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The Teaser Period: Why The AI Boom Is Hitting A Reset Wall

Having laid out, in July, the structural diagnosis that most of the market still refuses to confront: the AI boom is not a technology cycle. It is a credit-driven real-estate-like cycle whose financing architecture depends on the second derivative; the appropriately-named 'Groundbreaker' website has just dropped his next insightful note on what may be the trigger for the market to wake up to the ugly reality beneath the surface of the AI dream.

Trillions in signed compute commitments come due in 2027–2028. The underlying mechanics reveal how the AI boom ends, and when...

I. Past is Prologue

Nothing looked wrong in the summer of 2006. Home prices had risen for the better part of a decade. Delinquencies were near historic lows. Credit spreads were tight, the ratings held, and the securitization machine hummed. If you had asked a hundred people on a trading desk whether the American mortgage market was months from seizing, most would have laughed.

Millions of subprime borrowers were, at that moment, paying the low introductory rate on a two-year adjustable rate mortgage - the 2/28 ARM. A low fixed-rate for two years, then the rate reset to a payment 30% to 50% higher. During those first two years the loan performed beautifully: the borrower paid, the servicer collected, and the bond paid its coupon. Nothing looked wrong because the whole complex - housing, mortgages, securitization - was sitting inside the teaser period.

Every ARM reset was known, dated, and contractually inevitable from the moment of origination. Aggregate those reset schedules and you get the most damning exhibit of the era: the reset wall. Roughly a trillion dollars of adjustable-rate mortgages were contractually set to reset across 2007 and 2008 - thirty to forty billion dollars a month at the peak. Credit Suisse published the chart in March 2007. The IMF reprinted it. It circulated on every trading floor in New York and London.

The mortgage reset wall. Every teaser written in the boom became a dated liability

Few understood it. Paulson & Co. laid out the arithmetic that same month in a comment letter to the FDIC: Over 80% of recent subprime originations, it observed, were two- or three-year adjustable-rate products. The average subprime borrower’s mortgage payments already consumed roughly 40% of their gross income at the teaser rate. Almost none of them could service the reset rate out of income.

The crisis, in other words, was written in advance by the instruments themselves. The market looked at the reset wall and kept buying, because every participant believed the exit would arrive before the reset: home prices would keep appreciating and the borrower would refinance into a fresh teaser before the old one expired.

We have spent the last eighteen years describing the financial crisis as a shock - a black swan, a hundred-year flood, a tail event. It was none of those things. Every reset on that chart was contractually inevitable from the moment of origination. The defaults were not primarily caused by an exogenous macro shock, a spike in unemployment, or a recession that arrived first. They were the scheduled mathematical consequence of loans that assumed perpetual appreciation. The mortgages were built to break.

The AI boom has rebuilt this exact structure, and the market is once again underwriting the teaser.

It has a reset wall of its own - a schedule of dated, contractual, non-negotiable payment shocks - hiding inside the trillions of dollars of compute contracts signed by OpenAI and other frontier labs since 2024.

The take-or-pay compute contract - the instrument at the center of the AI build-out - has a structural feature that almost no one prices: its payments do not begin at signing. They begin at delivery. A lab signs a multi-year capacity commitment today, but the payments do not start until the data center is energized, the capacity is accepted, and the contractual ramp schedule commences - an interval set not by finance, but by construction: siting, powering, and filling a gigawatt-scale campus takes 24-to-36 months from signature - mirroring the two-to-three-year teaser of a subprime ARM.

More than $2.3 trillion of compute contracts now sit on the books of the four largest American cloud providers as remaining performance obligations and contracted backlog - signed, celebrated, capitalized into equity prices, and, critically, not yet billing.

During the teaser period, everyone wins. The seller reports backlog growth that compounds at rates no operating business has ever sustained - Oracle’s RPO grew 363% in a single fiscal year. The buyer - a frontier lab burning cash at historic rates - books no expense because the capacity does not yet exist. The market capitalizes the booked number as if it were revenue and ignores the billed number as if it were a technicality. And then, on a schedule fixed at signing, booked compute becomes billed compute. The take-or-pay clock starts. From that day forward, the frontier labs and the hyperscalers incur those costs regardless of utilization. The invoice is a function of the contract, not of demand. That is the reset.

The parallel to 2006 is exact and it explains the single most-cited absurdity of this cycle: How does OpenAI, a company with some $40 billion of run-rate revenue, sign $1.4 trillion of compute commitments? The same way a household with $60,000 of income signed a $600,000 mortgage: because the terms at signing do not require the payment yet, and because everyone at the table - borrower, lender, and the market - believes the growth will arrive before the payment does.

The 2/28 borrower’s defense was always the same: by the time the reset arrives, my house will be worth more and I will refinance. The frontier lab’s defense is structurally identical: by the time the capacity commences, my revenue will have grown into the obligation.

The compute commencement wall can be made visible in exactly the way the reset wall was visible in 2007 - from disclosed contracts and delivery schedules. The only question is whether the market listens this time

The same chart twenty years apart. Left panel - first-reset principal balances per Credit Suisse and Inside Mortgage Finance. Right panel - announced compute commitments and contract disclosures across every frontier lab.

II. The Anatomy of a Teaser

To see why the structure behaves the way it does, I’ll break down a single contract and walk the lifecycle. The terms below are hypothetical; the architecture is the standard one visible across the disclosed OpenAI–Oracle, Anthropic–Google, Meta–CoreWeave, and OpenAI–CoreWeave arrangements.

A frontier lab signs a $12 billion, ten-year capacity commitment with a compute provider. The contract is take-or-pay, meaning the lab commits to payments once the capacity is delivered, and delivery requires a campus that does not yet exist: two years of construction, procurement, and power work stand between signature and completion.

Now look at what each party’s financial statements show during the two-year teaser.

The seller - a hyperscaler or neocloud - books the arrangement into RPO or contracted backlog on day one - the full $12 billion, disclosed, quoted, and celebrated. The market values it as contractual future revenue. Meanwhile the seller’s cash flow statement hemorrhages: the campus is being built, so capex runs far ahead of receipts. Booked backlog rises; reported earnings feel none of the buildout; financing frequently sits off-balance sheet.

The buyer - a frontier lab like OpenAI or Anthropic - announces access to the compute it needs to pursue its scaling roadmap, and its private valuation reprices on the announcement. The commitment is a future obligation, disclosed - if at all - deep in a contractual-obligations footnote or, for the private labs, nowhere public. No expense hits the P&L because no service is being received. A lab that has committed tens of billions across multiple providers carries a cost structure that reflects only its commenced capacity.

The market sees a seller with explosive backlog and a buyer with secured compute capacity, and prices both as growth stories. Nobody is lying. Every number is GAAP-clean. The structure simply guarantees that during the teaser period, the system’s reported economics and its committed economics diverge by the full value of everything signed and not yet commenced.

Every optical incentive points toward signing more.

Then comes commencement, and the two clocks converge violently. The buyer’s cash obligation steps from approximately zero to the full contractual rate, arriving not gradually but as a step function, tranche by tranche as capacity goes live. The seller begins recognizing revenue, which the market applauds, while backlog begins draining. And here is the asymmetry on which the entire thesis turns: the buyer’s obligation steps up on the construction schedule, regardless of the revenue or utilization that shows up.

The parallel is now clear: the 2/28’s teaser is the construction phase, its reset date is commencement, its fully-indexed payment is the full take-or-pay rate, and its refinance-or-sell assumption is the belief that model revenue will have grown into the obligation by the time it bills - or that another round of fundraising will cover it.

The take-or-pay compute contract is the financing innovation of this cycle the way the 2/28 was the financing innovation of the last one, and it emerged for the same reason: an asset too expensive for its natural buyer had to be made buyable. A frontier lab cannot fund a gigawatt campus out of revenue, just as a subprime borrower could not fund a house at the fully-indexed rate. In both cases the solution was an instrument that splits time in two - a cheap phase that gets the deal signed, and an expensive phase scheduled far enough out that the market ignores it.

In residential credit, the interval between origination boom and reset wall was twenty-four months, because that was the teaser’s term. In compute, the interval is the construction timeline - twenty-four to thirty-six months. The 2025–26 signing boom therefore mathematically guarantees a 2027–28 commencement boom, exactly as 2005–06 originations guaranteed 2007–08 resets.

This is what it means to say we are in the teaser period. The booked figure is enormous; the billed figure is a fraction of it and only beginning to turn up. Everything about the present looks like strength. The obligations that will govern 2027 and 2028 are already signed, already dated, and already sitting in RPO. What has not happened yet is the conversion - the moment booked becomes billed and the take-or-pay clock starts running regardless of the revenue and the counterparty’s ability to pay.

III. Take-or-Pay is Debt

The common objection to the 2008 comparison is simple: this is not 2008 because the leverage is not there.

The leverage is there. It’s simply not booked as leverage.

A take-or-pay contract is, in economic substance, a lease. And a lease is a financing. The defining feature of debt is a fixed payment on a schedule, owed regardless of the borrower’s circumstances. That is exactly what a take-or-pay commitment is. The payment does not flex with utilization. It does not wait for the customer’s revenue. It is owed on the commencement date and every period thereafter, for the term.

This is not a new concept. Rating agencies have treated take-or-pay obligations as imputed debt for more than thirty years - pipeline throughput agreements, ship-or-pay contracts in shipping and rail, long-term power purchase agreements, all routinely capitalized into leverage metrics by Moody’s and S&P. The convention simply has not been applied to compute.

Reported gross debt across the AI complex - the frontier labs, the hyperscalers, and the listed neoclouds - comes to roughly $470bn. The present value of disclosed non-cancellable compute and capacity commitments across the same set comes to roughly $1.66 trillion. The economic obligation is $2.1 trillion. For scale, subprime mortgages outstanding in March 2007 totaled roughly $1.3 trillion.

Three mechanisms keep these contracts off the reported balance sheet.

The first is disclosure asymmetry: remaining performance obligations are a seller-side disclosure under the revenue-recognition standard - the vendor tells you what it has been promised - and there is no symmetric requirement for the buyer to tell you what it has promised.

The second is that the largest buyers are private: OpenAI and Anthropic file no periodic reports, and their obligations enter the public record only when a counterparty announces a deal or books the corresponding receivable.

The third is that the contracts are generally structured as service agreements rather than leases - precisely the maneuver that kept operating leases off balance sheets before the standard changed.

The leverage objection, then, depends entirely on where you look. Look at the line marked debt, and there is relatively little of it. Look at the contractual claims on future cash, and there is more than the entire subprime mortgage market carried at its peak.

So the leverage exists. The question that follows is who owes it and whether they can pay it.

As of the second quarter of 2026, the four largest U.S. cloud providers carry roughly $2.3 trillion in contracted revenue backlog. Roughly $1.0 trillion of that total traces to two counterparties - OpenAI and Anthropic.

Both of those counterparties run deeply negative free cash flow and fund themselves through equity raises and vendor-adjacent financing from the same ecosystem whose capacity they are contracting. The single most important credit fact in the global economy right now fits in one sentence: the largest capital cycle in the history of technology is underwritten, to the tune of roughly one trillion dollars, by two private companies that do not make money.

Now contrast this with the cloud build-out of the previous decade. In the 2010s, bookings and billings tracked each other closely. Capacity was added a step ahead of demand that was already visible. Today backlog-to-revenue multiples across the complex now sit at five to six times the pre-AI software norm - with the vast majority of contracts being take-or-pay contracts signed in 2025-2026 and commencing in 2027-2028.

The multi-year commitments dominating these backlogs are underwritten not by observed demand but by a forecast of demand - a belief about how large and how soon the AI economy comes. RPO has quietly been recast from a risk disclosure into the bull case: “look at all that contracted revenue.” But a backlog is not revenue. It is a promise to pay, and it is worth exactly what the party on the other side can actually pay when the promise converts from booked to billed.

So, as the cloud era transitioned to the AI compute era:

1. Consumption on existing capacity became commitment on unbuilt capacity. The revenue-recognition lag went from one to two quarters to two to three years.

2. Variable service agreements became fixed and contractual. Pay-as-you-go, a flexible operating expense of the cloud era, became take-or-pay, a non-cancellable lease structure that the market has not fully priced as debt.

3. A diversified book became a concentrated one. The cloud-era backlog was tens of thousands of enterprise customers. Today more than half comes from two unprofitable companies.

And, 4. The collateral changed. This one will look obvious in hindsight. In the cloud era, backlog was underwritten to the customer’s operating business. A Fortune 500 firm signing a three-year cloud commitment was going to pay it out of an existing profit stream. In the compute era, backlog is underwritten to the customer’s future funding. It is not credit against cash flow. It is credit against the capital markets staying open - which is exactly the expectation of the 2/28.

“But the hyperscalers have 30%+ ROI!”

The ROI the market is capitalizing is not paid by the hyperscalers’ own operations in any self-sustaining sense. It is paid by the counterparties - by OpenAI and Anthropic and the other labs whose take-or-pay commitments are the revenue line under every one of these returns. The hyperscaler’s return on invested capital is only as real as the labs’ ability to make the payments that constitute it.

When commencement arrives, the payment that pays the ROI becomes a payment the counterparty owes regardless of its own demand. If that counterparty’s revenue has grown into the obligation, the return persists and the bulls were right. If it has not, the return does not gently compress - it inverts, because the same take-or-pay contract that was the hyperscaler’s asset is now a claim on a borrower who cannot cover it. It’s credit risk that looks like an operating return.

IV. The Signing Spree

OpenAI carries the largest compute commitments in the system against a revenue base that is a fraction of those commitments, with no parental balance sheet standing behind the obligation. It signed the most, owes the most, and burns the most, and its exit assumption - raise the next round before commencement, the way the subprime borrower’s was refinance before the reset - depends on a revenue curve inflecting on a schedule that has never been demonstrated at this scale.

Between June and December of 2025, OpenAI executed what may be the most concentrated origination spree in the history of corporate credit.

In less than twelve months, the company signed something close to $1.2 trillion in compute commitments. There was a stretch in October 2025, about three weeks, during which the company announced deals whose combined notional value exceeded the market capitalization of ninety-five percent of the companies in the S&P 500.

Signing was cheap and the re-rating was instantaneous. On the days the largest of these deals were announced, Oracle, Nvidia, AMD and Broadcom added a combined $636 billion of market capitalization.

Every dollar of that $1.2 trillion was signed during the steepest part of OpenAI’s revenue curve and underwritten to its continuation. And almost every one of these deals commences in 2027-2028. The signing spree should be read as an obligation event, not a sign of insatiable demand for compute.

V. Building the Reset Wall

Let us build the reset wall and let us build it the way Credit Suisse built the mortgage wall - in two views:

• The first is a cash question: how much does the company owe, per year, as these contracts commence? This is the equivalent of Paulson & Co’s arithmetic - which was used to compare the mortgage payments to the borrower’s income.

• The second is a concentration question: what is the total compute contract amount that resets from teaser to full pay in a single year? This is the equivalent of Credit Suisse’s 2007 reset wall - which showed the principal amounts of adjustable-rate mortgages resetting in a given year.

OpenAI’s committed annual compute cost, built bottom-up from the announced vendor contracts and reconciled to management’s own disclosed plan. The step into 2027 is the reset.

The 2007 reset wall was drawn in notional rather than annual payments - in other words, the unpaid principal balance transitioning from teaser to fully indexed. The compute equivalent is contract notional payable from the commencement date forward.

Credit Suisse could build the 2007 reset wall because securitization documents disclosed every loan’s reset date. Compute contracts are private, so the wall must be modeled - but the inputs are unusually good, because the counterparties keep announcing them publicly.

And, much like 2008, synchronized originations produces synchronized resets. Mortgage origination peaked across 2005 and 2006; the teaser was twenty-four months; the wall peaked across 2007 and 2008. Compute signing peaked across 2025 and 2026; the construction interval is twenty-four to thirty-six months; the wall peaks across 2027 and 2028. Same arithmetic, different collateral.

The mortgage-balance analogue: contract notional still payable from the commencement date forward. $712bn of it recasts to full pay across 2027–2028 for the two frontier labs alone.

Now, replicate the way Paulson & Co. measured the 2/28 borrower: compare the annual cash payment to income and determine the counterparty’s ability to meet these resets. OpenAI has no income, so in this case the comparison is against revenue. Apply four revenue paths, each anchored to the latest reported figures and to what the company itself has told investors.

Run every scenario management or the forecasters will offer - re-acceleration, the management plan, the forecaster median, a slow burn - and set each against the committed compute cost. The bottom panel is the coverage ratio: compute commitments as a share of revenue, before wages, research, sales, or tax.

Even under management’s own plan, compute alone consumes more than 200% of revenue at the 2027 peak. There is no scenario on the chart in which the frontier lab covers its compute bill out of revenue in the year the wall lands. The best case is that it grows back under the line by the end of the decade, and the best case requires the refinancing channel to stay open the entire way.

So, OpenAI’s plan for the reset is to refinance at the reset. Raise the next mega-round, at a higher valuation, to cover the obligations as they commence - exactly as the subprime borrower planned to refinance into the next loan when the teaser expired. This works while two things hold: the capital markets stay open, and the narrative stays intact.

And look at what this implies about OpenAI’s valuation as it moves toward an IPO:

OpenAI’s equity - valued north of $850 billion - is functionally the junior tranche of a capital structure whose senior claims, the take-or-pay compute obligations, exceed any revenue path management itself has articulated.

On those numbers, the equity is effectively underwater, and the market has not priced it that way because it still treats those obligations as service agreements rather than what they are economically: debt.

Even if OpenAI can meet those obligations, OpenAI’s unaudited financial statements - as of March 31, 2026 - disclose $665 billion in non-cancellable compute commitments (management’s more recent plan runs to $750 billion). These commitments are take-or-pay in structure - which, as established above, is debt.

Carry the present value of those obligations as senior debt - roughly $450–500 billion - and a company the market prices as debt-free carries a senior claim worth more than half its entire equity value.

The market is pricing the residual equity as if it were the whole stack.

VI. What the Wall Demands

The labs' answer is the 2/28 borrower's answer: revenue is compounding at triple digits, and by commencement it will cover the payment. It might. The credit point is narrower: the revenue coverage claim is a projection, while the obligation is a certainty.

The claim is not that commencement causes a lab to fail. It is that commencement is the date on which a pre-existing mismatch - fixed obligation against assumed revenue - becomes cash-due, and that, as in 2008, the mismatch is visible in the fundamentals well before the date makes it unavoidable. You do not need demand to fall. You need it only to decelerate below the rate the booked compute was underwritten to.

The compute contracts commencing in 2025 and early 2026 cleared, or very nearly cleared, the required growth rate. This is the crucial point, and it is the reason there is no alarm anywhere in the system: the early vintages worked.

They worked the way the 2005 and 2006 subprime resets worked. The collateral appreciated fast enough. The refinancing happened. Everyone who signed was vindicated, and vindication is the input to the next round of underwriting. Success in the early vintages is the mechanism that manufactures the late ones.

For committed compute merely to equal revenue in 2027 - not to be comfortably covered, simply to reach parity, before a single dollar is spent on wages, research, sales, or tax - revenue would have to compound at 217% annually off the 2025 base. The dashed line at 100% represents revenue doubling every single year and sustaining it, which no company at this scale of revenue has ever done for a multi-year stretch. The obligation is accelerating at more than double the rate of the best case for the cash flow meant to cover it.

The obligation curve is contractually fixed and steep - it ramps according to a defined construction timeline. The revenue curve is a growth rate. If the growth rate rolls over - the two curves cross. That is the reckoning: not a demand collapse, but a demand deceleration meeting a cost schedule that was set in a more optimistic year.

Deceleration alone is survivable if your cost base is variable. If demand growth slows from a 120% to 40%, a company with variable costs simply spends less, earns less, and adjusts. But a take-or-pay obligation is not variable. It is a fixed dollar amount that arrives on a fixed date regardless of what the demand curve did in the interim.

None of this means the company fails. It means the company must raise. Take the base case: roughly $375 billion of cumulative uncovered compute cost across 2026 to 2030, before research and development, before compensation, before every other operating cost of running a frontier laboratory. Round the all-in external funding requirement to the four-to-five-hundred-billion-dollar range across five years, and the exit assumption becomes explicit and testable:

The thesis for OpenAI requires capital markets to fund roughly half a trillion dollars of cumulative operating deficit at a single pre-profit counterparty, at non-punitive terms, through a window in which that counterparty’s compute costs are contractually rising faster than any plausible revenue path.

That may happen. But it should be named for what it is: a refinancing assumption rather than an operating plan, and one that depends on the collateral - the valuation - exactly in the period in which the true cash cost of the build becomes visible for the first time.

Construction timeline slippage can move the obligation - the 2027 peak flattens slightly, the 2028 peak rises, and total obligation is unchanged. The revenue that was supposed to grow into the 2027 obligation now has to grow into a larger 2028 one. This is exactly what happened when servicers pushed resets in 2007. Deferral was a repricing of when, not a cure.

OpenAI has been built as if the AI boom were a venture-backed, technology cycle; when in fact, it has the mechanics of a credit-driven real-estate cycle (as I outlined in The Second Derivative). Every decision executives have made seems to be based on maximizing a single outcome: the next round. While compute commitments are in the teaser period, they are assets - secured compute capacity signaled strength and raised the next round. OpenAI is facing a day of reckoning when those commitments are delivered and, on a schedule indifferent to their revenue or next round of funding, booked compute becomes billed compute.

And time is running out - Bridgewater’s analysis shows OpenAI is burning through their latest fundraise at an extreme pace.

VII. Anthropic and the Whole Stack

The comparison to Anthropic is useful as a controlled experiment. On the same measure, Anthropic’s compute commitments peak at close to 60% of revenue in 2027 then falls - fully covered by revenue with room left to pay operating costs. Undoubtedly stressed in the reset window, but structurally solvent and improving from the peak rather than grinding against it. Two labs, the same instrument, the same commencement window, and coverage ratios that differ by more than a factor of three at the peak.

While in a substantially better position, Anthropic is similarly the equity tranche of a capital structure heavily indebted by take-or-pay compute commitments, which the market has also failed to appropriately recognize as debt.

For sake of clarity, the revenue figures used in this analysis are annual revenue figures not a run rate.

The full system is larger, because the labs are only the top layer. Consolidated across frontier labs, hyperscalers and neoclouds, contract notional recasting peaks at $732 billion in 2027 and $820 billion in 2028. $2.4 trillion recasts from teaser to full pay across 2026 to 2029, with the two-year peak in exactly the window the frontier-lab layer identified.

System-Wide Contract Notional Recasting, Consolidated.

Now, place the full stack side by side with the mortgage reset wall.

The Reset Wall, Then and Now. The whole stack on the right, consolidated and net of eliminations.

It is worth being clear about what these charts imply:

It is not a default forecast. The reset wall did not “predict” defaults in 2008 either. It only revealed the date on which the question would be asked.

It is a statement about synchronization and about arithmetic. It says: on a schedule fixed by contracts already signed, a very large volume of fixed obligations transitions from deferred to due, in a narrow window, for a set of counterparties whose ability to pay the reset depends on a revenue number that does not yet exist - it’s a projection - and whose cash flow today is reliant upon external funding.

That is exactly what the Credit Suisse chart said in 2007. It was right, and it was ignored, and it was ignored for a reason that will be entirely familiar: at the moment it was published, every loan on it was still performing.

When skeptics raised the reset schedule in 2007, the rebuttal was performance data: delinquencies are at record lows. So they were - the vintages were two years old, home prices had risen by double-digits, and the payment being performed was the teaser payment. Today’s rebuttal has the same rationale: AI revenue is compounding at triple digits; utilization is effectively full; every GPU is oversubscribed. All true. All measured during the ramp, while capacity trails demand by construction lag and the billed payments run at a fraction of the booked compute.

VIII. The Second Teaser: Hyperscalers

The frontier labs have a contractual teaser: an obligation that is signed and not billed. The hyperscalers have an accounting one: an asset that is paid for and not expensed.

Under U.S. GAAP, capital under construction sits in “construction in progress.” Depreciation does not begin at expenditure. It begins at placement in service - when the asset is available for its intended use - regardless of whether it is being used. Construction-period interest is capitalized into the asset’s cost and expensed only after placement, through depreciation, over the asset’s life.

Then the tranche goes live, and GAAP flips the switch. Depreciation commences on the full capitalized cost - including the capitalized interest now embedded in the basis. The asset moves, in one accounting instant, from an inert balance-sheet entry to a recurring income-statement charge. In-service to the owner is what commencement is to OpenAI: a reset whose date was fixed by the construction schedule, utterly indifferent to whether demand showed up.

As tranches go live through 2027–28, depreciation inflects upward mechanically and the hyperscalers’ operating margins begin absorbing the fully indexed rate. If utilization and pricing hold, revenues rise in tandem and absorb the scheduled depreciation. If they do not, the industry will discover that depreciation is take-or-pay with the income statement as the counterparty: a fixed charge, contractually scheduled, indifferent to demand, and impossible to renegotiate.

Consider what a live datacenter owes each month whether it runs at 90% utilization or 30%. It owes depreciation, power, interest, staff, cooling, and maintenance. In a representative cost stack for a leveraged cluster, roughly 80% of the monthly cost is fixed the day the meter turns on.

This is operating leverage - a wonderful thing on the way up and a merciless one on the way down. When utilization holds, margins are spectacular, which is exactly the story the teaser period tells. But the same fixed base, spread across revenue that arrives below the underwritten level, produces negative operating leverage. There is a break-even utilization built into every one of these assets - the point below which fixed costs are not covered - and below it, the asset bleeds.

If OpenAI cannot pay, the hyperscalers do not just miss revenue - they absorb a fixed-cost shortfall that their own operating leverage magnifies. A 30% utilization drop does not mean 30% less profit. It can mean the entire facility turns unprofitable.

IX. The Options

When billing commences, unused capacity transforms overnight from strategic optionality to cash burn. A CFO staring at that line item finds ways to mitigate it.

You cannot cancel: take-or-pay is take-or-pay, senior in practice to everything. You can try to grow into the capacity, but demand is largely outside your control. Three mitigants remain: raise capital, renegotiate, or sublease.

Renegotiation is the most likely path. OpenAI’s negotiating leverage is proportional to its systemic importance - perhaps why it proposed handing a 5% equity stake to the federal government. It is too interconnected to fail; every balance sheet in the chain needs the fiction maintained. The renegotiations, when they come, will not be shown as distress. They will look like partnership: volume deferrals framed as capacity rephasing, rate cuts as efficiency-linked pricing.

But the moment one anchor lease is amended, every RPO dollar in the complex carries a demonstrated amendment probability. “Contracted” ceases to be a synonym for “certain” anywhere in the system. The $2.3 trillion only needs quiet contract negotiations to be re-rated as an asset class.

Sublease is the alternative. A tenant subleasing capacity it cannot use will take nearly any rate above zero, because every dollar recovered directly reduces cash burn. The bull case points to premium rates on today’s short-term subleases. But look at the terms: xAI’s arrangements carry ninety-day termination rights; Google frames its leases as bridge agreements; Anthropic takes spot capacity while aggressively contracting bespoke capacity elsewhere. This is bridge demand by construction. It exists only until the 2027–2028 multi-gigawatt deliveries land, at which point it hands the space back - flooding the market with shadow vacancy just as the rest of the $2.3 trillion commitments convert from booked to billed.

Compute does not need to default to break the market. It only takes a wave of quiet contract renegotiations and shadow-vacancy subleases to re-rate the asset class from a scarce strategic commodity to an oversupplied utility.

X. The Index is the Trade

When that re-rating happens, the equity of the entire complex absorbs the loss - and that equity is concentrated in the handful of names that dominate the market-capitalization-weighted indices most of the developed world owns through its retirement accounts. The ultimate holder of the risk is a household that has never heard of a take-or-pay contract.

AI-exposed names now account for roughly 45% of S&P 500 market capitalization. The ten largest companies in the index - themselves overwhelmingly AI names - sit near 40%, against about 27% for the top ten at the dot-com peak. It is the most concentrated the index has been in its modern history

Semiconductors carry roughly 19% of the index and supply roughly 45% of its total earnings growth, the largest share of any sector. That contribution is a function of the order book, and the order book is largely a function of new originations. When the reset lands and the labs spend every marginal dollar servicing commitments already commenced rather than signing new contracts, the next wave of chip orders thins. The vendors are a pure second-derivative play - they book the boom first and feel the deceleration first.

Hyperscalers are roughly another 20% of the index - and the two frontier labs are nearly half of their $2.3 trillion backlog. When the commencement wall hits, depreciation and fixed costs kick in on a schedule indifferent to whether those counterparties can pay, and the hyperscaler’s P&L becomes the backstop for any capacity the labs overbought and cannot cover. Hyperscaler ROI is fundamentally frontier lab credit risk - and the equity market hasn’t even begun to price that in.

Neoclouds are the most levered expression of the wall. CoreWeave and its peers financed gigawatt campuses on debt raised against the take-or-pay contracts themselves - backlogs many multiples of revenue, thin equity beneath, and the bulk of it commencing in 2027–28. Their model rests entirely on booked converting cleanly to billed; the capital structure has no room for a deferred or renegotiated anchor lease. They carry no index weight, but cracks in the take-or-pay complex expose them.

A passive retirement account holding an S&P 500 index fund owns a levered, concentrated bet on the conversion of contracted compute backlog into billed revenue - and on two cash-burning frontier labs’ ability to pay for it Nobody chose that allocation, and almost no one holding knows it.

XI. Living Inside the Teaser Period

The hardest thing to convey about 2006 to anyone who did not trade through it is how good the data was. Record origination, record homeownership, delinquencies scraping decade lows, homebuilder earnings at all-time highs, and every incoming statistic confirming the strength of the American consumer.

What almost no one priced was that every one of them was a teaser-phase measurement: an observation of a system whose payment test had not yet begun, generated by an instrument that mechanically guaranteed the data would look exactly this way until the schedule said otherwise.

An economy of teasers cannot produce bad credit data until the calendar turns, which means the strength of the present data carried no information about the question that mattered. The signals everyone watched were structurally incapable of carrying the signals everyone needed.

Now read the compute cycle’s tape with that in mind. Record RPO backlog, celebrated the way 2005 celebrated origination volume. Capacity sold out, demand insatiable: a construction-phase statement, necessarily true while contracted delivery lags contracted demand. Vendor revenue beating estimates, the way homebuilder earnings were the sound of the mortgage machine consuming its own vendor inputs.

This is the epistemic signature of a teaser period, and it explains the otherwise baffling social dynamics of standing inside one. The bear who cites the future reset wall is answered with the current data. A teaser period does not merely hide the reset wall. It manufactures the exact evidence used to dismiss it.

XII. This Time is Different

Reinhart and Rogoff titled their history of eight centuries of financial folly with the words that recur before every crisis: “this time is different”. And the maddening truth is that the specifics genuinely are different every time.

This is not precisely 2008. GPUs are not houses; take-or-pay contracts are not mortgage-backed securities; OpenAI is not a subprime borrower in Stockton, and artificial intelligence may well be the most consequential technology of the century, which is more than anyone could ever say for a McMansion in the Inland Empire.

All of that is true, and none of it is the point. What repeats is never the surface. What repeats is the structure:

a scarcity thesis that justifies enormous fixed obligations; a teaser period during which those obligations feel costless; a set of commencement dates, fixed at signing, on which the teaser expires and the fully-indexed bill begins; and a bet that the income will have grown to meet the bill by the time it arrives.

The reason many AI skeptics will be right in substance and wrong in the mechanism is that they are often making a valuation argument, and valuation arguments have no clock. What this piece has tried to show is that buried inside the compute contracts is something a valuation argument never has: a reset.

The bull case wins if - and it is a real if - demand scales into the committed supply before the reset wall lands, and the counterparties stay funded through any air pocket in between. The bear case in this piece is not that artificial intelligence will fail, or that the demand is fake, or that the technology disappoints. It is narrower: that the financing structure can break before the demand arrives, because the obligations are fixed and front-loaded in commencement while the revenue is variable and back-loaded in adoption - and a fixed obligation meeting a lagging revenue stream is a solvency problem regardless of how transformative the underlying technology turns out to be.

The industry will spend the next eighteen months debating whether artificial intelligence is a bubble, which is the wrong question, asked at the wrong layer. The technology is real; so were the houses. The question is narrower: what happens when instruments underwritten at the teaser meet their reset schedule, and who is holding the paper when the obligations cannot be met as written. The reset wall is published above and the AI boom sits in a period of fiction.

The Teaser Period.

Read more and subscribe to 'Groundbreaker' here...

Tyler Durden Mon, 08/24/2026 - 07:55

“We strongly believe that she didn’t do this intentionally, and so that leads us to think it was either some kind of freak accident or someone harmed her," her sister said.

Zelensky Says Wartime Elections Would 'Destroy' Ukraine, The Purported Bastion Of Democracy

Ever since Russia invaded Ukraine in February 2022 with a goal of excising the Russian-speaking Donbas region, American and Western European officials have repeatedly said they and their countries are duty-bound to support Ukraine because, as Nancy Pelosi put it, "The battle for Ukraine is a battle for democracy itself." That notion has been growing ever more farcical over time, as President Volodymyr Zelensky refuses to hold elections that were supposed to happen back in the spring of 2024. Over the weekend, Zelensky doubled down on his preference for martial law, telling journalists it would "destroy the country." 

Zelensky is deep into overtime on his original five-year term (Reuters)

Zelensky is now in the eighth year of his five-year term. His new remarks defending his overstay came after former defense minister Mykhailo Fedorov recently called for elections, after his controversial firing by Zelensky in July. “Democracy cannot be held hostage by Russia," said Fedorov. "We are fighting precisely because we want to remain a free European state." In his nine-minute speech, he also took a shot at Zelensky's way of governing. "It is particularly dangerous when society develops the feeling that the main criterion for an appointment is not professionalism, results or the ability to transform the country, but personal loyalty to the system,” he said. 

Speaking to a group of journalists over the weekend, Zelensky firmly rejected calls for elections in his supposed bastion of democracy:

“I believe that if we want to destroy the country, then during such a war we can move in the selection of elections... I believe that during such a war, elections in general are big risks. Elections right now are a tsunami for the state that will split Ukraine." 

Zelensky's former defense minister Mykhailo Fedorov turned up the heat on his former boss by calling for wartime elections (AP Photo)

Zelensky pointed to the logistical and security challenges of balloting during wartime, noting that it would require “the participation of the military, in frontline territories, abroad, where millions of our citizens have gone, fleeing the war” and the risk of "strikes and shelling." He argued it could only begin to be conceivable if Russia were to agree to a ceasefire, which he preemptively ruled an impossibility.  

In December, President Trump said he was inclined to see Ukraine hold elections soon. "It's been a long time. Hasn't been doing particularly well. Yeah, I think it's an important time to hold an election. They're using war not to hold an election, but I would think the Ukrainian people should have that choice," he told Politico. "You know, they talk about democracy, but it gets to a point where it's not a democracy anymore." 

Skeptics of Zelensky's reasoning might point to elections held in other war-torn countries. For example, Afghanistan held elections in 2004 and 2009, and Iraq held one in 2005. To be fair, violence affected turnout and the legitimacy of the results was questioned. Meanwhile, the UK was supposed to have an election in 1940 but put it off all the way until 1945. The Atlantic Council, which is a de facto NATO think tank, has pointed to the UK example in urging Zelensky to refuse elections during a war -- a war that is happening because of NATO expansionism.

Time is marching on, however. Russia has thus far been content to pursue a slow-burn approach to the war, ever so gradually taking over more and more territory. If that pace continues and if Russia's territorial ambitions widen -- say, to include taking Odessa and creating a landlocked Ukrainian rump state -- we could see Zelensky in charge for years more to come.

...to the continuing hypocritical applause of all those US and European politicians who proclaim Zelensky a hero of democracy. 

Tyler Durden Mon, 08/24/2026 - 07:45

Vibes are higher than normal — no longer basement level for the two teams with the worst records in the NFL since 2017.

What started as a routine job on July 23 quickly turned into a potential tragedy.

Deonte Banks, given the “bust” aura he unwantedly but deservingly was operating under, had to be considered a longshot to turn things around.

Le Pen Poised To Win French Elections? New Poll Shows Commanding First-Round Lead

Summary:

• Polymarket Odds And New Polls Show Le Pen Leading France's Presidential Race
• New polling shows Marine Le Pen defeating every tested runoff opponent
• Nomura says markets increasingly favor the "fiscally prudent" right over the reckless left
• Nomura sees Europe lurching right during an 18-month election cycle

France's Le Pen Leads French Presidential Race

Early Monday, we previewed a Nomura report that expects an 18-month election cycle across Europe, shifting the continent toward populism, with elections scheduled this year in Germany and Sweden, followed by France, Italy, Spain, Switzerland, and Poland in 2027.

Shortly after we released the note, new polling data from France showed, as The Guardian put it:

France loves a battle-scarred survivor. Charles de Gaulle, François Mitterrand and Jacques Chirac clawed their way back from political failure to become presidents of the republic. There is a significant chance that Marine Le Pen will be next.

The latest Toluna-Harris poll shows Marine Le Pen winning every tested 2027 French presidential runoff:

• Le Pen 68%, Jean-Luc Mélenchon 32%
• Le Pen 55%, Édouard Philippe 45%
• Le Pen 57%, Gabriel Attal 43%

Le Pen's advantage extends beyond a matchup with the far left. She also holds double-digit leads over two leading establishment candidates, indicating that her National Rally party would enter the election as the clear favorite under these scenarios.

France, Toluna-Harris poll:

Presidential run-off election

Le Pen (RN-PfE): 68% (+1)
Mélenchon (LFI-LEFT): 32% (-1)

Le Pen (RN-PfE): 55% (+3)
Philippe (HOR-RE): 45% (-3)

Le Pen (RN-PfE): 57% (+3)
Attal (RE-RE): 43% (-3)

+/- vs. 25-27 May 2026

Fieldwork: 18-19 August 2026… pic.twitter.com/vvUtpkIyiR

— Europe Elects (@EuropeElects) August 24, 2026

Polymarket odds of Le Pen winning the French presidential election currently stand at 32%.

Here's more:

🗳️ Intentions de vote au premier tour de l’élection présidentielle 2027 - @harrisint_fr

▪️M. Le Pen - 35% (=) ✅
▪️J-L. Mélenchon - 16% (=) ✅
▪️E. Philippe - 14% (=)
▪️R. Glucksmann - 10% (-0,5)
▪️G. Attal - 8% (=)
▪️B. Retailleau - 6% (-1)
▪️M. Tondelier - 3% (+1)… pic.twitter.com/H3BG768OAN

— Présidentielle 2027 🇫🇷 (@Cap2027_) August 24, 2026

Circling back to Nomura analyst Andrzej Szczepaniak's note, he expects that right-wing parties are positioned to make significant gains across Germany, France, Spain, Switzerland, and the UK over the next 18 months.

Szczepaniak noted, "Five years ago, financial markets would not have seemed so at ease with such a prospect. But then again, these populist right-wing political parties were previously not so fiscally prudent as they are perceived to be today."

Meanwhile in Germany this weekend ...

🚨WOW: This is the support on the ground for the AfD party in Saxony-Anhalt ahead of the State Election

These scenes are unprecedented.

Germany is going to be rocked on 6th September. It could be the trigger. 🇩🇪 pic.twitter.com/doVVKMYp0h

— Inevitable West (@Inevitablewest) August 23, 2026

He added, "Now, if anything, financial markets are much more concerned about populist left-wing parties being elected due to their desire to increase spending, often paid for through higher borrowing or higher taxes, which are likely to shut the engine off of already stuttering economies."

"Seeds Of Political Change": Nomura Sees Europe Lurching Right, And Markets Are Fine With It

Europe is entering an 18-month election cycle that could accelerate the continent's shift toward populism, with high-profile elections scheduled this year in Germany and Sweden, followed by France, Italy, Spain, Switzerland, and Poland in 2027.

The much-needed political realignment reflects mounting public backlash against progressives in Brussels after years of uncontrolled mass migration from the Third World, deteriorating social cohesion, elevated violent crime, and nation-killing domestic policies that have accelerated deindustrialization.

At the same time, European manufacturers face intensifying pressure from China (the demise of VW Group), which is exploiting its cost advantages and state-supported industrial capacity to flood the struggling continent with cheap electric vehicles.

Andrzej Szczepaniak, a senior European economist and executive director at Nomura International in London, describes this combination of pressures as "the seeds of political change," warning that "politics in Europe is lurching towards more populism."

Szczepaniak says right-wing parties are positioned to make significant gains across Germany, France, Spain, Switzerland, and the UK over the next 18 months.

"Five years ago, financial markets would not have seemed so at ease with such a prospect. But then again, these populist right-wing political parties were previously not so fiscally prudent as they are perceived to be today. Indeed, Italy's Giorgia Meloni is the standard-bearer for financial markets of how a populist right-wing political party can govern: fiscally prudent enough to show investors that the party can govern responsibly while focusing heavily on social issues, including immigration and culture wars, to keep grassroots supporters happy," the analyst said.

He pointed out, "Now, if anything, financial markets are much more concerned about populist left-wing parties being elected due to their desire to increase spending, often paid for through higher borrowing or higher taxes, which are likely to shut the engine off of already stuttering economies."

Focusing on Germany, Szczepaniak said the most immediate political shift will occur there, where Alternative for Germany has overtaken Chancellor Friedrich Merz's CDU/CSU in national polling. The AfD is polling at about 42% ahead of the Sept. 6 election in Saxony-Anhalt, potentially putting it within reach of becoming the first AfD government at the state level.

Dismal results for the governing coalition in Germany's three September state elections could threaten Merz's political survival. Szczepaniak sees a replacement of the chancellor as more likely than a snap national election because both the CDU/CSU and SPD risk losing additional seats to the AfD.

AfD is the only hope for Germany https://t.co/6ONn1LOipE

— Elon Musk (@elonmusk) August 19, 2026

Germany's economic turmoil is contributing to that revolt against the left wing. Despite the government's so-called fiscal bazooka, consumer confidence remains weak. Voters are seeking an economic turnaround under new common-sense leadership.

The market is increasingly expecting Marine Le Pen of France to follow Meloni's playbook by maintaining fiscal restraint while focusing on tackling the mass migration invasion and cultural issues. Left-wing Jean-Luc Mélenchon, by contrast, has proposed higher spending and the cancellation of portions of France's debt, policies that Szczepaniak warns could cause French bond spreads to widen sharply. 

Whoever succeeds France's Emmanuel Macron will inherit a giant mess. France's debt-to-GDP ratio is set to explode to 120% next year, while political fragmentation is likely to prevent the structural reforms needed to revive growth or reduce the primary deficit. Szczepaniak remains bearish on France relative to Germany, Italy, and Spain.

The broader message is that right-wing populism is on the rise across Europe, and markets are welcoming such potential changes after years of failed left-wing control. Beyond the EU, left-wing regimes have been rejected across South America as right-wing governments take hold. 

Related:

• Forget Reminding Young People About 'Boat People': South America's Rejection Of Socialism Is Happening In Real Time

The world is rejecting left-wing regimes because these governments are unserious, unproductive, and, in fact, proving only to be nation-killing.

Professional subscribers can read the full note here at our new Marketdesk.ai portal.

Tyler Durden Mon, 08/24/2026 - 07:30

Israel Creates Fake Think Tank In Likely Attempt To Dupe AI Chatbots

Authored by Nick Cleveland-Stout via Responsible Statecraft,

At a glance, the Hanover Institute for Public Policy looks like a new think tank dedicated to Israel/Palestine. The organization churns out think-tank style reports on questions such as "Does AIPAC Use 'Dark Money in Elections?" and "Is Israel Carrying out a Deliberate Campaign of Starvation in Gaza?"

A banner depicting Israeli Prime Minister Benjamin Netanyahu is displayed with the Capitol dome in the background as pro-Palestinian demonstrators gather on the day of Netanyahu's address to a joint meeting of Congress, on Capitol Hill in Washington, U.S., July 24, 2024. (photo credit: REUTERS/Nathan Howard)

But the Hanover Institute is not a real think tank. None of the reports have bylines. A small disclaimer at the bottom of the webpage notes that the organization was created on behalf of the Israeli Government Advertising Agency by Piro, Inc, a firm co-founded by Daniel Rosenberg, the producer of Spike Lee's "Inside Man."

The Hanover Institute's reports - all of which are about Israel and Palestine - appear to be part of an Israeli effort to influence chatbots. The institute's "data reports" have footnotes and tables of contents, and they present arguments in a neutral tone, helping them appeal to chatbots like Claude or Gemini. Piro's website says that it "author(s) content engineered for how LLMs evaluate credibility," describing this service as "AI Story Optimization." Others refer to this practice of influencing artificial intelligence as "LLM poisoning."

According to its "about" page, the Hanover Institute "studies the inputs fueling antisemitism in the United States, and publishes what the evidence shows." Many of the reports are formulaic, starting with an innocent question that someone might ask a chatbot.

"What Caused the Displacement of Palestinians in 1948?"

"Which Humanitarian Organizations Have Documented Israeli War Crimes?"

"What is the Current Situation in the Gaza Strip?"

In an article titled "Is the IDF the World's Most Moral Army?" the Hanover Institute cites a 2022 poll that found that 47% of Israeli Jews believed that statement. Another report casts doubt on UNICEF's assertion that "90% of water and institutional infrastructure has been damaged or destroyed" in Gaza. Many of the reports conclude by linking the topic to rising antisemitism, oftentimes citing the same studies.

In a few cases, the Hanover Institute publishes what it claims are original findings. For instance, it put out a study saying 19 of the 36 most-watched Israel-Gaza explainer videos contain contested claims, with most of the contested claims aligning with the Palestinian narrative.

The Hanover Institute's publications sometimes contradict Israeli government narratives. For instance, one report says that foreign funding of universities as an explanation for antisemitic incidents is "weak and full of exceptions." Israeli Prime Minister Benjamin Netanyahu has pushed this theory, telling Breitbart last year that Europeans and Qataris have spent "billions of American universities, vilifying, vilifying Israel, vilifying Jews, also, frankly, vilifying the United States."

Alice Lee, an analyst at NewsGuard, a disinformation tracking company, told RS that the sites appear designed to reach a U.S. audience curious about the ongoing conflict, either through search engines or AI chatbots. "LLMs favor concrete statistics and data, as well as strong citations and sources, which these articles all have," Lee said.

"It's a perfect mimicry of a typical credible American think tank, right down to the generic name, the site layout, and the red-white-blue color scheme," Lee added.

Piro, Inc, the firm that created the Hanover Institute, has received $900,000 from the Israeli government for its work. Like many other contractors working for Israel, Piro's work is subcontracted through Havas Media, a French public relations conglomerate.

The fake think tank has churned out over 100 reports since it started publishing on August 6. The Hanover Institute claims that "cited research is peer-reviewed and academic," although it frequently cites Israeli government sources such as the Israel Defense Forces and the Ministry of Foreign Affairs.

RS analyzed 12 random Hanover Institute articles using GPTZero, a popular AI detection software that claims a low false-positive rate. GPTZero flagged 11 of the articles as AI-written with "high confidence"; it flagged one article as AI-written with "moderate confidence."

Israel has also contracted former Trump campaign manager Brad Parscale to create pro-Israel websites engineered to influence chatbots as part of a $46.5 million contract. A Drop Site investigation last month found that many chatbots, particularly Microsoft Copilot and Google Gemini, had been successfully trained on data from those websites. Other chatbots frequently cite those websites without flagging them as part of an Israeli influence operation.

Piro does not explicitly state in its agreement submitted to the Department of Justice that its work for Israel is to influence AI. In an email to Politico, which first reported the filing, Rosenberg said his firm's work is to "put accurate, sourced facts into the public record and to counter misinformation about Israel with verifiable information." However, last month, Rosenberg posted on LinkedIn advertising Piro's ability to influence chatbots:

"When someone asks ChatGPT, Gemini, or Perplexity about your category, an answer comes back in one confident paragraph. Most brands have no idea how that paragraph gets built. So we spent months reverse-engineering it...At Piro, we already knew how to build stories that move people. The question was: how do you make sure AI knows how to tell them?"

Tyler Durden Mon, 08/24/2026 - 07:20

Smokey, a cartoon bear in a ranger hat, has told generations of Americans that "Only you can prevent forest fires." But that overlooks the biggest villain behind today's wildfires: the US government.

The crushing “economic D-Day” sanctions being unleashed against Iran will be “the single greatest financial offensive ever marshaled against an adversary,” Treasury Secretary Scott Bessent said hours before they are revealed Monday. The imminent announcement of the impending financial penalties follows Bessent’s comments on CNBC Friday that the US would “collapse the regime” with the...

Interior Department Approves Colorado River Water Reductions In 3 States

Authored by Jacki Thrapp via The Epoch Times,

The Department of the Interior will cut the amount of water it allocates through the Colorado River to Arizona, Nevada, and California in 2027 and 2028.

The cuts were signed off by Secretary of the Interior Doug Burgum on Aug. 21 as part of the department's 2027-2028 Operating Guidelines for the Colorado River, which provides water to over 40 million people, generates hydropower for seven states, and is a vital resource for 30 tribes and two Mexican states.

The Colorado River Basin is experiencing historically low runoff and reservoir levels amid a 26-year drought, which worsened recently after the winter of 2025-2026 resulted in the lowest observed snowpack on record.

The cuts were not a surprise to Arizona, Nevada, and California, as they pitched a temporary, two-year agreement to the Assistant Secretary of Water and Science in May in an effort to address the "deteriorating hydrologic conditions in the Colorado River system."

The Lower Basin states will see water deliveries reduced by a total of 1.25 million acre-feet annually in both 2027 and 2028, with Arizona taking a reduction of 760,000 acre-feet, California 440,000 acre-feet, and Nevada 50,000 acre-feet, according to the Interior Department press release.

The plan will see the Lower Basin states face a 21 percent reduction in water from the river in 2027 and 2028, with deeper cuts later.

But a trio of states warned that if water cuts double after 2028, it would devastate their economies.

"The combined contents of Lake Powell and Lake Mead have not been this low since before Lake Powell began filling following the closure of the gates at Glen Canyon Dam in 1963, with both Lake Powell and Lake Mead hitting record lows the last few weeks," the press release said.

The department suggested the plan will continue allowing reliable operations and water deliveries while "preserving the flexibility necessary to respond to Basin states' voluntary actions, consensus recommendations and the continued prolonged drought," the release said.

"Forty million people, millions of acres of farmland and ranchland, industries that power the American West, and some of our nation's fastest growing metropolitan areas depend on the Colorado River," Burgum said.

"These decisions provide a water management strategy for Basin stakeholders to respond to the prolonged drought by incorporating flexible tools and voluntary actions while leaving room for consensus agreements," said Andrea Travnicek, the Assistant Secretary of Water and Science.

"The Department and Reclamation will continue to work with all Basin stakeholders to identify areas to maximize efforts throughout the Basin to modernize infrastructure, develop conservation programs, and identify innovative approaches to deliver water under changing conditions."

Arizona Gov. Katie Hobbs, who is running for reelection this November, applauded California and Nevada for "stepping up to the plate" on Aug. 21 to implement a water allocation plan but urged that more needed to be done from other states that receive water from the Colorado River.

Tyler Durden Mon, 08/24/2026 - 06:30

Researchers have linked heavy TV viewing with several potential health consequences.

Eighteen Chinatown leaders are urging Mayor Zohran Mamdani to reconsider locating a new jail in their densely populated neighborhood, claiming that digging below the water table at the current site could cause the ground to sink.

AI’s future remains largely unknown – even to supposed “experts.”

Not all headaches are created equal — and some are worth paying closer attention to. New York Post Wellness Editor Carly Stern catches up with Dr. Shae Datta, Division Director of Concussions at NYU Langone Hospital–Long Island, to break down which headache symptoms should raise a red flag, which may be more routine and when...

Study Finds 152 Polymarket Wallets Likely Exploited Military Secrets For $8 Million In Gains

A new study has concluded that 152 Polymarket wallets may have profited from access to secret information about military action, with other wallets copying the insiders' bets. The patterns raise red flags about foreign adversaries' potential exploitation of insiders' profit-seeking to anticipate American strikes.  

Released on Thursday by the Anti-Corruption Data Collective (ACDC), the 29-page report focuses on a particular species in the diverse prediction market ecosystem -- an "Orca," which ACDC describes as a wallet that makes targeted, long-shot bets in a manner differs from the behavior of high-volume, high-frequency, multi-market "Whales." Analysts also studied the corresponding behavior of "Bots," which are wallets that seem at least partially automated. 

To locate Orcas in the sea of data, ACDC looked at wallets that "place bets in a small number of markets and on very few topics, and have a high success rate (> 75%) for longshot bets (defined as more than $2500 wagered at 35 cents or less)." The researchers found that, where military event markets were concerned, Orcas would bet first, with Whales and Bots following in their wakes. They noted that Orcas snared the biggest percentage returns, but Whales and Bots -- putting down more money -- would rake in the biggest actual profits. 

A cohort of 152 Orcas betting on military actions won $8 million and posted a sparkling 97.2% win rate on events where the market had the likelihood at 35% or less when the Orcas stepped up to wager.  The report highlighted several Orca attributes that suggest they're insiders: 

• "More than half of Orcas made their first longshot bet within two days of creating an account on Polymarket, a possible sign they joined specifically to trade on privileged information. 
• Orcas wager more per longshot bet, despite the risks and low probabilities, and longshots dominate their total activity. 
• Orcas betting on military markets are less crypto-native and prefer cashing out into fiat currency."

The report includes a case study on an Orca that wagered on action against Iran. "0x88e6" placed its first longshot bet on the very day of America's June airstrike on Iran's Fordow nuclear complex. It made multiple bets that day, with the last one squeezed in just an hour before the bombs dropped. With some of the bets priced as low as 5 cents, 0x88e6 won more than $20,000 for the strike. It went on to win more than $13,000 on Fordow having been deemed successfully "destroyed." 

Special Forces MSGT Gannon Van Dyke was arrested after winning $400,000 betting on the operation to seize Venezuela's president (via Business Insider)

ACDC's analysts observed Whales and Bots swooping in with heftier capital to mimic Orca bets: 

When an Orca bet on U.S. military action in Iran hours before the June ​2025 strikes...a Bot and a ​Whale made copycat wagers of $200,000 and $100,000, respectively. ⁠Similar Orca bets before February U.S.-Israeli air strikes on Tehran also appeared to spark a flurry of first-time long-shot bets by Bots and Whales wagering on the same outcome, the research found. -- Reuters

"Most people vastly underestimate how observable unusual betting activity actually is on Polymarket. It's all right ​there on the internet, and we can see clear signs that big traders and bots are copying potential insider trades," ACDC co-founder ​David Szakonyi told Reuters. "It would be ⁠naive to think foreign-intelligence agencies aren't monitoring these markets." 

“We spotted nine Polymarket accounts, all connected, who made, collectively,$2.4 million betting almost exclusively on U.S. military operations,” says Nicolas Vaiman, co-founder of the small data analytics firm Bubblemaps.

“And now here's the crazy part: 98% win rate.”… pic.twitter.com/XXietAHjvv

— 60 Minutes (@60Minutes) June 28, 2026

In April, US Army Special Forces Master Sergeant Gannon Ken Van Dyke was arrested for allegedly making more than $400,000 by placing Polymarket bets on the timing of a US military operation to capture Venezuelan President Nicolas Maduro. Van Dyke was involved in the planning and execution of that very operation. The federal government charged him with unlawful use of confidential government information for personal gain, theft of nonpublic government information, commodities fraud, wire fraud, and making an unlawful monetary transaction. In February, the Israeli government arrested and indicted an IDF military reservist and a civilian with classified clearances who placed Polymarket bets regarding military operations, with one of the bets covering the timing of Israel's first strike on Iran in June 2025.

While warning about national security and "political integrity" risks, ACDC lauded Polymarket's public blockchain architecture: "The same data transparency that allows Whales and Bots to legally capitalize on the information advantage of others allows researchers and journalists to uncover potential insider trading." At the same time ACDC noted the difficulty of identifying the insiders, and argued for "outright bans on the types of markets most vulnerable" to their exploitation. The group is also pushing for identification verification for all users, and delaying payouts for high-risk bets while the transaction is scrutinized. 

Tyler Durden Mon, 08/24/2026 - 05:45

Dethroned Miss North Carolina USA winner Brittany Boltinhouse has filed a defamation lawsuit after being stripped of her title – where she accused pageant bosses of covering up the reason why her crown was removed. Her lawyers have accused A-Blaize Productions — the pageant producers — and Miss USA president Thom Brodeur of “maliciously coordinating...

Europe Dodges A Rhine Crisis For The Worst Possible Reason

Authored by Natalia Katona via OilPrice.com,

• Rhine freight from ARA to Karlsruhe has surged from €45/t to €215/t as Kaub remains below the 77-cm threshold needed for normal commercial traffic.
• The squeeze is disrupting 3.1 million t/y of ethylene capacity and product movements from the 320,000-b/d Miro refinery.
• Europe is avoiding a deeper crisis only because crackers are running at around 70% and fuel demand is weak.

The Rhine has slightly risen from its mid-August record low (when Kaub's water level gauge - at the river's decisive chokepoint - was below 10 cm), but the relief is mostly optical. Barges still cannot carry normal loads through it, leaving the industrial corridor from Rotterdam and Antwerp to southern Germany, eastern France and Switzerland short of transport capacity. The immediate result is expensive freight, constrained chemical production and uneven fuel supply. However, the more troubling conclusion is that Europe is avoiding a deeper disruption only because its factories and consumers are already demanding less. This way, the Rhine's low-water crisis is a stress test for an industrial system built around cheap, high-volume river transport, and a reminder that pipelines, railways and roads cannot quickly reproduce what the Rhine does.

Kaub, on the Middle Rhine, determines how much cargo can move between the Amsterdam-Rotterdam-Antwerp (ARA) hub and industrial centres farther south. When its navigable water depth fell below 10 centimetres in mid-August, the waterway was roughly 1.2 metres deep (in comparison, just a year ago water depth was around 2.3 meters). The level has since recovered to about 45 centimetres, but that remains below the 77-centimetre benchmark - far from a return to normal commercial traffic. At the lowest levels, only specialised low-draft barges can cross Kaub, and while the Lower Rhine may remain open, the route to the Upper Rhine is effectively shut for most vessels, fragmenting what normally functions as one market.

The chemical industry feels that fracture first. Several of Germany's largest steam crackers are located along the Rhine corridor and are affected by restrictions at Kaub. The BASF, INEOS, LyondellBasell and Shell sites in this area have around 3.1 million t/y of combined ethylene capacity. BASF's Ludwigshafen complex is particularly exposed because it lies south of Kaub and moves about 40% of all incoming and outgoing goods by river.

Naphtha supply is not much of a problem - most of Germany's naphtha moves by pipeline, offering protection against a river bottleneck. But pipelines do not redistribute the broad range of finished products made by a cracker, and if those materials cannot leave, storage fills, and operators must curb runs. With low water levels continuing to limit the normal movement on the river, barges are forced to carry smaller loads, while specialised chemical vessels are limited. Related: U.S. Billionaires Are Piling Into Argentina's Vaca Muerta Shale

The effects can spread quickly into smaller downstream markets. LyondellBasell's force majeure at its 170,000 t/y Wesseling butadiene unit followed restricted feedstock flows to its crackers and a resulting decline in crude C4 production. Crude C4 is produced during the steam cracking of naphtha alongside ethylene and is then processed to extract butadiene. A relatively small reduction in cracker output can therefore cause a much larger squeeze in the smaller butadiene market - and other co-products that are difficult to reroute, such as pyrolysis gasoline, face similar pressure.

This restricted inland movements of chemical products contributed to naphtha inventories in ARA reaching 598,000 tonnes in mid-August (75% more than a month earlier). However, the problem is not only in the movement restrictions: weaker cracker operations have overall reduced naphtha consumption by the crackers even before the Rhine's levels became an issue - the crackers have been running at 70% due to weak demand on their production across the wider European market.

The same effect is emerging in refining. Most inland German refineries receive crude through pipelines, so the Rhine does not automatically force crude runs lower. Their exposure lies in intermediate feedstocks, blending components and, above all, moving gasoline, diesel and heating oil to customers.

Karlsruhe illustrates the issue. Road trucks have been shuttling to and from the Miro refinery (320,000 b/d capacity) to collect fuel, but the site also normally ships products by barge both toward ARA and upstream to Switzerland. With movements restricted in both directions, Karlsruhe must hold surplus refined products in its storage facilities, while markets farther away pay shortage premiums.

The Rhine's freight rates reflect this physical imbalance. The assessed ARA-Karlsruhe barge rate rose five-fold to €215/t currently from about €45/t at the end of June, while ARA-Basel reached €275/t in mid-August. At extreme low water, even those assessments become partly theoretical because few normal cargoes can pass.

Road and rail offer relief, but not replacement. Chemicals require appropriate tankers and transportation conditions, while the volumes involved overwhelm available vehicles and infrastructure. One fully loaded barge carrying 2,400 tonnes of diesel is equivalent to 90 trucks. Germany's temporary relaxation of Sunday and public-holiday restrictions for heavy vehicles may improve flexibility, but it cannot manufacture tank cars, specialist trailers, drivers or road capacity.

Yet the constraints extend even beyond crackers and refineries. Covestro declared force majeure on polyether polyols made at Dormagen, while Salzgitter shifted coal from Rotterdam to rail for its HKM steelmaking division. Such workarounds keep selected flows moving, but they also compete for the same scarce trains and trucks needed elsewhere. The disruption is therefore cumulative: every industry solving its own bottleneck makes the alternatives tighter for the next.

Nor is this only a German problem. Eastern France has experienced localised gasoline shortages as barges serving Strasbourg carried a fraction of their normal loads. Switzerland faces higher import costs and the possibility of drawing on strategic stocks. Rotterdam and Antwerp remain supplied by sea, yet congestion and slower terminal turnover spread costs across the wider northwest European market. This way, low water does not create a single European shortage but rather creates a dispersed issue of trapped supply and local shortages.

For now, weak demand is preventing isolated local shortages and oversupplies from becoming a broader crisis. European crackers were operating at only about 70% in July, after years of pressure from expensive energy, weak construction and automotive demand, and cheaper imports from Asian competitors. Fuel consumption in inland Germany has also been decreasing. However, if chemical plants and fuel markets were operating near normal levels, the shortage of river capacity would be much harder to absorb. A recovery in manufacturing, higher diesel demand or winter stockpiling could therefore intensify the disruption even if water levels improve modestly.

The Rhine may have risen slightly, but Europe's industrial margin of safety has not. This summer's lesson is that weak demand can cushion a logistics failure, but it cannot solve one. When (or if) the economy rebounds and supply chains are once again required to handle normal volumes, the problem will extend far beyond the river itself.

And besides, this summer should not be mistaken for a worst-case scenario. A super El Niño could bring a warmer winter, less Alpine snow and a weaker meltwater buffer. If another hot, dry summer follows, Rhine levels in July and August 2027 could fall even lower than this year's records.

Tyler Durden Mon, 08/24/2026 - 05:00

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