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Honestly, it is, it is pretty hilarious. I also wonder, you know, how, how apocryphal is this story because it doesn't account for everything else that went. Like if, if the corn was planted by production assistance, right? Like you have to burden that cost into the actual to plant corn. Who planted the corn? I'm just saying, like who planted the corn? Is this gross? Is this gross profit or net profit? That's what I want to know. Christopher Nolan, everyone's talking a big game about the interstellar trade and it might not have been as good as you think. Also, who owns the rights? Does the value of the corn accrue to everyone who has points on the back end? Like, does Matthew McConaughey make a couple dollars off of that corn trade? I don't know. We'll have to get to the bottom of it. We have our next guest who welcomes for the stream Jay.

As soon as you gave the developers the ability to write code they were like let's make a game. It's amazing. And so to me, remember the biggest gaming business is the Windows business. To us gaming on Windows. And of course Steam has built a massive marketplace on top of it and done a very successful job of it. So to us the way we are thinking about gaming is let's first of all now we're the largest publisher after the Activision. So therefore we want to be a fantastic publisher. Similar approach to what we did with Office. We're going to be everywhere in every platform. So we want to make sure whether it's consoles, whether it's the PC, whether it's mobile, whether it's cloud gaming or the tv. So we just want to make sure the games are being enjoyed by gamers everywhere. Second, we also want to do innovative work in the system side on the console.

Marketplace on top of it and done a very successful job of it. So to us, the way we are thinking about gaming is let's first of all, now we're the largest publisher after the Activision, so therefore we want to be a fantastic publisher. Similar approach to what we did with Office. We're going to be everywhere in every platform. So we want to make sure whether it's consoles, whether it's the PC, whether it's mobile, whether it's cloud gaming or the tv. So we just want to make sure the games are being enjoyed by gamers everywhere. Second, we also want to do innovative work in the system side on the console.

You have. And then also to entrepreneurs who are building products maybe on top of Microsoft. How are you thinking about the entrepreneurial opportunity in. I think it's a very good point because at some level, if you sort of buy the argument I made that there's a lot more invention to happen. Yeah. By the way, the other thing that we should also talk about, I always say to this too. Right. Trades. All the conventional wisdom is, oh, intelligence is just simple, straightforward log of compute. So throw more compute in your diamond. Who the heck knows, man? One of the researchers comes from here, comes out of here and says, you know what? Got it. It requires. Less compute. Than any of you guys have thought about. Like that's a game changer. Oh, by the way, we're all like excited about reinforcement learning. Guess what? Pre training is a more efficient form of training because you can advertise it. So there's a. I think pre training will have new breakthroughs. Mid training will have new breakthroughs. RL will continue to improve. We will then have to add more innovation to it. And by the way, this is a. On another part of this partnership which is I'm GLAD you know, OpenAI is continuing to do great work. Jakob, Mark and others are great and we'll partner with them and we'll continue to do so. And Mustafa has built a world class team. Right. You know, Karen, Amar, Nando, these are, I mean we have now three cool models, whether it's speech or image or text and we're going to continue to innovate. So we'll write our worst as well. Yeah. How are you thinking about the interplay between OpenAI and what you do internally at Microsoft? So our simple. Are there certain things.

It. It requires less compute than any of you guys have thought about. Like that's a game changer. Oh, by the way, we're all like excited about reinforcement learning. Guess what? Pre training is a more efficient form of training. Yeah. Because you can advertise it. So there's a. I think pre training will have new breakthroughs. Mid training will have new breakthroughs. RL will continue to improve. We will then have to add more innovation. And by the way, this is on another part of this partnership which is I'm GLAD you know, OpenAI is continuing to do great work. Jakob, Mark and others are great and we'll partner with them and we'll continue to do so. And Mustafa has built a world class team. Right. You know, Karen, Amar, Nando, these are, I mean we have now three cool models, whether it's speech or image or text and we're going to continue to innovate. So we'll write our worst as well. Yeah. How are you thinking about the interplay between OpenAI what you do internally at Microsoft? So our simple. Are there certain things.

Changing business model, shifting your business model. It seems like the console wars are over. Take me through the journey. You're a peacetime CEO, now you're a peacetime CEO. The war is over. But take me through the evolution of the business model. Shift on the gaming side of the business. It's one of the most interesting pieces of Microsoft. Yeah, I mean, I think you've got to remember, in fact, Flight Simulator, I think, was the first product Microsoft built even before I think our devtools was first. Yeah. Flight Simulator was second. That says so much about the culture. Yeah, it is. As soon as you gave the developers the ability to write code, they were like, let's make a game. It's amazing. And so to me, remember, the biggest gaming business is the Windows business. Yeah. To us, gaming on Windows. And of course, Steam has built a massive marketplace on top of it and done a very successful job of it. So to us, the way we are thinking about gaming is let's first. First of all, now we're the largest publisher after the Activision, so therefore we want to be a fantastic publisher. Similar approach to what we did with Office. We're going to be everywhere in every platform. So we want to make sure whether it's consoles, whether it's the PC, whether it's mobile, whether it's cloud gaming or the tv. So we just want to make sure the games are being enjoyed by gamers everywhere. Second, we also want to do innovative work in the system side on the console.

It feels like the entire world's competition is far video. Yeah, I mean we've heard this thing a while ago. It just comes up again and again with public SaaS, companies that are maybe a little bit more of a point solution and they have to go through a business model transition and that can be harder than a tech transition. And we hear about, oh well, if you want to change your business model, maybe you want to be private, but it feels like is there some sort of advantage of being a hyperscaler, a $4 trillion company that you can go and retool a piece of the business over here, change the business model and, and have almost the, the privilege of, you know, not having shareholders come to you and beat you down about a slight shift in a business model in a subdivision. That's that you don't get that. I can't deny that, you know, diversity of business models, diversity of the portfolio that Microsoft has, has been helpful. I mean it's kind of. But that said, I don't think you can take that and say somehow you can make it if you don't reinvent yourself. So I think what happens in tech, unfortunately is that when these shifts happen. Yeah. Whether you like it or not, you have to first be relevant after having. It doesn't matter what the business model is. The business model may be like I had whatever 90% margins, you are going to at best have 10% but you have to jump all in because even that 90 is going to zero. Yeah. And so given the binary nature, you got to make it to the other side. But then the category economics matters because if you can't sustain long term innovation, if there is no category economics, I mean hyperscale is a great one. In fact the best day in hyperscale business was the day Amazon announced their operating margins. Ipo. Yeah. You know, because that's when everybody knew hyperscale business is an unbelievable business. It's a commodity, but at scale nothing is a commodity. And so to me that is kind of going to be the key here. Even SaaS applications quickly unpack why that was so good for you. Again, just because the market recognized that you were in the same business. And it was fantastic. That is one. And more importantly, it was much more expensive. Right. I mean think about our server business. It's super profitable except it was one tenth the size when I look at it compared to Azure. So we like, we sold a few servers but man, we sell a lot of cloud VMs or containers. Who would have thought how expansive the cloud consumption model is? Going to be in terms of people being able to sort of. It's kind of the Jevons paradox that sort of really played out in a massive way if you just. With cloud broadly. Yeah. And so I think on the business. Well timed Jevons paradox post, by the way, back during the deep Seq moment. That was an important post. I wish we could keep going.

Making to bring more coherence to the chaos. And that I think is going to make the big difference maker. I was talking to Eric Lyman at Ramp who makes the show possible. Of course, he had a question about how you. What, like what advice you would give to someone running a decacorn thousand plus employees in this age of spiky intelligence where there is the possibility that tools are going to get better very rapidly and maybe you don't want to scale up too fast and then have to do layoffs or retraining like you run a huge organization. How do you think about managing human capital in what feels like an uncertain time? Does it feel more uncertain to you now than it did 10 years ago? That's a great point. I mean, Eric's a great founder. I know him well and they're doing some unbelievable work. And so in fact, whenever I've talked to him, in fact, I learned from him even how he's rapidly changing the agents they have built. So to some degree, I think at Microsoft or its ram, I think the key is learning the new production function. So when I look back at Microsoft, I feel like, hey, look, platform ships we've navigated. I joined Microsoft when my our existential competitor was Novell. Right. And so, you know, in 92 and here we are. And so. But the bottom line is we've over the years navigated many platform shifts. Yeah, We've also navigated tough business model shifts. Right. When you suddenly have, you know, you have a 98, 99% gross margin, server business, and you move to the cloud and you don't even know, man, is there a margin here? And yet you have to make the shift and figure it out. This one is, interestingly enough, both a tech shift, a business model shift. Because this is the first time you have marginal cost of software. Just not like cogs of the SaaS world, but true marginal cost. And three, the way you produce your artifact, your software is changing. So the product development process is completely getting ripped and replaced. And that is whether it's for ram. Yeah, well, even the competitive dynamic too, because you have people that can say, hey, we can build this product in two months. Previously would have taken us 12 months. Why don't we enter that category? And it's kind of like rewiring yourself, right? Unlearning is the hardest part. Learning is easy. Sometimes if you have to unlearn and learn, it's much harder. And so to me, that I think is what all of us have to do. I mean, it's funny, I met a bunch of student developers right here. It is the first cohort of developers who grew up with GitHub Copilot a standard issue when they joined completely different environment. They say there was a world before gitopilot. They're like, I don't want to live in that world. Completely different abstraction level. On the topic of changing business model, shifting your business model, it seems.

DC presenting it in the double polo. It's iconic, but I didn't realize that you were doing business with them back then. And it started, I think, in 2016. In fact, we were. Azure was the first cloud provider. That's right. When OpenAI got started. In fact, I think Elon sent me the mail asking for Azure credits. So that's how it got started. Hey, I have this nonprofit. Come on. That's right. And they were obviously into reinforcement learning. They were doing dota and all of that stuff. And then at some point it reached where I think they went off. I think they went to other clouds. And so I lost touch for a while. And then I think in 2019, Sam came and talked about sort of, hey, we're going to really. We think the scaling stuff works. I forget now, it's a little hazy. When I read the paper, in fact, the paper was written by Dario Ilya and the scaling laws paper and that thing that's, you know, Microsoft has been obsessed since Bill started Microsoft Research in 95 is natural language. It's just being the thing. We are an office company. We are a knowledge work company. And so we always thought about text and AI as applied to text and natural language. So you could say it's the prepared mind. When sort of Sam said, hey, we're going to go take a run. You won't be on it. That's sort of what led to really coming together on this. It was a research lab, it was a nonprofit, as opposed to if they. Had stayed on the previous tech tree path of they were doing some humanoid robotics, they were doing some video game stuff. And.

Yeah, so that makes a ton of sense. Obviously, it's been a wild ride up and down. You started with just natural language, let's predict the next word. Now let's rewrite the entire global economy. How do you think about the territory that you at Microsoft have kind of claimed? And what do you want to hold on to? What's most important? To map out where Microsoft, where the edges of your territory are and then where founders and other business people can build in partnership with you. Yeah. So look, if you take sort of. I always say Microsoft's a platform company and a partner company and we define platforms as where the value capture about the platform is higher than by the platform. That's kind of who we are. And that's, you know, GitHub is a great place. So if you think about even at GitHub Universe today, it's interesting, right? As you said, we first started by saying, hey, code completion. Then we said, let's chat. Instead of getting distracted, stay in the flow of coding. You bring the information to the flow and that's chat became the thing. Then we said agent mode. Then we said, hey, let's have autonomous agents. And then now we have multiple autonomous agents working across all these different branches, then bringing the PRs to me. And so this entire conference is about what we call agent HQ and mission control, where you have Codex, you have Claude, you have Grok. Every model you want each working across their own branches. Then you have the IDE so you can bring up VS code where you can do the diff on each of the branches output. And then so the story goes on. So therefore, to me, building a system, yeah, that really brings the innovation across the ecosystem into some kind of an organizing layer is what platform companies do. Well, have you seen anyone here that you think might be working on AGI? Do you have a.

Against like a six year time horizon. But how are you thinking about managing over the next decade? Yeah, I mean, I think, you know, to me, you know, one of the things about tech is as a percentage of GDP, around 4 or 5%. Yeah. And if you ask me five years from now, 10 years from now, is that percentage going to be higher or lower? I think the answer is pretty straightforward. It's going to be higher. It's just a question, is it going to be 10 or 15? So why is that? Because the rest of the pie, the rest of the GDP would have grown faster. So that's why I always go back to, at the end of the day, the only rate limiter here is the overall economic growth and the factors of sort of input to it. So tech as an input, I think AI and everything that it entails is going to be a core driver and some of it will come from just this intelligence and its sort of continual march of capability. But it'll also come from ielts call it great engineering and product making around it. Like when I look at GitHub copilot today with agent HQ and what have you, that's great because right now I'm inundated with multiple models and everything is slightly different except I have one repo and I want all of these agents to come work on all of my repo in different branches. So you need great product making to bring more coherence to the chaos. And that I think is going to make the big difference maker. I was talking to Eric Lyman at Ramp who makes the show possible, of course. He had a question about how.

How you, how you imagine that kind of decision making process will go when. The time comes, we'll put you guys on the panel. Yeah. We've been doing evaluations on AGI, specifically around comedy candidate, funny comedy, comedy bench. I think, first of all, I think one of the reasons why, quite frankly, both Sam and I, I think, agree on this, which is it's become a bit of a nonsensical word. I mean, it's just changing and everybody defines it differently. And we now know what the issue is. Right. We know everybody describes even the intelligence we have, which has been exceptional, as jagged. Yep. Yeah. So spiky. Yeah, spiky intelligence. All right. And so if you sort of say, well, we have spiky intelligence. And in fact, I think Andrej Karpathy's point in one of the podcasts recently, which is a good one, which is even if you're having. Except, you know, let's call it exponential growth in one of the spikes. Sure. It's not as if the Jags are getting worked out. That's the nines problem. That is, each nine is maybe linear, even sublinear problem in terms of rate of progress. So first step to me is even to get to broad intelligence, forget sort of general intelligence, we've got to get rid of these jagged problems. And that, I think is the first place to do so, if you ask me. I think what may happen is we will achieve more robustness. Let's call it that for different systems. Right. So coding is a good one. I think the entire goal with GitHub and GitHub mission control and Agent HQ is can I just like how I use compilers, can I use agents to generate better coding artifacts today? Coding, I mean, so I sometimes think wipe coding is a sort of a slightly unfortunate term because it does lead to a lot of slopes. Right. I mean, it's kind of like, I'm sure you go away and then you lose control of the project and then you got to put everything back into a markdown and you. So, yeah, even traditional knowledge work that's happening in the Office suite, it's not like you want the biggest Excel model. Right. You want the one. But even Excel is a classic one. In fact, one of the other things that's happened is even in when I see Microsoft 365 copilot, man, the amount, just like right now, the number of repos on GitHub is exploding. Yeah. The other thing is everybody's generating PowerPoint and slide decks and sort of Excel models. The problem with Excel models is, you know, when intelligence is created Excel models, I mean it is like a thing of beauty, right? Assumptions are clear, the formulas are there. Even the formatting. And you can iterate. On it, you can change tells a story. It's not like a one shot and when I want to change I can't go back and say zero shot the entire thing. So in fact the agent mode in Excel which I like is it understands Office js, it puts the formulas I can then iterate like I iterate on GitHub copilot so those systems. So if you ask me about, you know first how do you get rid of this jagged intelligence problem is you build a great knowledge work system that is multi agent, multi model, multi form factor. Get to a great benchmark in an eval where you can trust it at two nines, three nines, four nines. And until you achieve that you're not going to be able to move and say hey, we have anything guided general intelligence. Yeah, it feels like there was a lot of uncertainty.

With me broadly. Yeah. And so I think on the business. Well timed Jevons paradox post by the way back during the the deep seek moment. That was an important post. Spot on with that process. I wish we could keep going. I think we have to wrap up. We would love for you to sign this gone. And of course give it a quick hit for 27%. Wow. That's a good hit. Good hit. Very strong here. As big as possible. Oh there we go. That is a fantastic signature. Thank you for coming on. Thank you for having us. This is really great. I've always whenever these big news, these big tech news things happen I always wish I could talk to the person who's making the news and now I get to and so what a wonderful conversation. What a moment. What a CEO. Yeah. What a moment in the tech world. Well thank you. If you're new here and you tuned in just because of.

Important spot. On with that process. I wish we could keep going. I think we have to wrap up. We would love for you to slide this gone. And of course, give it a quick hit for 27%. Wow. That's a good hit. Good hit. Very strong hit. As big as possible. Oh, there we go. That was a fantastic signature. Thank you for coming on. Thank you for having us. This is really good. I've always, whenever these big news, these big tech news things happen, I always wish I could talk to the person who's making the news. And now I get to.

World before get up. Yeah. They're like, I don't want to, I don't want to live in that world. Completely different abstraction. On the, on the topic of changing business model, shifting your business model, it seems like the console wars are over. Take me through the journey. You're a peacetime CEO now you're a peacetime CEO. The war is over. But take me through the evolution of the, of the business model shift on the gaming side of the business. It's one of the most interesting pieces of Microsoft. Yeah, I mean, I think you've got to remember, in fact, Flight Simulator I think was the first product Microsoft built even before I think our Dev tools was first. Flight Simulator was second. That says so much about the culture. Yeah, it is. As soon as you gave the developers the ability to write code, they were like, let's make a game. It's amazing. And so to me, remember, the biggest gaming business is the Windows business. To us, gaming on Windows and of course Steam has built a massive marketplace on top of it and done a very successful job of it. So to us, the way we are thinking about gaming is let's first of all now we're the largest publisher after the Activision. So therefore we want to be a fantastic publisher. Similar approach to what we did with Office. We're going to be everywhere in every platform. So we want to make sure whether it's consoles, whether it's the PC, whether it's mobile, whether it's cloud gaming or the tv. So we just want to make sure the games are being enjoyed by gamers everywhere. Second, we also want to do innovative work in the system side on the console and on the PC and bring, you know, it's kind of funny that, you know, people think about the console PC as two different things. We built the console because we wanted to build a better PC which could then perform for gaming. And so I kind of want to revisit some of that conventional wisdom. But at the end of the day, console has an experience, experience that is unparalleled. It delivers performance that's unparalleled, that pushes I think, the system forward. So I'm really looking forward to the next console, the next PC gaming. But most importantly, the game business model has to be where we have to invent maybe some new interactive media as well. Because after all, gaming's competition is not other gaming. Gaming's competition is short form video. And so if we as an industry don't continue to innovate both how we produce, what we produce, how we think about distribution, the economic model. Right. Best way to innovate is to have good margins because that's the way you can fund. So, so interesting saying gaming's competition is short form video. Feels like the entire world's competition is short form video. Yeah, I mean, we've heard this thing a while ago. It just comes up again and again with public SaaS, companies that are maybe a little bit more.

It became a thing. And remember that was all done before Chad GPT became a thing. Yeah. How do you. I think there's a general consensus now that it's, it feels very possible to predict like a year out, two years out and then 10 years out is extremely fuzzy. What's your view on that? Given that you look like going back to the original OpenAI investment and the original partnership, it seems like you've had at least really good like six year, kind of like foresight ability to sort of invest against like a six year time horizon. But how are you thinking about managing over, you know, the next decade? Yeah, I mean, I think, you know, to me, you know, one of the things about tech is as a percentage of GDP, they're like around 4 or 5%. Yeah. And if you ask me five years from now, 10 years from now, is that percentage going to be higher or lower? Think the answer is pretty straightforward. It's going to be higher. It's just a question, is it going to be 10 or 15? So why is that? Because the rest of the pie, the rest of the GDP would have grown faster. So that's why I always go back to. At the end of the day the only rate limiter here is the overall economic growth and the factors of sort of input to it. So tech as an input, I think AI and everything that it entails is going to be a core driver and some of it will come from just this intelligence and it's sort of continual march of capability. But it'll also come from, I'll call it great engineering and product making around it. Like when I look at GitHub copilot today with agent HQ and what have you, that's great because right now I'm inundated with multiple models and everything is slightly different except I have one repo and I want all of these agents to come work on all of my repo in different branches. So you need great product making to bring more coherence to the chaos. And that I think is going to be the big difference. I was talking to Eric Lyman at Ramp who makes the show possible. Of course. He had a question about how.

Yeah, that's a good model to create value. Do you think that there's increasing returns? This is going to sound like a loaded question, but I promise you it's not. There's increasing returns right now to being a deals guy or innovating on the, on the deal structuring side. And what I mean by that is there's all these difficult problems to solve with energy and data centers. And it feels like there's innovation in tech that we normally think of as like the code or the algorithm or the design of the system. But then there's also this difficulty sometimes to just marshal the resources. And is that, is that like a new phenomenon? Has that always been true? Is there, if somebody's pursuing a career in tech, is becoming a great deals guy or deal maker like an important path now? Yeah, I was just thinking about it, man, like, which is, yeah, you have this great investment and it has great return and no carry. All it, all the value goes to my shareholders. That's awesome. Maybe we should start a venture firm. You might do well there. I think the thing you're touching on is something that actually platform companies should think about, which is what's the ecosystem upstream and downstream. To your point, right now we have to as an industry, the reality is let's take power. Right. Which is if you sort of say intelligence is about tokens per dollar per watt, we've got to get efficient on all of it. Yeah. In order to get more efficient on it, you got to really think about even in our own industry, the token factory itself really getting better order of magnitude. This is like again, a renaissance time for systems architecture. And so we, you know, obviously Nvidia is doing great work. AMD is doing stuff, Broadcom is doing stuff. All of us are doing great work to just push that. Yep. Then the next barrier is going to be man. Can we generate energy faster? Can we build faster? Can we build a cooling. I mean, like, I mean, I now know more about campus cooling systems than I ever thought I'll know. Right. I mean, and these are all choke points. How much do you want that to live within Microsoft versus you want to just be a buyer and all the different power players are out there building nuclear, wind, solar, and you're just.

Speech or image. Or text and we're. Going to continue to innovate, so we'll. Write our worst as well. Yeah. How are you thinking about the interplay between OpenAI and what you do internally at Microsoft? So our simple are there certain things. That you can take your foot off the gas because you're like, actually OpenAI's got that handled or do you want a duopoly? Like, actually we're going to fight it out on everything. I'm much more like again my mindset is all platform man. Like, hey, on Azure. Do you run Windows? Yeah. Do you run Linux? Yeah. Do you run SQL Server? Yeah. Do you love Postgres? Absolutely. Net Java? Hey, I'm happy with OpenAI. I would love to have Anthropic Mai rock anyone. If Google wants to put Gemini on Azure, please do so what. Is that like culturally? Like, what does it mean for the next satya Nadella Somebody who's working their way up in Microsoft, do they need to be okay, I'm building something internally but.

Kind of an organizing layer is what platform companies do. Well, have you seen anyone here that you think might be working on AGI? Do you have a personal definition for AGI? Yeah, if you look at pretty much all the deal points, it keeps coming back to this moment when AGI will be declared right. There'll be a panel of experts. Maybe that panel is still being decided, but a lot of experts today have differing definitions. So I wanted to get a better sense of how you. How you imagine that kind of decision making process will go when the time comes. We'll put you guys on the panel. Yeah, we've been doing evaluations on AGI, specifically around comedy. Can it write something funny? There you go. Comedy. Comedy bench. To me, I think, first of all, I think one of the reasons why, quite frankly, both Sam and I agree on this, which is it's become a bit of a nonsensical word. I mean, it's just changing and everybody defines it differently. And we now know what the issue is. We know everybody describes even the intelligence we have, which has been exceptional, as jagged. Yep. Yeah. So spiky. Yeah, spiky intelligence. All right. And so if you sort of say, well, we have spiky intelligence. And in fact, I think Andrej Karpathy's point in one of the podcasts recently, which is a good one, which is even if you're having. Except, you know, let's call it exponential growth in one of the spikes. Sure. It's not as if the Jags are getting worked out. That's the nines problem. That is, each nine is maybe linear, even sublinear problem in terms of rate of progress. So first step to me is even to get to broad intelligence, forget sort of general intelligence, we've got to get rid of these jagged problems. And that, I think is the first place to do so, if you ask me, I think what may happen is we will achieve more robustness. Let's call it that for different systems. Right. So coding is a good one. I think the entire goal with GitHub and GitHub, mission control and agent HQ is can I just like how I use compilers? Can I use agents to generate better coding artifacts? Today? Coding, I mean, so I sometimes think wipe coding is a sort of a slightly unfortunate term because it does lead to a lot of slopes. Right. I mean, it's kind of like, I'm sure you go away and then you lose control of the project and then you got to put everything back into a markdown and you. So, yeah, even traditional knowledge work that's happening in the Office suite. It's not like you want the biggest Excel model, right? You want the one. But even Excel is a classic one. In fact, one of the other things that's happened is even in when I see Microsoft 365 copilot man, the amount just like right now, the number of repos on GitHub is exploding. Yeah. The other thing is everybody's generating PowerPoint and slide decks and sort of Excel models. The problem with Excel models is, you know, when intelligence is created, Excel models, I mean it is like a thing of beauty, right? Assumptions are clear, the formulas are there. Even the formatting. And you can iterate. On it, you can change, tells a story. It's not like a one shot and when I want to change I can't go back and say zero shot the entire thing. So in fact the agent mode in Excel which I like is it understands Office js, it puts the formulas, I can then iterate like I iterate on GitHub copilot so those systems. So if you ask me about, you know, first how do you get rid of this jagged intelligence problem is you build a great knowledge work system that is multi agent, multi model, multi form factor. Get to a great benchmark in an eval where you can trust it at two nines, three nines, four nines. And until you achieve that, you're not going to be able to move and say hey, we have anything guided general intelligence. Yeah, it feels like there was a lot of uncertainty.

Started there and then RL now is improving the quality of these models for sure. How big of a deal was writing a $1 billion check back then? I mean, it's a big company, Microsoft, we think it makes revenues around a billion dollars a business day. Was it one day of work for you or was it weeks of negotiation? Seriously, did you build memos? Were you building Excel sheets? What were you thinking? Even at Microsoft, you kind of have to get a board approval to just go throw a billion dollars out of there. But, you know, I must say, it was not that hard to convince anyone that this is an important area and it's going to be risky. Like, I mean, in retrospect, I mean, who have thought, hey, I didn't put in that, you know, billion dollars saying, oh, yeah, this is going to be a what of 100 bagger? Yeah, that's not like what was going through our head. This is a partnership that. I mean, by the way, remember, this is a nonprofit, right? And I think, you know, Bill even said, yeah, you're going to burn this billion dollars. Right? And yeah, we kind of had a little bit of tolerance and we said, we want to go and give this a shot. And then of course, we subsequently, you know, here we are at GitHub universe. In fact, this is probably the place where that billion to 10 billion happened. Because in 21 is when I first saw GitHub Copilot. And I said, man, this is a. Year before the release. No, actually, in fact, I was fact checking my thing. I think GitHub Copilot launched in 21 chat GPD in 22. Sure. And if I remember right, 23 is the blip, the November blip with OpenAI. And then everything has been smooth since then. The blip. Nicest way you could put that. That's fantastic. Yeah, so that makes a ton of sense. Obviously, it's.