Welcome to the XEI all hands. We've got a very exciting presentation for you. We're going to start off by recapping the incredible progress that the XEI 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 have 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. So 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. So our 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 ultimately be 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 100,000 H100 GPU training cluster and we're now about to achieve the first 100, I should say 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 to a blob of cells 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's 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.
Hey, thanks Elon. So Grok main and voice are going to be merged into one team and you know on voice one anecdote is September 2024 OpenAI had this product you could talk to advanced voice mode and we had nothing, no model, of course no product. We started much after that and in a span of few months, 6 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. 6 months fast forward six more months and now we have Grok in more than 2 million Teslas. We have a Grok voice agent API. You can do all kinds of amazing things with it. 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. We have small teams committed, mission focused, lots of compute. And we really really want to keep pushing. Same story on the chat models. You know, 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. You know, ask a legal question, make a slide deck or solve a puzzle, stuff like that.
Yeah. 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 magnitude of 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. And 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 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. Like this is it's a grind but we have I guess like interstellar ambitions so it's not going to be easy right so 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 done you can get done there isn't like organizational overhead getting in your way or kind of I don't know like having to write docs and all this kind of stuff you just do stuff at least for me I just you know just you can do things here and that's amazing and I invite more people to come here and just do awesome things.
Yeah. 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.
Yep. Absolutely. All right. Thank you. Yeah. Thanks.
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 was like trusting it and I wasn't really convinced but as of recently the models they actually produce good decent quality code. I mean you still need to review and give feedback but you can it's easy to 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 like 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 need 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 have I do like well we do like hours of Grok code running continuously to make sure that a more complex change to the training system actually works in production. So 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 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. Like we have a million H100 equivalents to train the best coding model in the world right now. So please join us.
Yeah, I'm God. I work pair with Macro on coding. So it become more and more obvious to us like over time like we are on a path to singularity at least on coding. So we decided like 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 like the main limiting factor is probably compute and energy where they can run the best model to support everyone to empower everyone and with SpaceX now we are one team and we will win on the compute and we are winning with SpaceX compute. And also for every engineer right? So if you are writing kernel, if you're writing compiler, just think about whether it's still worth it. Maybe you should join us, you know, for coding effort to automate yourself a little bit to speed yourself up. Yeah, I think it's like really amazing year. Basically what a year to be alive and I can already feel the AGI feel the AI at least for coding. Yeah.
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 I'd say the end of this year. And we do expect Grok code to be state-of-the-art in 2 to 3 months. So it's happening very quickly.
Yeah. Also do imaging. So you know I mean what do we all do right after post AGI right you probably do like digital life so that's what we are doing here as well and we have the Imagine team like started pretty much from scratch like six months ago we have a few people we decided we'll do the imaging we'll do the video gen like yeah look at what we achieved today like two weeks ago we released Imagine v1 we actually top 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 months. So yeah, to me there's like a really high chance like we actually may build a metaverse before Meta. Yeah, I will also pass to try to talk about the metrics we have the product. Yeah.
Yeah. Like Gorang said it's only been 6 months since we started working on Imagine. We had no code internally for diffusion at all 6 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. So 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 6 months ago. We are also generating 6 billion images in the last 30 days. Nano Banana you know Google recently posted that 1 billion images were generated using Nano Banana in 30 days so we're six times that right. And really the goal is it's not like 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 that basically is the goal yeah.
Hey I'm Hen. We as we keep scaling our model capabilities, building visual worlds that's indistinguishable from reality, we're also building system that unlocks much more possibility than what we have right now. They will be able to generate the videos that's 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 exciting future that we are going to build with ourself.
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 you know 6 months ago we didn't even have we had basically nothing or 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.
All right. Hi everyone. I'm Toby and I work on Macro, 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 Hard is building a fully capable digital realtime, 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.
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. Like we're actively using these every day. They are like tremendous productivity boost to the whole team. I know the voice team is like killing it on that and you know this is the reason why we need the compute you know we need the large scale compute to run these models to boost our own productivity. But you know 80 to 95% of the world's software has a GUI so that's like great representation and you know 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 you know 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. So, you know, 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, like go through your phone book, go for 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? But yeah, so thank you.
Yeah, the Macro Hard project is 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, they are their output is digital. So 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.
So, it's also pretty funny. Yeah, meant to be a joke.
It's me again. You might remember me from Macro Hard and 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 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, 400 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.
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 respective 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. You know, we're trying to build evals that are useful and training data that represents useful work and not necessarily proxies of intelligence a lot of the open source evals do today. Yeah.
Yeah. I'd like to say like 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.
