Why did the top runners suddenly reach a consensus on “slowing down AI development”?
In September 2026, an extremely unusual “alignment of steps” occurred at the forefront of the generative AI industry.
Anthropic CEO Dario Amodei proposed “Pacing the Frontier” as a concept for intentionally controlling and adjusting the pace of AI development. In response, OpenAI CEO Sam Altman, who had previously pushed for AGI (Artificial General Intelligence) development at superhuman speeds, immediately showed a harmonious stance.
Furthermore, industry leaders including Google DeepMind co-founder Demis Hassabis and xAI leader Elon Musk all expressed positive views on this “development pace adjustment.”
“The wise self-restraint of big tech companies regarding AI ethics, safety, and existential risk to humanity.” This story sounds like
It was reported as a noble leadership theory aimed at appealing to the world about the importance of “AI Alignment,” the methodology for controlling AI once it transcends humans.
However, something is a bit off.
Even without bringing up AI alignment or safety discussions, there exists “another pressing reason” why the speed of AI development has no choice but to slow down.
It is not an “abstract layer” like logic or ethics, but rather the collapse of the gritty “physical layer” of power, land, and environmental regulations, and the collapse of the “financial/contractual layer” where expensive training GPUs become obsolete before investment recovery, leading to finger-pointing over who is responsible for paying massive construction costs.
While they hold hands on the surface, smiling and saying, “We are aligning our development pace for the sake of humanity’s safety,” are they not hiding the disastrous reality behind those smiles that “further scaling is physically and financially impossible!!”?
From the symbolic infrastructure failure incident that occurred in September 2026 and the implicit financial structure surrounding GPU investment, we will approach the underside of the “noble story” that the AI industry is trying to cover up.
■ Infrastructure that hit a wall of reality—Oracle’s declaration of force majeure for “Project Jupiter”
The biggest engine supporting AI performance improvement has been the “Scaling Law,” which relentlessly increases computing resources and data.
Following this simple and clear dogma—that AI becomes smarter with more GPUs, more power, and larger data centers—companies have been engaged in a competition to build hyperscale data centers by investing huge amounts of capital.
The symbol of this is the “star attraction of the massive AI infrastructure concept “Stargate””, the super-large data center project “Project Jupiter”, scheduled to begin operations in 2028.
However, in September 2026, Oracle, a core participant in this plan, issued a decisive notice to the developer, a company under Blue Owl (STACK Infrastructure).
It was the application of the contractual “Force Majeure” clause.
What is a Force Majeure clause?
Usually, force majeure clauses are used to exempt contractual obligations in the event of natural disasters or catastrophes that cannot be avoided by human effort, such as “major typhoons,” “massive earthquakes,” or “war.” However, this time, it was not a natural phenomenon that stopped the construction of Project Jupiter.
-
Significant delays in essential power contracts and high-voltage transmission line development
-
Fierce opposition movements from local residents against noise, depletion of water resources, environmental impact, and the massive increase in power consumption
-
Rejection and freezing of construction and environmental permit applications by local governments and administrative authorities due to the intensification of resident movements
For data centers that devour massive amounts of power, the local community and infrastructure capacity caused a “rejection reaction,” resulting in administrative procedures becoming bogged down and the project schedule completely collapsing.
It is analyzed that one of the aims of Oracle invoking force majeure in this Project Jupiter is to “delay the payment of high rent after full-scale operation” if the operation schedule after 2028 is delayed.
Oracle side (tenant): “Since the operation time is delayed due to infrastructure-side delays (force majeure), the payment of high rent after full-scale operation should be postponed.”
Blue Owl/Developer side (owner/lending bank): “We are carrying huge upfront investments and debt costs, so the delay in high rent income due to operational delays is a direct financial blow.” As such, from the moment construction and infrastructure development hit a physical wall, a fierce contractual and financial tug-of-war has begun over “who will bear the financial burden (the bill) of development delays—the tenant (Oracle side) or the infrastructure investors (Blue Owl side/lending banks).” The notice of “force majeure” is not just a report of construction delays, but a struggle for realistic financial buffers over the massive risks brought about by the limits of the physical layer. Oracle’s notice of “force majeure” presents one decisive fact: that “securing power,” “local resident backlash,” and “delays in administrative procedures” in AI data center construction have become force majeure factors that can destroy a project from its foundation, on par with a massive earthquake or war.
“2-3 year” demand and “5-10 year” infrastructure development
Here, there exists an irrecoverable time lag.
-
The demand cycle sought by AI developers: 2–3 years (to beat competitors, they want a 1-million kW-class facility immediately)
-
The real-world infrastructure construction cycle: 5–10 years (new power plant construction, power grid installation, environmental assessments, community consensus, administrative permits)
Compared to the speed of demand, the speed of physical construction and consensus-building on Earth is far too slow. No matter how much AI algorithms evolve on the software side, if the power lines cannot be drawn, substations cannot be built, and resident permits cannot be obtained to power them, not even a single GPU can be operated.
Before even discussing advanced AI alignment problems, AI development faced an unavoidable reality that forced a slowdown in development speed for the simple reason that the physical layer had hit its physical limits.
■ The ‘Unspoken Truth’ of the Top Runners
When hitting physical limits, AI executives have only two paths. Either admit honestly that ‘development has stopped due to a lack of infrastructure’ and
let the stock price crash, or adopt a noble slogan claiming that ‘we are intentionally adjusting our pace out of consideration for human safety’.
The Background of Sam Altman’s Change of Heart and Failure to Walk the Talk
OpenAI CEO Sam Altman once repeatedly made bold statements. He declared that ‘we will have a model at the level we can call AGI within the year (by the end of 2026)’ and ‘as long as we have the capital and computing resources, intelligence can be expanded indefinitely,’ and he was the very person who kept fueling massive investments on the scale of hundreds of billions of dollars.
Why did Altman suddenly align with his biggest rival Dario Amodei’s ‘Pacing the Frontier’ and begin posturing toward curbing development speed?
The answer is simple and clear.
Even if he wanted to continue the conventional brute-force ‘scaling laws,’ the physical electricity to power them simply does not exist anywhere in the world.
Even if the formula that ‘increasing computing resources tenfold will make it even smarter’ is complete in his head, there is no land available anywhere on Earth to install that ‘tenfold computing resource,’ nor are there any outlets to plug it into.
The ‘real AGI’ that was supposed to be available within the year was not blocked by the limits of intelligence, but had long been blocked by the lack of physical power plugs.
However, he could not tell investors and the market that ‘we couldn’t build AGI because we ran out of outlets.’ That is why the noble story of ‘intentional deceleration due to ethical considerations’ was the perfect feast to jump on.
▫️ Who will pay the massive ‘bill’? — The structure of shifting responsibility
The collapse of infrastructure construction does not stop at just ‘the completion of AI being delayed.’ Behind it, a fierce blame game is occurring over ‘who will bear the bill’ for the hundreds of billions to trillions of yen in costs for building massive data centers and acquiring land.
‘The ladder pulled out’ from infrastructure developers and AI companies that ‘cannot pay’
Data center construction requires ‘ultra-large-scale upfront investments’ in the hundreds of billions to trillions of yen, including preliminary assessments, massive land acquisitions, and orders for custom-made substation equipment and cooling systems.
Until now, infrastructure development companies, real estate developers, and cloud providers (like Oracle) have relied on strong demand forecasts from AI development companies (like OpenAI) that ‘a gigawatt-class facility will absolutely be needed in a few years’ and long-term usage contracts, raising massive funds through loans and other means to move projects forward.
However, once construction stops due to physical and administrative bottlenecks, and furthermore, the AI development side begins to advocate for ‘Pacing the Frontier’ (development deceleration), this massive investment suddenly transforms into ‘homeless debt’.
-
The AI development company’s argument: ‘Since electricity cannot be physically drawn and the start of operations is delayed by several years, we have no obligation to pay. It is force majeure or a breach of contract.’ ‘It is the responsibility of the development side that failed to provide the infrastructure as planned.’
-
The infrastructure and developer side’s argument: ‘We secured land and equipment in advance to meet your unreasonable speed demands. The AI development companies should compensate for all plan changes, cancellation fees for slowing down, and the ballooning interest burden.’
Thus, from the moment the project hit a reef, a blame game over massive construction costs and liquidated damages began between the AI development companies and the data center developers.
The ‘force majeure notice’ issued by Oracle was not merely a report of construction delays, but a declaration that ‘we are not responsible for the responsibility and financial losses (the bill) of this failure,’ and it is nothing less than a precursor to the contractual troubles and quagmire of litigation exploding between the two parties.
▫️ Financial Hell—The Trap of GPU Depreciation
More than the shifting of construction costs, what is directly hurting the management of AI companies is ‘the collapse of GPU depreciation.’ Currently, the AI industry is facing a fatal structural defect: ‘the reversal of GPU service life and obsolescence speed.’
The ‘Turning into Trash in 1-2 Years’ of Ultra-Expensive Assets
The latest AI data centers, built with investments ranging from hundreds of billions to trillions of yen, are packed with tens of thousands to hundreds of thousands of ultra-expensive, state-of-the-art GPUs from companies like NVIDIA.
In accounting terms, these large-scale hardware facilities are usually set with a useful life of 3 to 5 years, and a business model is built to gradually recover the investment through the operating revenue (ROI) of AI services while recording depreciation expenses over that period.
However, a terrifying dilemma was occurring here.
-
The loop where AI improves AI: By having high-performance AI assist in the development, coding, and architectural optimization of next-generation AI, the speed of AI evolution itself has self-accelerated (improved exponentially).
-
Shortening of performance lifespan: As a result, long before the physical lifespan (3-5 years) of the hardware is reached, the performance requirements on the software and architecture side skyrocket, leading to a situation where the ultra-expensive GPU clusters that were just installed become ‘performance-obsolete’ in just 1 to 2 years.
The investment of hundreds of billions of yen that was supposed to be recovered by operating for 3 to 5 years and collecting usage fees has transformed into ‘outdated, unusable equipment’ within 1 to 2 years, with almost no recovery having taken place.
The End of the Scaling Law Chicken Race
The ‘scaling law chicken race’ of competing to buy up the latest GPUs and building massive infrastructure so as not to fall behind competitors. What awaited at the end of that was a hellish structure where the invested equipment turns into ‘liabilities that generate no profit even when running (effectively trash)’ before the depreciation of the existing massive infrastructure is finished.
-
The hundreds of billions of yen invested in GPUs fall out of the performance race in 1 to 2 years.
-
However, the accounting depreciation expenses remain, severely squeezing the company’s earnings.
-
Because investment recovery (ROI) is not keeping up at all, raising additional funds to purchase next-generation GPUs is also difficult.
They shift the burden of data center construction costs onto each other, and the GPUs on hand become outdated before their 1-2 year depreciation is finished. GPUs have now become the ‘assets with the fastest depreciation speed’ in the world, and to recover even a little of the GPU investment, AI companies have no choice but to slow down the speed of development.
Before AI reached the limits of intelligence, it reached the collapse of its balance sheet.
▫️ The Collapsed Initial Concept and the Smokescreen of ‘Alignment’
Here, all the dots connect.
In the early days of the generative AI boom, the initial vision held by Big Tech and AI startups was extremely simple.
“If we raise capital, buy unlimited GPUs, build massive data centers, and keep running the scaling laws, we will complete a perfect AGI in a few years and recover all costs.”
Initial Vision
However, what has become of the reality as of 2026?
■ The Collapsed Initial Vision: Expectations vs. Reality
1. Power and Power Grids
・Expectation：Can be procured preferentially if capital is available
・Reality：Requires 5–10 years for transmission line development, leading to a physical breakdown
2. Local Communities and Government
・Expectation：Welcomed as local investment and economic stimulus
・Reality：Permit applications frozen due to backlash against environmental impact and water/power consumption
3. Return on Investment (ROI)
・Expectation：Stable recovery over a 3–5 year useful life
・Reality：AI evolution speed is accelerating, rendering GPUs obsolete in 1–2 years
4. Development Pace
・Expectation：Will accelerate exponentially forever
・Reality：Forced slowdown due to limits in the physical and financial layers
“Did the foundation to develop AGI even exist from the start, given our current technical approach and infrastructure development methods?”
To this fundamental question, industry leaders cannot admit, “No, the foundation never existed (or has collapsed).” If they admitted that, the vast investment money they have scraped together would be withdrawn, and they would be ruined.
That is precisely why they needed the supreme excuse of ‘AI alignment’ and ‘safety concerns’.
“We are not slowing down development because we cannot build infrastructure or have hit a financial wall. We are practicing ‘Pacing the Frontier’ to carefully verify AI ethics and safety in order to protect the future of humanity.””
While ‘AI ethics’ and the ‘alignment problem’ are, of course, important research themes in their own right, in the current context, it feels nothing but ‘insincere’ when executives start preaching them loudly.
A ‘smoke screen that looks wise (buying time)’ to hide from the public and investors the fact that the initial vision of ‘AI infrastructure construction,’ ‘maintaining development speed,’ and ‘ROI roadmap’ has completely collapsed.—that is the cold, hard truth behind the recent AI safety movement.
■ Re-examining the ‘Reality Layer’ with Both Feet on the Ground
The agreement by various companies to ‘Pacing the Frontier’ in September 2026, and the invocation of force majeure clauses in Oracle’s ‘Project Jupiter.’ These are not just news items for a single company; they are the sound of the first domino falling as the generative AI rhapsody descends from an ‘idealized aerial battle’ to a ‘gritty physical and contractual war.’
Even if the algorithms beyond the cloud seem to evolve infinitely, what supports them are the high-voltage power lines buried in the ground, the water resources of the land where local residents live, and the depreciation figures that companies have borrowed from banks.
While we are captivated by abstract debates about ‘whether AI will surpass humans’ or ‘how to tune AI,’ the physical and financial layers beneath our feet are quietly, yet decisively, screaming.
When the speed of AI development slows down, what we should truly be looking at is not the ‘fear of AI becoming too smart.’ It is the frenzy of humans who lack enough power outlets, whose newly purchased GPUs have turned into trash, and who are unseemly pushing invoices onto each other.
And, in the midst of that collapsing feast of madness, it is likely the figure of ‘a certain man’ who continues to bet his entire fortune and keep his foot on the accelerator.
(End)
