Meta's AI Reality Check, Export Controls & The Next Cloud War | Software Sundays

First up for this week, on the news, Meta is looking to turn excess compute into cash.

So they're taking a page straight out of the AWS GCP Azure playbook, right? They already require for their business operations significant amounts of compute data storage networking in order to actually serve their customers and serve their customers using their primary services products.

They're saying, hey, we've invested billions of dollars now into this compute.

for our own products.

But if we decide that we don't need all of it, if there is a chance that we can sell some of that excess to other companies, then let's do that.

That's another way to get revenue.

That's another way for them to make their return on investment from that AI data center investments, right? They have...

Meta, along with all of these other hyperscalers, have invested billions of dollars and they plan on investing trillions of dollars over the next four years going into 2030 on data centers, on networking, on the infrastructure to power AI.

So with that type of investment required, it makes sense that other companies that don't have the same cash flow, that don't have the same balance sheet, they won't be able to make the same investments that these companies have.

So once you're in the position, once the meta got to the position, they're saying, hey, we have the memory available now.

We have the chips.

We have the energy.

We have the lane.

All of the things that make it incredibly easy for them or easier for them to compete on the AI space than another company.

So definitely is a smart move from their standpoint.

very interesting that even the companies that were not traditionally known for cloud, were not traditionally known for selling their excess compute, they're being able to make a significant amount of money in this current climate, current environment because of AI, because they have some of the resources that the AI labs need to actually grow their businesses.

And the expectation is that these labs are going to be able to generate the revenue that they're going to have the demand.

The only thing that they were missing was the supply.

When we look at SpaceX, when they recently IPO, it was clear that although they are a space company, the primary mission behind the business is to create services for space to be be the catalyst for that space industry.

But most of their revenue in the past 12 months is coming from them providing giga bytes or gigawatts worth of energy and worth of compute to Anthropic.

That's where they're getting their money from right now.

So it is very interesting that Meta is taking the same stance like all of these companies that invested heavily into the infrastructure, the hardware.

Now that we're seeing like supply chain issues, we're seeing memory, the price of memory going off through the roof.

The price of the chips already has been pretty expensive, but we're starting to see physical limitations to what can be done with AI, right? The energy, the chips, memory, all of these things, that is becoming a limiting factor So the AI labs that need these resources, they need the data center.

They need the compute inside of the data centers.