Chapter 1: What is the main topic discussed in this episode?
Welcome to the podcast. I'm your host, Jaden Schaefer. Today on the show, I'm talking about something pretty wild that just happened. Elon Musk just hosted a 45-minute all-hands meeting on X, and he did it for XAI and basically laid out their entire roadmap for getting data centers in space. This is something I've seen a bunch of articles that are kind of critical.
Chapter 2: What is Elon Musk's vision for XAI's data centers in space?
They don't think this is possible. A lot of people say this is just kind of an IPO play. And I think Elon's really making the case that he is going to try to do this. I think what's really interesting with this in particular is that this was an all hands meeting for the company and they publicly posted it.
I think this is, I mean, you wouldn't see Boeing or any of these other competitors doing this. Usually everything's, you know, has these roadmaps and there's all these NDAs and there's like these really carefully scripted keynotes. To me, this was really interesting to just see, you know, the whole thing laid out and, you know, the whole plan just put out to the public. So
In the video, I'm going to break down basically what Elon Musk's long-term vision is for XAI and also the near-term product execution. We'll talk about some of the infrastructure strategy and how X and SpaceX and XAI are all kind of tying together.
Chapter 3: What role does Starship play in reducing costs for orbital data centers?
This is a fascinating conversation. Before we get into all of that, I wanted to say if you want to try any of the top AI models, including all the latest from XAI, like their Grok model and everything else that they're rolling out, I'd love for you to try out AIbox.ai, my own startup.
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Chapter 4: What are the technical challenges of building data centers in space?
So for $8.99, you get access to over 50 of the top AI models. Basically, you consolidate all of your different subscriptions into one place. You chat with them all in the same place and you don't have to go shuffling through tabs or logging into different accounts to try to find where you had a conversation.
Or if you want to try the latest from Anthropic or Google Gemini or whatever, it's all in one place for $8.99. So if you want to try it out, it's AIbox.ai. You also can vibe code really cool tools and post them. So go check it out. I'll leave a link in the description. I think a lot of the address was kind of focused on a whole bunch of people that have recently just left XAI.
There was a bunch of kind of the original team members, a lot of founders of XAI that left. This is what he said about it. He said, as the company grows, especially as quickly as XAI, the structure must evolve. And this was actually an X post he put out. He said, this unfortunately required parting ways with some people.
I think like reorganizing inside of these companies are growing very fast is quite common. I think what was interesting to me with all of this is kind of the new structure. So XAI is now splitting into four primary teams. They have Grok, which is the voice, you know, the LLM and the voice that goes with it. And basically all the core chatbot experiences.
They then have the coding system powered software generation team. So that's really kind of being like a cloud code competitor is what they're trying to build. And they actually do have a model that ranks quite well on the benchmarks for software development. It might even be number one at times.
um but i because they don't have all the integrations and custom stuff that cloud code has cloud code is still far you know as far as usage goes is way ahead um then they have the imagine this is the video and image generation uh components of xai and then they have macro hard this is i mean basically i think they're just trying to make fun of microsoft and call it macro hard but basically it's an ai initiative which they're kind of focusing on full computer task automation and then corporate scale modeling
And really just trying to compete with everything that Microsoft makes and just call it Macro Hard. So anyways, this classic Elon. Macro Hard is going to be led by Toby Flynn. And that is, I think, maybe one of the most... I guess it's just a really big play. The goal is that they're not just trying to assist with workflows, they're actually trying to automate them.
So yeah, in addition to perhaps making some of the software that Microsoft has and embedding AI into it, I think more likely what they're going to be doing is doing like complete automation software and tools for enterprises. It's obviously going to be a very hot thing we see just with like NNN and Zapier and a lot of these companies that are really crushing it there.
And more likely, you know, you see like the comet perplexity kind of tools or the, you know, just basically all these agents that Anthropic and OpenAI are building. I think that's where they're going to be going with this, more of the agents.
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Chapter 5: How does AI infrastructure tie into SpaceX's broader strategy?
I think this was a whole bunch of this was driven by holiday marketing pushes and then a lot of product expansion. There's a bunch of executives over there that said that imagine their image generator and video generator is generating tens of millions of videos per day and billions of images over the last month. And that's according to a bunch of their internal metrics. That is a lot of usage.
I think it shows and kind of reflects a bit of a broader thing, which is basically AI is no longer experimental, right? It's pretty mainstream. And we're seeing this with Chad GBT and a lot of these other players. But it is being pushed out on every platform everywhere. And a lot of people might call this AI slop.
And especially with Grok and their image and video generation tools, I think there's a lot of problematic things there. But it's definitely hit scale, like there is, you know, billions of billions of images being generated. So a lot of those presentations were just kind of what's going on internally at the company.
The most interesting one that everybody is talking about is when the whole presentation they were giving kind of came towards the end. Elon started talking about what he's been talking about forever, which is space-based AI infrastructure. He kind of just reiterated what he has said in the past, that the cheapest place to run large scale AI within a few years is going to be in orbit.
Basically, the benefits are that space has, you know, constant solar energy, fewer land permitting bottlenecks, although I mean, you got to still got to get your satellites approved and stuff. But apparently that's easier than land permitting. on Earth. And then there's also a path to scale compute beyond just terrestrial constraints.
So SpaceX has already requested regulatory approval to build solar powered orbital data centers. I think, you know, we've seen that the administration looks like is kind of looking at this favorably and is going to grant this. I think they put out a tweet recently where they were saying, you know, they're requesting comments.
If anybody has any objections, speak now or forever hold your peace, basically. This is going to have their application that they put out for was like for a million orbital data centers. So there's going to be a massive satellite constellation. Elon has floated the idea. And a lot of people think this is like kind of science fiction.
But I think there's a lot of real engineering that goes into this. So one of the elements that a lot of people are talking about is lunar manufacturing. So literally building like factors on the moon that can launch and develop and create these satellites. data centers.
And I think one of the parts of this is that as far as like regulation goes, you have to, I think, deorbit your satellites every five years or have a plan for deorbiting so that we don't just have unlimited space junk. These things have to be able to basically come down. A lot of people have it where they just reenter the atmosphere and burn up. And that's kind of their, you know, deorbiting plan.
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Chapter 6: How is XAI structured and what teams are involved?
So being able to get things into space for cheaper, they're planning on doing a lot of optimizations. And if they are able to do those optimizations, perhaps this becomes a profitable business. Today, the Falcon 9 already delivers basically the best Yeah, absolutely.
part of basically saving a lot of their costs is how much of the rockets can be reused if they shoot something up, and they bring it back down. You know, and that's kind of the thing that they saved a killer of money over NASA was just that the rockets now we're not exploding or crashing on reentry, they're actually able to reuse them. So How many times can they reuse them?
How many parts can be reused? How much they need to be repaired? If they can bring all those costs down and just have a vehicle that goes up and down to space over and over again, that's where they start saving a lot of money. And they have a goal and a plan for that. So like theoretically it's possible, but it's not a reality today. I think there's a lot of real challenges.
There's radiation hardening. There's thermal management. There's satellite manufacturing costs. There's inter-satellite communications throughput. SpaceX has already shown that they can obviously mass produce and operate thousands of satellites, right? They have the Starlink constellation, which, by the way, if you didn't know, Starlink generates 80% of SpaceX's revenue.
They charge money to shoot things into space, and that's kind of what their company was built on. But Starlink is actually the biggest revenue generator for their company right now. So obviously, like they're able to do it, they can mass produce, they can, you know, mass operate 1000s of satellites, and they're doing a good job of that.
And so turning those satellites into data centers, so it's kind of the next
step of can they do it and if any company can it would appear you know they have the most experience they would be able to but it's tricky and I think the one thing they have going for them there's not a ton of competition that has obviously some insane operational experience and that's a huge moat not a lot of people are really competing directly but I will say Google's project Suncatcher is focusing on there's a startup called StarCloud and then even Amazon and Blue Origin are
are kind of showing that this orbital AI infrastructure is something that they're interested in. So there are other players that are competing, Google, Amazon, and StarCloud. And so, and then of course, SpaceX. So we have like four players in this. And to me, that's exciting. It feels less fringe and more like there's kind of a race.
And so, you know, we'll see which of these players can execute fastest and best. And I love the competition in all of this. A couple of things that I wanted to say from like a technical standpoint and some of the things that are tricky in all of this. So basically, early orbital deployments are more likely to focus on inference rather than full scale training. Right.
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