सुहास Suhas

speak less, listen, learn, stay calm

[सुहास Suhas @suhasgujarathi]

once upon a time

this is how it all began

all thieves and robbers got together

they realized only by stealing and thuggery they can only make so much and chances of losing the stolen wealth to others is certain

they made laws so that only they can stay as thieves and robbers but be called noble

first law - no one other than them can be a thief or a robber

they kept coming with new laws as time passed just to ensure that the first law is always valid

[सुहास Suhas @suhasgujarathi]

https://t.co/T1f0gd9IwS

[सुहास Suhas @suhasgujarathi]

IT ain't happening

#AI

Was IT a smoke screen to get people to spend their money ??

[सुहास Suhas @suhasgujarathi]

called IT

[DavidLinthicum @DavidLinthicum]

The Emperor Has No Clothes: Why the AI Infrastructure Buildout Math Doesn't Work

I have to give IBM CEO Arvind Krishna credit. He's saying what many of us in this industry have been thinking but haven't been willing to say out loud. The math just doesn't add up.

Here's what I'm seeing that's deeply troubling. We're in the middle of another mass hallucination. Just like the dot-com bubble, just like blockchain, just like the metaverse — everyone is convinced that building massive data centers will automatically create massive wealth.

But here's the thing about building infrastructure. You actually have to sell what's inside it.

Let's talk numbers. The planned data center buildout over the next 5-10 years is staggering. We're talking about commitments in the hundreds of gigawatts globally. The capital expenditure commitments are in the trillions. Yet when you look at the actual demand signals, not the projections, not the potential, but the actual consumption patterns, there's a massive gap. These AI companies are betting everything on demand that simply doesn't exist at the scale they're planning for.

Let me be direct. AI services are expensive. Enterprise adoption is slow. Consumer AI is still finding its footing. And the compute requirements being promised by the hyperscalers require a level of demand that would represent a fundamental shift in how businesses consume technology. That's a big ask.

I've seen this pattern before. The overbuilding. The belief that if you build it, they will come. The groupthink that turns critical analysis into heresy. The result is always the same. Companies are going to touch the stove. We're going to see massive write-downs. We're going to see pivots, shutdowns, and strategic reviews. We're going to see companies that spent years and billions trying to be the AI infrastructure leader become case studies in how not to read a market.

The IBM CEO is right. The math doesn't work. And unlike 1999, we don't have the excuse of we didn't know. We know exactly what's happening. We just don't want to believe it because the alternative, being a skeptic while everyone else is piling in, feels like career suicide. It's not. The ones who survive the next decade will be the ones who built for reality, not fantasy.

Wake up. The emperor has no clothes.

As reported by Futurism, Krishna laid out striking calculations: a 1 gigawatt data center costs roughly $80 billion today. If one company commits 20-30 gigawatts, that's $1.5 trillion in capital expenditure. The total commitments across the industry for chasing AGI are approximately 100 gigawatts, equaling $8 trillion. To break even, you'd need $800 billion in profit just to cover the interest. That's not investment. That's hoping.

https://t.co/4DAnF5OPfa

[सुहास Suhas @suhasgujarathi]

https://t.co/QCI14VBYiG

[DavidLinthicum @DavidLinthicum]

The Emperor Has No Clothes: Why the AI Infrastructure Buildout Math Doesn't Work

I have to give IBM CEO Arvind Krishna credit. He's saying what many of us in this industry have been thinking but haven't been willing to say out loud. The math just doesn't add up.

Here's what I'm seeing that's deeply troubling. We're in the middle of another mass hallucination. Just like the dot-com bubble, just like blockchain, just like the metaverse — everyone is convinced that building massive data centers will automatically create massive wealth.

But here's the thing about building infrastructure. You actually have to sell what's inside it.

Let's talk numbers. The planned data center buildout over the next 5-10 years is staggering. We're talking about commitments in the hundreds of gigawatts globally. The capital expenditure commitments are in the trillions. Yet when you look at the actual demand signals, not the projections, not the potential, but the actual consumption patterns, there's a massive gap. These AI companies are betting everything on demand that simply doesn't exist at the scale they're planning for.

Let me be direct. AI services are expensive. Enterprise adoption is slow. Consumer AI is still finding its footing. And the compute requirements being promised by the hyperscalers require a level of demand that would represent a fundamental shift in how businesses consume technology. That's a big ask.

I've seen this pattern before. The overbuilding. The belief that if you build it, they will come. The groupthink that turns critical analysis into heresy. The result is always the same. Companies are going to touch the stove. We're going to see massive write-downs. We're going to see pivots, shutdowns, and strategic reviews. We're going to see companies that spent years and billions trying to be the AI infrastructure leader become case studies in how not to read a market.

The IBM CEO is right. The math doesn't work. And unlike 1999, we don't have the excuse of we didn't know. We know exactly what's happening. We just don't want to believe it because the alternative, being a skeptic while everyone else is piling in, feels like career suicide. It's not. The ones who survive the next decade will be the ones who built for reality, not fantasy.

Wake up. The emperor has no clothes.

As reported by Futurism, Krishna laid out striking calculations: a 1 gigawatt data center costs roughly $80 billion today. If one company commits 20-30 gigawatts, that's $1.5 trillion in capital expenditure. The total commitments across the industry for chasing AGI are approximately 100 gigawatts, equaling $8 trillion. To break even, you'd need $800 billion in profit just to cover the interest. That's not investment. That's hoping.

https://t.co/4DAnF5OPfa

[सुहास Suhas @suhasgujarathi]

IT ain't happening

#AI

Was IT a smoke screen to get people to spend their money ??

[Dwarkesh Patel @dwarkesh_sp]

The first question I asked @elonmusk: What’s the point of sending GPUs into space?

The whole idea behind orbital data centers is that if the launch costs continue to drop, it will become cheaper to put GPUs in orbit than to build power plants on Earth.

The problem with this argument is that energy is only about 15% of a datacenter’s lifetime cost. The chips themselves are around 70%. And you still have to launch those to space!

Elon kept returning to one point over and over again: It will simply not be physically possible to scale power production to the scale needed for AI on Earth.

He kept pointing out the bottlenecks we’ve already run into on Earth:

You can’t plug into the utilities - the interconnect queues are too long.

You can’t do behind-the-meter natural gas and generate power yourself - lead times for turbines stretch past 2030.

You can’t do solar on Earth, because of permits, and because of the tariffs.

For it to make economical sense to shift compute to space, all of the following things would need to be true:

- Power generation on Earth hits a ceiling, or AI demand outstrips every terrestrial option (for context, 1 TW of solar power is only 1% of the land area of the US, and AI currently only uses about 20 GW globally).

- Chip production scales faster than power generation (because Elon builds TeraFab). It would be surprising if building and placing solar panels turned out to be harder than scaling semiconductor manufacturing.

- Starship reaches thousands of launches per year.

In that world, Elon wins the AI race outright.

SpaceX is the only entity that can launch at that scale. xAI would have unlimited power. Everyone else will be stuck fighting over grid interconnects and turbine orders.

And if those 3 conditions aren’t met?

Well, on Earth, xAI is just gonna be one of the pack anyways - and there’s no market for the 4th best AI model. Elon’s comparative advantage was never going to be navigating utility interconnect queues or filing permits faster than Google. His advantage is SpaceX.

So why not just bet on the world where SpaceX becomes the kingmaker?

I asked Elon what that world looks like. 100 GW = 10,000 starship launches, and he wants to do more than that every year by 2030.

That’s one starship launch every hour.

[सुहास Suhas @suhasgujarathi]

https://t.co/FUwXPO6Irh

[zerohedge @zerohedge]

*PJM SEES POTENTIAL 60GW POWER SUPPLY SHORTFALL OVER NEXT DECADE

This means all batshit insane capex spending plans will be scrapped since there is not enough juice to power the DCs

[सुहास Suhas @suhasgujarathi]

@DavidLinthicum https://t.co/T1f0gd9IwS

[सुहास Suhas @suhasgujarathi]

IT ain't happening

#AI

Was IT a smoke screen to get people to spend their money ??

[सुहास Suhas @suhasgujarathi]

100%

[John LeFevre @JohnLeFevre]

Jamie Dimon calls out the WEF to their faces...

The moderator:

"OK. We're running out of time."

[सुहास Suhas @suhasgujarathi]

@DataRepublican AI is the new D E I and climate change?

New trick to get everyone to shell out money

Fraud has to go on

Incase that does not work W A R is always an option

System always wins

People get poor and burnt

Not the old world order

Not the new world order

Nothing is for people

[सुहास Suhas @suhasgujarathi]

@zerohedge It is an on going experiment

They make money with the experiments to keep experimenting

[सुहास Suhas @suhasgujarathi]

@zerohedge Coalition of the willing, it's such a apt description. So much more to it. Deep thinking is just awesome on this one.

[सुहास Suhas @suhasgujarathi]

@catturd2 it will self destruct

lot of money will be spent

lot of time and human intelligence will be spent

normies will get junk versions of AI to play

the real versions will be exclusive access

[सुहास Suhas @suhasgujarathi]

@GovNuclear @ENERGY great target - 2026 Independence day - 250 years celebration is going to be super lit

[सुहास Suhas @suhasgujarathi]

@ksorbs Because we have a weak @TheJusticeDept and not a MAGA @AGPamBondi

They know to use power only against normal people

They care only about their own ilk

[सुहास Suhas @suhasgujarathi]

They know what they are doing

The more we know

[Charlie Kirk @charliekirk11]

Mass import Islam, destroy America. It’s that simple.

[सुहास Suhas @suhasgujarathi]

@Thomas1774Paine interesting

[सुहास Suhas @suhasgujarathi]

The more we know

[Charlie Kirk @charliekirk11]

CAIR is the most danergous foreign lobby in America and its not even close. Deport CAIR, and learn who is infilitrating America.

[सुहास Suhas @suhasgujarathi]

@RapidResponse47 https://t.co/Ilo8Qiu1W8

[सुहास Suhas @suhasgujarathi]

@RapidResponse47 https://t.co/RY3QGq2M4T