Big tech companies are on track to spend $720 billion on AI infrastructure in 2026, with AI compute workloads growing 10x per year.

A $50 billion data center's physical materials are worth only cents on the dollar as scrap, with almost all value residing in intellectual property.

“If you just knocked down the entire data center and kind of sold it for scrap it would be literally worth cents on the dollar like few cents.”

Nebius claims it could sell its entire 2027 compute capacity today, indicating enormous unmet demand.

“Demand for what we are building continues to be enormous. We could sell today our entire 2027 capacity if we wanted.”

vLLM is currently running on half a million GPUs at any moment.

“The open- source inference engine now running on half a million GPUs at any moment.”

The compute resources required to de-risk OpenAI's current large-scale training runs are equivalent in magnitude to the total compute used for an entire training run 18 months ago.

“Our biggest d-risks now for upcoming runs are as big as like the entire compute run from 18 months ago or something.”

Token costs are doubling every 45 days.

“Right now, our token costs are doubling every 45.”

Scaling laws have held for almost 10 orders of magnitude and there is no reason they should not continue to hold.

“It's held for you know almost 10 orders of magnitude but there's no reason it should not keep holding.”

OpenAI has scaled back its planned compute buildout from approximately $1.4 trillion to roughly $600 billion.

“One of them has scaled back open AAI their ambitions in this regard of their buildout from like 1.4 trillion to like butt 600 billion.”

AI capex will be approximately $100 billion this year.

“AI capex is going to be about a hundred billion this year.”

Compute scaling will slow down in the late 2020s due to fab capacity constraints.

“Compute scaling will start to slow down probably in the late 20s because just like at some point you use up basically almost there.”

Historically, infrastructure spending surges that exceed 2-3% of GDP are almost always followed by a market crash.

“The greatest spends on infrastructure, when they get above 2 or 3% of GDP, there's almost always a crash afterwards.”

Every single time in the last 180 years that more than 3% of the economy has been spent on an infrastructure buildout, the result has been either a massive recession or a depression.

“Every single time in the last 180 years that we've spent more than 3% of our economy on an infrastructure buildout, we've ended up with either a massive recession or a depression.”