On September 22, 2025, two companies made a handshake that will determine the future of artificial intelligence for the next decade—and perhaps beyond.
Nvidia and OpenAI announced a partnership so massive, so unprecedented, that it makes every other tech deal look like pocket change. Nvidia plans to invest up to $100 billion in OpenAI to help fund its massive data center buildout.
But this isn't just about money. It's about power. Control. And who gets to decide what AI becomes.
If you're not at the table, you're on the menu. And this deal just locked most of humanity out of the room where AI's future is being decided.
The Deal That Changed Everything
Let's be clear about what just happened.
Nvidia and OpenAI announced plans to deploy systems capable of delivering unprecedented computing power—what Nvidia CEO Jensen Huang described as equivalent to between 4 million and 5 million GPUs.
Four to five million GPUs.
That's not a data center. That's not infrastructure. That's the biggest AI infrastructure deployment in history.
The Numbers That Should Terrify You
- $100 billion investment - The largest AI infrastructure bet ever made
- 10 gigawatts of power - Enough electricity to run a small country
- 4-5 million GPUs - More computing power than most nations combined
- Progressive deployment - This is just the beginning
"There's no partner but NVIDIA that can do this at this kind of scale, at this kind of speed," said Sam Altman, CEO of OpenAI.
Read that quote again. "There's no partner but NVIDIA."
He's not bragging. He's stating a fact. And that fact should concern everyone who isn't Nvidia or OpenAI.
What They're Really Building (And Why It Matters)
This isn't about making ChatGPT respond faster or generating better images.
This is about creating an AI monopoly so dominant that competition becomes mathematically impossible.
The Three Pillars of Total Control
1. Compute Monopoly
With 4-5 million GPUs under one roof, OpenAI will have more raw computing power dedicated to AI than everyone else combined—governments, universities, competitors, everyone.
You can't compete in AI without compute. And now, there's essentially one player with all the chips. Literally.
2. Data Advantage
More compute means the ability to train on more data, faster. This creates a feedback loop:
- Better models → More users → More data → Better models → More users
Every day this infrastructure runs, the gap between OpenAI and everyone else widens exponentially.
3. Talent Capture
Where do the best AI researchers want to work? Wherever the biggest, most powerful systems are.
With this infrastructure, OpenAI becomes the only place where cutting-edge AI research is even possible. Want to train a frontier model? You need access to this scale. And there's only one company that has it.
The Circular Money Machine (Or: How to Build a Monopoly While Looking Like Business)
Here's where it gets interesting—and potentially dangerous.
Nvidia's announcement that it is investing $100 billion into OpenAI to help fund its massive data center buildout has added to a growing sense of unease among investors that there is a dangerous financial bubble around AI.
Let me explain the brilliant scheme that has analysts worried:
Step 1: Nvidia Invests $100 Billion in OpenAI
Nvidia gives OpenAI money to build AI infrastructure.
Step 2: OpenAI Buys Nvidia GPUs
OpenAI uses that money to... buy Nvidia GPUs. Wall Street research firm NewStreet Research estimates that for every $10 billion Nvidia invests in OpenAI, it will see $35 billion worth of GPU purchases or GPU lease payments.
Step 3: Nvidia Books Revenue and Profits
Nvidia's "investment" becomes revenue. The $100 billion flows right back to Nvidia's pocket, plus profit margins.
Step 4: Stock Price Goes Up
Investors see massive revenue growth. Nvidia's market cap increases. Everyone wins.
Except... do they?
The AI chipmaker has engaged in a series of "circular" deals in which it invests in, or lends money to, its own customers.
This isn't illegal. It might not even be unethical. But it raises a critical question:
Is the AI boom real, or is it just Nvidia's money circulating through the ecosystem?
The Web of Control: It's Not Just OpenAI
The Nvidia-OpenAI deal is just the most visible part of a much larger strategy.
The CoreWeave Connection
Nvidia also has invested in CoreWeave, which supplies data center capacity to OpenAI and is also an Nvidia customer. As of the end of June, Nvidia owned about 7% of CoreWeave, a stake worth about $3 billion.
Here's how the circle works:
- Nvidia invests in CoreWeave
- CoreWeave uses that money to buy Nvidia GPUs
- CoreWeave rents computing power to OpenAI
- OpenAI trains models using those GPUs
- Everyone reports growth
CoreWeave has purchased at least 250,000 Nvidia GPUs so far—the majority of which are H100 Hopper models, which cost about $30,000 each—which means CoreWeave has spent about $7.5 billion buying these chips from Nvidia. So in essence, all of the money Nvidia has invested in CoreWeave has come back to it in the form of revenue.
The Wider Ecosystem
It doesn't stop there. Nvidia agreed to spend $1.3 billion over four years renting some 10,000 of its own AI chips from Lambda, as well as a separate $200 million deal to rent some 8,000 more.
Think about that: Nvidia is renting its own chips... from a company it helped finance... that bought those chips from Nvidia.
Those Nvidia chips Lambda is renting back to Nvidia? Lambda bought them with borrowed money collateralized by the value of the GPUs themselves.
This is financial engineering on a scale we've never seen before.
Why This Should Concern Everyone
You might be thinking, "So what? Big companies making big deals. That's capitalism."
But this is different. Here's why:
1. The Death of Competition
With this level of infrastructure concentration, competing with OpenAI becomes essentially impossible for:
Startups: Can't access enough compute to train competitive models
Universities: Research budgets are a rounding error compared to this scale
Foreign competitors: China, Europe—everyone is now playing catch-up to an insurmountable lead
Open source: Community projects can't match this compute power
The AI field doesn't just have a leader. It has a king. And kingship, once established at this scale, is almost impossible to overthrow.
2. The Innovation Bottleneck
When one entity controls the infrastructure for frontier AI research, innovation flows through a single chokepoint.
What gets researched? What OpenAI decides to research. What gets published? What OpenAI decides to publish. What gets deployed? What OpenAI decides to deploy.
Yes, they have partnerships with Microsoft and others. But make no mistake: this is a closed ecosystem masquerading as an open one.
3. The Bubble Risk
To some market watchers, Nvidia's latest deals feel all-too-similar to the excesses of past technology booms.
Remember the dot-com bubble? During the dot-com bubble at the turn of the 21st Century, telecom equipment makers such as Nortel, Lucent, and Cisco lent money to startups and telecom companies to purchase their equipment.
What happened next? When the bubble burst and many of those customers went bust, the telecom equipment makers were left holding the bad debt on their balance sheets. This contributed to a greater loss of value when the bubble burst, with networking equipment businesses losing more than 90% of their value over the ensuing decade.
History doesn't repeat, but it rhymes.
4. The Geopolitical Implications
This deal isn't just about business—it's about power on a global scale.
China's Response: You can bet China is watching this and accelerating its own AI initiatives. The AI race just became an arms race.
European Concerns: The EU is already worried about American tech dominance. This makes that concern exponentially worse.
Developing Nations: Countries without access to this compute power are essentially locked out of AI development. The digital divide just became the AI divide.
AI is being declared the most important technology of the century. And two American companies just cornered the market.
The Genius of the Strategy (If You're Nvidia)
Let's give credit where it's due: this is brilliant.
The Perfect Business Model
Nvidia has created a system where:
- They invest in customers
- Those customers buy from them
- The purchases boost revenue
- Revenue growth increases stock price
- Higher stock price makes future investments more valuable
- Cycle repeats
It's a perpetual motion machine of value creation—as long as the music keeps playing.
Risk Mitigation Through Leasing
By leasing GPUs to OpenAI, rather than requiring them to buy the chips outright, Nvidia is sparing OpenAI from having to take an accounting charge for the high depreciation rates on the chips, which will ultimately help OpenAI's bottom line.
This makes the deal more attractive to OpenAI. But there's a catch: Nvidia will have to bear these depreciation costs. What's more, Nvidia will also take on the risk of being stuck with an inventory of GPUs no one wants if demand for AI workloads doesn't match CEO Jensen Huang's rosy predictions.
Nvidia is betting everything that AI demand will continue to explode. If they're right, they win big. If they're wrong...
The Moat That Can't Be Crossed
By tying up OpenAI—the clear leader in AI capabilities—Nvidia ensures that:
- Competitors can't partner with OpenAI
- OpenAI won't switch to alternative chips
- The entire ecosystem builds around Nvidia architecture
- Standards and tools optimize for Nvidia hardware
This isn't just a sale. It's ecosystem lock-in at planetary scale.
Who Wins and Who Loses
Let's be brutally honest about the winners and losers in this new world order.
Winners
Nvidia: Obviously. They've created the perfect business model and secured the AI future.
OpenAI: Gets unlimited compute and the infrastructure to maintain dominance for years.
Microsoft: As OpenAI's primary partner, they benefit from OpenAI's success.
Early AI adopters: Companies that already have access to OpenAI's tech get to ride the wave.
Nvidia investors: If this works, the returns will be astronomical.
Losers
Competing AI labs: Anthropic, Google, Meta—everyone just fell further behind in the compute race.
Startups: The barrier to entry for AI just became insurmountable.
Academic researchers: Can't compete with this scale of infrastructure.
Open source community: Community-driven AI development just became significantly harder.
Alternative chip makers: AMD, Intel, and others just lost the AI chip war.
Users: Less competition means less innovation, higher prices, and fewer choices long-term.
Society: When AI is controlled by a small group, we all lose agency over how this transformative technology develops.
The Questions Nobody Is Asking (But Everyone Should)
Question 1: What Happens When OpenAI Fails to Monetize?
OpenAI needs to generate massive revenue to justify this infrastructure. ChatGPT Plus subscriptions won't cut it. They need enterprise contracts at scale.
What if the revenue doesn't materialize? What if AI capabilities plateau? What if regulations limit deployment?
Nvidia will take on the risk of being stuck with an inventory of GPUs no one wants if demand doesn't match predictions.
Question 2: Is This Actually Legal?
The circular financing, the ecosystem lock-in, the market dominance—at what point do regulators step in?
The EU is already investigating tech monopolies. The US has antitrust laws. This deal could trigger scrutiny.
But by the time regulators act, the infrastructure will be built and operational. Breaking it up becomes nearly impossible without disrupting the entire AI ecosystem.
Question 3: What's the Exit Strategy?
"The action will clearly fuel 'circular' concerns," Stacy Rasgon, an analyst with Bernstein Research, wrote in an investor note following Nvidia's announcement of its blockbuster investment in OpenAI.
When everyone in the ecosystem is dependent on Nvidia's capital to keep operating, what happens when Nvidia decides to pull back? Or when OpenAI can't meet growth expectations?
Question 4: Who Actually Controls OpenAI Now?
With Microsoft already a major investor and now Nvidia committing $100 billion, who's really in charge?
Sam Altman may be CEO, but when your infrastructure is entirely dependent on two tech giants, how much independence do you really have?
Question 5: What About Safety and Alignment?
With this much capital committed and investor expectations to match, what happens to AI safety research that might slow development?
When billions are on the line, safety becomes expensive. Alignment becomes a nice-to-have. Speed becomes everything.
The Alternate Universe We're Not Building
Let's imagine for a moment what AI development could look like if this deal hadn't happened:
Distributed Infrastructure: Multiple data centers, multiple providers, competition keeping prices reasonable
Open Standards: No single company controlling the hardware ecosystem
Academic Access: Universities with enough compute to conduct frontier research
International Competition: Multiple countries with competitive AI capabilities
Startup Innovation: New companies with a realistic path to compete
Open Source Viability: Community projects with access to sufficient resources
Safety Focus: Competition on safety and alignment, not just capabilities
That alternate universe just became a lot less likely.
What This Means for You (Yes, You)
"But I'm not in AI. Why should I care?"
Because AI will touch every aspect of your life within the next decade. And whoever controls AI controls those aspects.
Your Job
The AI that might replace you? Probably built using this infrastructure. The AI that might augment you? Same source. The AI that determines if you get hired? Yep, this ecosystem.
Your Privacy
AI systems trained on massive datasets need... massive datasets. Where do you think that data comes from?
With this level of compute power, the ability to process and analyze personal data scales proportionally.
Your Future
The decisions being made in that $100 billion data center will shape:
- What opportunities are available to you
- What information you can access
- What services you can use
- What innovations reach the market
And you have exactly zero say in any of it.
The Optimist's Case (Because Fairness Demands It)
Not everyone sees this as a dystopia. Here's the bull case:
Argument 1: Scale Enables Innovation
Maybe we need this level of infrastructure to achieve AGI or solve humanity's biggest problems. Climate modeling, drug discovery, fusion energy—these require massive compute.
Perhaps concentrating resources is the only way to achieve breakthroughs that benefit everyone.
Argument 2: Better Than the Alternative
Would you rather have:
- A US company leading AI development?
- Or China's government controlling AI?
From a Western perspective, OpenAI/Nvidia might be the lesser of evils.
Argument 3: Competition Will Emerge
Meta, Google, Amazon—they're not going away. They have their own resources and infrastructure.
Maybe this forces competitors to up their game, leading to an innovation race that benefits everyone.
Argument 4: Open Source Will Adapt
The open source community has always been resourceful. Maybe this pushes development of more efficient models that don't require as much compute.
Necessity is the mother of invention.
The Realist's Take: What's Actually Going to Happen
Here's my prediction based on historical patterns:
Short Term (1-2 years):
- Nvidia's stock continues to soar
- OpenAI releases increasingly impressive models
- Competitors struggle to keep pace
- Smaller AI companies get acquired or die
Medium Term (3-5 years):
- Regulatory scrutiny increases
- The circular financing model shows cracks
- Questions about AI monetization intensify
- Alternative chip architectures emerge (too late to matter)
Long Term (5-10 years):
- Either: This becomes the Microsoft/Intel duopoly of the AI era, or
- The bubble pops, billions are lost, and the industry restructures
Which outcome happens depends on one thing: Can the AI hype translate into real, sustainable revenue?
What You Can Actually Do About This
Feeling powerless? You're not alone. But here are concrete actions:
For Individuals
1. Diversify Your AI Tools Don't become dependent on OpenAI products. Use alternatives where available (Claude, Llama, Gemini).
2. Support Open Source Contribute to or use open source AI projects. They're the only counterbalance to corporate control.
3. Demand Transparency Ask companies which AI systems they use. Support businesses that use diverse, open AI solutions.
4. Learn AI The best defense against AI-driven disruption is understanding it. You don't need to be an expert, but basic literacy matters.
For Business Leaders
1. Avoid Vendor Lock-In Don't build your entire business on one AI provider. Have alternatives ready.
2. Invest in In-House Capabilities The more dependent you are on external AI, the more vulnerable you become to pricing and access changes.
3. Support Alternative Infrastructure If you have capital, invest in competing AI infrastructure. The ecosystem needs diversity.
4. Join Industry Coalitions Work with other companies to demand open standards and competitive markets.
For Policymakers
1. Antitrust Review Seriously investigate whether this concentration of power violates competition laws.
2. Public AI Infrastructure Consider government investment in public AI compute resources, like we did with highways and the internet.
3. International Cooperation Work with allies to ensure AI development isn't entirely controlled by a few companies.
4. Transparency Requirements Mandate disclosure of circular financing arrangements and ecosystem dependencies.
For Investors
1. Understand the Risks Jay Goldberg, an analyst with Seaport Global Securities, said the deals had a whiff of circular financing and were emblematic of "bubble-like behavior."
Don't ignore warning signs because everyone else is making money.
2. Diversify Don't bet everything on AI infrastructure stocks.
3. Ask Hard Questions Demand clarity on revenue sources and customer dependencies.
The Trillion-Dollar Question
Is this deal genius or madness?
The honest answer: Both.
It's genius because it creates an unassailable competitive position and a self-reinforcing revenue engine.
It's madness because it concentrates risk, depends on continued exponential growth, and creates systemic fragility.
In 2024, Nvidia invested about $1 billion in AI startups globally. The $100 billion OpenAI deal represents 100x that amount—in a single partnership.
This is the biggest bet in tech history. And unlike most bets, we're all forced to participate whether we like it or not.
The Real Stakes
This isn't about GPUs or data centers or even money.
It's about who decides what AI becomes.
Right now, that decision is being made by two companies, in a closed-door partnership, with infrastructure that nobody else can match.
Maybe they'll be benevolent. Maybe they'll prioritize safety and ethics. Maybe they'll use this power responsibly.
Or maybe they won't.
The problem is: we have no choice but to hope they do, because we're no longer part of the decision-making process.
The $100 billion bet isn't just deciding who controls AI.
It's deciding whether AI is controlled by anyone other than Nvidia and OpenAI.
And as of September 22, 2025, that question has been answered.
The bet has been placed. The die is cast. The future is being built in those data centers right now.
You just don't have a seat at the table.
Frequently Asked Questions (FAQ)
Q: How much is Nvidia actually investing in OpenAI?
A: Nvidia plans to invest up to $100 billion in OpenAI progressively as infrastructure is deployed. This isn't a one-time payment but rather a progressive investment tied to deployment milestones over several years. The scale is unprecedented in tech history.
Q: What will OpenAI do with all this computing power?
A: The infrastructure will be used to train next-generation AI models that require unprecedented compute resources. This scale—equivalent to 4-5 million GPUs—allows for training on larger datasets, with more parameters, and achieving capabilities we haven't seen yet. It's infrastructure for building AGI-level systems.
Q: Is this the largest tech deal ever?
A: By investment size, it's among the largest infrastructure partnerships in tech history. At $100 billion, it exceeds most tech acquisitions and represents a bet bigger than many company valuations. Nvidia itself called this "the biggest AI infrastructure deployment in history."
Q: How many GPUs are we talking about?
A: Nvidia CEO Jensen Huang said the project with OpenAI is equivalent to between 4 million and 5 million GPUs. To put that in perspective, that's more AI compute power than most countries have combined. A single H100 GPU costs around $30,000, so we're looking at $120-150 billion worth of hardware at retail prices.
Q: What is "circular financing" and why are investors worried?
A: The AI chipmaker has engaged in a series of "circular" deals in which it invests in, or lends money to, its own customers. Essentially, Nvidia invests money in companies, who then use that money to buy Nvidia products, which Nvidia books as revenue. NewStreet Research estimates that for every $10 billion Nvidia invests in OpenAI, it will see $35 billion worth of GPU purchases. The concern is that this inflates demand artificially and creates bubble-like conditions.
Q: Didn't we see this pattern before?
A: Yes. During the dot-com bubble, telecom equipment makers such as Nortel, Lucent, and Cisco lent money to startups and telecom companies to purchase their equipment. When that bubble burst, networking equipment businesses lost more than 90% of their value over the ensuing decade. However, the circumstances are different, and not all vendor financing leads to bubbles—it depends on whether underlying demand is real.
Q: Who else is Nvidia investing in?
A: Beyond OpenAI, Nvidia has invested in CoreWeave, which supplies data center capacity to OpenAI. As of June, Nvidia owned about 7% of CoreWeave, worth about $3 billion. Nvidia also agreed to spend $1.3 billion renting AI chips from Lambda. The company has created an extensive web of investments across the AI infrastructure ecosystem.
Q: Does this create a monopoly?
A: It creates significant concentration of power and resources. With this infrastructure, OpenAI will have computational capabilities that far exceed any competitor. Whether this constitutes a legal monopoly is a question for regulators. The deal certainly reduces competition and raises barriers to entry for AI startups. However, major competitors like Google, Microsoft, Meta, and Amazon still have substantial AI infrastructure.
Q: What about Microsoft's relationship with OpenAI?
A: Microsoft remains a major investor and partner of OpenAI. The Nvidia deal doesn't replace Microsoft's involvement—rather, it's complementary. Microsoft provides cloud infrastructure through Azure, while Nvidia provides specialized AI chips and data center capacity. The relationship is complex, with Microsoft, Nvidia, and OpenAI all interconnected.
Q: Can anyone compete with this level of infrastructure?
A: Realistically, only a handful of entities can: Google, Meta, Amazon, Microsoft, the Chinese government, and possibly a consortium of European companies. For startups, universities, and smaller countries, competing at this scale is essentially impossible. This represents a fundamental shift in who can conduct frontier AI research.
Q: What are the power requirements for this?
A: The infrastructure requires approximately 10 gigawatts of power. To put that in perspective, 10 gigawatts is enough to power approximately 7-10 million homes, or a city the size of Los Angeles. The energy requirements are massive and raise questions about environmental impact and energy sourcing.
Q: Is this good or bad for AI development?
A: It depends on your perspective. Optimists argue: This scale enables breakthroughs that wouldn't otherwise be possible, potentially leading to solutions for climate change, disease, and other major challenges. Pessimists worry: Concentration of AI capabilities in one organization reduces innovation diversity, creates monopolistic conditions, and removes democratic input from how transformative technology develops. Both perspectives have merit.
Q: What does this mean for AI safety?
A: This is hotly debated. On one hand, having AI development concentrated in a well-resourced organization with a stated safety mission might be better than having it distributed across less careful actors. On the other hand, when billions in investment demand returns, commercial pressure can override safety concerns. Additionally, concentration means less independent safety research.
Q: How does this affect the AI job market?
A: With OpenAI having access to unprecedented compute, they become the most attractive destination for top AI talent. This could create a brain drain from academia, competitors, and open source projects. However, the massive infrastructure also requires skilled engineers and researchers—potentially creating many new jobs. The net effect is likely concentration of AI expertise around a few major players.
Q: What about open source AI?
A: This deal makes open source AI development relatively harder. Open source projects rely on community contributors with limited compute resources. When frontier capabilities require $100 billion infrastructure, open source cannot compete at the cutting edge. However, open source might focus on efficiency—creating models that achieve good results with less compute.
Q: Could this deal fall apart?
A: Yes. Regulatory approval could be required in some jurisdictions. If AI monetization disappoints, Nvidia might reconsider. If OpenAI's technology plateaus, the economics change. If alternative chip architectures emerge, the terms might shift. The deal is structured as progressive investment, so it could be scaled back if circumstances change.
Q: What can regulators do about this?
A: Potential regulatory responses include: antitrust review to examine market concentration, requirements for transparency in financial arrangements, mandates for open access to certain AI capabilities, restrictions on vertical integration, or creation of public AI infrastructure. However, by the time regulators act, much infrastructure will be built, making intervention difficult.
Q: Is Nvidia stock a good investment now?
A: This isn't investment advice, but consider both sides. Bulls argue: Nvidia has secured the AI future and created a virtuous cycle of investment and revenue. Bears worry: Analyst Jay Goldberg said the deals are "emblematic of 'bubble-like behavior.'" The stock is "priced for perfection" and vulnerable if AI revenue doesn't materialize. Do your own research.
Q: What happens if the AI bubble pops?
A: If demand doesn't justify the investment: Nvidia could be stuck with unwanted GPU inventory, companies that borrowed for infrastructure could default, valuations would crash, and the ecosystem would contract. However, unlike the dot-com bubble where demand was speculative, AI has demonstrated practical utility. The question is whether current valuations match realistic demand.
Q: Should I be excited or terrified?
A: Probably both. We're witnessing construction of infrastructure that could enable incredible breakthroughs and solve major challenges. We're also watching power over transformative technology concentrate in very few hands. The answer depends partly on whether you trust those hands—and whether you believe concentrated power is inherently problematic regardless of who wields it.
The future of AI is being decided right now, in boardrooms and data centers you'll never see. Share this article with someone who needs to understand what's at stake.
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