The recent AI boom is being propelled by circular financing, where a few large companies, including Nvidia, Microsoft and AMD, finance each other’s expansions and lock in future demand.
These few companies are signing multibillion-dollar contracts, borrowing against hardware and investing in each other’s projects. The money that is circulating within this closed economy is counted as fresh wealth every time it passes through the system.
Some are warning that this is causing an AI bubble that is unsustainable and could lead to a crash, comparing it to the dot-com bubble. Others are defending the funding model and see it as a sign of a powerful technological transformation.
Related:
- The AI bubble is bursting
- AI Industry’s Illegal $1 Trillion Funding Loop: Here’s What’s Really Happening
Let’s not lose touch…Your Government and Big Tech are actively trying to censor the information reported by The Exposé to serve their own needs. Subscribe to our emails now to make sure you receive the latest uncensored news in your inbox…
The following is paraphrased from the article ‘Welcome to the AI loop-de-loop economy’ published by Quartz. People within the AI industry, and in the computer industry in general, are inventing their own language. To help with understanding, we have included some explanatory notes at the end.
The AI boom is a “loop-de-loop economy,” Quartz says, meaning that a few giant companies are financing each other’s buildouts[1] and pre-selling years of infrastructure to each other, creating a circular economy.[2] This raises concerns about an “AI bubble” that will ultimately burst.
The AI circular economy has been created by companies signing multibillion-dollar contracts to host AI workloads[3], dragging other power and chip suppliers into the mix with compute deals[4] and equity-for-chips[5] arrangements. These contracts are then used as proof of demand for AI. Nvidia, Microsoft and AMD are key players in this interconnected web of financing.
How this circular economy works is “new” AI dollars are used to support someone’s credit line or equity stake, with the same promised workloads propping up a cloud backlog, a GPU[6]-backed loan and a chipmaker’s growth slide, leading to concerns that the AI economy is inflating demand and valuations without creating economic value.
Goldman Sachs and Morgan Stanley are warning about the increasing circular financing within the AI industry.
Goldman Sachs wrote that “AI bubble concerns are back, and arguably more intense than ever,” citing “the increasing circularity of the AI ecosystem” as part of the problem.
Morgan Stanley’s Todd Castagno has said that circular financing can inflate demand and valuations without creating economic value.
The Bank of England has warned that valuations for AI-focused technology stocks look “materially stretched.”
Key Players and Alliances in the AI Circular Economy
Companies such as Microsoft, Nvidia and Advanced Micro Devices (“AMD”) are forming alliances and partnerships, with Microsoft CEO Satya Nadella stating that “we are increasingly going to be customers of each other” and Veritas Investment Research’s Anthony Scilipoti identifying “another 80-100” circular deals involving Nvidia.
The situation is being described in various ways: a “three-companies-in-a-trench-coat” economy, an “ouroboros”, a “Jenga tower” and a “crazy” round of Monopoly, where the same stack of pretend money keeps getting counted as fresh wealth every time it passes “go.”
The AI circular economy is centred around OpenAI. Quartz describes OpenAI as a “black hole” due to its significant influence and lack of transparency.
Companies like Oracle and Nvidia are making massive commitments to support OpenAI’s growth, including Oracle’s $300 billion compute commitment over five years starting in 2027.
Nvidia has taken significant stakes in GPU clouds, which borrow billions against towers of Nvidia hardware and then sell that capacity back to AI labs, many of which Nvidia also backs or courts.
Nvidia has also invested in Synopsys, a software company that helps design the next generation of chips and systems, further embedding itself in the AI circular economy. Additionally, Nvidia has agreed to buy capacity from GPU cloud startup CoreWeave, acting as a backstop customer for the compute that CoreWeave is selling to OpenAI and others.
Nvidia has also announced in a letter of intent that it intends to invest up to $100 billion in OpenAI’s next-generation infrastructure.
AMD has its own orbit in the AI circular economy, having committed to supply up to 6 gigawatts of Instinct GPUs by 2030 as part of the OpenAI-Oracle megaproject. It has also teamed up with Cisco and Saudi-backed startup Humain in a joint venture to deliver up to 1 gigawatt of AI infrastructure over the next several years.
The significant investments and commitments made by these companies have created a situation where backing down or exiting the AI market would carry a significant political and reputational cost, making it difficult for companies to change course even if the market were to shift or decline. It raises questions about whether the current situation represents a bubble or acceleration in the AI economy.
The convergence of industrial policy, grid planning and corporate capital expenditures on the AI economy has created a complex and interconnected system; companies like Nvidia and AMD are playing key roles in shaping the future of the AI industry and local public infrastructure. As Quartz noted:
Utilities [such as power and water] have rewritten long-term plans. Local officials have posed with shovels in fields that now double as collateral. Sovereign funds have stamped their names on AI parks meant to prove they are on the right side of the future. Industrial policy, grid planning and corporate capex now converge on the same bet: that this small cast of [roller coaster] riders will keep screaming excitedly around every turn.
Boom or Bust: Differing Perspectives on the Impact of AI’s Circular Financing
The circular economy being created within the AI industry means vendors are essentially financing their own growth. David Meier, a senior investment analyst at The Motley Fool, told Quartz that this phenomenon has been seen before in the buildout of the internet – which ultimately led to the dot-com bubble in the late 1990s that burst in the early 2000s.
“I won’t say the same thing is going to happen, but people should be a little bit concerned because in a situation like that, you could get a bubble that essentially propagates itself,” he said.
Meier noted that much of the capital is equity rather than debt, as was the case with the dot-com bubble. He warned that where much of the capital is equity rather than debt, the pain of losses could spread through equity markets and pension funds, rather than being confined to a few lenders, if a bubble were to form.
David Wagner, the head of equities at Aptus Capital Advisors, believes that the companies at the centre of the AI boom have the financial stability to handle fresh debt and have a significant “runway” to keep spending, even if the cycle wobbles. He sees AI already generating real revenue in cloud and software.
Some critics point to circular deals, such as Microsoft being both a shareholder and a major customer of CoreWeave, as evidence of a bubble. However, CoreWeave’s CEO, Michael Intrator, argues that debt and vendor financing are just ways to keep up with demand from customers like Meta and Microsoft that keep overshooting the forecasts.
Mark Jamison argues that while the AI economy may appear to be a circular money machine, the evidence suggests a powerful technological transformation that is grounded in fundamentals. This view is shared by banks. Morgan Stanley’s technology team argues that AI capex has “considerable potential for return” and predicts significant growth in AI software revenue by 2028. And J.P. Morgan’s outlook says tech-led gains don’t yet resemble a bubble.
Despite these optimistic predictions, some experts, such as Charles Schwab’s Liz Ann Sonders, warn that disappointment relative to sky-high expectations could still roil markets.
And, as Quartz points out, the stock market is eager to know how much of the current motion reflects real demand, considering the significant contracts with OpenAI and Meta, for example, are used as evidence of strong demand for AI.
Nvidia can cite the 10 gigawatts of planned OpenAI capacity and AMD’s six-gigawatt pledge as evidence of growth, but these numbers do not distinguish between end users paying for AI and companies buying each other’s capacity.
Conclusion
The AI circular economy appears to some as unstoppable momentum, with the money being real and the dealmaking looking impressive. Others see it as an elaborate way to maintain the momentum of the AI boom.
The chipmakers, clouds and labs that dominate the AI story are building power-hungry infrastructure around promises that stem from the same circle of names, further reinforcing the circular nature of the economy.
Despite the appearance of momentum, the AI boom’s circular economy raises questions about the sustainability of this model, with some viewing it as a complex way to keep the growth story going rather than a genuine indication of unstoppable progress.
Explanatory Notes:
- [1] The term “AI buildout” refers to the massive, ongoing investment in infrastructure and technology required to support the development, deployment and scaling up of artificial intelligence systems. This includes the construction of large-scale (hyperscale) data centres, power grid upgrades, the production of specialised hardware like AI chips and the expansion of global supply chains for semiconductors, servers and power systems.
- [2] Circular financing is a system where investors give money to a company, which then buys the investor’s products in a self-reinforcing loop. In AI, this helps startups afford costly hardware and cloud services, accelerating growth and innovation. But it also concentrates risk among a small group of players, and can make demand look stronger than it actually is.
- [3] AI workloads refer to computational tasks and processes involved in developing, training, deploying and running artificial intelligence models.
- [4] AI compute deals refer to large-scale financial and operational agreements that facilitate the acquisition and deployment of high-performance computing resources essential for training and running artificial intelligence models. These deals are central to the AI industry’s infrastructure, involving massive investments between chipmakers, cloud providers and AI companies to secure access to critical compute power, often through long-term contracts, equity investments or “innovative” marketplaces.
- [5] Equity-for-chips arrangements are a form of circular financing where semiconductor companies provide equity investments to artificial intelligence startups in exchange for long-term commitments to purchase their hardware. This structure allows chipmakers like Nvidia and AMD to secure massive future demand for their products while simultaneously injecting capital into AI companies, which then use that capital to buy the very chips they are investing in.
- [6] A GPU, or graphics processing unit, is a specialised electronic circuit designed to accelerate computer graphics and image processing tasks.
The Expose Urgently Needs Your Help…
Can you please help to keep the lights on with The Expose’s honest, reliable, powerful and truthful journalism?
Your Government & Big Tech organisations
try to silence & shut down The Expose.
So we need your help to ensure
we can continue to bring you the
facts the mainstream refuses to.
The government does not fund us
to publish lies and propaganda on their
behalf like the Mainstream Media.
Instead, we rely solely on your support. So
please support us in our efforts to bring
you honest, reliable, investigative journalism
today. It’s secure, quick and easy.
Please choose your preferred method below to show your support.
Categories: Breaking News, World News