🤖 Google Dropped an $80B AI Bomb

Good morning, AI infrastructure nerds.

Even Google says AI demand is growing faster than it can keep up with.

Today, we're breaking down who gets paid when AI demand outpaces supply.

Google is raising $80B to accelerate its AI infrastructure buildout.

That is a huge amount of money (about the same size as Target), but the reason behind it matters more.

Google said demand for its AI products and services is exceeding available supply.

Meaning customers want more AI than Google can currently deliver.

And this is not a tiny company trying to keep the lights on.

Google already has a massive balance sheet ($595 billion), huge cash flow ($164 billion), and one of the largest AI compute footprints in the world.

Google Cloud grew 63% year-over-year, its cloud backlog nearly doubled to $460B, and revenue from generative AI products surged nearly 400% year-over-year.

So this is not a demand problem.

It is a supply problem.

Google has customers waiting, products growing, and AI demand showing up faster than the infrastructure can handle it.

That is why the financing choice matters.

Google chose to raise equity (usually the most expensive way to raise money) instead of simply waiting for cash flow or leaning entirely on debt.

When a company issues new shares, existing shareholders own a slightly smaller percentage of the business.

That is called dilution.

Companies usually try to avoid it.

But Google appears willing to take the hit because waiting 6 to 12 months could mean falling behind in the AI compute race.

Google is basically saying: getting more AI infrastructure now is worth more than protecting shareholder ownership percentages in the short term.

On May 14, we published AI Is Eating All The Memory and said AI was starting to squeeze the memory market.

Since then, Micron is +31%.

And DRAM ETF, the clean memory play we sent to readers who replied, is +23%.

Think this was early?

The next setup could be even bigger.

Reply “SKY” and we’ll send you the special edition before the crowd catches on.

Global defense budgets are expanding, but the allocation has changed. A growing share of spending is going toward AI-enabled systems, satellite networks, and advanced aerospace, not the platforms that dominated the last generation of procurement. We identified five companies at the center of this reallocation in a single research brief. Inside, you'll find the investment case for each, the contracts driving revenue, and the risks worth understanding before you commit capital. If you want exposure to defense sector growth beyond the traditional mega-caps, this report is a practical starting point. Free, concise, and built for investors who want to move ahead of the crowd.

Read the report

The key word here is not just “spending.”

It is speed.

When one of the richest companies in the world raises expensive capital to move faster, it tells us the bottleneck is urgent.

And right now, the bottleneck is compute.

AI companies can have great models, millions of users, and massive enterprise demand.

But without enough chips, power, networking, cooling, and data centers, they cannot serve all that demand.

That is why Google is doing more than buying infrastructure.

It is trying to lock up capacity before competitors do.

When a resource becomes scarce, companies start securing it in advance.

And when the biggest companies start locking up supply in advance, the businesses that provide that supply become much more valuable.

That is why this story is bigger than Google.

If you look closer, the real winners may be the companies:

That's where a huge chunk of the AI spending is flowing.

Broadcom is the perfect example.

Most people see Google spending $80B and think, “Google wins because they get more compute”

But Google does not build the entire AI factory alone.

Its AI strategy is built around TPUs, Google’s custom AI chips built to train and run AI models.

And Broadcom helps turn those TPUs into reality through chip design, high-speed interconnects, advanced packaging, and coordination.

The AI boom is not only creating demand for better models.

It is creating demand for the entire physical supply chain needed to run those models.

That includes Broadcom, memory suppliers, networking providers, power equipment companies, cooling systems, and data center infrastructure.

AI may still look like a software story from the outside, but the money behaves like this is an industrial buildout.

The biggest investing opportunity may not be buying the companies spending the most on AI.

It may be buying the companies selling the chips, networks, memory, power, and infrastructure that make all that AI growth possible.