Co-Founder, Technoking of Tesla, Chief Executive Officer & Director, Tesla
Elon Musk Reveals xAI's Insane Supercluster & SpaceX Moon Mission Secrets–Full All-Hands Breakdown!🚀
Dive into the latest xAI All-Hands meeting featuring Elon Musk and the team! This edited version removes silences and boosts ...
About Elon Musk
Elon Musk recently oversaw SpaceX’s public listing on the Nasdaq on June 12, 2026, which he said was the largest initial public offering in the history of capital markets. During the event, Musk stated that he had originally given SpaceX “less than a 10% chance of succeeding at all” and recalled telling people, “Look, we’re probably going to fail, but you know, we should give it a try because if we don’t… we will never be a truly spacefaring civilization.” He described SpaceX’s mission as “to take the fiction out of science fiction” and said the company aims to make humanity multi-planetary, adding, “We want to be able to take anyone who wants to go to the moon, anyone who wants to go to Mars… not just a few astronauts.” The IPO was widely reported to have made Musk the world’s first trillionaire. In addition to the IPO, Musk discussed SpaceX’s plans to build AI satellites and space-based data centers. In an interview with SpaceX employees in Bastrop, Texas, he said that the company’s AI satellite is “actually much simpler than a Starlink satellite” and noted that the current reference design calls for Nvidia Rubin chips. He also spoke about a “terrafab” facility that he said would be approximately 100 million square feet, roughly 10 times the size of Tesla’s Gigafactory Texas, and discussed using a mass driver on the moon to launch materials into deep space. Separately, Musk oversaw the final delivery of Tesla’s Model S and Model X vehicles, which he called a “bittersweet moment,” emphasizing that those cars “showed that an electric car could actually be the best car of any period.”
Transcript (91 segments)
✨ AI-enhanced transcript with speaker attribution
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Elon Musk0:00
Welcome to the xAI all hands. We've got a very exciting presentation for you. We're going to start off by recapping the incredible progress that the xAI team has made in just two and a half years. It's really remarkable in pursuit of our goal of understanding the universe. So just going over our accomplishments since inception. It's important to bear in mind that xAI is only two and a half years old, basically a toddler, and we've nonetheless achieved an incredible amount in a very short period of time.
So our competitors are five, ten, in some cases twenty years old. They've had much larger teams. They started off with far more resources, and yet nonetheless we have achieved number one in many arenas in just a few years. We've achieved number one in voice, in image and video generation. I think we now at this point are actually generating more images and video based on the last numbers I saw than all of our competitors combined. We are winning in terms of forecasting, which is one of the key metrics of intelligence. The Grok 420 forecasting model beat all the other AIs in forecasting. And we've topped many leaderboards.
We've got now a great app with Imagine, with the core Grok. We've made radical improvements to the X app and we've launched Grokipedia which is on its way to far exceeding Wikipedia and will ultimately be two orders of magnitude more comprehensive and more accurate and have more information as well as video and image data that simply isn't there on Wikipedia. So it's intended ultimately to be Encyclopedia Galactica, a distillation of all knowledge. And we're the first to achieve a 100,000 H100 GPU training cluster and we're now about to achieve the first 1 million H100 GPU equivalents in training.
So really an incredible amount of work in a very short period of time. And it's important to consider for competitiveness of any technology company, what matters is not the position at any point in time, but what is your velocity and acceleration? And if you're moving faster than anyone else in any given technology arena, you will be the leader. And xAI is moving faster than any other company. No one's even close.
So let's go to our team. As we grow as a company, a natural thing that happens is you reorganize the company as it scales up. So when you first have a startup, you might have just a few dozen people and they all just chat amongst themselves. As you grow to several hundred people, you have to then add more structure just like an organism that grows from a single cell. And then you get organ differentiation, limbs, you grow a tail. Hopefully the tail disappears and then you become a baby. You go through these stages.
And so we're organizing because we've reached a certain scale. We're organizing the company to be more effective at this scale. Now naturally when this happens there's some people who are better suited for the early stages of a company and less suited for the later stages. And so for the people that have departed, I'd just like to say thank you for your contribution. Thank you for getting us this far and we wish you very well in your future endeavors.
So now going on to the new structure of the company. The company is organized in four main application areas. There's Grok main and voice which is really the main Grok model. That's why it's called Grok main. Then there's a coding specific model. There's an image and video model which is Imagine and then Macro Hard which is intended to do full digital emulation of entire companies. And then we've got the infrastructure layers. So I'd like to invite members of the team to come up and talk about each of their areas.
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Team Presenter4:03
Hey, thanks Elon. So Grok main and voice are going to be merged into one team. On voice, one anecdote: in September 2024 OpenAI had this product you could talk to, advanced voice mode, and we had nothing, no model, no product. We started much after that and in a span of six months we developed the model in-house from scratch without a bunch of people who knew audio and had a product that was surpassing OpenAI in six months. Fast forward six more months and now we have Grok in more than two million Teslas. We have a Grok voice agent API you can do all kinds of amazing things with. In a span of one year we went from nothing to being leaders. That kind of stuff is only possible in a place like xAI where you have small teams, committed mission, focused, lots of compute.
And we really, really want to keep pushing. Same story on the chat models. We've always been at the forefront of reasoning, starting from Grok 1.5, Grok 2, Grok 3. And we want to really move to a world where it's no longer about just question answering. We want to build an everything app. So you should be able to come to it and really get done whatever you want. Ask a legal question, make a slide deck, or solve a puzzle, stuff like that.
So I really think on the product side we're really going to see a huge transformation happening in a very short period of time. We're going to see the amount of work that all knowledge workers are going to be able to produce increase tenfold in the next short period of a few months. The models that we are building out are incredibly amazing and we have a lot on the way and we're really excited to share that with you all. On a product side, the goal is to just build that portal that allows you to accomplish all of your work. And how do we amplify everyone to achieve much more than what they can accomplish alone? And we're building that out. And it's going to be an incredibly easy to use experience that just works seamlessly.
That being said, we are hiring and we're looking for intelligent and smart people. This is not an easy place to work, guys. It's a grind, but we have interstellar ambitions, so it's not going to be easy. I will say having come to xAI, it has been an opportunity of a lifetime to work among really smart and really passionate people. The vibes here are amazing and it's truly an environment where if you're a smart person, you want to get stuff done, you can get stuff done. There isn't like organizational overhead getting in your way or having to write docs and all this kind of stuff. You just do stuff. At least for me, you can do things here and that's amazing and I invite more people to come here and just do awesome things.
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Elon Musk6:35
So with the Grok main, the sort of main foundation model, the intent is that it's genuinely useful in a wide range of areas. So if you're doing engineering or law or medicine, anything, it is useful to you in your job. That's essential to understanding the universe and making things as useful as possible. Like when Grok gives you an answer that you can count on it.
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Team Presenter7:08
Hey everybody, I'm Mro. So the world changed a lot recently in terms of coding. The coding models I was always complaining, people were trying to convince me to use a coding model and I wasn't really convinced, but as of recently the models actually produce good, decent quality code. I mean you still need to review and give feedback, but you can see how they can accelerate you quite a lot. So it's not only about coding, it's like they understand your intuition much better than before. Now when I describe a problem, I only have to phrase it like I would to another colleague engineer who has already seen the codebase. That's a huge change.
Before you kind of needed to handhold a toddler to make a change. And they don't only write your code, but they also can debug your code. So now we do hours of Grok code running continuously to make sure that a more complex change to the training system actually works in production. It's easy to see for us that this is not only about accelerating us ourselves writing code and making us 10x more productive, but we're really on this path for recursive self-improvement where the current generation of Grok code is training the next generation of Grok code. And we see that this path, we're on exponential takeoff here. This path will continue.
So, we are doubling down on coding and making coding one of the highest priority efforts in the company. So if you're out there and you're excited about coding and you're either very good at training modeling or you're a really good low-level software engineer interested in systems design, this is the place to work. We have a million H100 equivalents to train the best coding model in the world right now. So please join us.
I'm Gone. I work paired with Macro on coding. So it's become more and more obvious to us over time that we are on a path to singularity at least on coding. So we decided to have our best engineer in the company, Micro, to lead the coding and we'll build the best coding model for everyone to empower everyone to build. And for me, the main limiting factor is probably computer and energy, what they can run, the best model to support everyone, to empower everyone. And with SpaceX, we are one team and we will win on the compute.
And we are winning with SpaceX compute. And also for every engineer, if you're writing kernel, if you're writing compiler, just think about whether it's still worth it. Maybe you should join us for the coding effort to automate it yourself, to speed yourself up. I think it's really an amazing year. Basically what a year to be alive and I can already feel the AGI, feel the AI at least for coding.
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Elon Musk9:49
Yeah, I think actually things will move maybe even by the end of this year to where you don't even bother doing coding, the AI just creates the binary directly. And the AI can create a much more efficient binary than can be done by any compiler. So just say create optimized binary for this particular outcome and you actually bypass even traditional coding. That's an intermediate step that actually will not be needed probably by the end of this year. And we do expect Grok code to be state-of-the-art in two to three months. So it's happening very quickly.
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Team Presenter10:32
So we also do imaging. What do you do right after post-AGI? You probably do like digital life. So that's what we are doing here as well. And we have the Imagine team, started pretty much from scratch six months ago. We have a few people, we decided to do the imaging, we'll do the video generation. Look at what we achieved today. Two weeks ago we released the Imagine v1, we actually topped the leaderboard across many of them and people really love our product, love our model. And we have many more releases actually this month and next month. So to me there's a really high chance we actually may build a metaverse before Meta.
Like Goran said, it's only been six months since we started working on Imagine. We had no code internally for diffusion at all six months ago and basically now we've launched Imagine on every product surface that we have including seamlessly integrating into X. So you can open the X app right now. You can long press on any image. You can edit the image. You can make a video out of the image. We also ran a contest recently where we had some really funny submissions that I'm sure many of you have seen.
Imagine is growing extremely, extremely fast. And it's because of the speed at which we iterate. Basically we do multiple product updates every day. We do model updates every other week. And effectively what this has led to is now users are generating close to 50 million videos every day using Imagine. And just to reiterate what Elon said earlier, that to the best of our knowledge that is more than every other provider combined, which again is an astonishing place to be compared to where we were six months ago.
We are also generating 6 billion images in the last 30 days. Nano, Google recently posted that 1 billion images were generated using Nano Banana in 30 days. So we're six times that. And really the goal is not that we don't just want to win. We want to win like over a long period of time and have sustained greatness. And so the goal with Imagine is to take anything that you can imagine and turn it into reality. And so that's what we're going to speedrun, basically, is the goal.
Hey, I'm Hatin. As we keep scaling our model capabilities, building visual worlds that's indistinguishable from reality, we're also building systems that unlock much more possibility than what we have right now. They will be able to generate videos that are much longer than what we have right now with stories or with souls of your Imagine. And by the end of the year, we likely will be having models that allow you to generate videos of 10 minutes or 20 minutes in one shot without any intervention. You just need to give your imagination and our model, our agents will do it for you.
And moreover, those are the videos we generate and we're also going to allow rendering those. We're already the fastest in generating the videos and we're going to keep pushing the extreme where we're going to render those videos in real time and you will be able to imagine, build, and interact with your own world and the world will respond to you in real time. And it is an exciting future that we are going to build with ourselves.
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Elon Musk13:42
Absolutely. My prediction is that most of AI compute is going to be real-time video understanding and real-time video generation and we expect to be the leaders in that. It's worth emphasizing these points that six months ago we had basically nothing or were very weak in video and image generation and editing and went in six months to number one spot. And in fact generating more videos and images than everyone else combined. We're going to do the same thing with coding and we're going to do the same thing with Macro Hard.
And I think people will be pretty impressed with the Grok 4.2 model that's coming out. That's a significant improvement. And that's really just the small version of our new model. So we'll have a medium and a large version that are even more intelligent.
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Team Presenter14:36
Hi everyone. I'm Toby and I work on Macro Hard, the most serious of all product names. So arguably giving computers to humans was a good idea. So we're doing the same thing for AI. It's kind of like inception. We're giving computers to computers. Macro is building a fully capable, digital, real-time, very important human emulator. So it's able to do anything on a computer that a human is able to do, including using advanced tools in engineering and medicine. So there should be rocket engines fully designed by AI. And in a sense, it's one of the last few remaining areas where AI is significantly worse than humans, which is why I think it's one of the most exciting areas to actually innovate in and actually change the field.
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John15:24
Hi everyone. So yeah, my name is John and so we're building these strong reasoning models which are now going to control our CLI. We're actively using these every day. They are a tremendous productivity boost to the whole team. I know the voice team is killing it on that and this is the reason why we need the compute, we need the large-scale compute to run these models to boost our own productivity.
But you know, 80 to 90, 95% of the world's software has a GUI, so that's a great representation. And to truly make people's lives easier, we need to develop models that are capable of solving day-to-day tasks on GUI. So Macro Hard, we will emulate a company where the output is digital, and so this is the obvious next step for agents. Macro Hard will enable true end-to-end orchestration across the desktop and it will lead to immense economic prosperity.
So yeah, we're entering an era where we need to tackle the hardest of tech problems, but in order to solve this we need to hire the best people. Think of the smartest people that you've worked with and put them forward for a position here. And if you can't think of anybody, go through your phone book, go through your LinkedIn. You'll be surprised how big your actual network is. And they just need three properties obviously that we want to optimize for. Are they clever? Can they solve hard problems? And the second property is are they driven? Do they have the ambition? Do they want to win? And the third is are they a nice person? Like do you want to actually work with them?
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Elon Musk16:54
The Macro Hard project over time actually will probably be our most important project because what we're talking about is emulation of entire human companies. So when you look at the most valuable companies in the world, their output is digital. They don't actually make hardware. So it should be possible to completely emulate any company where the output is digital. And this will usher in an age of prosperity like which we could barely imagine at this point. You need Imagine to imagine it. So this is a big deal and this is why the words Macro Hard are painted on the roof of the training cluster. Because that's what it's going to build.
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Team Presenter17:36
It's also pretty funny.
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Elon Musk17:37
Yeah. Going to be a joke.
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Team Presenter17:44
It's me again. You might remember me from Macro Harding computer use from a long time ago, but I also actually work on core product infrastructure and API. In fact, this is what I've done for most of my time at xAI. So, anytime you use any of our products like grok.com, API, authentication, you go to status.x.ai. This is done by the core product infra team. And a large portion of them actually sit in London and we work with Haime over there. So, we keep the lights on at peak hour, 4:00 p.m. every day. We get paged at night when stuff goes down. Also, thank you to anyone in Palo Alto getting paged. There's really important work, reliability, security, core product infrastructure. So if you're really interested in solving difficult distributed problems with messy data, this is the team to join.
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Diego18:34
Hey everyone, my name is Diego. So I think one of the main bottlenecks in this next year for these models is going to be very high quality evals and training data and one of the ways we solve that is by taking the world's foremost experts in these rich domains, bringing them here and having them evaluate the model. We do this for domains like medicine, finance, law. We have voice actors, we have video editors who contribute daily to making Grok better. And yeah, we're going to be continuing to work on very high quality evals over the next few months. We have some exciting stuff in the frontier of useful tasks in finance and law. We're trying to build evals that are useful and training data that represents useful work and not necessarily proxies of intelligence where I think a lot of the open source evals do today.
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Elon Musk19:20
I'd like to say we're shifting from using these sort of common internet evals which I think are actually not a real indicator of usefulness to having expert tutors in each domain. So every domain of engineering, medicine, law, whatever the case may be. And the actual eval is does the expert in that arena or does our group of experts in that arena, human experts, agree that Grok is extremely useful and that the results are correct? That's actually the only eval that really matters.
Yeah, exactly. You'll see this in Grok 420. But we've made some improvements because of that type of data in truth-seeking and minimizing political bias. The responses are much more cogent. That's exciting. And we are also working on Grokipedia. So the goal of Grokipedia is to create a distillation of all human knowledge. I kind of like to think of this as a modern-day version of the Library of Alexandria. And in the quest to build Encyclopedia Galactica, which it will one day be called, we've gone from essentially having nothing to around six million articles. For context, Wikipedia is around seven million English articles. And yeah, we're improving on hallucination. And our goal is essentially for Grok 5 to not have to search out of the data center.
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Team Presenter20:45
So in the ML infra team, we are building the training, inference, and tooling software for the company. So to give you an example, when we were training Grok 3, we built the pre-training framework for this and these are some of the coolest systems, in my opinion, that you can build as a software engineer. So we have 100k H100s at the time and they were just delivered and we didn't quite have the software. We thought we'd have the software, but then at 30k scale we realized actually the software is not quite working.
And it took a major almost halfway rewrite of the software because there's so much going on in a data center that you can't actually account for. Switches are flapping, links are flapping, switches are going down, GPUs are just burning through, you have numeric issues and it's a system where you want really 100k H100s to behave in lockstep. So a training step is like five seconds and you're going five seconds in lock but during that five seconds everything can happen. So you need to write a system that makes progress despite all these things that can happen in the environment. And we did this successfully and it was one of the coolest times in my life where the system was actually running at the same time my son was born. So that was extra excitement.
But these problems you don't find anywhere else. Nobody has this kind of compute and also nobody has this kind of talent density. So at the time to give you a perspective, in overall team in pre-training we were probably like 15 people. Out of that maybe like seven people were working on the actual training system and we still maintain that talent density in the team. So if you're interested in working on these problems and you don't want to be just part of a bigger organization where you're one of like a thousand people working on this, then this is the place. We are still a very small team.
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Leon Min22:33
With me is Leon Min from the RL and inference team.
Hi, I'm Leon. So at our team we run a reinforcement learning training job and production inference at a large scale on the earth and probably soon in space. And we are kind of already designing a lot of things to make it more resilient and scalable. So we're building a system to scale from 100k chips to millions of chips and we optimize every aspect of the stack like parallelism, prefill, decode and make it resilient to every known and unknown hardware failure.
So if you are system hackers obsessed with extreme performance and reliability, here is where you will find the most interesting problems to work with. And I think actually very similar to all kinds of things, it's very important for you to first see the problem and then you will develop the solution that no one else can develop before. I'll hand over to the tooling team.
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Ash23:30
Hello, I'm Ash from the tooling team. Every software needs to have a great interface to be able to make it useful. So as the tooling team we are responsible for building the platforms, frameworks and infrastructure which is required for humans as well as agents to be able to use our products. We started by building out the human data platform. This is a place where we collect all of our human data and eventually expanded on to build our internal engineering platform through which we basically run deployments, run evaluations, or look at what training results exist. So if you really care about building a good interface or providing a really useful framework for researchers, for agents, as well as our tutors, then you should definitely join our team.
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Yulong24:14
Hi everyone, I'm Yulong from the JAX team. So now JAX at xAI is a really small team with a couple of engineers working on JAX GPU to optimize our ultra large scale GPU training. So you can imagine that training at scale can be very complicated. Even if you run hello world at scale it can be complicated, right? Then we are actually responsible for supporting the entire company from pre-training foundation models, RLS, and also multimodal to scale things from first 10k, 100k, then probably 1 million H100 equivalent GPU scale. And we have to implement a lot of practical optimizations. We have to customize the entire JAX stack from compiler and runtimes and there will be a lot of interesting problems.
And also if you really want to, you know, obsessed on optimizing the entire stack at scale, then we are probably the best place to go because we really have very large scale GPU clusters and we have a lot of interesting problems to work with.
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Pranul25:23
Hey, I'm Pranul from the kernels team. Basically the kernel team sits at the very bottom of the training and serving stack. Our code runs inside the million equivalent GPUs that we have. And if you look inside the GPU, there's hundreds of thousands of threads. And these threads are trying to talk to each other to multiply matrices, compute attention scores, and some of them even talk to the million other GPUs that we have. And this is the low-level system that we have. And we like optimizing every single microkernel in this. And we care deeply about squeezing every last drop of performance from these GPUs. So if you like these low-level systems problems, algorithms, please join us.
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Elon Musk25:58
Now, we'll try to bring in Hiner and Spencer who are actually at our supercomputer cluster in Memphis. Hey, Hiner.
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Hiner26:12
Hey, I'm Hin from the computer and networking infrastructure team. We are mainly based in Palo Alto, but today we're here in Memphis in the supercomputer. So the data center here in Memphis runs the largest compute on the planet and it is still growing. Our job is to keep all this compute up and running.
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Elon Musk26:37
Actually just put the mic really close to your mouth because your ambient noise is high.
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Hiner26:44
So I was saying it's our job to keep the computer up and running, the next model of Grok and serve AI to our users. So for GPUs to work well, a lot of ingredients have to come together, mainly software and hardware. So there's all these chips, TPUs, Infiniband switches, hundreds of thousands of operating systems running as one big supercomputer. And what we need is folks who really understand how computers work on a deep level. That is, reach out. And I'm handing over to Dan.
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Dan27:13
All right. So we have 300,000 GB300 platform to use here today. Still growing, still building. 847 miles of fiber per data hall. 12 data halls. You want to be part of the world's largest supercomputer. Come join us.
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Team Presenter27:29
So it's quite marvelous what we've been able to do in less than one year's time here. Once we're completely finished, we'll have north of a gigawatt of power online and running. We'll have the largest Tesla Megapack system in the world, larger than Hawaii or South Australia. And Zach is really quickly going to talk a little bit about actually constructing the data center.
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Zach27:50
So behind me you can see data hall 11. So one of the most incredible things about what we're doing here at Macro Hard is how fast we do it. Like they were saying before, over 850 miles of fiber at every single data hall, over 27,000 units and over 200,000 connections. So all of this that you can see behind me was put up in less than six weeks. We do that over and over and over again. We massively parallelize it. It's pretty much the most complex and consistent type of engineering design and construction project you possibly imagine. So come join us.
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Team Presenter28:25
You know the other really awesome thing about this is that everything is completely vertically integrated within this team. From architecture, mechanical, electrical, trucks, all the disciplines. And we also care a lot about efficiency while we're designing all of this, too. So it's not just about getting the most compute online the fastest, but also achieving the highest PUE in the industry. Using as much power smoothing technology as we can and being really good partners in the community here in Memphis. With the Tesla Megapacks that we have going, you can check them out, xAI Memphis. Back to you.
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Elon Musk29:04
All right. Thank you. So that was live from the front lines in Memphis. So fundamental to any AI company's success is the compute advantage. And what we've demonstrated over and over again is that xAI can actually deploy more AI compute faster than anyone else. And actually, as Jensen Huang, CEO of Nvidia, has said many times in interviews, there is no one faster at getting AI compute online than xAI. So congratulations guys.
Yeah, this is what it looks like. So that's really phase one which is 330,000 Grace Blackwells with Macro Hard on the building that's on the image edit. It actually is on the roof of the building. And then Macro Harder will be the building that you can see which has got the Macro Harder with the rockets on it. And that will be another 220,000 GB300s. So all of this will be training the models that you experience. So it's absolutely fundamental obviously to have large-scale training compute in order to get the best models.
Yeah, I'm sort of reminded of the Jose meme where you see one guy digging and there's like seven people watching. And one of the big differences between xAI and other companies is we are actually Jose.
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Nikita30:21
Hello. All right. I'm Nikita. You might know me as a part-time shit poster, full-time customer support for X. So, we're now reaching over a billion people across our family of apps. Every time news breaks, it just becomes evident that this is the most important communication tool of our time. It's where the most influential people convene. It's where truth is crystallized. Everything is downstream of X. The reason they say this is going to hit Facebook in a week because it happens here. And I think we're only beginning to realize its full potential.
We had a remarkable year for the app. We rolled up our sleeves and got a ton done. January was our biggest month ever for the app, in terms of engagement. And then February is on track to beat that. Much of the credit lies with the algorithm team. They've been putting in crazy hours and it's clearly paying off, but there's still a huge amount of work to be done.
On the top-of-funnel side, first-time downloads are up over 50% every month. And we're exhibiting right now like basically the growth rates of an early-stage consumer product. We also made a ton of headway in solving one of the like twenty-year-old problems of the app, which was ramping up new users. New users are now spending 55% more time per day in the app than they were six months ago.
And on the core product side, we're hitting our stride, too. Not only did we rebuild the algorithm, we rebuilt our onboarding flows and we're seeing double-digit increases on all our key metrics. We rebuilt notifications, our web browser, X Chat, basically every surface of the app has been rebuilt to be better than ever. And it's clear that if we're focused, we can move mountains and evolve this platform. Just last month, we did a little push on articles. Articles published are up 10x. Articles read are up 17x.
And on all other fronts, like over the holidays, we did a big push on subscriptions. We just crossed a billion dollars in ARR there. I think with the X app, you know, there's very few unknowns, like the path for us to win and become the number one app in the world. We know what to do. The ball's in our court. It's for us to win and it's just a matter of us executing.
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Elon Musk33:01
Yep. And so we've evolved the what used to be the old Twitter DM stack, which was unencrypted, basically just text, to a fully encrypted messaging system that allows you to do audio and video calls. It has all the things you'd want from any messaging app: disappearing messages, screenshot blocks, like there's a whole list of all the features that you'd want in an app.
And we will be open-sourcing the code for this in the next few months as we are open-sourcing the recommendation algorithm code so people can actually see what we're doing. Nothing beats transparency for believing in a company. So we're going to be the only recommendation algorithm that actually open-sources so you can see what it does and how it's evolving. With Grok Chat, it will also be open-source. So you can actually see if there are any vulnerabilities. There will be no hooks for advertising or anything else like that in Grok Chat which is really intended to be a generalized communication system.
And in the next few months we'll be releasing a standalone X Chat app. So if you just want to do messaging, you can do that. You don't have to go to the core product. And it will have desktop sharing and multi-user. So you can do video calls with lots of people. It's really intended to be a fully functional communication system with X Chat.
For X Money, we actually had X Money live in closed beta within the company. And we expect in the next month or two to go to a limited external beta and then to go worldwide to all X users. And this is really intended to be the place where all the money is, the central source of all monetary transactions. So it's really going to be a game-changer. And the reason we say one billion users is actually over a billion users is that while our monthly users are on average around 600 million, the number of people who have the X app installed is well over a billion.
It's just that most people only occasionally come to the X app when there's some major world event. But as we give people more reasons to use the X app, whether it's for communications, for Grok, or for X Money, whatever the case may be, we want it to be such that if you wanted to, you could live your life on the X app. And as we make it more and more useful, we'll obviously give people compelling reasons to use the app every day. And my expectation is well over a billion daily active users.
Now, in order to understand the universe you must explore the universe. There's only so much you can learn from just being on Earth with telescopes and colliders on Earth. Ultimately you have to go out there and you have to explore the universe to understand it. And that's the motivation behind the combination of SpaceX and xAI is to accelerate humanity's future in understanding the universe and extending the light of consciousness to the stars.
So in the grand scheme of things, when you look at how much energy Earth is actually using for civilization, we're only right now using roughly one percent of the potential energy of Earth. And if we wanted to use even a millionth of the sun's energy, that would be roughly a million times more energy than civilization currently uses. The only way to access that energy, the energy of the sun, is to extend beyond Earth. Earth is really a tiny, tiny dust mote in vast darkness. The sun is 99.8% of all mass in the solar system. So you have to expand beyond the tiny dust mote that is Earth to make any significant dent in using the sun's energy.
Like I said, you'd have to expand roughly a million times just to get to a millionth of our sun's energy and then going beyond that, exploring, extending to the galaxy and maybe someday even to other galaxies. So the next step beyond Earth data centers is our Earth-orbital data centers. And we'll be launching with SpaceX orbital data centers at the 100 to 200 gigawatt per year level. Not cumulative, I mean per year. And ultimately we see a path to maybe launching as much as a terawatt per year of compute from Earth.
But what if you want to go beyond a mere terawatt per year? In order to do that you have to go to the moon. So, by having factories on the moon building AI satellites and having a mass driver, which is the kind of thing you really only read about in science fiction, but we're going to make it real. We're actually going to have a mass driver on the moon. And if you do that, you can go several orders of magnitude greater. You can go to a thousand gigawatts or more per year. And ultimately get to maybe a millionth and then a thousandth and maybe even a few percent of the sun's energy.
It's difficult to imagine what an intelligence of that scale would think about, but it's going to be incredibly exciting to see it happen. I really want to see the mass driver on the moon that is shooting AI satellites into deep space. It's going just one after the other. I can't imagine anything more epic than a mass driver on the moon and a self-sustaining city on the moon and then going beyond the moon to Mars. Going throughout our solar system and ultimately being out there among the stars and visiting all these star systems. Maybe we'll meet aliens. Maybe we'll find some civilizations that lasted for millions of years and we'll find the remnants of ancient alien civilizations. But the only way we're going to do that is if we go out there and we explore. And this is the path to making it happen. Thank you.
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Narrator38:43
Wow. Epic end to a great presentation. Yes, it's done. If that's all you wanted to see, catch you later. I'm going to share a few of my key takeaways and a bit of a recap. First of all, the incredible rate of progress. This is really important, not just for people who are interested in the progress of xAI themselves, but any of the Musk-led engineering efforts out there. Tesla, SpaceX, xAI, X, Neuralink, The Boring Company, you name it. Despite being just two and a half years old, competing with companies very well-funded, deep-pocketed, gigantic companies, some of them five, ten, twenty years old, xAI has now equaled in terms of capabilities, if not exceeded in many areas, including voice, image generation, and image editing.
Grok 4.2 and other variations at the top of many of the intelligence leaderboards. And Grok 420 now absolutely crushing it with forecasting, including by the way making money in the stock market, crushing all other AI models. This has been achieved with a much smaller team arriving late to the party with far less capital required. This matters. We also heard that as of today xAI via some of the Grok products now generating more images and video than all competitors combined. A phenomenal but unsurprising result.
Recall, well under a year ago xAI acquired the X platform not only unlocking a massive exclusive data stream, all the posts on X, text, video, images, for training, which is incredible, but also a massive platform to start integrating Grok, massively accelerating user growth. The X integration was a masterstroke. They've also launched Grokipedia, which is already showing an enormous amount of promise. Compared to the burning dumpster fire that is the left-hearted, completely deranged, entirely captured Wikipedia, it's only a matter of time before Grokipedia transitions into Encyclopedia Galactica, and nobody even remembers where Grokipedia's original name had come from.
Another fairly direct flex: xAI, the first company with a 100,000 H100 GPU training cluster, which went up in record time. Jensen Huang, Nvidia CEO, on the record said no one else could have done this as quickly as xAI did. He didn't, by the way, need to say that. Probably offended every single other company buying H100s from Nvidia. But the facts are the facts. They weren't done flexing though. xAI is about to become the first company with the equivalent of 1 million H100 GPUs in training. Unbelievable.
That's a 10x from the monumental milestone we just discussed of 100,000, which was a first, and not just the first but went up in record time. Some people recently concerned about a few departures from some of the xAI founding members, early team members and so on. Musk pointing out the company's growing at a phenomenal rate. They've done some recent restructuring just so that as the company scales they are more effective at their new size.
xAI broke down the four main areas of the company. Grok main and voice, that's one. Coding, two. Imagine, i.e. images and video generation, three. And Macro Hard, four. And at this point in time, if you hadn't already noticed, this entire presentation was a massive recruiting drive. Please join us. Come join us. If you like working on hard problems, big impact, come join us. Join the team.
We also heard some astonishing numbers. Users are currently generating almost 50 million videos per day and around 6 billion images per day. Unbelievable. They also expect, and this is really big, that by end of year users will be able to generate 10 to 20 minute videos from text prompts and in the future these videos will be rendered in real time. Now think about the implications. Hey Grok, my favorite TV show is XYZ. My favorite episodes from TV show XYZ. Analyze why I like these episodes in particular and then create me some new content based on the themes, the topics, the characters I like in this particular style. Bam. Done in real time.
This is going to be a revolution for content. Real-time on demand, completely custom prompts tailored exactly to you, rendered in real time. Does this mean that Netflix is about to get Blockbustered? Something to ponder. This will also have massive implications for the video game industry, but we'll save that conversation for another day.
After this, Musk pointed out that he believes in the future most AI compute will be used for real-time video understanding and real-time video generation. So let that sink in, especially if anyone involved in the entertainment industry is listening. Then onto Macro Hard, likely to be the most important, impactful, and lucrative project. The goal of Macro Hard is essentially developing human emulators that can use computers. Any company whose primary or sole output today is digital, which by the way is most companies, and absolutely the vast majority of value in terms of market capitalization is companies whose entire output is digital. Electrons. Think about all the tech companies, you know, the largest companies in the world.
A human emulator can do all the work of a human on a computer except doesn't need to take a break. Can work 24 hours a day, 7 days a week without any time off. Macro Hard will be creating entire digital companies. And an important clarification, because a lot of people intuitively will think, oh, you know, Apple's safe because they make phones and computers. Nvidia is safe because they make AI training GPUs. No, actually, as Musk pointed out quite recently, Apple doesn't make hardware. They design hardware. And then they FTP or email, whatever terminology you want to use, they send the plans for their design to Taiwan or to China or to pick your overseas manufacturing location. That's who actually makes the hardware.
Same is true of Nvidia. They design the chips. But Nvidia does not manufacture anything. They send their plans to Taiwan. They're manufactured by third parties. Macro Hard in theory, if successful, could replicate a company like Apple, Nvidia, Microsoft, Google. The output of most companies is digital. In the future, you can count on it. Macro Hard will have a company specifically involved in designing rockets, another AI chips, another doing physics, customer service. You name it, the industry, the technology, whatever it is, you can guarantee Macro Hard will penetrate that market. Again, there are very strong recruiting efforts specifically around the Macro Hard project. Come join us. Join our team.
Another cool disclosure: X absolutely crushing it now. One billion dollars in annual recurring revenue from subscriptions. The X platform itself, well, in excess of one billion users. Coming soon, not just Macro Hard, but a standalone X Chat app. In other words, they're going after the likes of WhatsApp, Telegram, blah blah blah. Importantly, with all the standard features you'd expect, including disappearing messages, the blocking of screenshots.
So, yes, no doubt there'll be plenty of titties being transmitted on the X Chat standalone app in the future. And this is important. This app will be distinct from the X platform. So if you just want to use X Chat, which they're obviously going to try and make the best chat app, period, you don't even need to be an X user. And then the big one: X Money, currently in closed beta within the company, soon a limited external beta and then a global launch.
Bit of a full-circle moment for those who don't know your history about Musk. Early days after founding Zip2, selling the company, making a bit of spare change. The guy's working in online banking, trying to digitize the whole system. Eventually, two companies emerge, X.com and PayPal, continuing with the name PayPal. Musk's vision at the time: online digital banking services for everything. And here we are a few decades later.
PayPal, I believe 99, was founded, sold to eBay, I think a couple years after that. A big moment and a massive innovation. Musk stating quite clearly the goal is for X Money to be the place where all the money is, the central place for all transactions. Now in case you are unaware, the global financial services industry today is gigantic. I just want to explain a few things when he's talking about where all the money is, the central place for all transactions. We're not just talking about savings accounts, transactions accounts. No, no, no. We're talking about mortgages, business loans, construction loans, lines of credit, owning stocks, shitcoins, crypto, you name it. All the money. And boy, is this industry ripe for disruption. X Money is going to print money for the company.
And importantly, the big final message explaining why xAI and SpaceX are now one. In case you missed it, SpaceX recently acquired xAI, which again previously acquired X. So, there's a lot of X's in this entity. And the short answer to this is the only way for massive increases in the amount of AI training compute available and actually able to be turned on, i.e. powered, requires getting off Earth. Hence orbital AI data centers.
I continue to call this project Starlink at least until somebody comes up with a better name. Just to be clear, they are serious about this. SpaceX has already filed an application with the FCC to launch a million AI satellites for both training and inference. A million. And that's for starters. Musk says ultimately annual launches from Earth for orbital data centers in space could be somewhere in the vicinity of 200 to 300 gigawatts per year which is ridiculous. But in order to get beyond that... I mean we are in the best timeline dude, seriously.
Longer term they want to have factories on the moon building satellites and a gigantic mass driver. And not to get like too nerdy here but the purpose of the mass driver is to basically launch the AI satellites into orbit without needing a rocket launch but it's basically a gigantic rail gun to shoot satellites into orbit on the moon. And they're serious about this and this could get them to over a thousand gigawatts per year. And again, I reiterate, this is a serious endeavor. In fact, this is almost the entire reason that SpaceX will be IPOing this year is to raise capital to start this truly insane project.