That's good Mojo - Creating a Programming Language for an AI world with Chris Lattner

Hey friends, it's Scott. I want to thank Hey friends, it's Scott. I want to thank our new sponsor, Mail Trap. Modern email our new sponsor, Mail Trap. Modern email our new sponsor, Mail Trap. Modern email delivery for developers. They integrate delivery for developers. They integrate delivery for developers. They integrate straight into your code with their SDKs. straight into your code with their SDKs. straight into your code with their SDKs. You get unified transactional and You get unified transactional and You get unified transactional and promotional email delivery. 24/7 promotional email delivery. 24/7 promotional email delivery. 24/7 support. You contact humans, not AI chat support. You contact humans, not AI chat support. You contact humans, not AI chat bots. We'll give you 3,500 emails bots. We'll give you 3,500 emails bots. We'll give you 3,500 emails monthly in the free tier. And you can monthly in the free tier. And you can monthly in the free tier. And you can try them out at mail.io try them out at mail.io try them out at mail.io today. That's m a lap.io. today. That's m a lap.io. today. That's m a lap.io. io today. io today. io today. [music] [music] Hey friends, I'm Scott Hansel [music] Hey friends, I'm Scott Hansel and this is another episode of Hansel and this is another episode of Hansel and this is another episode of Hansel Minutes. Today I'm chatting with Chris Minutes. Today I'm chatting with Chris Minutes. Today I'm chatting with Chris Latner. He's a creator of LLVN, the Latner. He's a creator of LLVN, the Latner. He's a creator of LLVN, the compiler infrastructure that underpins compiler infrastructure that underpins compiler infrastructure that underpins huge swasts of modern software. And he's huge swasts of modern software. And he's huge swasts of modern software. And he's also the original architect of Swift and also the original architect of Swift and also the original architect of Swift and he's had engineering leadership roles at he's had engineering leadership roles at he's had engineering leadership roles at Apple and Tesla and Google, but now he's Apple and Tesla and Google, but now he's Apple and Tesla and Google, but now he's at Modular AI focused on the next at Modular AI focused on the next at Modular AI focused on the next generation of AI native programming generation of AI native programming generation of AI native programming tools. How are you, sir?

tools. How are you, sir? tools. How are you, sir? >> I'm doing well, Scott. I'm excited to be >> I'm doing well, Scott. I'm excited to be >> I'm doing well, Scott. I'm excited to be here. Um, I'm I'm happy you finally had here. Um, I'm I'm happy you finally had here. Um, I'm I'm happy you finally had me on. me on. me on. >> It only took a thousand episodes and you >> It only took a thousand episodes and you >> It only took a thousand episodes and you know I know I know I >> Well, you have standards so I can >> Well, you have standards so I can >> Well, you have standards so I can understand. understand. understand. >> Well, I wanted more accomplished people >> Well, I wanted more accomplished people >> Well, I wanted more accomplished people so I was waiting for your Wikipedia page so I was waiting for your Wikipedia page so I was waiting for your Wikipedia page to scroll more. to scroll more. to scroll more. >> Oh, yeah. I mean, maybe if we don't >> Oh, yeah. I mean, maybe if we don't >> Oh, yeah. I mean, maybe if we don't offend you and your audience too badly, offend you and your audience too badly, offend you and your audience too badly, you'll have me on again sometime. So, you'll have me on again sometime. So, you'll have me on again sometime. So, >> I think a lot of things we could talk >> I think a lot of things we could talk >> I think a lot of things we could talk about. about. about. >> Yeah, it is it is kind of funny though. >> Yeah, it is it is kind of funny though. >> Yeah, it is it is kind of funny though. You're right. I mean, you should have You're right. I mean, you should have You're right. I mean, you should have been on seven or 800 episodes ago, so been on seven or 800 episodes ago, so been on seven or 800 episodes ago, so that is 100% my bad. And I will take that is 100% my bad. And I will take that is 100% my bad. And I will take that feedback to the team. Uh, which is that feedback to the team. Uh, which is that feedback to the team. Uh, which is me. Um, I'm curious though. I'm thinking me. Um, I'm curious though. I'm thinking me. Um, I'm curious though. I'm thinking about I'm thinking about history and I'm about I'm thinking about history and I'm about I'm thinking about history and I'm thinking about being, you know, doing thinking about being, you know, doing thinking about being, you know, doing this for so many years and you've been this for so many years and you've been this for so many years and you've been doing this for, you know, we're kind of doing this for, you know, we're kind of doing this for, you know, we're kind of contemporaries. Um, but LVM was a contemporaries. Um, but LVM was a contemporaries. Um, but LVM was a research project, right? You just kind research project, right? You just kind research project, right? You just kind of had had a Jones for this when you of had had a Jones for this when you of had had a Jones for this when you were a grad student at University of were a grad student at University of were a grad student at University of Illinois. Was this a long con? Have you Illinois. Was this a long con? Have you Illinois. Was this a long con? Have you been working on all this stuff for 30 been working on all this stuff for 30 been working on all this stuff for 30 years to get to this moment right now? years to get to this moment right now? years to get to this moment right now? >> Well, so I mean, I wouldn't say it's a >> Well, so I mean, I wouldn't say it's a >> Well, so I mean, I wouldn't say it's a con, it's a passion. It's my life's con, it's a passion. It's my life's con, it's a passion. It's my life's work. That That's probably a nicer way work. That That's probably a nicer way work. That That's probably a nicer way to put it.

to put it. to put it. >> Um, I mean, I'm I'm a special kind of >> Um, I mean, I'm I'm a special kind of >> Um, I mean, I'm I'm a special kind of nerd. I think you know uh I am very nerd. I think you know uh I am very nerd. I think you know uh I am very enthralled with compute and with enthralled with compute and with enthralled with compute and with compilers and systems and hardware and compilers and systems and hardware and compilers and systems and hardware and chips and like how it all works together chips and like how it all works together chips and like how it all works together but I really identify as a developer but I really identify as a developer but I really identify as a developer right and so I write a lot of code still right and so I write a lot of code still right and so I write a lot of code still you can check me out on GitHub the uh um you can check me out on GitHub the uh um you can check me out on GitHub the uh um I care about the craft I care about what I care about the craft I care about what I care about the craft I care about what it means I care about people developing it means I care about people developing it means I care about people developing in their careers I care about building in their careers I care about building in their careers I care about building teams of people I care about you know teams of people I care about you know teams of people I care about you know building things and hopefully making an building things and hopefully making an building things and hopefully making an impact on the world so impact on the world so impact on the world so >> I'm good at certain things I'm way >> I'm good at certain things I'm way >> I'm good at certain things I'm way better at building a compiler than uh an better at building a compiler than uh an better at building a compiler than uh an iPhone app or a HTML page. But uh that's iPhone app or a HTML page. But uh that's iPhone app or a HTML page. But uh that's cool with me. I just kind of try to be cool with me. I just kind of try to be cool with me. I just kind of try to be useful. useful. useful. >> Did you see the AI moment coming? Like I >> Did you see the AI moment coming? Like I >> Did you see the AI moment coming? Like I feel like mo a lot of people will say feel like mo a lot of people will say feel like mo a lot of people will say like as of October now they can code for like as of October now they can code for like as of October now they can code for us, but like I suspect you saw this us, but like I suspect you saw this us, but like I suspect you saw this coming a little sooner than October of coming a little sooner than October of coming a little sooner than October of last year. last year. last year. >> Yeah, I fell in love with AI or >> Yeah, I fell in love with AI or >> Yeah, I fell in love with AI or enthralled with AI actually uh in like enthralled with AI actually uh in like enthralled with AI actually uh in like 2016. So it's about a decade ago, which 2016. So it's about a decade ago, which 2016. So it's about a decade ago, which makes me I guess a pretty old-timer at makes me I guess a pretty old-timer at makes me I guess a pretty old-timer at this point. That was right when the this point. That was right when the this point. That was right when the photos app at Apple was getting the photos app at Apple was getting the photos app at Apple was getting the ability to see cats and dogs in photos.

ability to see cats and dogs in photos. ability to see cats and dogs in photos. And I'm like, And I'm like, And I'm like, >> how do you write for loops to figure out >> how do you write for loops to figure out >> how do you write for loops to figure out if there's a cat in a picture? And uh if there's a cat in a picture? And uh if there's a cat in a picture? And uh because of that, I just kind of fell because of that, I just kind of fell because of that, I just kind of fell down the rabbit hole. What is what is a down the rabbit hole. What is what is a down the rabbit hole. What is what is a neural network? What is a convolutional neural network? What is a convolutional neural network? What is a convolutional neural net? How does all this kind of neural net? How does all this kind of neural net? How does all this kind of stuff work? And that's actually when I stuff work? And that's actually when I stuff work? And that's actually when I was kind of getting kind of bored and was kind of getting kind of bored and was kind of getting kind of bored and ready to go embark on new things. And ready to go embark on new things. And ready to go embark on new things. And since then, I've been chasing what is since then, I've been chasing what is since then, I've been chasing what is AI? What is the developer platform? What AI? What is the developer platform? What AI? What is the developer platform? What are the tools look like? What are the are the tools look like? What are the are the tools look like? What are the systems? How do we unlock the hardware? systems? How do we unlock the hardware? systems? How do we unlock the hardware? And this has been my mission for the And this has been my mission for the And this has been my mission for the last last decade now, which is kind of last last decade now, which is kind of last last decade now, which is kind of scary how that works. But scary how that works. But scary how that works. But >> but did you feel that GPTs were going to >> but did you feel that GPTs were going to >> but did you feel that GPTs were going to be able to spit code out as well as they be able to spit code out as well as they be able to spit code out as well as they can now? can now? can now? >> Well, so the the funny thing about AI, >> Well, so the the funny thing about AI, >> Well, so the the funny thing about AI, if you've been in the space, is that if you've been in the space, is that if you've been in the space, is that it's always changing, right? And so it's always changing, right? And so it's always changing, right? And so being in the AI space necessarily means being in the AI space necessarily means being in the AI space necessarily means that you become like acclimated to that you become like acclimated to that you become like acclimated to discomfort like you you're used to discomfort like you you're used to discomfort like you you're used to things changing all around you. You things changing all around you. You things changing all around you. You never know what model or capability or never know what model or capability or never know what model or capability or demo or whatever will launch next month, demo or whatever will launch next month, demo or whatever will launch next month, right? And so when chat GPT happened, I right? And so when chat GPT happened, I right? And so when chat GPT happened, I that was a huge deal. I think that's that was a huge deal. I think that's that was a huge deal. I think that's that was the first wakeup call for a lot that was the first wakeup call for a lot that was the first wakeup call for a lot of people when they started to realize of people when they started to realize of people when they started to realize that AI is a real thing. Um but chat GPT that AI is a real thing. Um but chat GPT that AI is a real thing. Um but chat GPT for me was just the next the next step, for me was just the next the next step, for me was just the next the next step, right? And so what's happening, I think right? And so what's happening, I think right? And so what's happening, I think even the last few months is that AI even the last few months is that AI even the last few months is that AI coding has really come onto the scene in coding has really come onto the scene in coding has really come onto the scene in a way that people didn't see coming. But a way that people didn't see coming. But a way that people didn't see coming. But it's really also the accumulation of a it's really also the accumulation of a it's really also the accumulation of a bunch of exponentials. And so I've been bunch of exponentials. And so I've been bunch of exponentials. And so I've been tracking the AI coding thing for over a tracking the AI coding thing for over a tracking the AI coding thing for over a year now. Um I've been using cursor for year now. Um I've been using cursor for year now. Um I've been using cursor for my daily driver personally um and been my daily driver personally um and been my daily driver personally um and been experimenting with some of the agentic experimenting with some of the agentic experimenting with some of the agentic stuff and um it's amazingly stuff and um it's amazingly stuff and um it's amazingly it's amazing what can be done but it is

it's amazing what can be done but it is it's amazing what can be done but it is also more a continuation of the same and also more a continuation of the same and also more a continuation of the same and so I see it building and the thing that so I see it building and the thing that so I see it building and the thing that we all wrestle with as developers now is we all wrestle with as developers now is we all wrestle with as developers now is what does it mean? How do I best use it? what does it mean? How do I best use it? what does it mean? How do I best use it? What is hype? What is real? Like do I What is hype? What is real? Like do I What is hype? What is real? Like do I still have purpose? And so for these still have purpose? And so for these still have purpose? And so for these things like again it's not like a new things like again it's not like a new things like again it's not like a new question. It's more about like what is question. It's more about like what is question. It's more about like what is the purpose? How do we shape our time? the purpose? How do we shape our time? the purpose? How do we shape our time? How do we best use the tools? And as the How do we best use the tools? And as the How do we best use the tools? And as the tools evolve, I think we we need to tools evolve, I think we we need to tools evolve, I think we we need to adapt. adapt. adapt. The uh speaking of uh I think about The uh speaking of uh I think about The uh speaking of uh I think about every era panics like I remember when I every era panics like I remember when I every era panics like I remember when I went from assembler to C and some of the went from assembler to C and some of the went from assembler to C and some of the old heads would tell me that like no no old heads would tell me that like no no old heads would tell me that like no no you got to do assembler like real real you got to do assembler like real real you got to do assembler like real real programmers use assembler and then when programmers use assembler and then when programmers use assembler and then when I got color syntax highlighting they're I got color syntax highlighting they're I got color syntax highlighting they're like no it's going to rot your brain man like no it's going to rot your brain man like no it's going to rot your brain man you can't do that you know so like you can't do that you know so like you can't do that you know so like there's always every era is in a panic there's always every era is in a panic there's always every era is in a panic and you know oh you're copy pasting code and you know oh you're copy pasting code and you know oh you're copy pasting code directly from stack overflow into directly from stack overflow into directly from stack overflow into production don't do that uh recently production don't do that uh recently production don't do that uh recently anthropic announced the claude c anthropic announced the claude c anthropic announced the claude c compiler and you did a blog post about compiler and you did a blog post about compiler and you did a blog post about this just literally today as of the this just literally today as of the this just literally today as of the record or yesterday rather the recording record or yesterday rather the recording record or yesterday rather the recording of uh this this um this podcast and I I of uh this this um this podcast and I I of uh this this um this podcast and I I think we have similar takes on it like think we have similar takes on it like think we have similar takes on it like you said it's an AI building a C you said it's an AI building a C you said it's an AI building a C compiler is not revolutionary but it compiler is not revolutionary but it compiler is not revolutionary but it does tell us about like where AI is does tell us about like where AI is does tell us about like where AI is right now and where it's heading.

right now and where it's heading. right now and where it's heading. >> Yeah. Well, so when when I bubble out >> Yeah. Well, so when when I bubble out >> Yeah. Well, so when when I bubble out and just to plus one your humans don't and just to plus one your humans don't and just to plus one your humans don't like change. So when when I was building like change. So when when I was building like change. So when when I was building Swift, when we came out with Swift, Swift, when we came out with Swift, Swift, when we came out with Swift, there was a really interesting aha there was a really interesting aha there was a really interesting aha moment for me that I didn't really moment for me that I didn't really moment for me that I didn't really expect. So when we launched Swift, uh expect. So when we launched Swift, uh expect. So when we launched Swift, uh just contextualized, only about 250 just contextualized, only about 250 just contextualized, only about 250 people in the world knew about it. And people in the world knew about it. And people in the world knew about it. And so because of Apple secrecy, it turns so because of Apple secrecy, it turns so because of Apple secrecy, it turns out most of the software engineers out most of the software engineers out most of the software engineers within Apple had no clue. And then it within Apple had no clue. And then it within Apple had no clue. And then it went from not even being on their radar went from not even being on their radar went from not even being on their radar to what Apple's switching to a new to what Apple's switching to a new to what Apple's switching to a new language. And it was just a big head language. And it was just a big head language. And it was just a big head exploding moment for a bunch of people. exploding moment for a bunch of people. exploding moment for a bunch of people. That was fun. Um, but the thing I didn't That was fun. Um, but the thing I didn't That was fun. Um, but the thing I didn't expect was that uh the existing expect was that uh the existing expect was that uh the existing community really resisted it. community really resisted it. community really resisted it. >> Not everybody, but particularly the >> Not everybody, but particularly the >> Not everybody, but particularly the people that were super expert at people that were super expert at people that were super expert at Objective C. They really did not want a Objective C. They really did not want a Objective C. They really did not want a new thing to come onto the scene because new thing to come onto the scene because new thing to come onto the scene because they were experts. They they really they were experts. They they really they were experts. They they really understood how to use the existing understood how to use the existing understood how to use the existing tools. Uh, people came to them. They had tools. Uh, people came to them. They had tools. Uh, people came to them. They had built their careers as being the guru. built their careers as being the guru. built their careers as being the guru. And so getting reset back to the same And so getting reset back to the same And so getting reset back to the same starting point as everybody else, being starting point as everybody else, being starting point as everybody else, being a Swift newbie, was not something that a Swift newbie, was not something that a Swift newbie, was not something that they wanted. And um on the flip side, they wanted. And um on the flip side, they wanted. And um on the flip side, people coming to Apple Platforms for the people coming to Apple Platforms for the people coming to Apple Platforms for the first time or people that had been in first time or people that had been in first time or people that had been in for 6 months or something like that are for 6 months or something like that are for 6 months or something like that are like, "Oh, thank goodness. Now I can like, "Oh, thank goodness. Now I can like, "Oh, thank goodness. Now I can actually do way more. It's so much actually do way more. It's so much actually do way more. It's so much easier. I can grow and scale faster. Now easier. I can grow and scale faster. Now easier. I can grow and scale faster. Now I can close the gap with uh the I can close the gap with uh the I can close the gap with uh the experienced people." And I and it's not experienced people." And I and it's not experienced people." And I and it's not that they're against the experienced that they're against the experienced that they're against the experienced people, but they're just they want to people, but they're just they want to people, but they're just they want to get more done. I see that pattern get more done. I see that pattern get more done. I see that pattern playing out exactly today, right? Where playing out exactly today, right? Where playing out exactly today, right? Where you have a lot of people that are taking you have a lot of people that are taking you have a lot of people that are taking these very diametrically opposed these very diametrically opposed these very diametrically opposed opinions. either AI is completely

opinions. either AI is completely opinions. either AI is completely nonsense or oh my god we're all doomed nonsense or oh my god we're all doomed nonsense or oh my god we're all doomed but really there's a middle path like but really there's a middle path like but really there's a middle path like neither neither of those is right. It's neither neither of those is right. It's neither neither of those is right. It's not that we're all doomed because of AI. not that we're all doomed because of AI. not that we're all doomed because of AI. It's not it's not that uh AI is stupid. It's not it's not that uh AI is stupid. It's not it's not that uh AI is stupid. The question is we have these amazingly The question is we have these amazingly The question is we have these amazingly powerful tools. How do we use them? And powerful tools. How do we use them? And powerful tools. How do we use them? And some people will deny them and say okay some people will deny them and say okay some people will deny them and say okay well this is nonsense. But other people well this is nonsense. But other people well this is nonsense. But other people will upskill very quickly. and the will upskill very quickly. and the will upskill very quickly. and the people that adopt the tools and figure people that adopt the tools and figure people that adopt the tools and figure out the best ways to use them. Figure out the best ways to use them. Figure out the best ways to use them. Figure out both AI the good way to use it and out both AI the good way to use it and out both AI the good way to use it and not the bad way to use it because a lot not the bad way to use it because a lot not the bad way to use it because a lot there's a lot of learning that we have there's a lot of learning that we have there's a lot of learning that we have to do like those those are the folks I to do like those those are the folks I to do like those those are the folks I think that will uh grow quickly that think that will uh grow quickly that think that will uh grow quickly that will have new opportunities and that will have new opportunities and that will have new opportunities and that their careers will be progreg but this one is so obviously profound um but this one is so obviously profound um it becomes a new tool it's just like it becomes a new tool it's just like it becomes a new tool it's just like source control 20 years ago or source control 20 years ago or source control 20 years ago or something. Yeah. Profound for all things something. Yeah. Profound for all things something. Yeah. Profound for all things or profound for software engineering or or profound for software engineering or or profound for software engineering or do you have different levels of do you have different levels of do you have different levels of >> Yeah. The art of software engineering >> Yeah. The art of software engineering >> Yeah. The art of software engineering and I think that you and I love building and I think that you and I love building and I think that you and I love building things, right? And so the the um I don't things, right? And so the the um I don't things, right? And so the the um I don't see building software as writing code, see building software as writing code, see building software as writing code, right? Writing code is one thing. That's right? Writing code is one thing. That's right? Writing code is one thing. That's that is that is an issue and a lot of that is that is an issue and a lot of that is that is an issue and a lot of people struggle with that. I'm at the people struggle with that. I'm at the people struggle with that. I'm at the phase where I have flow moments of phase where I have flow moments of phase where I have flow moments of writing code. Like code the syntax like writing code. Like code the syntax like writing code. Like code the syntax like the the art of like hacking stuff out on the the art of like hacking stuff out on the the art of like hacking stuff out on a keyboard isn't actually a challenge a keyboard isn't actually a challenge a keyboard isn't actually a challenge for me. Um, which good news, I'm a for me. Um, which good news, I'm a for me. Um, which good news, I'm a senior developer or something. Uh, but senior developer or something. Uh, but senior developer or something. Uh, but but that's not true for everybody, but that's not true for everybody, but that's not true for everybody, right? And so again, I think that a lot right? And so again, I think that a lot right? And so again, I think that a lot of people associate

of people associate of people associate coding with the writing of code. But coding with the writing of code. But coding with the writing of code. But when you bubble out and you think about when you bubble out and you think about when you bubble out and you think about um what are we trying to achieve, um what are we trying to achieve, um what are we trying to achieve, >> what are we building? Why? What does >> what are we building? Why? What does >> what are we building? Why? What does better look like? What does the better look like? What does the better look like? What does the architecture look like? What does good architecture look like? What does good architecture look like? What does good design look like? These questions are design look like? These questions are design look like? These questions are things that I think are purely human. things that I think are purely human. things that I think are purely human. They they are something that we are in They they are something that we are in They they are something that we are in innately responsible for and I think innately responsible for and I think innately responsible for and I think that a lot of people again the that a lot of people again the that a lot of people again the extremists say oh well when AI means you extremists say oh well when AI means you extremists say oh well when AI means you don't have to know how anything works don't have to know how anything works don't have to know how anything works right the AI will just write the machine right the AI will just write the machine right the AI will just write the machine code for you when AGI happens all this code for you when AGI happens all this code for you when AGI happens all this stuff blah blah blah blah blah like that stuff blah blah blah blah blah like that stuff blah blah blah blah blah like that train of thought completely dismisses train of thought completely dismisses train of thought completely dismisses the fact that it has not happened and it the fact that it has not happened and it the fact that it has not happened and it may not happen and so I like to live in may not happen and so I like to live in may not happen and so I like to live in the real world and so the way I kind of the real world and so the way I kind of the real world and so the way I kind of contextualize and look at this moment contextualize and look at this moment contextualize and look at this moment that we're in is how do we best use this that we're in is how do we best use this that we're in is how do we best use this technology right? Because it is technology right? Because it is technology right? Because it is profound. It does allow us to accelerate profound. It does allow us to accelerate profound. It does allow us to accelerate a ton of stuff. As an experienced coder, a ton of stuff. As an experienced coder, a ton of stuff. As an experienced coder, it means I can get out of doing a lot of it means I can get out of doing a lot of it means I can get out of doing a lot of the boilerplate mechanical stuff, but the boilerplate mechanical stuff, but the boilerplate mechanical stuff, but for other people that are earlier in for other people that are earlier in for other people that are earlier in their journey, it means that they can be their journey, it means that they can be their journey, it means that they can be way more productive and can close a lot way more productive and can close a lot way more productive and can close a lot of gaps. So, of gaps. So, of gaps. So, >> yeah, I I I was I think about it in the >> yeah, I I I was I think about it in the >> yeah, I I I was I think about it in the context of if you come at this with code context of if you come at this with code context of if you come at this with code is art and the AI is stealing my art is art and the AI is stealing my art is art and the AI is stealing my art from me, that would hurt a certain way.

from me, that would hurt a certain way. from me, that would hurt a certain way. Um, I don't like AI generated images. Um, I don't like AI generated images. Um, I don't like AI generated images. because I don't like AI generated video because I don't like AI generated video because I don't like AI generated video and I would not use an AI to generate and I would not use an AI to generate and I would not use an AI to generate poetry. poetry. poetry. So if but if the job of poetry is to So if but if the job of poetry is to So if but if the job of poetry is to evoke emotion then I could see where one evoke emotion then I could see where one evoke emotion then I could see where one could argue in some philosophy you know could argue in some philosophy you know could argue in some philosophy you know 2011 class that like well I evoked an 2011 class that like well I evoked an 2011 class that like well I evoked an emotion doesn't really matter how I did emotion doesn't really matter how I did emotion doesn't really matter how I did it that doesn't that's not the purpose it that doesn't that's not the purpose it that doesn't that's not the purpose of poetry in my opinion of poetry in my opinion of poetry in my opinion >> well it depends on your goal and I can't >> well it depends on your goal and I can't >> well it depends on your goal and I can't say that everybody's goal is the same say that everybody's goal is the same say that everybody's goal is the same right but is your [clears throat] goal right but is your [clears throat] goal right but is your [clears throat] goal of writing poetry to get paid for it if of writing poetry to get paid for it if of writing poetry to get paid for it if so then accelerating the production of so then accelerating the production of so then accelerating the production of poetry is probably a good thing poetry is probably a good thing poetry is probably a good thing >> but isn't that poetry slop [laughter] >> but isn't that poetry slop [laughter] >> but isn't that poetry slop [laughter] >> but if if the goal if the goal of >> but if if the goal if the goal of >> but if if the goal if the goal of writing poetry is to enjoy enjoy the art writing poetry is to enjoy enjoy the art writing poetry is to enjoy enjoy the art of building and discovering and making of building and discovering and making of building and discovering and making the poetry, then that's like saying, the poetry, then that's like saying, the poetry, then that's like saying, "Hey, Scott is a woodworker." Like using "Hey, Scott is a woodworker." Like using "Hey, Scott is a woodworker." Like using a hand plane is like actually a very a hand plane is like actually a very a hand plane is like actually a very fulfilling thing to do. Probably not fulfilling thing to do. Probably not fulfilling thing to do. Probably not what you're going to do in a cabinet what you're going to do in a cabinet what you're going to do in a cabinet shop where you're volume producing shop where you're volume producing shop where you're volume producing things, right? But it doesn't mean that things, right? But it doesn't mean that things, right? But it doesn't mean that one is good or the other's bad. It's one is good or the other's bad. It's one is good or the other's bad. It's about what is the right tool for the about what is the right tool for the about what is the right tool for the job, job, job, >> right? And then that's where things get >> right? And then that's where things get >> right? And then that's where things get get artificially broken down into ones get artificially broken down into ones get artificially broken down into ones and zeros. And by ones and zeros, I mean and zeros. And by ones and zeros, I mean and zeros. And by ones and zeros, I mean there's either IKEA or there's the there's either IKEA or there's the there's either IKEA or there's the Yankee Workshop and there's nothing in Yankee Workshop and there's nothing in Yankee Workshop and there's nothing in between or it's like code is poetry or between or it's like code is poetry or between or it's like code is poetry or it's AI slop and there's nothing in it's AI slop and there's nothing in it's AI slop and there's nothing in between.

between. between. >> Well, and so I think that the thing that >> Well, and so I think that the thing that >> Well, and so I think that the thing that we're both channeling is that we're both we're both channeling is that we're both we're both channeling is that we're both artists when it comes to code like artists when it comes to code like artists when it comes to code like >> Yeah, for sure. >> Yeah, for sure. >> Yeah, for sure. >> Yeah. And we care about the the craft >> Yeah. And we care about the the craft >> Yeah. And we care about the the craft and and things like this. and and things like this. and and things like this. >> I care about that for two different >> I care about that for two different >> I care about that for two different reasons actually. One is um and this is reasons actually. One is um and this is reasons actually. One is um and this is something I think that people hugely something I think that people hugely something I think that people hugely gloss over in the AI discussion is that gloss over in the AI discussion is that gloss over in the AI discussion is that um outcomes are not the only thing that um outcomes are not the only thing that um outcomes are not the only thing that matters. It turns out that in my opinion matters. It turns out that in my opinion matters. It turns out that in my opinion building a software artifact, building building a software artifact, building building a software artifact, building something in code is not about solving something in code is not about solving something in code is not about solving today's problem. It's about building an today's problem. It's about building an today's problem. It's about building an investment in a technology. And the investment in a technology. And the investment in a technology. And the thing that's always true about software thing that's always true about software thing that's always true about software is that the the requirements change all is that the the requirements change all is that the the requirements change all the time. And so what you need is you the time. And so what you need is you the time. And so what you need is you need both to have the outcome, but then need both to have the outcome, but then need both to have the outcome, but then you also need to be able to move it you also need to be able to move it you also need to be able to move it quickly, adapt to change, add new quickly, adapt to change, add new quickly, adapt to change, add new features, uh move into the new economy, features, uh move into the new economy, features, uh move into the new economy, add the mobile features, like what add the mobile features, like what add the mobile features, like what whatever the thing is that you're doing, whatever the thing is that you're doing, whatever the thing is that you're doing, right? And so to do that, you need not right? And so to do that, you need not right? And so to do that, you need not just uh an outcome oriented, okay, the just uh an outcome oriented, okay, the just uh an outcome oriented, okay, the the code appears to pass the unit test, the code appears to pass the unit test, the code appears to pass the unit test, but you need people that can manage but you need people that can manage but you need people that can manage that, that can work with it, that can that, that can work with it, that can that, that can work with it, that can understand the considerations, that can understand the considerations, that can understand the considerations, that can make good judgment about where to invest make good judgment about where to invest make good judgment about where to invest and how to achieve things. And for that and how to achieve things. And for that and how to achieve things. And for that you need a really visceral kind of you need a really visceral kind of you need a really visceral kind of understanding of how stuff works. Um I understanding of how stuff works. Um I understanding of how stuff works. Um I think the AI and again this this gets think the AI and again this this gets think the AI and again this this gets back into the AI is very powerful but back into the AI is very powerful but back into the AI is very powerful but it's a tool. Um it can encourage really it's a tool. Um it can encourage really it's a tool. Um it can encourage really sloppy work. It can encourage laziness.

sloppy work. It can encourage laziness. sloppy work. It can encourage laziness. It can encourage a lot of really bad It can encourage a lot of really bad It can encourage a lot of really bad things. I think that we we as a team it things. I think that we we as a team it things. I think that we we as a team it can it can certainly encourage people can it can certainly encourage people can it can certainly encourage people wasting other people's time on the team. wasting other people's time on the team. wasting other people's time on the team. >> I've coded this thing go review it for >> I've coded this thing go review it for >> I've coded this thing go review it for me. Right? That's that's not actually a me. Right? That's that's not actually a me. Right? That's that's not actually a good outcome. And so I think we need to good outcome. And so I think we need to good outcome. And so I think we need to figure out how to best use these tools. figure out how to best use these tools. figure out how to best use these tools. >> Okay. So putting all of this into the >> Okay. So putting all of this into the >> Okay. So putting all of this into the context of this the C compiler which you context of this the C compiler which you context of this the C compiler which you again wrote about recently. You call out again wrote about recently. You call out again wrote about recently. You call out a lot of things that I very much agree a lot of things that I very much agree a lot of things that I very much agree with like good software depends on with like good software depends on with like good software depends on judgment. It feels like human judgment judgment. It feels like human judgment judgment. It feels like human judgment is the only thing that matters right now is the only thing that matters right now is the only thing that matters right now and you know good taste or code smell as and you know good taste or code smell as and you know good taste or code smell as we would have called it in the past we would have called it in the past we would have called it in the past matters. Is uh I'll just ask you out out matters. Is uh I'll just ask you out out matters. Is uh I'll just ask you out out straight. Is this a good C compiler? Did straight. Is this a good C compiler? Did straight. Is this a good C compiler? Did they just oneshot a C compiler or is it they just oneshot a C compiler or is it they just oneshot a C compiler or is it a little more nuanced than that? Cuz a little more nuanced than that? Cuz a little more nuanced than that? Cuz it's a long article you wrote. it's a long article you wrote. it's a long article you wrote. >> Yeah. Well, so it's not a oneshot C >> Yeah. Well, so it's not a oneshot C >> Yeah. Well, so it's not a oneshot C compiler. Uh they burn $10,000 worth of compiler. Uh they burn $10,000 worth of compiler. Uh they burn $10,000 worth of tokens over the course of two weeks. And tokens over the course of two weeks. And tokens over the course of two weeks. And so it's definitely a a very agent swarm so it's definitely a a very agent swarm so it's definitely a a very agent swarm iterative thing, right? And if you look iterative thing, right? And if you look iterative thing, right? And if you look at this kind of agent swarm building at this kind of agent swarm building at this kind of agent swarm building against a objective function, it kind of against a objective function, it kind of against a objective function, it kind of looks like training a neural net itself.

looks like training a neural net itself. looks like training a neural net itself. Like because you have a loss function of Like because you have a loss function of Like because you have a loss function of like how many tests fail and then you're like how many tests fail and then you're like how many tests fail and then you're you're hill climbing into that. Um, is you're hill climbing into that. Um, is you're hill climbing into that. Um, is it good? Um, I think it's extremely it good? Um, I think it's extremely it good? Um, I think it's extremely impressive as what they achieved in impressive as what they achieved in impressive as what they achieved in terms of uh zero human input and proving terms of uh zero human input and proving terms of uh zero human input and proving that you can match to an objective that you can match to an objective that you can match to an objective function. I don't consider that to be function. I don't consider that to be function. I don't consider that to be wildly surprising. That's what AI is wildly surprising. That's what AI is wildly surprising. That's what AI is good for. Like in if you look at what good for. Like in if you look at what good for. Like in if you look at what happened, it basically transcoded LVM, happened, it basically transcoded LVM, happened, it basically transcoded LVM, GCC, other C compilers that it has in GCC, other C compilers that it has in GCC, other C compilers that it has in its training set into Rust. And so it its training set into Rust. And so it its training set into Rust. And so it uses the language translation abilities uses the language translation abilities uses the language translation abilities of transformers very effectively. But of transformers very effectively. But of transformers very effectively. But again, no is good at that. again, no is good at that. again, no is good at that. >> I didn't see anything novel. I didn't >> I didn't see anything novel. I didn't >> I didn't see anything novel. I didn't see anything where I'm like, "Wow, see anything where I'm like, "Wow, see anything where I'm like, "Wow, that's a good idea." that's a good idea." that's a good idea." >> But doesn't that make sense, though? >> But doesn't that make sense, though? >> But doesn't that make sense, though? Because I did a I've been using it. Um Because I did a I've been using it. Um Because I did a I've been using it. Um like everyone knows that Claude, as an like everyone knows that Claude, as an like everyone knows that Claude, as an example, in Opus makes websites of a example, in Opus makes websites of a example, in Opus makes websites of a certain style. So I skinned a couple of certain style. So I skinned a couple of certain style. So I skinned a couple of my websites and you can see the kind of my websites and you can see the kind of my websites and you can see the kind of pieces of Claude where it's like, "Oh, pieces of Claude where it's like, "Oh, pieces of Claude where it's like, "Oh, they love a a text gradient and their they love a a text gradient and their they love a a text gradient and their their light modes and their dark modes their light modes and their dark modes their light modes and their dark modes look the same." And I asked my son about look the same." And I asked my son about look the same." And I asked my son about my website and he says it looks mid cuz my website and he says it looks mid cuz my website and he says it looks mid cuz he's young and everything's mid when he's young and everything's mid when he's young and everything's mid when you're 18. And but mid is the you're 18. And but mid is the you're 18. And but mid is the statistical fat part of the bell curve.

statistical fat part of the bell curve. statistical fat part of the bell curve. So people are like, "Oh man, they stole So people are like, "Oh man, they stole So people are like, "Oh man, they stole they stole Latler's LLVM and they stole they stole Latler's LLVM and they stole they stole Latler's LLVM and they stole some GCC code. It's total ripoff." And some GCC code. It's total ripoff." And some GCC code. It's total ripoff." And it's like, well, no, it's it's the one it's like, well, no, it's it's the one it's like, well, no, it's it's the one that we all use. Like I would look at it that we all use. Like I would look at it that we all use. Like I would look at it if I were to do a compiler tomorrow. if I were to do a compiler tomorrow. if I were to do a compiler tomorrow. Like it's mid, not in a bad way, in the Like it's mid, not in a bad way, in the Like it's mid, not in a bad way, in the fat part of the bell curve way. It's fat part of the bell curve way. It's fat part of the bell curve way. It's expected. You would have been surprised expected. You would have been surprised expected. You would have been surprised if it had come up with something novel if it had come up with something novel if it had come up with something novel >> because it's not trained on novel. It's >> because it's not trained on novel. It's >> because it's not trained on novel. It's trained on the standard. trained on the standard. trained on the standard. >> Well, absolutely. I completely agree >> Well, absolutely. I completely agree >> Well, absolutely. I completely agree with you and I both agree with you and with you and I both agree with you and with you and I both agree with you and then I'll lean in further, right, which then I'll lean in further, right, which then I'll lean in further, right, which is AI and LLMs are distribution is AI and LLMs are distribution is AI and LLMs are distribution followers, followers, followers, right? And so they're finding that right? And so they're finding that right? And so they're finding that midpoint in the distribution and they midpoint in the distribution and they midpoint in the distribution and they can rapidly follow that. Um they can do can rapidly follow that. Um they can do can rapidly follow that. Um they can do some air quote innovative stuff in some air quote innovative stuff in some air quote innovative stuff in limited spaces, but um but really that's limited spaces, but um but really that's limited spaces, but um but really that's what they're designed for. But let me what they're designed for. But let me what they're designed for. But let me also give you another hot take. LVM like also give you another hot take. LVM like also give you another hot take. LVM like it's a good thing. I'm a fan. Uh but it's a good thing. I'm a fan. Uh but it's a good thing. I'm a fan. Uh but it's also 25 years old and not a great it's also 25 years old and not a great it's also 25 years old and not a great thing, right? And so following thing, right? And so following thing, right? And so following >> 25 years old compiler technology is >> 25 years old compiler technology is >> 25 years old compiler technology is actually not even that awesome. LVM is actually not even that awesome. LVM is actually not even that awesome. LVM is one of the most widely understood uh one of the most widely understood uh one of the most widely understood uh compilers out there because there's so compilers out there because there's so compilers out there because there's so many people working on it and it gets many people working on it and it gets many people working on it and it gets used in a lot of ways, but that doesn't used in a lot of ways, but that doesn't used in a lot of ways, but that doesn't make it the best. And so I've been make it the best. And so I've been make it the best. And so I've been working on a lot of new compilers since working on a lot of new compilers since working on a lot of new compilers since then that are way better.

then that are way better. then that are way better. >> Okay. So that's a great >> Okay. So that's a great >> Okay. So that's a great >> also very interesting to see that. >> also very interesting to see that. >> also very interesting to see that. >> Yeah. Because there's a mid bias and >> Yeah. Because there's a mid bias and >> Yeah. Because there's a mid bias and it's like yes I'm going to use the last it's like yes I'm going to use the last it's like yes I'm going to use the last 25 years of work but is it interesting 25 years of work but is it interesting 25 years of work but is it interesting that it didn't discover and think about that it didn't discover and think about that it didn't discover and think about mojo and the work that you're doing mojo and the work that you're doing mojo and the work that you're doing there and why did it there and why did it there and why did it >> or ML or these things that are much more >> or ML or these things that are much more >> or ML or these things that are much more new and this is also where it's very new and this is also where it's very new and this is also where it's very funny. uh the LVM community is actively funny. uh the LVM community is actively funny. uh the LVM community is actively working on getting rid of this thing working on getting rid of this thing working on getting rid of this thing called get element pointer out of LVM called get element pointer out of LVM called get element pointer out of LVM >> and so it's totally in the design for >> and so it's totally in the design for >> and so it's totally in the design for the cloud C compiler and so again this the cloud C compiler and so again this the cloud C compiler and so again this uh you can project forward and say well uh you can project forward and say well uh you can project forward and say well teams that proactively and actively teams that proactively and actively teams that proactively and actively adopt LLM based codegen adopt LLM based codegen adopt LLM based codegen >> in the absence of judgment right are >> in the absence of judgment right are >> in the absence of judgment right are they actually going to be held back they actually going to be held back they actually going to be held back >> right because they're not even going to >> right because they're not even going to >> right because they're not even going to be at the forefront of tech they're be at the forefront of tech they're be at the forefront of tech they're going to be I don't know probably not 25 going to be I don't know probably not 25 going to be I don't know probably not 25 years behind But they're going to be uh years behind But they're going to be uh years behind But they're going to be uh not not getting the best technology and not not getting the best technology and not not getting the best technology and the best outcome for the product. the best outcome for the product. the best outcome for the product. >> Yeah. >> Yeah. >> Yeah. >> Now, I think the mediator on that is >> Now, I think the mediator on that is >> Now, I think the mediator on that is that not all software needs to be quote that not all software needs to be quote that not all software needs to be quote the best or the industry leader. It just the best or the industry leader. It just the best or the industry leader. It just needs to be effective. And so there's needs to be effective. And so there's needs to be effective. And so there's probably space for all these things.

probably space for all these things. probably space for all these things. >> Yeah. And there's arguably like they had >> Yeah. And there's arguably like they had >> Yeah. And there's arguably like they had a very well understood uh goal. they had a very well understood uh goal. they had a very well understood uh goal. they had a tests laid out like making one like a tests laid out like making one like a tests laid out like making one like you said in your blog post that it's you said in your blog post that it's you said in your blog post that it's something that a good quality team of something that a good quality team of something that a good quality team of undergraduates would come together and undergraduates would come together and undergraduates would come together and get a B on or something like that like get a B on or something like that like get a B on or something like that like it's pretty pretty decent it's pretty pretty decent it's pretty pretty decent >> they'd probably get an A. It is it is >> they'd probably get an A. It is it is >> they'd probably get an A. It is it is quite a lot of work but quite a lot of work but quite a lot of work but >> but um but yeah I mean I think it's it's >> but um but yeah I mean I think it's it's >> but um but yeah I mean I think it's it's super interesting as an artifact. Um but super interesting as an artifact. Um but super interesting as an artifact. Um but this is also where when people jump to this is also where when people jump to this is also where when people jump to it's the end of times and humans are it's the end of times and humans are it's the end of times and humans are obsolete and things like this that's obsolete and things like this that's obsolete and things like this that's obviously a hyperbole and it's I don't obviously a hyperbole and it's I don't obviously a hyperbole and it's I don't think it's constructive and I think it think it's constructive and I think it think it's constructive and I think it distracts from where the actual value distracts from where the actual value distracts from where the actual value is. Yeah, I think I do I do agree that is. Yeah, I think I do I do agree that is. Yeah, I think I do I do agree that every time some president or or you know every time some president or or you know every time some president or or you know some billionaire person says, "Oh, yeah, some billionaire person says, "Oh, yeah, some billionaire person says, "Oh, yeah, all all these jobs will be gone in 12 all all these jobs will be gone in 12 all all these jobs will be gone in 12 months." That's probably not helpful for months." That's probably not helpful for months." That's probably not helpful for anyone to be saying stuff like that. anyone to be saying stuff like that. anyone to be saying stuff like that. >> Yeah, it's well and it's not backed up >> Yeah, it's well and it's not backed up >> Yeah, it's well and it's not backed up by data. Yeah. by data. Yeah. by data. Yeah. >> Right. I mean, there are more >> Right. I mean, there are more >> Right. I mean, there are more programmers now than ever. Um the job programmers now than ever. Um the job programmers now than ever. Um the job market is actually quite hot. It's a lot market is actually quite hot. It's a lot market is actually quite hot. It's a lot of people are scared and there's a lot of people are scared and there's a lot of people are scared and there's a lot of questions, right? But um it's more of questions, right? But um it's more of questions, right? But um it's more about projecting forward. And so this is about projecting forward. And so this is about projecting forward. And so this is also the question of like okay when AGI also the question of like okay when AGI also the question of like okay when AGI happens dot dot dot well you can you can happens dot dot dot well you can you can happens dot dot dot well you can you can you can speculate whatever you want but you can speculate whatever you want but you can speculate whatever you want but AGI hasn't happened and nobody can even AGI hasn't happened and nobody can even AGI hasn't happened and nobody can even define AGI so I I think that there's a define AGI so I I think that there's a define AGI so I I think that there's a lot of work to be done between now and lot of work to be done between now and lot of work to be done between now and that theoretical future.

that theoretical future. that theoretical future. >> Yeah. And will next token prediction and >> Yeah. And will next token prediction and >> Yeah. And will next token prediction and all the things behind it lead us into all the things behind it lead us into all the things behind it lead us into like a really smart fella or you know like a really smart fella or you know like a really smart fella or you know gal that's like we can talk to gal that's like we can talk to gal that's like we can talk to >> but also I mean again I look at AI as >> but also I mean again I look at AI as >> but also I mean again I look at AI as closing gaps right? If you don't know closing gaps right? If you don't know closing gaps right? If you don't know what rate radic sort is or some exotic what rate radic sort is or some exotic what rate radic sort is or some exotic data structure or something like that data structure or something like that data structure or something like that you don't know what a b tree is um well you don't know what a b tree is um well you don't know what a b tree is um well cool like you can say hey AI like I have cool like you can say hey AI like I have cool like you can say hey AI like I have this problem what is the best way to this problem what is the best way to this problem what is the best way to solve it and it can come up with some solve it and it can come up with some solve it and it can come up with some exotic data structure and maybe you have exotic data structure and maybe you have exotic data structure and maybe you have no idea and it magically lifts you and no idea and it magically lifts you and no idea and it magically lifts you and fills in something that you didn't know fills in something that you didn't know fills in something that you didn't know and that's incredibly powerful that can and that's incredibly powerful that can and that's incredibly powerful that can lead to much better software and so it's lead to much better software and so it's lead to much better software and so it's not BS right but it's also not magic and not BS right but it's also not magic and not BS right but it's also not magic and so like that's the nuance you have to so like that's the nuance you have to so like that's the nuance you have to fight fight fight >> well that's a great point like I'd like >> well that's a great point like I'd like >> well that's a great point like I'd like to always abuse um Arthur C. Clark and to always abuse um Arthur C. Clark and to always abuse um Arthur C. Clark and say that like each additional layer of say that like each additional layer of say that like each additional layer of abstraction is indistinguishable from abstraction is indistinguishable from abstraction is indistinguishable from magic. And like the stack is pretty deep magic. And like the stack is pretty deep magic. And like the stack is pretty deep now. And if you're a if you're a React now. And if you're a if you're a React now. And if you're a if you're a React programmer, the world's magic for you. programmer, the world's magic for you. programmer, the world's magic for you. And like maybe you don't even know that And like maybe you don't even know that And like maybe you don't even know that V8 exists as a concept. And you know, V8 exists as a concept. And you know, V8 exists as a concept. And you know, people tease me for my Altars and my people tease me for my Altars and my people tease me for my Altars and my PDP11s, but it's a way of staying PDP11s, but it's a way of staying PDP11s, but it's a way of staying grounded just as you going and wood grounded just as you going and wood grounded just as you going and wood working on woodworking as opposed to working on woodworking as opposed to working on woodworking as opposed to going to IKEA is a way of you being going to IKEA is a way of you being going to IKEA is a way of you being grounded. That's grounded. That's grounded. That's >> right.

>> right. >> right. >> As well. >> As well. >> As well. >> Well, the analog world's also pretty >> Well, the analog world's also pretty >> Well, the analog world's also pretty cool. So pretty. cool. So pretty. cool. So pretty. >> Knowing how things work is pretty cool, >> Knowing how things work is pretty cool, >> Knowing how things work is pretty cool, too. So, too. So, too. So, >> and everything's a conspiracy when you >> and everything's a conspiracy when you >> and everything's a conspiracy when you don't know how things work. Um, one don't know how things work. Um, one don't know how things work. Um, one other thing that's I think worth noting, other thing that's I think worth noting, other thing that's I think worth noting, of course, is that they they targeted of course, is that they they targeted of course, is that they they targeted CPUs, but I know that you believe that CPUs, but I know that you believe that CPUs, but I know that you believe that we're not necessarily in a CPUcentric we're not necessarily in a CPUcentric we're not necessarily in a CPUcentric world right now and that we've got these world right now and that we've got these world right now and that we've got these perfectly chromulent GPUs that are out perfectly chromulent GPUs that are out perfectly chromulent GPUs that are out there and so few ways to talk to them, there and so few ways to talk to them, there and so few ways to talk to them, but uh you're going to crack that. but uh you're going to crack that. but uh you're going to crack that. >> Yeah. So, I mean, if you extrapolate >> Yeah. So, I mean, if you extrapolate >> Yeah. So, I mean, if you extrapolate even more, like forget about AI, go back even more, like forget about AI, go back even more, like forget about AI, go back to humans. Um because I I I'm I admit to humans. Um because I I I'm I admit to humans. Um because I I I'm I admit I'm kind of fond of humans. I don't know I'm kind of fond of humans. I don't know I'm kind of fond of humans. I don't know about you. I think humans are actually about you. I think humans are actually about you. I think humans are actually the more the more important thing here, the more the more important thing here, the more the more important thing here, particularly at R at large. particularly at R at large. particularly at R at large. >> Um so many humans are worried about >> Um so many humans are worried about >> Um so many humans are worried about CPUs. CPUs are cool. They're very CPUs. CPUs are cool. They're very CPUs. CPUs are cool. They're very important. Like they run a ton of important. Like they run a ton of important. Like they run a ton of compute, but that's not where the compute, but that's not where the compute, but that's not where the billions of dollars of capex are going. billions of dollars of capex are going. billions of dollars of capex are going. That's not where uh all the big That's not where uh all the big That's not where uh all the big developments are happening. And what's developments are happening. And what's developments are happening. And what's happened is that, you know, kind of you happened is that, you know, kind of you happened is that, you know, kind of you can peg it in different ways, but Moors can peg it in different ways, but Moors can peg it in different ways, but Moors law ended, right? We're not getting free law ended, right? We're not getting free law ended, right? We're not getting free single core, single thread CPU single core, single thread CPU single core, single thread CPU performance like we used to back in the performance like we used to back in the performance like we used to back in the day.

day. day. >> Yeah. >> Yeah. >> Yeah. >> And so we went from single core machines >> And so we went from single core machines >> And so we went from single core machines to, you know, two cores or four cores. to, you know, two cores or four cores. to, you know, two cores or four cores. You know, now a cell phone has eight You know, now a cell phone has eight You know, now a cell phone has eight cores. Woohoo. But now you have GPUs cores. Woohoo. But now you have GPUs cores. Woohoo. But now you have GPUs with hundreds or thousands of cores. You with hundreds or thousands of cores. You with hundreds or thousands of cores. You have A6 that are designed for specific have A6 that are designed for specific have A6 that are designed for specific workloads. And let me tell you, Rust workloads. And let me tell you, Rust workloads. And let me tell you, Rust does not run on a cerebrous system, does not run on a cerebrous system, does not run on a cerebrous system, [laughter] right? That's not a thing. [laughter] right? That's not a thing. [laughter] right? That's not a thing. And so to me, I think it's really And so to me, I think it's really And so to me, I think it's really interesting. And you go back to the 2016 interesting. And you go back to the 2016 interesting. And you go back to the 2016 2017 time for me it wasn't just about AI 2017 time for me it wasn't just about AI 2017 time for me it wasn't just about AI is interesting. It became a well how do is interesting. It became a well how do is interesting. It became a well how do you do this effectively? And I you know you do this effectively? And I you know you do this effectively? And I you know got AI pill back in the day because of got AI pill back in the day because of got AI pill back in the day because of the things that only AI could do back the things that only AI could do back the things that only AI could do back then. You know started by seeing dogs then. You know started by seeing dogs then. You know started by seeing dogs and cats. Um but then it turned into and cats. Um but then it turned into and cats. Um but then it turned into this really interesting form of compute. this really interesting form of compute. this really interesting form of compute. And one of the things that I think is And one of the things that I think is And one of the things that I think is just sitting there in plain sight that just sitting there in plain sight that just sitting there in plain sight that I'm looking at all day long that very I'm looking at all day long that very I'm looking at all day long that very few other people see is that well few other people see is that well few other people see is that well rewriting CC code into Rust might be rewriting CC code into Rust might be rewriting CC code into Rust might be fun, right? But that's not actually fun, right? But that's not actually fun, right? But that's not actually moving the world forward. Meanwhile, we moving the world forward. Meanwhile, we moving the world forward. Meanwhile, we have all these crazy GPUs and all this have all these crazy GPUs and all this have all these crazy GPUs and all this compute out there that nobody knows how compute out there that nobody knows how compute out there that nobody knows how to program. And so to me, my mission, to program. And so to me, my mission, to program. And so to me, my mission, current mission is saying like, let's current mission is saying like, let's current mission is saying like, let's crack that open. Let's make it so it's crack that open. Let's make it so it's crack that open. Let's make it so it's way more accessible. Let's make it so way more accessible. Let's make it so way more accessible. Let's make it so that the tools are actually a joy to that the tools are actually a joy to that the tools are actually a joy to use. And by the way, even CPUs are crazy use. And by the way, even CPUs are crazy use. And by the way, even CPUs are crazy complicated vector SIMD. They have complicated vector SIMD. They have complicated vector SIMD. They have tensor cores on your CPU, all this tensor cores on your CPU, all this tensor cores on your CPU, all this stuff. And most programming languages stuff. And most programming languages stuff. And most programming languages can't even acknowledge or spell float 4 can't even acknowledge or spell float 4 can't even acknowledge or spell float 4 or float 8 or things like this. And um or float 8 or things like this. And um or float 8 or things like this. And um if you're using languages for 15 years if you're using languages for 15 years if you're using languages for 15 years ago, which all of uh at least Swift that

ago, which all of uh at least Swift that ago, which all of uh at least Swift that I worked on and Rust and TypeScript all I worked on and Rust and TypeScript all I worked on and Rust and TypeScript all kind of came from 2010, um well then how kind of came from 2010, um well then how kind of came from 2010, um well then how are you programming modern hardware? and are you programming modern hardware? and are you programming modern hardware? and CPUs. There's just not a good answer CPUs. There's just not a good answer CPUs. There's just not a good answer there. And so, this is where I think we there. And so, this is where I think we there. And so, this is where I think we we all uh benefit from leaning into this we all uh benefit from leaning into this we all uh benefit from leaning into this and solving this. And that's my current and solving this. And that's my current and solving this. And that's my current mission. This leads us to Mojo and mission. This leads us to Mojo and mission. This leads us to Mojo and modular and what we're doing here. modular and what we're doing here. modular and what we're doing here. >> I [snorts] hope I can ask this right >> I [snorts] hope I can ask this right >> I [snorts] hope I can ask this right because I'm trying to see the big because I'm trying to see the big because I'm trying to see the big picture in my own personal context. picture in my own personal context. picture in my own personal context. Window is still quite limited. But when Window is still quite limited. But when Window is still quite limited. But when I teased you earlier about the long con, I teased you earlier about the long con, I teased you earlier about the long con, I mean that in a positive way. by the I mean that in a positive way. by the I mean that in a positive way. by the long con. I mean, life's work is like long con. I mean, life's work is like long con. I mean, life's work is like you can kind of see down a tunnel and you can kind of see down a tunnel and you can kind of see down a tunnel and you're like, you know, you built LVM, you're like, you know, you built LVM, you're like, you know, you built LVM, you now you've got multi-level you now you've got multi-level you now you've got multi-level intermediate representation, ML. It's intermediate representation, ML. It's intermediate representation, ML. It's not the intermediate language from .NET. not the intermediate language from .NET. not the intermediate language from .NET. It's not bite code, but it's a way to It's not bite code, but it's a way to It's not bite code, but it's a way to have a hybrid intermediate language that have a hybrid intermediate language that have a hybrid intermediate language that can have different representations and can have different representations and can have different representations and also be specific to certain hardware. also be specific to certain hardware. also be specific to certain hardware. >> Yeah. So, >> Yeah. So, >> Yeah. So, did you know that you were kind of did you know that you were kind of did you know that you were kind of building these stair steps and then building these stair steps and then building these stair steps and then stepping on them and you knew what you stepping on them and you knew what you stepping on them and you knew what you were reaching for? Cuz this is a long were reaching for? Cuz this is a long were reaching for? Cuz this is a long series of steps.

series of steps. series of steps. >> I mean, 25 years goes faster than you >> I mean, 25 years goes faster than you >> I mean, 25 years goes faster than you might think. might think. might think. >> Yeah. But to look back and go, "Yeah, >> Yeah. But to look back and go, "Yeah, >> Yeah. But to look back and go, "Yeah, exactly as I planned." You know what I exactly as I planned." You know what I exactly as I planned." You know what I mean? Because you're building Mojo on mean? Because you're building Mojo on mean? Because you're building Mojo on top of MLI, which is in, you know, part top of MLI, which is in, you know, part top of MLI, which is in, you know, part of LVM, which is part of which is part of LVM, which is part of which is part of LVM, which is part of which is part of which part of like it's it's it's of which part of like it's it's it's of which part of like it's it's it's it's thoughtful turtles all the way it's thoughtful turtles all the way it's thoughtful turtles all the way down. Well, so so my journey is is down. Well, so so my journey is is down. Well, so so my journey is is how how should I say this? Like not how how should I say this? Like not how how should I say this? Like not satisfied with the status quo ever. satisfied with the status quo ever. satisfied with the status quo ever. >> Like I'm always pushing and um kind of I >> Like I'm always pushing and um kind of I >> Like I'm always pushing and um kind of I mean part of the reason I left Apple is mean part of the reason I left Apple is mean part of the reason I left Apple is I was bored, right? And it was not I was bored, right? And it was not I was bored, right? And it was not exciting and I I wanted to be learning exciting and I I wanted to be learning exciting and I I wanted to be learning and growing and doing new things and so and growing and doing new things and so and growing and doing new things and so amazing. I love the Apple team. I love amazing. I love the Apple team. I love amazing. I love the Apple team. I love my position and love swift. It's a good my position and love swift. It's a good my position and love swift. It's a good thing but but also uh there's a whole thing but but also uh there's a whole thing but but also uh there's a whole world out there that's happening and world out there that's happening and world out there that's happening and changing. And so what I've been kind of changing. And so what I've been kind of changing. And so what I've been kind of on is this quest of figuring this stuff on is this quest of figuring this stuff on is this quest of figuring this stuff out. And so AI I I fig I feel like I out. And so AI I I fig I feel like I out. And so AI I I fig I feel like I finally understand what's going on with finally understand what's going on with finally understand what's going on with compute. compute. compute. >> Finally now this is the time. >> Finally now this is the time. >> Finally now this is the time. >> Finally 10 years in, right? Um and what >> Finally 10 years in, right? Um and what >> Finally 10 years in, right? Um and what we need is LVM but for AI chips we need is LVM but for AI chips we need is LVM but for AI chips >> basically >> basically >> basically >> like we need we need a way to program it >> like we need we need a way to program it >> like we need we need a way to program it that scales across all the silicon. We that scales across all the silicon. We that scales across all the silicon. We need something that's easy to use, need something that's easy to use, need something that's easy to use, that's familiar to people, and we need that's familiar to people, and we need that's familiar to people, and we need people to be able to adopt this, which people to be able to adopt this, which people to be able to adopt this, which means good tools and a good experience means good tools and a good experience means good tools and a good experience and easy to use and like all these and easy to use and like all these and easy to use and like all these things that are consistent across dev things that are consistent across dev things that are consistent across dev tools um but in their own context. And tools um but in their own context. And tools um but in their own context. And so what that journey is, what that so what that journey is, what that so what that journey is, what that bridge is is the world's best way to bridge is is the world's best way to bridge is is the world's best way to program CPUs because that's what program CPUs because that's what program CPUs because that's what everybody's on. A lot of people are in

everybody's on. A lot of people are in everybody's on. A lot of people are in Python for example and C++ and that's Python for example and C++ and that's Python for example and C++ and that's the way things are and but none of these the way things are and but none of these the way things are and but none of these things are actually that great either my things are actually that great either my things are actually that great either my humble opinion. Um and so if you can humble opinion. Um and so if you can humble opinion. Um and so if you can meet people there you can lift them then meet people there you can lift them then meet people there you can lift them then get them onto GPUs, get them onto AS6 get them onto GPUs, get them onto AS6 get them onto GPUs, get them onto AS6 and give a progressive path. I believe and give a progressive path. I believe and give a progressive path. I believe that we can actually crack open this that we can actually crack open this that we can actually crack open this gigantic compute problem. And part of my gigantic compute problem. And part of my gigantic compute problem. And part of my core hypothesis, which has been core hypothesis, which has been core hypothesis, which has been consistent for years now, is that if you consistent for years now, is that if you consistent for years now, is that if you look forward at any point in time five look forward at any point in time five look forward at any point in time five years from now, like compute's only years from now, like compute's only years from now, like compute's only going to be weirder. It's only going to going to be weirder. It's only going to going to be weirder. It's only going to be more specialized, more heterogeneous, be more specialized, more heterogeneous, be more specialized, more heterogeneous, more chaotic, more fragmented. And so we more chaotic, more fragmented. And so we more chaotic, more fragmented. And so we as a programmer community need to have a as a programmer community need to have a as a programmer community need to have a the ability to build that and use that the ability to build that and use that the ability to build that and use that because you don't want to use 52 because you don't want to use 52 because you don't want to use 52 different compilers from all the different compilers from all the different compilers from all the different vendors that don't work different vendors that don't work different vendors that don't work together. They're same language. like together. They're same language. like together. They're same language. like not to like pull out a specific example, not to like pull out a specific example, not to like pull out a specific example, but it's like I got this brand new but it's like I got this brand new but it's like I got this brand new Windows ARM machine and I was so Windows ARM machine and I was so Windows ARM machine and I was so excited. I'm going to do this. I'm gonna excited. I'm going to do this. I'm gonna excited. I'm going to do this. I'm gonna I'm gonna take over the world with my I'm gonna take over the world with my I'm gonna take over the world with my Windows ARM laptop and it's like, okay, Windows ARM laptop and it's like, okay, Windows ARM laptop and it's like, okay, I'm doing some Python now we're going to I'm doing some Python now we're going to I'm doing some Python now we're going to do some computer vision and it's like, do some computer vision and it's like, do some computer vision and it's like, oh, now I just brought a C compiler oh, now I just brought a C compiler oh, now I just brought a C compiler along for the ride and oh, that one along for the ride and oh, that one along for the ride and oh, that one doesn't support ARM and oop, this wheel doesn't support ARM and oop, this wheel doesn't support ARM and oop, this wheel doesn't do this and that. It's just doesn't do this and that. It's just doesn't do this and that. It's just like, oh man, I just want to do a thing.

like, oh man, I just want to do a thing. like, oh man, I just want to do a thing. I want a hot dog or not a hot dog. This I want a hot dog or not a hot dog. This I want a hot dog or not a hot dog. This was not a hard hello world. And then was not a hard hello world. And then was not a hard hello world. And then suddenly suddenly suddenly >> supposed to be >> supposed to be >> supposed to be >> the stack leaked and because I was on a >> the stack leaked and because I was on a >> the stack leaked and because I was on a new processor or a new npu or a new new processor or a new npu or a new new processor or a new npu or a new this, I was juggling literally Python this, I was juggling literally Python this, I was juggling literally Python and C# and Rust and then like wondering and C# and Rust and then like wondering and C# and Rust and then like wondering where CUDA was and D and um you know where CUDA was and D and um you know where CUDA was and D and um you know like you say it it all works until it like you say it it all works until it like you say it it all works until it doesn't. doesn't. doesn't. >> This is the problem with these deep deep >> This is the problem with these deep deep >> This is the problem with these deep deep piles of layered abstractions where none piles of layered abstractions where none piles of layered abstractions where none of the layers knows how the other layer of the layers knows how the other layer of the layers knows how the other layer works, right? It's beautiful in the works, right? It's beautiful in the works, right? It's beautiful in the demo, but then it falls apart when you demo, but then it falls apart when you demo, but then it falls apart when you do anything weird. Um, let me give you do anything weird. Um, let me give you do anything weird. Um, let me give you an analogy because, uh, you and I come an analogy because, uh, you and I come an analogy because, uh, you and I come from a similar epoch. Um, most people from a similar epoch. Um, most people from a similar epoch. Um, most people forget what the world was like before forget what the world was like before forget what the world was like before GCC. GCC. GCC. >> Oh, yeah. [laughter] >> Oh, yeah. [laughter] >> Oh, yeah. [laughter] >> Right. And they don't know what autocomp >> Right. And they don't know what autocomp >> Right. And they don't know what autocomp was or why it existed. was or why it existed. was or why it existed. >> But if you go if you go back in time, >> But if you go if you go back in time, >> But if you go if you go back in time, everybody building CPUs had their own C everybody building CPUs had their own C everybody building CPUs had their own C compiler. compiler. compiler. >> Yeah. >> Yeah. >> Yeah. >> They didn't have AI to build it for them >> They didn't have AI to build it for them >> They didn't have AI to build it for them either, right? And so you got the the either, right? And so you got the the either, right? And so you got the the deck C compiler and the uh sequent C deck C compiler and the uh sequent C deck C compiler and the uh sequent C compiler and the Borland C compiler and compiler and the Borland C compiler and compiler and the Borland C compiler and the uh Sun and the SGI and the HP UX and the uh Sun and the SGI and the HP UX and the uh Sun and the SGI and the HP UX and all these different C compilers. Uh C all these different C compilers. Uh C all these different C compilers. Uh C wasn't even really standardized at that wasn't even really standardized at that wasn't even really standardized at that point either. There was a vague point either. There was a vague point either. There was a vague [clears throat] understanding of what it [clears throat] understanding of what it [clears throat] understanding of what it was and so none of them actually worked was and so none of them actually worked was and so none of them actually worked together. And what drove the world together. And what drove the world together. And what drove the world forward is when GCC came on the scene, forward is when GCC came on the scene, forward is when GCC came on the scene, it was free and it was portable and it it was free and it was portable and it it was free and it was portable and it kind of scored earth all this kind of scored earth all this kind of scored earth all this proprietary nonsense and it unified the proprietary nonsense and it unified the proprietary nonsense and it unified the world. And as a consequence of that world. And as a consequence of that world. And as a consequence of that happening, Linux was possible like an happening, Linux was possible like an happening, Linux was possible like an entire ecosystem entire ecosystem entire ecosystem like exploded in vibrancy and like

like exploded in vibrancy and like like exploded in vibrancy and like capability because people were able to capability because people were able to capability because people were able to move on with life and get get rid of all move on with life and get get rid of all move on with life and get get rid of all this weird junk. And so what I see today this weird junk. And so what I see today this weird junk. And so what I see today in the hardware is exactly the same in the hardware is exactly the same in the hardware is exactly the same thing. I see every hardware maker thing. I see every hardware maker thing. I see every hardware maker building their own stacks out of building their own stacks out of building their own stacks out of necessity. They don't really want to do necessity. They don't really want to do necessity. They don't really want to do all this stuff. It's actually really all this stuff. It's actually really all this stuff. It's actually really hard and expensive and slow. Some of hard and expensive and slow. Some of hard and expensive and slow. Some of them end up with a better thing than them end up with a better thing than them end up with a better thing than some of the other people, but none of some of the other people, but none of some of the other people, but none of them is compatible, right? And them is compatible, right? And them is compatible, right? And particularly in the AI and the GPU particularly in the AI and the GPU particularly in the AI and the GPU space, everybody's trying to take space, everybody's trying to take space, everybody's trying to take Nvidia's lunch to certain extent, but Nvidia's lunch to certain extent, but Nvidia's lunch to certain extent, but CUDA doesn't run on their stuff and CUDA doesn't run on their stuff and CUDA doesn't run on their stuff and their stuff doesn't run on Nvidia. their stuff doesn't run on Nvidia. their stuff doesn't run on Nvidia. [snorts] [snorts] [snorts] And so a lot of what our aha moment is And so a lot of what our aha moment is And so a lot of what our aha moment is is saying several different factors have is saying several different factors have is saying several different factors have to come together to crack this open. One to come together to crack this open. One to come together to crack this open. One is there's the technical pieces. You is there's the technical pieces. You is there's the technical pieces. You know you can talk about uh being able to know you can talk about uh being able to know you can talk about uh being able to target GPUs and unlock full performance target GPUs and unlock full performance target GPUs and unlock full performance of silicon and scale from CPUs to GPU of silicon and scale from CPUs to GPU of silicon and scale from CPUs to GPU all that kind of stuff. But the other is all that kind of stuff. But the other is all that kind of stuff. But the other is incentive structure. You need an incentive structure. You need an incentive structure. You need an organization which is modular that is organization which is modular that is organization which is modular that is not tied to a chip. It's not tied to a not tied to a chip. It's not tied to a not tied to a chip. It's not tied to a hyperscaler. Not tied to an LLM. not hyperscaler. Not tied to an LLM. not hyperscaler. Not tied to an LLM. not tied to an autonomous car. Right.

tied to an autonomous car. Right. tied to an autonomous car. Right. >> And I want to make sure people >> And I want to make sure people >> And I want to make sure people understand yours. You're you're talking understand yours. You're you're talking understand yours. You're you're talking modular the proper noun. You're saying modular the proper noun. You're saying modular the proper noun. You're saying modular. You're a company, not a modular modular. You're a company, not a modular modular. You're a company, not a modular company. company. company. >> The company, my mission, right, is >> The company, my mission, right, is >> The company, my mission, right, is formed because we need to solve this formed because we need to solve this formed because we need to solve this problem of having a team of people that problem of having a team of people that problem of having a team of people that could go and build this stuff. But then could go and build this stuff. But then could go and build this stuff. But then we also had to solve another problem we also had to solve another problem we also had to solve another problem which is an economic problem which is which is an economic problem which is which is an economic problem which is this is a really hard problem. this is a really hard problem. this is a really hard problem. >> Mhm. >> Mhm. >> Mhm. >> You need a very large team >> You need a very large team >> You need a very large team years to do this work. You're implying years to do this work. You're implying years to do this work. You're implying you're not in the pocket of like Nvidia you're not in the pocket of like Nvidia you're not in the pocket of like Nvidia or the pocket of these people, right? or the pocket of these people, right? or the pocket of these people, right? Which would be able to provide all of Which would be able to provide all of Which would be able to provide all of those resources, but then they would those resources, but then they would those resources, but then they would make the the default be the Nvidia chip. make the the default be the Nvidia chip. make the the default be the Nvidia chip. >> That's right. Well, and so I was at >> That's right. Well, and so I was at >> That's right. Well, and so I was at Google, for example, and I was trying to Google, for example, and I was trying to Google, for example, and I was trying to solve and crack and I learned a solve and crack and I learned a solve and crack and I learned a tremendous amount from Google working on tremendous amount from Google working on tremendous amount from Google working on TPUs and scaling their software stack. TPUs and scaling their software stack. TPUs and scaling their software stack. Um, amazing team, amazing people, but it Um, amazing team, amazing people, but it Um, amazing team, amazing people, but it it wasn't nefarious. Google's a very uh it wasn't nefarious. Google's a very uh it wasn't nefarious. Google's a very uh open- source friendly community and open- source friendly community and open- source friendly community and that's actually where we built and that's actually where we built and that's actually where we built and released ML donate to LVM. Google's released ML donate to LVM. Google's released ML donate to LVM. Google's amazing and lots and lots and lots of amazing and lots and lots and lots of amazing and lots and lots and lots of different ways but like any business different ways but like any business different ways but like any business they have their priorities. They have they have their priorities. They have they have their priorities. They have their internal workloads and of course their internal workloads and of course their internal workloads and of course all your best people always get sucked all your best people always get sucked all your best people always get sucked in the fire drill of the day.

in the fire drill of the day. in the fire drill of the day. >> They also at the time had a performance >> They also at the time had a performance >> They also at the time had a performance review process that ticked every six review process that ticked every six review process that ticked every six months. And so projects that took longer months. And so projects that took longer months. And so projects that took longer than six months to do were pretty hard than six months to do were pretty hard than six months to do were pretty hard to justify both uh up up the chain but to justify both uh up up the chain but to justify both uh up up the chain but much more importantly to anybody that much more importantly to anybody that much more importantly to anybody that wants to get good performance reviews wants to get good performance reviews wants to get good performance reviews and wants to get you know demonstrate and wants to get you know demonstrate and wants to get you know demonstrate their impact on key workloads and things their impact on key workloads and things their impact on key workloads and things like this. And so I found it to be like this. And so I found it to be like this. And so I found it to be extremely difficult to justify that extremely difficult to justify that extremely difficult to justify that work. And I'm a pretty stubborn, pretty work. And I'm a pretty stubborn, pretty work. And I'm a pretty stubborn, pretty bullheaded guy. And so like yes, was bullheaded guy. And so like yes, was bullheaded guy. And so like yes, was able to build mir was able to build a able to build mir was able to build a able to build mir was able to build a new runtime for TPUs, this PGRT thing uh new runtime for TPUs, this PGRT thing uh new runtime for TPUs, this PGRT thing uh that underlies jacks and all that kind that underlies jacks and all that kind that underlies jacks and all that kind of stuff and made some major of stuff and made some major of stuff and made some major contributions to the stack uh moving contributions to the stack uh moving contributions to the stack uh moving beyond what they had. Um but it was very beyond what they had. Um but it was very beyond what they had. Um but it was very very very difficult. And so this is this very very difficult. And so this is this very very difficult. And so this is this is actually a pretty significant is actually a pretty significant is actually a pretty significant challenge when you want to do something challenge when you want to do something challenge when you want to do something that is like a fundamental step forward that is like a fundamental step forward that is like a fundamental step forward in terms of languages systems in terms of languages systems in terms of languages systems particularly in the AI space. particularly in the AI space. particularly in the AI space. >> You could have just taken the language >> You could have just taken the language >> You could have just taken the language and just pick one and just made Rust++. and just pick one and just made Rust++. and just pick one and just made Rust++. >> You could have made Swift super swift.

>> You could have made Swift super swift. >> You could have made Swift super swift. >> But you didn't do that. >> But you didn't do that. >> But you didn't do that. >> That's right. >> That's right. >> That's right. >> Cuz none they were all designed for CPUs >> Cuz none they were all designed for CPUs >> Cuz none they were all designed for CPUs and everyone's thinking about CPUs and everyone's thinking about CPUs and everyone's thinking about CPUs because that's what everyone had in 2010 because that's what everyone had in 2010 because that's what everyone had in 2010 when they were thinking about these when they were thinking about these when they were thinking about these languages. Well, so so funny story. When languages. Well, so so funny story. When languages. Well, so so funny story. When we started Modular, which is now over we started Modular, which is now over we started Modular, which is now over four years ago, um, uh, my co-founder four years ago, um, uh, my co-founder four years ago, um, uh, my co-founder and I looked at each other and we said, and I looked at each other and we said, and I looked at each other and we said, "We're definitely not doing a language." "We're definitely not doing a language." "We're definitely not doing a language." Everybody knows that languages are a Everybody knows that languages are a Everybody knows that languages are a terrible idea. Uh, we have a lot of terrible idea. Uh, we have a lot of terrible idea. Uh, we have a lot of stuff to get done. Like, we have a big stuff to get done. Like, we have a big stuff to get done. Like, we have a big mission of unifying compute and mission of unifying compute and mission of unifying compute and democratizing and locking all this democratizing and locking all this democratizing and locking all this compute, but everybody knows that's a compute, but everybody knows that's a compute, but everybody knows that's a bad idea. And so we spent um almost a bad idea. And so we spent um almost a bad idea. And so we spent um almost a year working on hardcore runtimes, year working on hardcore runtimes, year working on hardcore runtimes, low-level thread pools, uh asynchronous low-level thread pools, uh asynchronous low-level thread pools, uh asynchronous communication primitives, communication primitives, communication primitives, and then dove into the okay, how do we and then dove into the okay, how do we and then dove into the okay, how do we generate high performance kernels first generate high performance kernels first generate high performance kernels first for CPUs? And so in that case, we said, for CPUs? And so in that case, we said, for CPUs? And so in that case, we said, how do we go meet and beat Intel MKO and how do we go meet and beat Intel MKO and how do we go meet and beat Intel MKO and Intel's libraries on their own chips? Intel's libraries on their own chips? Intel's libraries on their own chips? Can we beat them? We need to be able to Can we beat them? We need to be able to Can we beat them? We need to be able to do that. And we need to be able to show do that. And we need to be able to show do that. And we need to be able to show generalization at scale. And so what we generalization at scale. And so what we generalization at scale. And so what we did was we built a whole bunch of really did was we built a whole bunch of really did was we built a whole bunch of really fancy compiler technology using ML from fancy compiler technology using ML from fancy compiler technology using ML from first principles. We started with an first principles. We started with an first principles. We started with an empty git repo and built an entirely new empty git repo and built an entirely new empty git repo and built an entirely new construct and proved that we could construct and proved that we could construct and proved that we could generate very highly parametric very uh generate very highly parametric very uh generate very highly parametric very uh powerful very high leverage abstractions powerful very high leverage abstractions powerful very high leverage abstractions for generating high performance matrix for generating high performance matrix for generating high performance matrix multiplications and similar algorithms multiplications and similar algorithms multiplications and similar algorithms but then ran directly in the problem of but then ran directly in the problem of but then ran directly in the problem of okay well nobody wants to write compiler okay well nobody wants to write compiler okay well nobody wants to write compiler IR by hand. That's actually a really IR by hand. That's actually a really IR by hand. That's actually a really painful and very terrible idea. And so

painful and very terrible idea. And so painful and very terrible idea. And so then we said, "Okay, let's go shopping. then we said, "Okay, let's go shopping. then we said, "Okay, let's go shopping. What syntax do we want?" And I did look What syntax do we want?" And I did look What syntax do we want?" And I did look at Swift. I did look at Rust. I did look at Swift. I did look at Rust. I did look at Swift. I did look at Rust. I did look at Clang. Like I know many of these at Clang. Like I know many of these at Clang. Like I know many of these systems. Um but to the point, they don't systems. Um but to the point, they don't systems. Um but to the point, they don't solve the problem. Like saying, "Okay, solve the problem. Like saying, "Okay, solve the problem. Like saying, "Okay, how are we going to add all the how are we going to add all the how are we going to add all the floatingoint data types to C." Well, AI floatingoint data types to C." Well, AI floatingoint data types to C." Well, AI has seven forms of float 8. It feels has seven forms of float 8. It feels has seven forms of float 8. It feels like all kinds of new forms of float 4, like all kinds of new forms of float 4, like all kinds of new forms of float 4, Bflat 16, like all of this stuff. and Bflat 16, like all of this stuff. and Bflat 16, like all of this stuff. and it's evolving at a rate that you can't it's evolving at a rate that you can't it's evolving at a rate that you can't just keep hard coding this into the just keep hard coding this into the just keep hard coding this into the compiler. And so we said, okay, well compiler. And so we said, okay, well compiler. And so we said, okay, well clearly we need library extensibility. clearly we need library extensibility. clearly we need library extensibility. And so Mojo, the way it turned out is And so Mojo, the way it turned out is And so Mojo, the way it turned out is like yeah, almost everything's in the like yeah, almost everything's in the like yeah, almost everything's in the library, not in the compiler. We also library, not in the compiler. We also library, not in the compiler. We also need the ability to to scale across uh need the ability to to scale across uh need the ability to to scale across uh you know, predictability and compile you know, predictability and compile you know, predictability and compile time and all these things that really time and all these things that really time and all these things that really matter at scale for developer matter at scale for developer matter at scale for developer experience. And so these Python DSLs we experience. And so these Python DSLs we experience. And so these Python DSLs we looked at really were unsatisfactory. looked at really were unsatisfactory. looked at really were unsatisfactory. And so despite not wanting to do this, And so despite not wanting to do this, And so despite not wanting to do this, we basically kind of as a team looked at we basically kind of as a team looked at we basically kind of as a team looked at this and said, "Okay, well building a this and said, "Okay, well building a this and said, "Okay, well building a language is a heck of a lot of work."

language is a heck of a lot of work." language is a heck of a lot of work." It's also not rocket science like have It's also not rocket science like have It's also not rocket science like have done this before. Swift is a good thing done this before. Swift is a good thing done this before. Swift is a good thing for example, but like LVM there's a lot for example, but like LVM there's a lot for example, but like LVM there's a lot of swift the bad parts and we can do of swift the bad parts and we can do of swift the bad parts and we can do something that learns from that something that learns from that something that learns from that experience and do something that really experience and do something that really experience and do something that really moves the world forward. And though it moves the world forward. And though it moves the world forward. And though it would be a long journey, we thought that would be a long journey, we thought that would be a long journey, we thought that you know the stakes and compute and the you know the stakes and compute and the you know the stakes and compute and the future of all these architectures are so future of all these architectures are so future of all these architectures are so important that it was worth the important that it was worth the important that it was worth the investment. investment. investment. Yeah, it feels like if you want to get Yeah, it feels like if you want to get Yeah, it feels like if you want to get something done today, you end up something done today, you end up something done today, you end up bouncing around from language to bouncing around from language to bouncing around from language to language. You prototype it in Python, language. You prototype it in Python, language. You prototype it in Python, then you rewrite it in C++ and CUDA and then you rewrite it in C++ and CUDA and then you rewrite it in C++ and CUDA and then you bunch of do a bunch of bindings then you bunch of do a bunch of bindings then you bunch of do a bunch of bindings and you end up maintaining two code and you end up maintaining two code and you end up maintaining two code bases. So my kind of like armchair ar my bases. So my kind of like armchair ar my bases. So my kind of like armchair ar my armchair quarterback analysis is that armchair quarterback analysis is that armchair quarterback analysis is that you kind of wanted Python ergonomics. you kind of wanted Python ergonomics. you kind of wanted Python ergonomics. You kind of want C and C++ PF. You like You kind of want C and C++ PF. You like You kind of want C and C++ PF. You like Swift style safety, but then you need Swift style safety, but then you need Swift style safety, but then you need awareness of things that didn't exist 10 awareness of things that didn't exist 10 awareness of things that didn't exist 10 years ago, like AI hardware. years ago, like AI hardware. years ago, like AI hardware. >> So, >> So, >> So, >> all of those things combined, >> all of those things combined, >> all of those things combined, >> while you're at it, bring in some cool >> while you're at it, bring in some cool >> while you're at it, bring in some cool new ideas like linear independent types. new ideas like linear independent types. new ideas like linear independent types. Let's bring in like much better uh Let's bring in like much better uh Let's bring in like much better uh ownership and memory destruction ownership and memory destruction ownership and memory destruction behavior and things like this. And let's behavior and things like this. And let's behavior and things like this. And let's move the world forward because, move the world forward because, move the world forward because, >> you know, again, people like to zero in >> you know, again, people like to zero in >> you know, again, people like to zero in on Rust with ownership and stuff like on Rust with ownership and stuff like on Rust with ownership and stuff like this, but Rust is 15 years old. It's not this, but Rust is 15 years old. It's not this, but Rust is 15 years old. It's not it's it's it's a it's a wonderful thing it's it's it's a it's a wonderful thing it's it's it's a it's a wonderful thing for what it does, but it's not the best for what it does, but it's not the best for what it does, but it's not the best thing.

thing. thing. >> Yeah. Interesting. Interesting. Okay. So >> Yeah. Interesting. Interesting. Okay. So >> Yeah. Interesting. Interesting. Okay. So then how do I like this seems like this then how do I like this seems like this then how do I like this seems like this is a vision, right? And surely this is a is a vision, right? And surely this is a is a vision, right? And surely this is a vision that's many many years. This will vision that's many many years. This will vision that's many many years. This will come out in a half a decade or a decade, come out in a half a decade or a decade, come out in a half a decade or a decade, right? When am I when do I get to right? When am I when do I get to right? When am I when do I get to actually have this though? actually have this though? actually have this though? >> Uh so this exists today. A lot of people >> Uh so this exists today. A lot of people >> Uh so this exists today. A lot of people are actually using this people. It's in are actually using this people. It's in are actually using this people. It's in production which is pretty cool. production which is pretty cool. production which is pretty cool. >> It's in prod now. That's awesome. >> It's in prod now. That's awesome. >> It's in prod now. That's awesome. >> Oh yeah. Yeah. We have customer >> Oh yeah. Yeah. We have customer >> Oh yeah. Yeah. We have customer workloads are running all this stuff. workloads are running all this stuff. workloads are running all this stuff. It's it's not a theory. Um, today you It's it's not a theory. Um, today you It's it's not a theory. Um, today you can run Mojo, you can download pip, can run Mojo, you can download pip, can run Mojo, you can download pip, install it, install it, install it, >> you can run it on wide variety of CPUs, >> you can run it on wide variety of CPUs, >> you can run it on wide variety of CPUs, u embedded devices like Raspberry Pies u embedded devices like Raspberry Pies u embedded devices like Raspberry Pies and stuff like that. It's fine. Okay. and stuff like that. It's fine. Okay. and stuff like that. It's fine. Okay. >> Uh, runs on Nvidia A100, H100, B100, and >> Uh, runs on Nvidia A100, H100, B100, and >> Uh, runs on Nvidia A100, H100, B100, and a ton of their consumer cards. Runs on a ton of their consumer cards. Runs on a ton of their consumer cards. Runs on AMD, the 300, 355, their RDNA cards, AMD, the 300, 355, their RDNA cards, AMD, the 300, 355, their RDNA cards, which are their consumer ones. Um, and which are their consumer ones. Um, and which are their consumer ones. Um, and Apple GPU. And so we have other stuff Apple GPU. And so we have other stuff Apple GPU. And so we have other stuff that we'll announce later, but this that we'll announce later, but this that we'll announce later, but this isn't a theoretical thing. This actually isn't a theoretical thing. This actually isn't a theoretical thing. This actually works. Mhm. works. Mhm. works. Mhm. >> Um, and one of the things that's really >> Um, and one of the things that's really >> Um, and one of the things that's really cool about it is, you know, zoom back to cool about it is, you know, zoom back to cool about it is, you know, zoom back to the modern world and AI. Not only is it the modern world and AI. Not only is it the modern world and AI. Not only is it possible to do this stuff, but we've possible to do this stuff, but we've possible to do this stuff, but we've unified the programming model for GPUs.

unified the programming model for GPUs. unified the programming model for GPUs. >> That's huge because that's definitely >> That's huge because that's definitely >> That's huge because that's definitely not in Nvidia's best interest. not in Nvidia's best interest. not in Nvidia's best interest. >> Correct. Or anybody else's. It's it's >> Correct. Or anybody else's. It's it's >> Correct. Or anybody else's. It's it's not in Apple's best interest either, not in Apple's best interest either, not in Apple's best interest either, right? It's it's a hardware company right? It's it's a hardware company right? It's it's a hardware company problem, right? problem, right? problem, right? >> Yeah. Yeah. Um, and so we have, I think, >> Yeah. Yeah. Um, and so we have, I think, >> Yeah. Yeah. Um, and so we have, I think, the biggest open- source kernel library the biggest open- source kernel library the biggest open- source kernel library that exists with all the matrix that exists with all the matrix that exists with all the matrix multiplications run all this hardware. multiplications run all this hardware. multiplications run all this hardware. It's like over half a million lines of It's like over half a million lines of It's like over half a million lines of Mojo code. Um, and it's now indexable by Mojo code. Um, and it's now indexable by Mojo code. Um, and it's now indexable by AI. And so one of the coolest things AI. And so one of the coolest things AI. And so one of the coolest things about AI and one of the things it's about AI and one of the things it's about AI and one of the things it's actually really good at is translate actually really good at is translate actually really good at is translate thing A into language B. And so it turns thing A into language B. And so it turns thing A into language B. And so it turns out that if you have Python code running out that if you have Python code running out that if you have Python code running on CPU, we have people that are saying, on CPU, we have people that are saying, on CPU, we have people that are saying, "Hey, Claude skill move this to Mojo and "Hey, Claude skill move this to Mojo and "Hey, Claude skill move this to Mojo and they get 100 times thousand times speed they get 100 times thousand times speed they get 100 times thousand times speed up." up." up." >> Seriously. And you've got Python interop >> Seriously. And you've got Python interop >> Seriously. And you've got Python interop as well, right? You can pass Python as well, right? You can pass Python as well, right? You can pass Python objects into Mojo functions. Yeah. objects into Mojo functions. Yeah. objects into Mojo functions. Yeah. >> Yeah. And it just works. And so this is >> Yeah. And it just works. And so this is >> Yeah. And it just works. And so this is also where because Mojo is designed for also where because Mojo is designed for also where because Mojo is designed for modern langu [clears throat] modern modern langu [clears throat] modern modern langu [clears throat] modern CPUs. CPUs. CPUs. >> Yeah. Has really badass SIMD vector >> Yeah. Has really badass SIMD vector >> Yeah. Has really badass SIMD vector support. It's it's natively multi-core support. It's it's natively multi-core support. It's it's natively multi-core and so you can just kind of go the AI and so you can just kind of go the AI and so you can just kind of go the AI tools and say hey uh can you make this tools and say hey uh can you make this tools and say hey uh can you make this go faster and we'll say oh yeah I'll go faster and we'll say oh yeah I'll go faster and we'll say oh yeah I'll vectorize this for you oh I'll paralyze vectorize this for you oh I'll paralyze vectorize this for you oh I'll paralyze this for you and because all the this for you and because all the this for you and because all the abstractions are there like what what abstractions are there like what what abstractions are there like what what happens is it just like up uplevels your happens is it just like up uplevels your happens is it just like up uplevels your code code code >> sit you and so you can understand it >> sit you and so you can understand it >> sit you and so you can understand it which is really cool and so this is which is really cool and so this is which is really cool and so this is where like we're in a different era and where like we're in a different era and where like we're in a different era and this code design between what AI can do this code design between what AI can do this code design between what AI can do and what uh the language can do is I and what uh the language can do is I and what uh the language can do is I think a completely different dynamic

think a completely different dynamic think a completely different dynamic than what we had 5 years ago. than what we had 5 years ago. than what we had 5 years ago. >> Yeah. I think for the rank and file >> Yeah. I think for the rank and file >> Yeah. I think for the rank and file developers just there's there's the CPU developers just there's there's the CPU developers just there's there's the CPU and then there's these other mysterious and then there's these other mysterious and then there's these other mysterious chips that happen to be in my computer chips that happen to be in my computer chips that happen to be in my computer and to make to unlock that and be able and to make to unlock that and be able and to make to unlock that and be able to do stuff with it even on laptops and to do stuff with it even on laptops and to do stuff with it even on laptops and TPUs and MPUs and things like that uh is TPUs and MPUs and things like that uh is TPUs and MPUs and things like that uh is going to be huge because they're very going to be huge because they're very going to be huge because they're very opaque. If you start thinking I'm going opaque. If you start thinking I'm going opaque. If you start thinking I'm going to learn how to program a GPU. Yeah, to learn how to program a GPU. Yeah, to learn how to program a GPU. Yeah, good luck buddy. good luck buddy. good luck buddy. >> Yeah, that is not fun. >> Yeah, that is not fun. >> Yeah, that is not fun. >> If you're interested, go to the GPU >> If you're interested, go to the GPU >> If you're interested, go to the GPU puzzles on the modular website and we'll puzzles on the modular website and we'll puzzles on the modular website and we'll teach you how to program a GPU. It's teach you how to program a GPU. It's teach you how to program a GPU. It's actually not that hard when you get actually not that hard when you get actually not that hard when you get decent tools and that actually work decent tools and that actually work decent tools and that actually work together. Um, one now one, let me tell together. Um, one now one, let me tell together. Um, one now one, let me tell you the bad thing about Mojo. you the bad thing about Mojo. you the bad thing about Mojo. >> Okay, >> Okay, >> Okay, >> so the bad thing about Mojo is it's not >> so the bad thing about Mojo is it's not >> so the bad thing about Mojo is it's not stable. We haven't hit our 1.0 yet stable. We haven't hit our 1.0 yet stable. We haven't hit our 1.0 yet >> and so we've been building it for just >> and so we've been building it for just >> and so we've been building it for just about four years now. It's really cool. about four years now. It's really cool. about four years now. It's really cool. People were seeing amazing, amazing People were seeing amazing, amazing People were seeing amazing, amazing results and a lot of people love it. results and a lot of people love it. results and a lot of people love it. >> Um, but again, I have this burden of >> Um, but again, I have this burden of >> Um, but again, I have this burden of wanting to do something that's actually wanting to do something that's actually wanting to do something that's actually good. [laughter] It's not just the good. [laughter] It's not just the good. [laughter] It's not just the outcome, but it's the design. It's the outcome, but it's the design. It's the outcome, but it's the design. It's the it's the ability to scale. the ability it's the ability to scale. the ability it's the ability to scale. the ability to like enable new things and last for to like enable new things and last for to like enable new things and last for the next hopefully 10, 20, 30 years of the next hopefully 10, 20, 30 years of the next hopefully 10, 20, 30 years of compute, right? And so we've been very compute, right? And so we've been very compute, right? And so we've been very deliberate about that and we've been deliberate about that and we've been deliberate about that and we've been building in the open, but we're saying building in the open, but we're saying building in the open, but we're saying like, yeah, we're going to fix it. We're like, yeah, we're going to fix it. We're like, yeah, we're going to fix it. We're we're going to change things. We're we're going to change things. We're we're going to change things. We're going to laser focus in on getting to a going to laser focus in on getting to a going to laser focus in on getting to a 1.0 and stable. And the thing that I'm 1.0 and stable. And the thing that I'm 1.0 and stable. And the thing that I'm very excited about is that it's almost very excited about is that it's almost very excited about is that it's almost here.

here. here. >> And so come April, May, I think we'll >> And so come April, May, I think we'll >> And so come April, May, I think we'll have our 1.0 beta. have our 1.0 beta. have our 1.0 beta. >> And so it's not very far away anymore, >> And so it's not very far away anymore, >> And so it's not very far away anymore, which is really exciting. And I think which is really exciting. And I think which is really exciting. And I think we'll declare uh 1.0 and then open we'll declare uh 1.0 and then open we'll declare uh 1.0 and then open source the rest of the compiler and all source the rest of the compiler and all source the rest of the compiler and all this kind of stuff probably in you know this kind of stuff probably in you know this kind of stuff probably in you know August Septemberish. August Septemberish. August Septemberish. >> It's going to be a big year >> It's going to be a big year >> It's going to be a big year >> coming very soon. And so the team's >> coming very soon. And so the team's >> coming very soon. And so the team's working super hard on this. Um I think working super hard on this. Um I think working super hard on this. Um I think that we all realize what a big moment that we all realize what a big moment that we all realize what a big moment this will be for the community because this will be for the community because this will be for the community because we have a bunch of amazing people in the we have a bunch of amazing people in the we have a bunch of amazing people in the community doing amazing things. community doing amazing things. community doing amazing things. >> Uh but we want them to not be constantly >> Uh but we want them to not be constantly >> Uh but we want them to not be constantly thrashed by change. [laughter] thrashed by change. [laughter] thrashed by change. [laughter] So the stabilization point will be a big So the stabilization point will be a big So the stabilization point will be a big deal for us as a community. deal for us as a community. deal for us as a community. >> Very cool. Mojo 1.0 coming soon. And >> Very cool. Mojo 1.0 coming soon. And >> Very cool. Mojo 1.0 coming soon. And folks can go to puzzles.mmodular.com. folks can go to puzzles.mmodular.com. folks can go to puzzles.mmodular.com. There's a really great eight-part There's a really great eight-part There's a really great eight-part tutorial series. You can just go through tutorial series. You can just go through tutorial series. You can just go through it and you can do hands-on GPU it and you can do hands-on GPU it and you can do hands-on GPU programming using Mojo. And you can do programming using Mojo. And you can do programming using Mojo. And you can do that today getting ready for the coming that today getting ready for the coming that today getting ready for the coming 1.0 in the next month or two. This is 1.0 in the next month or two. This is 1.0 in the next month or two. This is super exciting. I really appreciate you super exciting. I really appreciate you super exciting. I really appreciate you spending the time to sit down with me spending the time to sit down with me spending the time to sit down with me today.

today. today. >> Yeah, it's awesome to chat with you, >> Yeah, it's awesome to chat with you, >> Yeah, it's awesome to chat with you, Scott. like I I I love your work and Scott. like I I I love your work and Scott. like I I I love your work and you're you're a legend. Um I'll also say you're you're a legend. Um I'll also say you're you're a legend. Um I'll also say all this stuff's free. So please do join all this stuff's free. So please do join all this stuff's free. So please do join our open source community. We I do love our open source community. We I do love our open source community. We I do love developers and I love seeing the developers and I love seeing the developers and I love seeing the creative things that people can make and creative things that people can make and creative things that people can make and this is this is why I coming back to the this is this is why I coming back to the this is this is why I coming back to the top what I care about in the human top what I care about in the human top what I care about in the human experience is the act of creation. You experience is the act of creation. You experience is the act of creation. You know, being able to build something and know, being able to build something and know, being able to build something and being proud of it and saying I did that. being proud of it and saying I did that. being proud of it and saying I did that. Uh but also I think that many folks out Uh but also I think that many folks out Uh but also I think that many folks out there are looking at you know what what there are looking at you know what what there are looking at you know what what do I do in this uncertain future, do I do in this uncertain future, do I do in this uncertain future, >> right? Do I just keep building the thing >> right? Do I just keep building the thing >> right? Do I just keep building the thing I was building yesterday? I mean, I I was building yesterday? I mean, I I was building yesterday? I mean, I think it's such an great opportunity to think it's such an great opportunity to think it's such an great opportunity to lean in. And again, there's this amazing lean in. And again, there's this amazing lean in. And again, there's this amazing form of compute, all these new tools and form of compute, all these new tools and form of compute, all these new tools and technologies. It's the easiest time ever technologies. It's the easiest time ever technologies. It's the easiest time ever to learn something like Mojo or whatever to learn something like Mojo or whatever to learn something like Mojo or whatever your new technology is. And so, I really your new technology is. And so, I really your new technology is. And so, I really do encourage people to go out there and do encourage people to go out there and do encourage people to go out there and try out new things. And uh yeah, AI has try out new things. And uh yeah, AI has try out new things. And uh yeah, AI has got a lot of hyperbole and BS laden in got a lot of hyperbole and BS laden in got a lot of hyperbole and BS laden in it sometimes, but but some of the it sometimes, but but some of the it sometimes, but but some of the stuff's also really cool. stuff's also really cool. stuff's also really cool. >> Yeah, I really feel like it's a time >> Yeah, I really feel like it's a time >> Yeah, I really feel like it's a time where the curious are going to thrive. where the curious are going to thrive. where the curious are going to thrive. And I know it's scary, but craft And I know it's scary, but craft And I know it's scary, but craft matters. Learning still matters. Keep matters. Learning still matters. Keep matters. Learning still matters. Keep learning. And we just want to let you learning. And we just want to let you learning. And we just want to let you know we appreciate you. The community know we appreciate you. The community know we appreciate you. The community appreciates you. And I thank you so much appreciates you. And I thank you so much appreciates you. And I thank you so much for spending time with me.

for spending time with me. for spending time with me. >> Yeah. Well, thank you for having me. >> Yeah. Well, thank you for having me. >> Yeah. Well, thank you for having me. >> This has been another episode of >> This has been another episode of >> This has been another episode of Handsome Minutes, and we'll see you Handsome Minutes, and we'll see you Handsome Minutes, and we'll see you again next week. again next week. again next week. [music]