Wall Street slips as OpenAI apparently seeks a government bailout
·
At 223 TTM EPS (Q2CY25) and 7000 levels, SPX-500
TTM PE is 31; well into bubble zone of 30; projected CY25-26 EPS 234-259;
best-base case PE: 25-20
·
OpenAI is seeking an AI infra ecosystem funded by a
public-private partnership (PPP mode) for the benefit of the government (as a
big AI client)
·
The market is concerned about AI circular/vendor
finance like a Ponzi scheme and sky-high valuation amid hopes of blockbuster
future growth and innovations
OpenAI's Chief Financial Officer (CFO), Sarah
Friar, highlighted the CAPEX challenge during a Wall Street Journal (WSJ)
conference on November 5, 2025, noting that the company's expansion requires
unprecedented investments—potentially over $1 trillion—for AI chips, data
centers, and related infrastructure. She suggested that U.S. government loan
guarantees or a "backstop" (rather than direct subsidies) could lower
financing costs and de-risk these massive projects, especially given
uncertainties around the lifespan of AI data centers and the scale of private
capital needed.
Highlights:
·
Scale of Investment: OpenAI and partners like Microsoft are eyeing a
buildout that dwarfs historical corporate efforts, with estimates exceeding $1
trillion over the coming years to support advanced models like potential
successors to GPT-4.
·
Rationale: AI
infrastructure demands enormous upfront capital with long gestation periods.
Government support, Friar argued, would mirror models used for other critical
sectors (e.g., energy or telecom) to attract investors by reducing perceived
risks.
·
Clarification: In a LinkedIn post shortly after, Friar walked back some phrasing,
emphasizing that OpenAI isn't actively seeking a "government
backstop" but is open to policy discussions that could facilitate private
funding. This came amid backlash, including from tech investor David Sacks, who
quipped on X that "there will be no federal bailout for AI" and that
market competition would handle any failures.
Broader
Context
This push aligns with growing industry calls for
public-private partnerships (PPP) in AI, especially as the U.S. aims to
maintain a lead over global competitors like China. Similar requests have come
from Meta and others for energy infrastructure to power data centers. However,
it risks political scrutiny in a cost-conscious environment, with critics
viewing it as a veiled subsidy for Big Tech profits.
David
Sacks, President Trump's newly appointed "AI Czar" (or White House AI
advisor), who posted it on X on
November 6, 2025, in response to OpenAI CFO Sarah Friar's recent comments about
needing government loan guarantees for AI infrastructure.
“Buildout,
not bailout: There will be no
federal bailout for AI. The U.S. has at least 5 major frontier model companies.
If one fails, others will take its place.
To be clear, no one is asking for a bailout—that would be ridiculous.
But if execs want to talk policy to make private financing easier, let's have
that discussion. Just call it what it is: deregulation, not a backstop. That
said, we do want to make permitting and power generation easier. The goal is
rapid infrastructure buildout without increasing residential rates for
electricity.
The two biggest narratives about AI right now are
that (1) it's a massive bubble (i.e., totally fake) and (2) it's about to give
rise to superintelligence (i.e., totally real). Both narratives can be fake
(which is what I believe), but it's very unlikely that both can be true. Finally, to give the benefit of the
doubt, I don't think anyone was actually asking for a bailout. (That would be
ridiculous.) But company executives can clarify their own comments. Everyone in
Silicon Valley understands that the way to win a technology race is to get the
most users and developers on your platform. Yet the anti-export lobby in
Washington keeps inventing reasons why America’s friends and allies shouldn’t
be allowed to build on the American tech stack. This is profoundly damaging to
American interests and jeopardizes our lead in the AI race.”
This came hours after Friar's WSJ conference
remarks (and her partial walk back on LinkedIn), where she floated U.S.
government "backstops" to de-risk $1T+ investments in chips and data
centers. David Sacks, a PayPal Mafia alum and vocal Trump supporter, is pushing
a hands-off approach: Let private markets fund AI growth, with government
focused on deregulation and export controls to counter China. It's a signal of
the Trump administration's stance—pro-innovation but anti-subsidy for Big Tech.
Sacks has been vocal about AI policy, arguing that over-reliance on a few
players (like OpenAI/Microsoft) stifles competition. Sacks' role was formalized
just days ago, positioning him as a key voice in Trump's AI agenda.
On late
October 6, 2025, the OpenAI CEO Sam Altman said the Company Won’t Seek Government Datacenter
Guarantees. Altman said the company does not seek government guarantees for
datacenters, emphasizing that taxpayers should not back private ventures. He
supports governments building and owning AI infrastructure for public benefit,
potentially at lower capital costs. Altman noted OpenAI may help with U.S.
semiconductor fab expansion but distinguishes this from private datacenter
support. OpenAI expects $20 billion annualized revenue in 2025, aiming for
hundreds of billions by 2030, with $1.4 trillion in eight-year compute commitments.
Altman stressed the company could fail like any other, investing now to meet
anticipated AI demand and scientific breakthroughs.
Altman
tweeted:
I would
like to clarify a few things.
First, the
obvious one: we do not have
or want government guarantees for OpenAI datacenters. We believe that
governments should not pick winners or losers, and that taxpayers should not
bail out companies that make bad business decisions or otherwise lose in the
market. If one company fails, other
companies will do good work.
What we do
think might make sense is governments building (and owning) their own AI
infrastructure, but then the
upside of that should flow to the government as well. We can imagine a world
where governments decide to offtake a lot of computing power and get to decide
how to use it, and it may make sense to provide lower cost of capital to do so.
Building a strategic national reserve of computing power makes a lot of sense.
But this should be for the government’s benefit, not the benefit of private
companies.
The one
area where we have discussed loan guarantees is as part of supporting the buildout of semiconductor fabs in the US,
where we and other companies have responded to the government's call, and where
we would be happy to help (though we did not formally apply). The basic idea
there has been ensuring that the sourcing of the chip supply chain is as
American as possible in order to bring jobs and industrialization back to the
US, and to enhance the strategic position of the US with an independent supply
chain, for the benefit of all American companies. This is, of course, different
from governments guaranteeing private-benefit datacenter buildouts.
There are
at least 3 “questions behind the question” here that are understandably causing
concern.
First, “How
is OpenAI going to pay for all this infrastructure it is signing up for?” We expect to end this year with $20 billion, an
annualized revenue run rate, and grow to hundreds of billions by 2030. We are looking
at commitments of about $1.4 trillion over the next 8 years. Obviously, this
requires continued revenue growth, and each doubling is a lot of work! But we
are feeling good about our prospects there; we are quite excited about our
upcoming enterprise offering, for example, and there are categories like new
consumer devices and robotics that we also expect to be very significant. But
there are also new categories we have a hard time putting specifics on, like AI
that can do scientific discovery, which we will touch on later.
We are also looking at ways to more directly sell
compute capacity to other companies (and people); we are pretty sure the world
is going to need a lot of “AI cloud”, and we are excited to offer this. We may
also raise more equity or debt capital in the future.
But everything we currently see suggests that the
world is going to need a great deal more computing power than what we are
already planning for.
Second, “Is OpenAI
trying to become too big to fail, and should the government pick winners and
losers?” Our answer to this is an
unequivocal no. If we screw up and can't fix it, we should fail, and other
companies will continue doing good work and servicing customers. That's how
capitalism works, and the ecosystem and economy would be fine. We plan to be a wildly successful company,
but if we get it wrong, that’s on us.
Our CFO
talked about government financing yesterday, and then later clarified her point, underscoring that she could have
phrased things more clearly. As mentioned above, we think that the US
government should have a national strategy for its own AI infrastructure.”
The AI
Ecosystem: A Circular Financing Revolution or an Impending Bubble?
The AI Gold
Rush: How OpenAI Became Silicon Valley's Most Expensive Customer
This diagram reveals something extraordinary:
OpenAI isn't just raising capital—it's orchestrating the most sophisticated
circular financing scheme in tech history, where every dollar invested flows
right back to the investor's pocket.
The
Perpetual Motion Machine
Look closely at the arrows. Microsoft invests
billions; then charges OpenAI for Azure compute. NVIDIA “invests” $100 billion;
then sells OpenAI the very GPUs that money will buy. Oracle inks a $300 billion
cloud deal while simultaneously taking an equity stake. Even AMD offers GPUs in
exchange for equity options. This isn't
venture capital; It is vendor financing dressed in an equity wrapper, and the
Wall Street is scaling a fresh lifetime high every other day, primarily led by
AI stocks at exorbitant valuations on hopes of future growth and further
innovations.
Why This
Structure Is Brilliant (and Dangerous)
For the
investors, it's genius:
·
Zero risk: Your
“investment” returns as immediate revenue
·
Double-dipping:
You profit from both equity appreciation and operational spending
·
Strategic moat:
OpenAI becomes structurally dependent on your ecosystem
·
Accounting
magic: Investment goes on the balance sheet; revenue flows through the income
statement
For OpenAI,
it's a gilded cage:
·
That $1 trillion
IPO valuation? Built largely on committed spend obligations, not free capital.
·
Infrastructure
lock-in means no negotiating leverage
·
The “partners”
control the picks and shovels of AI development
The Broader
Implications
This diagram illustrates vertical integration
through financial engineering—a way to control the AI supply chain without
triggering antitrust scrutiny. Microsoft doesn't need to own OpenAI outright;
they've achieved something more elegant: OpenAI cannot operate without
Microsoft's infrastructure. Notice the
web of smaller AI companies (xAI, Mistral, Figure AI, Anthropic) all connected
to the same investors? They're all trapped in similar dependency structures.
NVIDIA especially sits at the centre, collecting rent from every AI Company,
regardless of who “wins.”
The
Emperor's New Valuation
Here's the uncomfortable truth: OpenAI's $500-1000B
valuation assumes it can eventually generate profits that justify this number.
But if most of its capital inflows are pre-committed to outflows for compute
and infrastructure, the actual equity value is a fraction of the headline
number.
Is it going
for the infamous 1990s dot-com bubble?
It may be a reminder of the telecom/dot-com bubble
of the late 1990s, when equipment vendors financed their own customers'
purchases, inflating both their revenues and their customers' apparent
value—until the music stopped.
Conclusions
When the AI hype cycle corrects, or if OpenAI fails,
who's holding the bag? The answer might be "everyone except NVIDIA,"
to a lesser extent, which has already been paid in cash for those chips, the
fundamental pillar for the entire AI infrastructure ecosystem, growing at ~45%
CAGR. OpenAI may now be in the 'too big to fail' category. The growing tech
bubble (AI+ Cryptos), subprime crisis/delinquencies, weak labor market, higher
cost of living, and never-ending Trump policy tantrum (24/7 nonsensical
talks)-we may see another financial crisis in 2026. The AI ecosystem needs huge
energy at a cheaper rate, something in which China is far ahead of the US. The
US needs green & alternative energy at a cheaper cost like China to
compete; otherwise, China is clearly way ahead in the longer run AI
competition.
Valuation:
SPX-500
In the stock market, the bottom line is earnings
(EPS); everything else is noise. The TM EPS (Q2CY25) for SPX-500 was 223 vs 217
sequentially (+2.6%) and 196 yearly (+13.6%). At the current run rate, the CY25-26
SPX-500 EPS should be around 234-259, indicating 7000-7778 levels are a bubble
zone for 2025 26. Overall, the average (median-bubble/best/base/worst case)
fair value should be around 5273-5834 for 2026.
Market Wrap
Wall Street slid Thursday, October 6, 2025, on the
concern of an AI bubble, reported big tech shorts by 2008 GFC short sellers
(Murry), hawkish Fed talks, upbeat ADP private payroll data & fading hopes
of another rate cut in December. This came against the backdrop of an ongoing
federal government shutdown, costing the economy dearly. Dow Jones (DJ-30) and
SPX-500 slipped around 1%, while tech-savvy NQ100 slid 2%.
Key Drivers
of the Selloff
AI and Tech
Valuation Worries:
Mixed earnings reports reignited debates over
whether AI hype has outpaced fundamentals. High-profile names tumbled, with
semiconductor and software firms hit hardest, led by AMD, NVIDIA, Palantir,
Qualcomm (muted report card tied to AI chip demand); Tesla (pre-shareholder
meeting jitters over EV demand and AI integrations), Oracle, Microsoft, Amazon,
and Meta. Despite year-to-date gains
(S&P 500 up ~13% YTD), analysts noted the market's concentration in AI
mega-caps—eight of the top 10 stocks by market cap are AI-tied—raising bubble
fears.
Government
Shutdown Ripple Effects:
·
Now in its 38th
day (longest in US history), the
shutdown—sparked by budget disputes over rescissions, DOGE cuts, and ACA
credits—has furloughed ~2 million federal workers and delayed data like BLS
employment stats.
·
SNAP benefits
halved for November (affecting 41M recipients), WIC programs strained, and food
banks overwhelmed. This uncertainty amplified Thursday's downside, as softer
private indicators filled the data void.
·
42 million
people face interruption of SNAP
·
3.5 million
people have seen airfare disruptions
·
750,000
employees furloughed
·
5,000 flights
set to be cancelled per day
·
$15 billion in
US GDP lost per week
·
$10 billion of
SNAP payments at risk
·
23% of federal
employees set to be furloughed
·
10% reduction in
flight capacity at 40 airports
Technical
outlook: DJ-30, NQ-100, SPX-500 and Gold
Looking
ahead, whatever may be the narrative, technically Dow Future (CMP: 47700) now has to sustain over 48000 for a
further rally to 48300* and 48600/49000-49700/50000 in the coming days;
otherwise sustaining below 47900-47700, DJ-30 may fall to 47200/47000-46500/46200
and further 45500/44950-44500/44200 and 43500 in the coming days.
Similarly,
NQ-100 Future (25800) now has
to sustain over 26100 for a further rally to 26200-26500 in the coming days;
otherwise, sustaining below 25750, NQ-100 may fall to
25300/25000-24700/24500-24300/24300 and 23700/23400/23000 and 22600/22400 in
the coming days.
Looking at
the chart, technically SPX-500
(CMP: 6880) now has to sustain over 7050-7100 for a further rally to
7200/7300-7500/8300 in the coming days; otherwise, sustaining below
7025/6900-6800/6750, may fall to 6650/6595 and 6490/6450-6375/6300-6250/6200
and further fall to 6080 in the coming days.
Looking at
the chart, Technically Gold (CMP:
$4025) has to sustain over 4060-4125 for a further recovery to 4395-4405 for
4425/4455-4475/4500 to 4555-4575 and even 5000 zone in the coming days;
otherwise sustaining below 4050-3875, Gold may again fall to 3770 and
3700/3600-3500/3450 and 3350 levels in the coming weeks.
