OpenAI and Oracle: Cloud Meets Intelligence

0:00Today on the podcast, I want to talk about Oracle and OpenAI, who recently we found OpenAI has agreed to pay Oracle$30 billion. This is an absolutely insane, you know, announcement, basically. But the interesting thing was right after it came out, it basically came out because Oracle released some filings to the SEC where they said, you know, we have a$30 billion contract. And based off of that, Oracle's stock price skyrocketed, making the owner of Oracle the second richest man in the world after Elon Musk. So all of this is part of a much bigger$500 billion project, which the Wall Street Journal yesterday said was delayed and is off to a bad start.

0:43What exactly are they building that cost this much money? Who is the customer for this$30 billion? All of that we're going to be breaking down on the podcast today. And, of course, all of the drama from the Wall Street Journal saying that maybe this is, you know, smoke and mirrors off to a bad start. This isn't going to be as good as you basically were told when they made this big kind of Stargate announcement earlier this year. So we're going to be diving into all of that. Before we do, I wanted to mention, if you want to try any of the latest models from OpenAI to Anthropic to Cohere DeepSeek Google, I would love for you to try out my platform, which is AIbox.ai.

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1:47So if you want to check it out, there's a link in the description to AIbox.ai, and let me know what you think. All right, let's get into this$30 billion deal that's going on with Oracle and OpenAAC. So basically, Wall Street Journal reports that, you know, everything is not going to plan with the$500 billion Stargate announcement that Sam Altman, Oracle and SoftBank made earlier this year. Sam Altman came on and essentially cleared the air. He went on Twitter and said, quote, we have signed a deal for an additional 4.5 gigawatts of capacity with Oracle as part of Stargate. easy to throw around numbers, but this is a gigantic infrastructure project, some progress photos from Abilene.

2:28So this is being built out in Abilene, Texas. And he shares a couple pictures, of course, one of just like the wires of the servers. But again, another of like an aerial view of exactly what they're building, which is an absolutely massive compound. This thing is huge. And there's a ton of buildings that are already up. There's a ton more space for way more capacity that is getting built out, right? The way these things work is they kind of roll in phases. So it's not like everything start to finish is going to be ready at the same time, they'll get certain buildings done and actually get them into production before others.

3:01Now the Wall Street Journal said this was off to a rocky start, they weren't going to be able to get things online when they were hoping for. I think Sam Altman basically had a response to that. But before I get to that, I want to say five or 4.5 gigawatts of capacity, that is enough, like basically energy to power 4 million different homes. This is like two Hoover dams, gigawatts of capacity. So this is like an absolutely massive project that is so much. And they're basically building out all of this capacity to fuel all of the AI projects that OpenAI is going to be needed to do in the future.

3:39And Oracle made a great partnership and is obviously going to be benefiting a lot. Their company is growing a ton based off of this, but also they have the experience. So it makes sense to make it is basically a pretty good partner for the opening app. So I think this is funny. So back in June, Oracle told pretty much made an SEC. Finally, they said that they signed a new deal that was going to generate about$30 billion a year in revenue. So of course their stock absolutely exploded. One thing that I just want to mention though, like we all get$30 billion, Oracle's big company, yada, yada. I think it's like important to know how big$30 billion is, even for Oracle as a company.

4:17So collectively, Oracle last year sold about$24.5 billion worth of cloud services for its fiscal year 2025 to all of its customers combined. So all of its customers generated about$24 billion so far in, I guess, fiscal year 2025. and now they're adding$30 billion from one customer. That is absolutely massive. So what's interesting here is, you know, it's definitely, it's part of the$500 billion data center project, but this is apparently not, like this is in addition to that$500 billion. So they're doing a$500 billion project. That's including SoftBank. This$30 billion is not including it. It's just basically they're paying this money in addition to just to get extra gigawatts online.

5:07And I'm assuming it's because the$500 billion thing is going to take so much longer. It's a huge project. There's a lot of stuff that's going on. But they probably could get, you know, something with$30 billion down faster and online quicker. So this is going to be pretty crazy. Definitely not a straightforward project. This is going to use a ton of time, energy, and money to build this out. But it's important. And we're seeing, you know, basically we're seeing all of these AI companies integrate in this way where you see someone like OpenAI building out their own data centers. you have Amazon's and they got AI tools and they're relying heavily on AWS.

5:39Google is greatly benefited because they have Google cloud. And then basically you see companies like, um, Amazon web servers or sorry, uh, Anthropic that is partnering with Amazon web servers, AWS, and they kind of have to use them in order to get the compute that they need. But it's a tricky situation. They keep getting billions of dollars invested into their company from AWS, uh, Anthropic has, but like Like they're kind of stuck with them, right? And so it's kind of interesting to see a company like OpenAI partner with Oracle. Now, Oracle doesn't really have some sort of headline AI competing product.

6:12They're just more in kind of the data center space. And so it feels like a better partnership. Whereas like Anthropic, they're going to Amazon who also builds their own AI tool. So it's almost like a direct competitor in a way. Now, I will say it's not like everyone's using Amazon AI per se. It's not really the thing. But like built into Amazon's website, they have the Rufus AI and they have a bunch of other AI tools that like I think not a lot of people think about, but they actually use. And so Amazon is a competitor and I think will be more and more of a competitor in the future. So all this to say, Oracle is spending very heavily in order to build out these data centers.

6:49Last year, Oracle spent twenty one point two billion dollars just on CapEx. And so that was last fiscal year. They're expecting to spend about twenty five billion dollars this year. So about$50 billion total, and almost all of this was on data centers. So this also doesn't include any land purchases. This is just like literally building out the data centers. And so I think that that is absolutely a massive sum. So one other thing that's really interesting on this, Sam Altman said that he just last month, he was talking and he said that opening, I finally passed$10 billion in annual recurring revenue.

7:25So what's interesting about this is, yeah, this is huge because it's up from about$5.5 billion last year. So they're seeing huge growth. But this$10 billion, this is only a third of the commitment they just made to Oracle just for data centers. And this is in addition to all of the other data center deals they have. Of course, how much money they have to spend for data, for their researchers, for everything else they have going on. That's absolutely massive. Their, you know, their 3x, their annual revenue, they just gave away in one deal to Oracle. So this is a huge amount of money, but I think it really goes to like basically the picture that this is painting to me is that open AI sees absolutely massive potential, but it's all contingent on how much compute they can get access to.

8:08They know that they're going to be dead if Elon Musk and XAI get access to more compute and basically can build out, you know, have more compute, build out more data centers than them. they're going to get killed because it kind of comes to this point where the bigger your scale is, the cheaper you can make your AI, the more you can compete. Otherwise you're going to get crushed by all the competitors. And we know that these AI models, basically open AI has shown that if you give more compute to an AI model, it will get a better result. Like, and, and that's not cheap, right? So they're like, if we, for every question you ask chat GPT, if we gave it a thousand dollars worth of compute, then the responses were like world-class PhD level insane.

8:46So they're amazing. But that is very expensive to the point where they were giving it like$10 ,000 to answer some questions. And on the benchmarks, those are the greatest questions that have ever been answered by AI. They're amazing, right? But that's$10 ,000 a question. It's like insane. So what is the solution, right? We have access to super, super smart AI, but the cost is so astronomical, it doesn't make any sense. So what's the solution? The solution basically is to spend billions and billions of dollars building out massive data centers, massive compute, you can make these things at scale so you can bring down the costs, you can make them cheaper and faster.

9:20And this essentially is going to be the solution that it seems like every company, every major AI company is trying to build towards or work towards. It's a huge, it's a huge expense, a lot of capex, but this is how they're trying to keep their competitive advantage and stay ahead. So all of this is amazing. If you are if you learned anything new from this episode, and if you want to give back, the number one way to do it would be to leave a rating and review wherever you get your podcast. If you're on YouTube, drop a like and subscribe to the channel. It helps other people find the channel or find this podcast.

9:51So make sure to leave a rating, review, or comment. Really, really appreciate them. And make sure to go check out AIbox.ai if you want to get access to all of the top AI models in one place for one price. You don't have to pay for subscriptions to everything to test out all the top platforms. Thanks so much for tuning in today, and I will catch you in the next episode.