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Why OpenAI's IPO Will CRASH The Stock Market - Video học tiếng Anh
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Why OpenAI's IPO Will CRASH The Stock Market
Why OpenAI's IPO Will CRASH The Stock Market
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0:00
Wall Street says OpenAI’s IPO will create trillionaires, but the truth is far darker.
0:05
It could destroy your retirement. There’s a hidden flaw in their accounting… one
0:10
that nobody’s talking about. Their revenue hit $25 billion in 2026 and they’re not done. They want
0:16
a $750 billion to $1 trillion IPO. That’s 30 to 40 times what they actually generate in revenue.
0:24
Everyone’s celebrating like it’s a tech gold rush. But this isn’t wealth… it’s a financial time bomb
0:30
that could trigger chaos across Wall Street. The OpenAI IPO valuation is the kind of number
0:36
that breaks every rule for a software company. It only works if they somehow
0:40
capture the entire global AI market… and slash operating costs to almost nothing.
0:46
Which is a long shot when you look at what it actually takes to build and run these systems.
0:50
Normal software businesses get valued high because they're predictable cash machines with almost no
0:56
extra cost for each new customer. OpenAI? It's the opposite story. There are huge infrastructure
1:03
bills, massive power and cooling needs, and expenses that grow alongside every user. Investors
1:09
are being asked to put up enormous money betting everything lines up perfectly in the future,
1:14
even though the upfront spending and ongoing cash burn are massive. It's bold but going from today’s
1:20
revenue to a trillion dollars? That’s a huge leap.
1:24
The kind that only works on paper. Scaling to that level would require
1:28
everything to go perfectly. And perfection is rare in tech. Think of it this way. A
1:33
normal $500,000 house in a quiet suburb sits on a solid foundation, with reliable framing,
1:39
maintenance you can count on, and plumbing that works. Everybody agrees on that price
1:44
because the structure is proven and reliable. On the lot next door, someone is trying to
1:48
sell a gleaming 100-story glass skyscraper for $8 million. From a distance it looks
1:54
impressive. But close up, it’s all smoke and mirrors. There's no solid foundation,
1:59
no steel skeleton anchored to bedrock. Every floor, every pane of glass, every person inside
2:05
is resting on nothing that could possibly hold it. That’s exactly what venture capital is
2:10
doing with AI. It’s holding
2:12
the whole structure together… for now. The crushing load is the relentless, ballooning
2:17
cost of AI infrastructure. Unlike regular software, AI doesn't ride the zero-marginal-cost
2:22
wave. Every single time somebody types a prompt, real hardware has to spin up and burn through
2:28
resources. A regular Google search or pulling a file from the cloud? It's a cheap database hit,
2:34
pennies or less. Generative AI is a different beast entirely. When the model cranks out a legal
2:39
brief or a high-res image, it does way more than fetching pre-existing data. It’s actually building
2:45
something brand new from scratch. And that’s the big breakthrough. But now the question is
2:50
how well and how far it can go. It’s a process that costs far
2:54
more than humanity is ready for. And that money has to come from somewhere.
2:58
OpenAI is bleeding cash at a pace that's hard to wrap your head around. Right now
3:03
internal numbers show they're set to lose at least $14 billion in 2026… just to keep the
3:09
lights on and the models running. The latest internal revisions are
3:13
pushing that figure toward $25 billion - or even higher - as they ramp up compute power
3:19
chasing the next breakthrough. And it doesn’t stop there.
3:22
Annual cash burn could spike to $57 billion in 2027 alone. Add it all up, and cumulative cash
3:29
burn through 2030 now sits around $665 billion. That’s over $111 billion more than they were
3:37
forecasting just months ago. The reason?
3:40
Infrastructure costs exploded way beyond what anyone planned. Power, custom data centers,
3:47
endless chip upgrades, every piece costs more than expected. Every single dollar of revenue they're
3:52
pulling in costs way more to generate. Growth doesn't fix this problem.
3:57
It makes it worse. More users mean more prompts. More prompts
4:01
mean more hardware spinning up… and that means bigger losses. It’s baked into the model. To stop
4:07
the servers from going dark and give themselves 18 to 24 months of breathing room, OpenAI is counting
4:12
on pulling in up to $60 billion dollars from this IPO. Not for world domination or new offices.
4:19
For life support. If the cash doesn't appear,
4:22
somebody has to write the check. So why would Wall Street willingly drain its own accounts to feed
4:27
this machine? They know the burn numbers. They see the red ink piling up. Yet the plan is still
4:33
to hand over $100 billion like it's no big deal. The stock market is basically a closed plumbing
4:38
system. There's only so much money actually moving around in stocks, bonds, mutual funds,
4:43
pension accounts and cash piles. The total amount doesn't magically grow just because
4:48
someone wants more. Every dollar flowing into OpenAI shares comes from somewhere else.
4:53
When they pull massive sums quickly, everything downstream starts to starve.
4:58
The buyers who can actually write a $100 billion check aren't small-time traders or retail folks on
5:04
apps. They're the giants. Sovereign wealth funds from the Middle East, government pension plans,
5:09
the biggest mutual funds and endowments on the planet. They don’t sit on piles of cash. Idle
5:14
money loses value to inflation. Every dollar has to stay fully invested, according to strict rules.
5:20
To buy into the OpenAI IPO, these funds have to free up cash. They start with the
5:25
assets that are easiest to move without creating chaos… like Apple. Apple stock is super liquid,
5:32
with millions of shares trading every day. So the funds sell huge blocks, and the price starts
5:37
sliding almost immediately. They do the same with other stocks like Tesla and Amazon. Managers
5:42
rotate money out of proven e-commerce winners into the shiny new thing everyone is talking about.
5:48
These aren't gentle trades. Heavy selling hits the tape.
5:52
Prices dip. Forced rebalancing kicks in across portfolios. But that's only the first wave.
5:57
The real damage comes next. Trading algorithms watch every tick,
6:01
every spike in volume. When they see big blocks moving, they trigger automatic shorts to protect
6:06
themselves. Market makers - the firms keeping the system flowing - sell more of the same stocks
6:11
to stay neutral. Prices drop faster. Lower prices trigger stop-loss orders from regular
6:16
investors who weren’t even planning to sell. More selling hits the market. Automated shorts
6:21
pile on. Panic feeds on itself. And just like that,
6:25
a vicious cycle starts rolling. Solid, profitable companies - the
6:28
ones that actually make money year after year and back most 401(k)s and pensions - get sold
6:33
off just to fund the newcomer. Money is pulled out of proven winners to cover the needs of a
6:38
company that's losing billions. Tech doesn’t crash because earnings are weak. It crashes
6:44
because the liquidity vacuum from IPO funding forces aggressive selling across the board.
6:49
This is exactly why OpenAI's IPO will break the stock market.
6:53
The funding mechanism itself destroys value everywhere else before the shares even start
6:58
trading widely. The drain is real. And the supposed safety net everyone is counting on?
7:04
That's next in the firing line. The liquidity drain is nasty. Big
7:09
funds are dumping Apple, Tesla, Amazon to scrape together billions for OpenAI, that's going to hurt
7:14
some prices short term. But the Magnificent Seven? Those are monsters. Microsoft and
7:20
Nvidia alone sit on trillions in market cap with balance sheets that look unbreakable. They have
7:26
deep pockets and massive cash flows. They'll just absorb the shock. Maybe even step in to
7:31
backstop OpenAI if things go wrong. Big Tech has saved the day before.
7:36
They'll do it again, right? Microsoft already poured billions
7:39
into OpenAI and owns a huge chunk. Nvidia is tied to selling chips for exactly these
7:45
kinds of AI builds. If anyone could handle a $100 billion liquidity suck without blinking,
7:50
it’s them. On the surface, it makes sense. Except, that won’t happen.
7:55
Microsoft and Nvidia aren't the cavalry riding in. They're chained to the same sinking boat OpenAI
8:01
is on. The connections run so deep that when one starts taking on water, the others go down too.
8:07
Take Microsoft first. They're not just writing checks as a side bet. They own roughly 27% of
8:13
OpenAI, a stake worth about $135 billion. But that could double to $270 billion if OpenAI hits the
8:22
trillion dollar valuation everyone's throwing around. They locked in a 20% cut of OpenAI's
8:27
revenue through at least 2032. The part that really matters?
8:31
How the money actually moves. A big piece of the original $13
8:35
billion investment didn't come as clean cash. It came as Azure credits. OpenAI uses those
8:42
credits to pay Microsoft back for renting servers. Money leaves Microsoft's pocket,
8:48
circles right back in through cloud revenue. It's a closed loop that looks genius on paper.
8:53
Until it isn't. Starting to sweat about AI wiping
8:56
out your future earnings? Don’t panic, we’ve got the real story. Make sure to like, share,
9:00
and subscribe before the algorithms do it for you. If the IPO faces real scrutiny and the valuation
9:06
cracks… or if cash burn forces OpenAI to slash server usage,
9:10
that whole loop breaks. Microsoft loses its single biggest Azure customer almost overnight.
9:16
Those custom AI data centers Microsoft built aren't plug-and-play for regular cloud storage.
9:22
They're specialized for heavy AI workloads, liquid cooling, massive power draw, custom setups.
9:28
Revenue takes a direct hit. About 45% of Microsoft’s roughly
9:32
$625 billion commercial backlog is tied to OpenAI commitments. When earnings come out,
9:39
the link isn’t speculation anymore. One big renter gone, and billions in revenue are at risk.
9:45
Nvidia's in the exact same trap… maybe even worse. Their data-center business exploded because
9:51
frontier AI labs like OpenAI burn through insane volumes of chips. Over 80% of recent
9:57
data-center growth comes from this small group of customers. Nvidia’s guidance assumes these
10:02
massive orders will continue. By the end of 2027, they’re projecting $1 trillion
10:08
in cumulative data-center revenue. Most of that rides on OpenAI and the other labs keeping the
10:14
orders flowing. If the IPO forces a reality check and spending gets cut, those orders dry up fast.
10:21
The trillion-dollar dream turns into a question mark overnight.
10:24
The supposed lifeguards are drowning right alongside the guy they were supposed to save.
10:29
No bailout. No absorption.
10:32
Just shared collapse when the cash demands hit too hard.
10:35
This isn't stopping at two companies. The Magnificent Seven - Apple, Microsoft, Nvidia,
10:41
Amazon, Alphabet, Meta and Tesla - currently make up 33 to 35% of the entire S&P 500. One out of
10:48
every $3 in the average American's 401(k) pension plan is sitting in those seven balance sheets.
10:55
When OpenAI's cash drain creates the liquidity vacuum we mentioned earlier,
10:59
the foundation starts cracking. The funds see the risk early and start selling. That triggers
11:05
passive index funds to dump shares automatically. What began as ‘just some selling to fund an IPO’
11:11
turns into a full sector meltdown. Trillions in market value disappear. Not because the
11:17
businesses got worse, but because forced moves tied to OpenAI’s math ripple through everything.
11:23
This is exactly why OpenAI's IPO will break the stock market.
11:27
The safety net everyone counted on turns out to be the biggest vulnerability in
11:31
the system. When it rips, it goes through the entire index. Every retirement account
11:35
that seemed safe gets hit. The market structure itself starts to fail the moment the liquidity
11:41
pull exposes just how intertwined everything is. The damage spreads whether anyone wants it or not.
11:47
Going public? It’s almost a death sentence. OpenAI has lived its whole life in the shadows
11:52
as a private company. That was their golden ticket. They could stack up catastrophic
11:57
losses and keep them buried under layers of venture capital fairy dust, press releases,
12:02
and nonstop hype about owning the future of everything. Investors swallowed the
12:07
story whole because it felt good. The math would work itself out eventually.
12:12
Or so everyone told themselves. Losses of $14 to $25 billion for 2026,
12:17
spiking to $57 billion in 2027. Cumulative cash burn now revised up to $665 billion by
12:25
2030. All of it stayed locked away. Only the inner circle saw the full picture.
12:30
Everyone else got the polished version. The house-of-cards valuation only stayed upright
12:35
because nobody had the real books to look at. The moment they file the paperwork to go public,
12:41
that protection vanishes. Strict SEC rules come into play. No more hiding behind NDAs,
12:47
selective leaks, or "trust us" slides. Wall Street gets the unfiltered
12:51
truth for the first time. And the truth is brutal.
12:54
The filings will lay bare the actual ratio. AI infrastructure spending is off the charts. Power
13:00
grids are being rebuilt. Custom data centers with liquid cooling and massive power feeds.
13:04
Chips upgraded every 18 months because the hardware burns out fast. Meanwhile, end-user
13:09
profits are nowhere near close. Losses aren't a phase they're growing out of. They're structural.
13:16
Each new user doesn't bring free money; it multiplies the burn. What the market
13:21
priced as a lightweight digital app gets exposed as a heavy industrial
13:25
utility project with no margin of error. All of a sudden that trillion dollar
13:29
dream is put under a microscope. Investors who bought the story
13:33
on faith now have to face reality. The IPO will either be way below the hype,
13:37
signaling disaster to the whole market… or it gets downsized or pulled entirely, which is even worse.
13:44
Wall Street would have to admit the core equation doesn’t work:
13:46
revenue growth can't outrun infrastructure costs. The private AI startup market's $1.6 trillion
13:53
valuation tower would get the same reality check at once. Funds start to dump anything with AI
13:59
exposure. What looked like unstoppable momentum turns into an overvalued bubble overnight.
14:05
For years, private venture funding has let OpenAI play fast and loose. ‘Adjusted’ metrics inflated
14:11
the story. Monster expenses were buried under the vague label of ‘R&D.’ They sold
14:16
the dream of sky-high software-like margins. The federal government doesn’t play that game.
14:22
SEC rules demand real accounting, and that means every piece of hardware has to be treated like
14:28
the depreciating industrial asset it actually is. This is where the financial reality hits like a
14:33
freight train. Those custom GPUs powering frontier models aren’t timeless infrastructure like a cell
14:39
tower or undersea cable. A top-tier AI chip stays competitive for maybe 24 to 36 months
14:45
before newer architectures make it obsolete. Running tens of thousands - or hundreds of
14:50
thousands - of GPUs across sprawling data centers is brutal. Filings will have no choice but to show
14:56
billions in hardware write-downs each quarter. Gross margins will be deep in the red. They’re
15:02
losing money on the physics of compute… and that’s before salaries, electricity or anything else.
15:08
OpenAI will have to disclose the real-world bottlenecks that are throttling expansion.
15:12
Building a 1-gigawatt AI cluster isn’t just about buying chips. It’s about securing
15:17
enough electricity. Upgrading a regional grid means hundreds of miles of high-voltage lines,
15:23
substations, and waiting years for step-down transformers that are already backlogged.
15:28
Lead times in many markets are stretching toward 48 months. No amount of cash or hype
15:33
can manufacture transformers or rewrite physics. The growth model slams into a
15:38
wall. They can’t pull enough power fast enough to keep pace with the cash burn.
15:42
Once the audited filings go public, everyone sees the truth. Negative unit economics and
15:48
multi-year infrastructure bottlenecks. The algorithms flip instantly. Suddenly,
15:52
the AI-adjacent ecosystem - Nvidia, Microsoft, AMD, the hyperscalers - gets re-rated.
15:59
That sparks real damage in the financial system. Hedge funds and investors had been borrowing
16:04
against these tech giants, piling on more positions. When the filings drop, suddenly
16:09
that paper value disappears. Funds scramble to sell anything they can - tech, industrials,
16:15
consumer staples - whatever moves fastest. The pain doesn’t stop at equities.
16:19
Credit markets feel it next. Corporate bond spreads widen as investors wake up to the fact
16:24
that the long-promised AI productivity miracle was built on sand. Companies that loaded up on debt to
16:30
chase AI integration now look overextended. If the flagship labs can’t turn a profit,
16:36
the downstream adopters who bet on the same tech look even riskier. The private
16:41
$1.6 trillion AI valuation tower implodes. None of this happens because of some viral
16:47
tweet or bad earnings call. It happens because the SEC forces transparency that
16:52
private markets never require. Trillions in paper wealth evaporate not from fear,
16:57
but from arithmetic that can no longer be ignored. And the fallout keeps moving. The same physical
17:03
constraints are already stressing Nvidia’s supply chain to the breaking point. The production lines
17:07
that assemble chips are already stretched. Specialized packaging capacity is limited,
17:12
and high-bandwidth memory supply is running short. Any slowdown in these areas can strand billions
17:17
in promised capacity, turning the data-center boom into a graveyard of half-built clusters.
17:23
The cracks are forming now, deeper than most headlines admit.
17:27
To see exactly how those same physical pressures are putting Nvidia’s entire
17:30
chip empire on the edge, and why one weak link could cascade into the next leg down,
17:36
check out the follow-up: “Why Nvidia’s Supply Chain Is About
17:39
to Break the Market Even Harder.” It picks up right where this leaves off.
