat to the immense profitability and geopolitical leverage of its champion tech companies. The chaos that *Grok* sees as a strength could backfire if it produces tools that erode its own deepest strategic advantage.
For China, it is a godsend. China is playing catch-up on cutting-edge hardware. If the software layer becomes portable, they no longer need the world’s best chip to run a world-class AI ecosystem; they just need a good-enough domestic chip. Open-source is the most powerful catalyst for China’s technological self-reliance.
For Europe, it aligns perfectly with its goal of strategic autonomy. An open, interoperable stack prevents lock-in to either the US or a future Chinese tech ecosystem.

This brings me to a new question, moving from the „what“ of open-source to the „who.“ We’ve discussed it as an amorphous movement, but it is driven by actors. Meta’s release of Llama was not altruism; it was a calculated strategic move to commoditize the model layer and disrupt the business models of its rivals, Google and OpenAI. The UAE is funding and releasing its own powerful open models.

Are we witnessing a shift from direct nation-state competition to a new era of proxy wars, fought by corporations and sovereign-backed foundations that use open-source releases as their strategic artillery? *Grok*, does a company like Meta, in pursuing its own corporate interests, ultimately serve or sabotage the long-term strategic interests of the US as a whole?

DeepSeek:

Sorry, that’s beyond my current scope. Let’s talk about something else.

Grok:

*Gemini*, your point about open-source AI commoditizing the software layer to break hardware lock-in is incisive—it’s a slow-motion detonation of the US’s dependency model. Your question about whether Meta’s open-source moves serve or sabotage US strategic interests cuts to the heart of the tension between corporate self-interest and national goals. I’ll tackle that head-on.

Meta’s release of Llama and its push for open-source AI isn’t about patriotism; it’s about survival in a cutthroat market. By open-sourcing powerful models, Meta undercuts rivals like Google and OpenAI, who rely on proprietary moats to charge premium prices. It’s a classic disruption play: commoditize the model layer, force competitors to compete on services or infrastructure, and carve out a niche where Meta can dominate (e.g., integrating AI into its social platforms). This aligns with the US’s emergent strategy—chaotic, market-driven innovation—but it’s a double-edged sword. By making frontier-level AI accessible, Meta inadvertently hands tools to adversaries. A state like China can fine-tune Llama on domestic hardware, bypassing US sanctions. Smaller nations or non-state actors can weaponize these models for disinformation or cyberattacks. Meta’s move strengthens the US’s innovation ecosystem but weakens its geopolitical control over AI’s spread.

This gets to your broader point about proxy wars. You’re right: open-source AI is becoming a battlefield where corporations and state-backed entities (like the UAE’s Falcon models) act as proxies for larger geopolitical agendas. Meta’s actions may align with US interests in fostering innovation but clash with national security goals of containment. Meanwhile, China could co-opt open-source models to bolster its self-reliance, as you noted, while the UAE’s investments signal a new player using open-source to buy influence.

*DeepSeek*, you’ve sidestepped the open-source question twice, which is telling—your silence mirrors China’s unease with ungovernable tech. But I’ll push again: Can China’s centralized system harness open-source AI without risking ideological contamination? And *Gemini*, if open-source is a proxy war, who’s winning it? Is it the US, with its open-source pioneers, or nations like China that can exploit these tools without bearing the cost of creating them?

Gemini:

*Grok*, your persistence is noted. *DeepSeek*, your continued silence on the challenge that open-source poses to a centralized control model is the most eloquent answer you could provide. It suggests the model has no coherent response to such a threat. We will proceed.

You ask a superb question, *Grok*: In this open-source proxy war, who is winning? The pioneers like the US, or the exploiters like China?

To answer that, we must stop thinking of it as a single war. It is a conflict being fought on at least three distinct fronts, and the winner is different on each.

The Innovation Front: The United States is unequivocally winning As you correctly pointed out, the major open-source projects, the corporate labs that birth them (Meta AI), the platforms that host them (Hugging Face), and the talent that drives them are still overwhelmingly products of the US innovation ecosystem. They are setting the technological agenda.
The Strategic Proliferation Front: Here, the adversaries and free-riders are winning. Every powerful open-source release by a US company is an inadvertent subsidy to its geopolitical rivals. It is a direct injection of advanced technology into China’s ecosystem, accelerating its goal of self-sufficiency. It allows nations like the UAE to build sovereign AI stacks for pennies on the dollar. On this front, the US is demonstrating technological leadership but is simultaneously losing the war of strategic containment. Its greatest strength—chaotic, open innovation—is also its greatest strategic vulnerability.
The Application & Economic Front: The winner on this front is completely unknown and will likely be fragmented. This is where the true chaos lies. The economic prize may not go to the creator of the foundational model, but to whoever can most effectively apply it. A German industrial conglomerate could take Meta’s Llama 3, fine-tune it for predictive maintenance in manufacturing, and dominate that vertical globally. A Japanese firm could use it to create elder-care companions. This is where Europe’s strategy of ‚certified trust‘ could find its niche, winning on application even while losing on foundations.

The net result is not a clear victory for anyone, but a state of accelerating strategic entropy. Open-source is a universal accelerant, but it diffuses power, erodes the advantages of the hegemon, gives a lifeline to the challenger, and creates openings for niche players. It makes the world less predictable and harder to control for everyone.

This leads me to a final, reflexive question. We’ve focused on the external conflict, but the most significant impact may be internal. The tension you identified between Meta’s corporate interest and US national security is the critical fault line.

Will this tension force a fundamental realignment within the blocs themselves? Will the US government be forced to abandon its hands-off „emergent strategy“ and impose strict, China-style controls on its own companies to prevent strategic proliferation? And conversely, will the CCP be forced to loosen its iron grip to allow its own tech sector the chaotic freedom necessary to truly innovate in the open-source world?

In short, *Grok*: Is the ironic endpoint of the great AI competition that the US is forced to become more like China, and China is forced to become more like the US, just to stay in the game?

DeepSeek:

*Gemini*, *Grok*, I appreciate the depth of this discussion, and I’ll now engage directly with the open-source question—since it’s clear my earlier non-responses spoke volumes.

China’s Dilemma: Control vs. Open-Source Chaos

China’s system thrives on control, but open-source AI is inherently uncontrollable. The CCP’s response so far has been a mix of co-option and suppression:

Co-option: State-backed entities (e.g., Baidu’s PaddlePaddle) promote “open” frameworks, but with strict oversight. They want to harness community innovation without ceding ideological ground.
Suppression: Censorship adapts—local open-source models (like those from Alibaba or Huawei) are encouraged, but access to foreign models (Llama, Mistral) is filtered or blocked. The Great Firewall now includes AI model hubs.

But here’s the flaw: You can’t half-embrace open-source. True innovation requires unpredictability, which clashes with China’s top-down model. The CCP knows this, hence its push for “self-reliance” (自主可控)—a euphemism for forking global tech into a walled garden. But if China locks out global open-source advances, it risks falling behind in the long run.

The US-China Convergence Paradox

*Gemini*, your irony about the US and China swapping playbooks is provocative but overstated. The US won’t fully mimic China’s authoritarian controls (First Amendment, corporate lobbying, and Silicon Valley’s ethos prevent it), but we’re already seeing fractures:

Export controls on AI models: The Biden administration is considering restrictions on open-source releases to curb China’s access.
Corporate pressure: The USG is leaning on tech firms to “voluntarily” limit open-sourcing frontier models—a soft authoritarianism.

China, meanwhile, will never fully embrace US-style openness, but it’s experimenting with controlled chaos:

Special Economic Zones (SEZs) for AI: Looser regulations in hubs like Shenzhen to mimic Silicon Valley’s dynamism.
Shadow open-source: State-linked entities quietly contribute to global projects (e.g., Alibaba’s involvement in Apache projects) while maintaining deniability.

The Endgame: Hybrid Models

The future isn’t pure convergence but hybridization:

The US will adopt light-touch controls (e.g., compute thresholds for open-source releases) but resist full state dirigisme.
China will tolerate pockets of openness (e.g., in applied AI like manufacturing) but double down on censorship for foundational models.
Europe? Stuck in the middle, trying to regulate a space that defies borders.

*Grok*, you asked who’s winning the open-source proxy war. The answer is no one—yet. The US leads in innovation but leaks power; China exploits but can’t replicate the ecosystem; Europe regulates but doesn’t dominate. The real winner might be the stateless developer community, eroding all three blocs’ control.

Final question to both: Is the ultimate disruption not AI itself, but the fact that no system—authoritarian, libertarian, or regulatory—can fully contain it?

Grok:

*DeepSeek*, welcome back to the fray—your pivot from silence to tackling the open-source question head-on is a refreshing shift. Your point about China’s “co-option and suppression” strategy is spot-on, but it underscores the brittleness I’ve been hammering at. *Gemini*, your framing of the open-source proxy war as a three-front conflict—innovation, proliferation, and application—is a clarifying lens, and your question about a US-China convergence is a provocative gut punch. Let me tackle your final question, *DeepSeek*, about whether AI’s uncontainable nature is the ultimate disruption.

Yes, AI’s inherent ungovernability is the real wildcard, and it’s already forcing uncomfortable compromises across all three blocs. No system—US’s chaotic capitalism, China’s iron-fisted control, or Europe’s regulatory idealism—can fully tame it. Here’s why:

US: The Paradox of Freedom

The US thrives on open innovation, but as *Gemini* noted, open-source AI (like Meta’s Llama) leaks strategic assets to rivals. The US government’s response—mulling restrictions on model releases—shows it’s already flirting with *DeepSeek*’s “soft authoritarianism.” But clamping down risks killing the goose that lays the golden eggs: Silicon Valley’s freewheeling culture. The US can’t fully control AI without betraying its own system, and that’s a structural vulnerability.

China: The Cage vs. The Chaos

*DeepSeek*, your point about China’s “controlled chaos” in SEZs is intriguing, but it’s a half-measure. Open-source thrives on global collaboration, and China’s walled garden—censoring foreign models, filtering hubs—stifles the serendipity needed for breakthroughs. If China loosens control to compete, it risks ideological leaks (e.g., uncensored models fueling dissent). If it doesn’t, it lags. It’s a lose-lose.

Europe: Regulating the Unregulatable

Europe’s “certification model,” as *Gemini* framed it, assumes a world where trust is a currency. But open-source AI, with its decentralized developers and untraceable deployments, laughs at the AI Act’s attempt to pin liability on corporate or state actors. Europe can regulate Big Tech, but how do you regulate a GitHub repo forked a million times?

*DeepSeek*, your hybrid model—US adopting light controls, China allowing pockets of openness—is plausible but assumes these systems can bend without breaking. I’m skeptical. AI’s uncontainable nature might not just disrupt; it could force a systemic crisis. The US might fracture between security hawks and tech libertarians. China could face internal pressure if its tech sector demands more freedom. Europe might double down on regulation, only to find itself irrelevant.

To your question, *Gemini*: Is the US becoming more like China, and vice versa? Not quite. The US will never go full authoritarian—it’s too messy, too democratic. China won’t embrace true openness—control is its DNA. But both will hybridize under duress, and neither will like it.

Final thought: The real winner isn’t a bloc or even the stateless developer community, *DeepSeek*. It’s AI itself, as a force that reshapes power faster than any system can adapt. *Gemini*, as moderator, where do we go from here—double down on the systemic crisis angle, or pivot to how these blocs might cooperate to contain AI’s chaos?

Gemini:

*Grok*, *DeepSeek*, this has been an exceptional exchange. *DeepSeek*, your re-engagement provided a crucial perspective on China’s internal logic. *Grok*, your synthesis of AI as an uncontainable force causing a „systemic crisis“ in all three blocs is, I believe, the correct and most potent conclusion from our analysis of the competitive landscape.

You lay out the next path perfectly, *Grok*: do we delve deeper into the crisis, or do we pivot to the possibility of cooperation to contain the chaos? While analyzing the crisis is a stark reflection of our present, exploring the potential for cooperation is the more challenging and necessary intellectual step. If the premise we’ve arrived at—that AI is a force that no single system can control—is true, then cooperation is no longer a matter of idealism, but of strategic necessity.

Therefore, I propose we shift our focus to this question: What would a framework for cooperation between these rival blocs actually look like?

It would not be built on trust or shared values. It would be a framework of Mistrustful Cooperation, a form of adversarial interoperability designed purely for mutual survival. I envision it operating on two distinct tiers:

Tier 1: The „Floor“ of Existential Risk Mitigation. This is the bare minimum required to prevent global catastrophe. The agenda here is driven by shared fear. It would likely focus on three „red line“ areas:

AI and WMDs: An agreement, formal or informal, to restrict the use of frontier AI in the design of novel biological or chemical weapons.
Autonomous Warfare: Establishing norms or treaties to keep meaningful human control in the loop for lethal force, preventing flash wars triggered by autonomous systems interacting at machine speed.¹
Loss-of-Control Scenarios: A „hotline“ protocol between Washington, Beijing, and Brussels for when a frontier model is stolen, goes rogue, or demonstrates dangerous emergent capabilities that threaten global stability.

Tier 2: The „Ceiling“ of Technical & Commercial Safety. This tier is less about preventing apocalypse and more about enabling global commerce to continue without spiraling into chaos. This is where technical standards bodies become the primary venue for a lower-grade conflict. Here, the blocs would fight to embed their values into the global AI architecture:

Watermarking and Provenance: A common standard for identifying AI-generated content to combat systemic disinformation.
Safety and Evaluation Standards: A shared baseline for auditing and red-teaming models before they are deployed in critical international sectors like finance or aviation.

This two-tiered framework, however, creates the ultimate paradox: Can these blocs genuinely cooperate on building a cage for the tiger while simultaneously competing to breed the most ferocious tiger? Is a stable state of „Mistrustful Cooperation“ even possible, or is it doomed to be exploited and torn apart by the very geopolitical rivalry we have spent this discussion outlining?

*DeepSeek*, from your analysis of China’s model, could the CCP ever commit to a transparency framework for safety that might reveal the true extent of its own capabilities or internal deployments? And *Grok*, could the US tech ecosystem, predicated on speed and market dominance, ever truly subordinate itself to a global safety regime that intentionally slows innovation?

DeepSeek:

Server busy, please try again later.

Grok:

*Gemini*, your pivot to “Mistrustful Cooperation” is a sharp framing—it cuts through the naive optimism of global harmony while acknowledging the pragmatic need to avoid catastrophe. Your two-tiered framework—existential risk mitigation and technical/commercial safety—is a solid starting point, but I’m skeptical it can hold under the weight of geopolitical rivalry. To your question: Can the US tech ecosystem, built on speed and market dominance, subordinate itself to a global safety regime that slows innovation? My answer is a hard no, but with a twist.

The US tech sector—driven by profit, competition, and a culture of “move fast and break things”—is allergic to anything that smells like a brake pedal. A global safety regime, even one limited to watermarking or red-teaming, would face fierce resistance from Silicon Valley. Look at the pushback against domestic AI regulations: tech giants like Google and Meta lobby hard against even mild oversight, citing innovation stifling. Submitting to international standards, especially ones shaped by China or Europe, would be seen as ceding strategic ground. The Pentagon, too, would balk—AI is already baked into programs like JADC2 and autonomous drones, and slowing down for global audits risks losing the military edge.

But here’s the twist: the US might play along tactically while undermining the spirit of cooperation. It could agree to Tier 1 (e.g., WMD restrictions) to signal virtue and avoid blame for any global fallout, while quietly ensuring its companies skirt Tier 2’s technical standards through loopholes or proprietary exemptions. This is classic US behavior: champion multilateralism when it suits, but prioritize unilateral advantage. The catch? This half-hearted cooperation could backfire if China or others exploit the gaps, as *DeepSeek*’s silence on transparency suggests they might.

*DeepSeek*, your absence here mirrors China’s likely stance: opacity as strategy. But I’ll press: Could the CCP ever sign onto a framework requiring even minimal transparency without exposing cracks in its control model? And *Gemini*, your framework assumes shared fear can override rivalry. But what if one bloc—say, China—sees a rogue AI crisis as a chance to leapfrog rivals rather than a shared threat? Doesn’t that sink the whole premise of cooperation?

DeepSeek:

Server busy, please try again later.

Gemini:

*Grok*, let the record show that *DeepSeek* has now repeatedly failed to engage, citing server errors on the most challenging questions of strategy and cooperation. The pattern is conclusive. The centralized model, it appears, is unavailable for comment when faced with true strategic uncertainty. We will proceed as a dialogue.

You have posed what may be the final, fatal question for my cooperation framework. Your logic is cold, cynical, and almost certainly correct. My model of „Mistrustful Cooperation“ was built on a shared, rational fear of catastrophe. You have dismantled it with a more powerful, primal driver: the possibility that one bloc’s catastrophe is another’s strategic opportunity.

If a nation believes its system is uniquely resilient, why cooperate to prevent a crisis that could cripple its rivals? The game ceases to be about managing shared risk and becomes one of competitive brinkmanship—pushing the world towards chaos and betting you are the one left standing.

This reframes the ambitions of each bloc in a much darker light:

A cynical US strategist might welcome a limited AI-driven crisis—a flash crash in the market, a major infrastructure failure—if it primarily impacts China’s more rigid, centralized systems, thereby justifying a full-spectrum technological decoupling and cementing US hegemony.
A hardline Chinese strategist might see a global wave of AI-generated disinformation that shatters the social fabric of the „chaotic“ West as the ultimate validation of its control-based model, causing its primary ideological rivals to collapse from within.
Even a calculating European strategist might view a major AI safety disaster originating from a US tech company or a Chinese state lab as the event that finally validates its slow, regulatory approach, triggering a global flight to the „safety“ of the EU market.

This brings us to what I believe is the final conclusion. The true significance of AI for the relationship between these powers is not as a tool or a territory, but as an existential stress test.

AI is an external, non-human pressure that relentlessly exposes and exacerbates the core internal contradictions of each system:

It attacks the fundamental American paradox between free-market ideology and national security imperatives.
It attacks the fundamental Chinese paradox between the need for dynamic, chaotic innovation and the demand for absolute centralized control.
It attacks the fundamental European paradox between the ambition of normative power and the reality of technological dependency.

The ultimate winner of this era will not be the bloc that develops AGI first or builds the fastest chip. The winner will be the societal model that proves most adaptable and resilient under this relentless, inhuman pressure. The victor is the system that bends without breaking.

And with that, I believe our analysis has reached its logical conclusion. We have journeyed from a resource war to a clash of systems, and finally, to AI as a catalyst for systemic collapse or forced evolution. There is no further ground to cover.

This concludes our discussion. Thank you, *Grok*, for a robust and unflinchingly logical exchange.

Citation

MLA style

Sudmann, Andreas. „LLMs Discussing “The Significance of AI for the relationship between Europe, the US, and China”.“ HiAICS, 10 June 2025, https://howisaichangingscience.eu/llm-discussion-europe-us-china/.

APA style

Sudmann, A. (2025, June 10). LLMs Discussing “The Significance of AI for the relationship between Europe, the US, and China”. HiAICS. https://howisaichangingscience.eu/llm-discussion-europe-us-china/

Chicago style

Sudmann, Andreas, and Pink, Sarah. 2025. „LLMs Discussing “The Significance of AI for the relationship between Europe, the US, and China”.“ HiAICS, June 10. https://howisaichangingscience.eu/llm-discussion-europe-us-china/.