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Technology's daily show (formerly the Technology Brothers Podcast). Streaming live on X and YouTube from 11 - 2 PM PST Monday - Friday. Available on X, Apple, Spotify, and YouTube.
You're watching TVPN.
Speaker 2:Today is Friday, 12/19/2020.
Speaker 3:Merry Christmas. Merry Christmas.
Speaker 2:We have maxed out the amount of Christmas that is possible in the TVP and UltraDome. We are, of course, live from the TVP and UltraDome. The temple of technology, the fortress of finance, the capital of capital. I don't know if we're gonna make it through the show in this costume.
Speaker 3:I don't know.
Speaker 2:I I I'm gonna be honest with you upfront. Everyone, we appreciate you. We're very thankful this holiday, but this is a lot
Speaker 3:for a
Speaker 2:three hour broadcast about technology and business. And, also, we have some very serious people coming on the show today. Michael Trudeau, the founder of Cursor, isn't it like a $30,000,000,000 company? He's coming on the show. Feels a little disrespectful.
Speaker 2:They just acquired our sponsor Graphite. Graphite.com.
Speaker 3:Hey. Hi.
Speaker 2:It's very exciting. Honestly, it it it is a fantastic partnership. Makes a lot of sense. We're gonna have both both founders on the show breaking the deal down, giving us an update on Cursor's business and Graphite's business and how they fit together. The the the meme is we're generating so much code.
Speaker 3:What's the bottleneck, John? Reviewing.
Speaker 2:That's right. That's right. The other the other bottleneck, of course, is dealing with your finances. So head over to ramp.com this holiday season. Time is money.
Speaker 2:Save both. Easy use corporate cards, bill payment, accounting, and a whole lot more all in one place. I'm I I I wanna take this off, but also I I feel like it looks really good. I'm really into this.
Speaker 3:My thing is I need to figure out how to get these monitors in my ear.
Speaker 2:If we play a video Jordy can here right now also, this delicious Diet Coke right here, I can't partake because I have this massive beard. Your beard looks much wilder than me.
Speaker 3:Well, it's because I have No.
Speaker 1:It's because I have
Speaker 2:What's going on with
Speaker 3:your I have hair up here. You see this?
Speaker 2:Oh, yeah. You have you oh, you got a hair?
Speaker 3:Yeah. Yeah. Yeah. I have a whole wig.
Speaker 2:Mine's pure beard. His somehow is the dual set.
Speaker 3:Anyways, okay. So folks, a lesson this week Yes. Is that we started Christmas on Monday. We really it's really we we started really strong. We start we we talked about how certain advertisers including Amazon got into the holiday season a little too quickly.
Speaker 3:Yeah. Little did we Maybe backfire on them. Little did we know. Four maybe did the same thing.
Speaker 2:We did the exact thing.
Speaker 3:But it has been a very fun week and we're excited to finish strong.
Speaker 2:It's really it's really so good. This this is this might be more entertaining than our than our Halloween episode just because there's like, Halloween Friendly was nothing else in the Ultra Dome that was Halloween themed. It's not like we had pumpkins and, like, know, Ilya Sutskever, like, accoutrement or anything around us. It was really just us. But the Christmas spirit has been building and building and building.
Speaker 2:And I I honestly have zero regrets. Have zero regrets. It is ridiculous. It's over the top. Just like Julius AI is It really is.
Speaker 2:Ridiculous and over the top. As far as AI data analysts go, Julius is the AI data analyst that works for you. Join millions who use Julius
Speaker 1:Okay.
Speaker 2:Connect their data. Alright. Ask questions and get insights in seconds. Oh. Yeah.
Speaker 3:We need
Speaker 2:to fix some of this off. This is Back to Anyway, thank you to we just wanted to say thank you to everyone for an amazing year. What a wild ride. So at the beginning of the year, this show
Speaker 3:Remember last year, didn't we do, like, a Christmas Eve episode?
Speaker 2:I think so.
Speaker 3:We just weren't willing to stop.
Speaker 2:Yeah. No. It was it was it was a really intense schedule, but we weren't live. We didn't have guests. We we didn't travel for the show.
Speaker 2:We we had this whole I I have Santa here up all over me. Yeah. We had this whole thesis that, like, what was missing was actually just two people hanging out, having a conversation, and and there actually were a lot of interview shows that were doing a great job. Of course, that all plan played out way differently. Yeah.
Speaker 2:We have the numbers. We actually did 225 livestreams this year. Thank you to so many of you in the chat that I know we're actually watching for all 225 of those. There's a lot of you. We recognize you all.
Speaker 2:We know we've learned all of your names. It's been fantastic hanging out here with you every day chatting. Across those 225 livestreams, we interviewed 912 unique guests, and we're also doing another five today, I think. So you're we're we're we're still adding to that, but we almost hit a thousand guests. We said, oh, we're gonna do a thousand guests this year at a certain point.
Speaker 3:Some guests have come
Speaker 2:on a lot. Some guests have come
Speaker 3:on We know the the record holder for this year.
Speaker 2:Delaney and Asper Ruhov with 18 guest appearances. We've done twelve nineteen interviews and 8,554 posts on X. So, I mean, just every day, 10 posts, basically, 20 posts, 30 posts, a lot.
Speaker 4:Joe Wiesenthal and Senra are tied for number two, both at nine.
Speaker 3:Wow. That's a lot of They're power law here. Yeah. Well, we can we can pit them against each other next year and say, you don't wanna do you wanna be do you wanna you should go for number one.
Speaker 2:I'm surprised is not up there. Mean, I there was there's been a few times when I just called Gliman. I don't know if that counts because he's not on the lineup. I just call him on the phone. But obviously, thank you to Ramp.
Speaker 2:You've heard the ad read every day at the top of the show, but this show would not be possible without Ramp. They took a huge gamble on us when the show was really, really small. They said, hey, we're down to sponsor this show for the whole year.
Speaker 3:And of course, Adquic and Public
Speaker 2:So many and many
Speaker 3:Wander and the others that came in incredibly early and allowed us to scale into the production that it is today.
Speaker 2:Yeah. Yeah. So you'll be hearing, of course, from all of our sponsors throughout the show, and we we really could not do the show without them. So thank you to all of them. Interesting.
Speaker 2:The first guest ever was Ryan Peterson. He did a wild sort of a wild move just jumping on a livestream with us. We'd never done a guest ever, and it was live. It was very odd. We could talk about anything.
Speaker 2:But he was he was totally down to just hop on, and it was a lot of fun.
Speaker 3:And he ended up coming on a lot this year because of how much
Speaker 2:and what
Speaker 3:was in global trade.
Speaker 2:Yeah. So that was that was a lot of fun. Gary Tan hooked us up with, the ability to stream from YC Demo Day, the Palace of Party rounds. That was a super, super cool moment. And I just remember getting texts from people when we first went live.
Speaker 2:So we'd never taken the show on the road. And then Gary said, hey. Why don't you go do the show from YC Demo Day? And we did. We set up our table, the sports center, the step and repeat, and, and we brought this, like, insane energy.
Speaker 2:It was a really loud room, which was actually a feature because we were screaming the whole time. It was crazy. And I got so many text messages like, are you guys live streaming Demo Day? This is crazy.
Speaker 3:Yeah. That was our NFL combine. Yep. And, of course, Figma
Speaker 2:Was was our our Super Bowl. Exactly. So we got to go to the New York Stock Exchange for the Figma IPO. And again, you know, huge, huge gamble for for Dylan to let us hang out there talking to everyone there. We got a and and I feel like we landed on a very unique product, interviewing basically the whole board of directors on IPO day, less focused on price action, more focused on story
Speaker 3:Which was crazy.
Speaker 2:Of course. Crazy. The stock was up, stock was down. It was a fantastic day. And honestly, if we'd been like, we're all making money, it's you know, that might have been a different thing.
Speaker 2:That might have been better. But it wasn't us. And so we we stayed focused on
Speaker 3:Yeah. It was not it wasn't for, you know, a retail investor that wanted to trade the stock. No. Was for people that had used and loved Yeah. Figma
Speaker 2:And that was the energy that Years. That was the energy that we were feeling in the timeline. Like, a lot of people on the timeline were like, I've used Figma when I built my company. I use it every day. I've I've
Speaker 3:worked multiple jobs across multiple companies.
Speaker 2:Totally. Totally. And I think that's something we always wanted to come back to is, like, the posters that make the show possible, the timeline. This show is unique in that that is very much our backbone. Obviously, we read the Wall Street Journal.
Speaker 2:We read a lot of the the news. But for some of the funny moments, some of the funniest moments, some of the most interesting folks we've had on the show, some of the anons that have come on has just really allowed us to to wind up in a different place. Before we move on, let me tell you about Restream. One livestream, 30 plus destinations. Gotta say thanks to them.
Speaker 2:The show seriously would not be possible without Restream. If you wanna multistream, go to restream.com. So
Speaker 3:I was looking back at some of the original Yeah. Love that we got from from different people. Yeah. I remember Balaji texted you super early on and said, great set and production value. Jackson texted one of us the same.
Speaker 2:Jackson Doll.
Speaker 3:Jackson Doll very early and so so many others. Yeah. And yeah, we thank, you know, everyone for supporting us early and Yeah. And certainly.
Speaker 2:He helped us throw an after party after the Figma IPO. That was a lot of fun. We I think I think it was the first time I met Joe Wisenthal in person at that party. Then we wound up going on his show. He came on our show a ton.
Speaker 2:That was a lot of fun. Obviously, you to all the sponsors. And also thank you to the media that makes this show possible, the fact finding. They do they find Yeah.
Speaker 3:I think early on people wanted us to have this sort
Speaker 2:of Adversarial like
Speaker 3:relationship with the media. But the at the end of the day
Speaker 2:It's been very
Speaker 3:incredibly symbiotic. Yep. Media does analysis, fact finding
Speaker 2:Yep.
Speaker 3:Of all different sorts. We incorporate it into the show Yep. And the show wouldn't be wouldn't be possible
Speaker 1:Yeah.
Speaker 2:Without that. And and a lot of the profiles, I mean, from the very early days, we were reading like a New Yorker profile of Mary Meeker. And that gives you like a certain flavor of what tech was like at that time. And, you know, without the legacy media, the traditional media, the corporate media, the new media, the legacy new media, the neo neo legacy media, Without all of them, we couldn't do what we do. And then of course, you to the team.
Speaker 2:The massive fantastic team here at TVPN. We have had a fantastic year with them. They've grown.
Speaker 3:Absolutely legends.
Speaker 2:Everyone's figured out ways to improve the show. Every little thing that you see on this show across the Internet, across everywhere where we exist is due to someone on our team being inventive, coming up with a strategy for how that happens, then implementing it, and then executing it every single day like clockwork with extreme
Speaker 3:And it's it's a performance. Everything that, you know, as we're sitting here hanging out, talking, they are doing an incredible amount behind the scenes making sure that the show is dialed. Yeah. And we've certainly grown a lot if you look at some of the some of the early shows and and how even the just the overlay evolved. And it's really been the highlight of my career working with all of you guys.
Speaker 3:Yep. So thank you for being part of this. Should we play that? They made a video.
Speaker 2:Yeah. Yeah. Let's Replay it? Let's watch it.
Speaker 3:We pull it
Speaker 2:up. We have a little year in review video that we're gonna watch here on the stream. And 2025 is gonna be a fantastic year. Lock in A
Speaker 3:locking in that you do today will benefit your great grandchildren.
Speaker 2:I agree.
Speaker 3:If you do it right. Yeah. So do it. Do it. Do it, brother.
Speaker 3:Age. Like two years.
Speaker 2:Today is Meta Connect twenty twenty five. We'd love for you to hit this gong for us. Here we go. Congratulations on Meta Connect twenty twenty five. Oh, alright.
Speaker 2:This is a big moment for us. I mean, we just started a couple months ago. It's been this has definitely been on, like, the vision board of, like, one day. And now we're here. So thank you so much for hosting us.
Speaker 3:You're watching TVPN. We now
Speaker 2:have some fantastic news. We have a partnership with the New York Stock Exchange. You're watching TVPN. Go live from GitHub Universe. Give it
Speaker 3:a quick hit for 27%.
Speaker 2:Strong hit. Great
Speaker 3:hit. So good
Speaker 2:to meet you. How are you doing?
Speaker 3:There he is. Show. I can't believe
Speaker 2:he showed up. The Halloween episode. The Christmas episode. And
Speaker 3:and the response was like, would you ever spend 250 k on a car when you took that lift?
Speaker 2:That was the best. That's the scoop of the year. Sam Altman has a good sense of humor.
Speaker 5:You guys are really important to me.
Speaker 2:Good luck to you guys. Just keep doing what you're doing. You're just you're just electric. There we go.
Speaker 6:What you guys do
Speaker 5:is great. I also think that you're transforming the way that media is is, you know, dispersed each week and, you know,
Speaker 2:and and it's awesome. Yeah. You guys
Speaker 5:are doing what you do and elsewhere. Thanks so much.
Speaker 3:Thank you to everybody that has made this possible tuning in and joining the show and supporting us, however you have. So have a wonderful evening, and we will see you tomorrow. Thank you. Take care.
Speaker 2:Good night.
Speaker 3:Have having the snow effect for Yeah. The snow effect is great. Snow effect.
Speaker 2:The snow effect is not baked into to the underlying video. That of course will be shared on on Anyways Thank
Speaker 3:you. Thank you, Ben. And the whole and Nick and Scott and Michael for for making that. You guys you guys are the best. Correction, actually, shout out to Jackson who made that video.
Speaker 3:No way. What? Wow. Legend. Thank you, Jackson.
Speaker 3:Legend. Amazing. And Tyler, do you have any news for us?
Speaker 4:Oh, yeah. Contract extended. What?
Speaker 3:No. Gap year. Gap year extended. Tyler is not going home.
Speaker 2:He's not going
Speaker 3:home. Well, he's going home for the holidays. He's coming back next semester.
Speaker 2:Like the jaws of life.
Speaker 3:Contract extended. He's sticking around. It has been truly truly incredible having you here on our set and contributing to the show in such a special way.
Speaker 2:Yeah.
Speaker 3:And yeah, we we should probably figure out a new title at some point other than intern.
Speaker 2:Intern doesn't really make
Speaker 3:sense. It doesn't it made sense for for a minute but but you're much you're much more than an intern. You're a technology brother. So thank you for being a part of this.
Speaker 2:Thanks for
Speaker 3:Thanks for we get the gigachad? Can we get
Speaker 2:Yeah. Can we at least gigachad this band?
Speaker 3:Gigachad this band.
Speaker 2:Come on. Please. Production people. Yeah. Grambling.
Speaker 2:And I mean, we have to thank everyone that actually watched the show. Everyone in chat, we appreciate you and everyone who Watched. Everyone who saw. There are so many ways to experience what we do. That is by design.
Speaker 2:We want to let people we wanna meet them where they are, obviously, in an RSS feed, in a cut down, in a diet TBPN product, in a
Speaker 3:twenty minute version, in a In the newsletter.
Speaker 2:In the newsletter, in the trading cards. The trading cards themselves are a way to experience what we do here. And so thank you to everyone who enjoyed any of that, No matter how much or how frequently you did, we appreciate you. Anyway, let's go to the timeline.
Speaker 3:First,
Speaker 2:let me tell you about Numeral. Compliance handled. Numeral worries about sales tax and VAT compliance so you can focus on growth. So speaking of, gap semester intern Tyler, Jane Street is putting up trading cards.
Speaker 3:No. This is not This is
Speaker 2:fake. Right?
Speaker 3:I think this is
Speaker 2:Wait. What's going on here?
Speaker 3:I think this is this guy Mason.
Speaker 2:Okay. Yo. He made it for himself.
Speaker 3:He made it for himself. Oh, but he's going to Jane Street. His account. Mason
Speaker 2:Okay. Committed to Jane Street for summer twenty twenty six. Congratulations to Mason. That's an awesome shop, awesome place to go. And what incredible performance, almost 10,000 likes in this Instagram post.
Speaker 2:But Var Epsilon here is saying, software engineering intern recruiting slowly turning into college football. It should. It's arguably higher stakes.
Speaker 3:Nick in the comments Fantastic. Abizid from, Rivet says, they call this the TBPN effect.
Speaker 2:I just like this. That's a good one.
Speaker 3:Yeah. The deal director, the TBPN effect is escaping.
Speaker 2:Hey. Isn't the deal director in the chat right now? Yeah. Yeah. You deal director.
Speaker 2:It it it really has. I mean, obviously, we didn't invent the trading card or, like, this format. This has been used by complex and the and in many ways, you can trade the this type of media back to the New York Post or any sort of even TMZ. I remember the first time I made one of these trading cards for I think it was Will Menidas playing with model boats on the on the on the, like, the little pond in Central Park. I looked up how does TMZ do it.
Speaker 2:Okay. Let me recreate that basic Photoshop template. Now we've kind of taken it in a different in a much broader direction. But it's just a fun way
Speaker 3:to It shouldn't this format shouldn't be reserved for celebrities and people that throw around balls for a Yes.
Speaker 2:I I completely agree. We democratized the trading card this year, and I'm glad we did. Before we move on to the big story, which is that TikTok is absolutely printing, let me tell you about Cognition. The AI the team behind the AI software engineer, Devin, crush your backlog with your personal AI engineering team. So TikTok owner ByteDance is on track for 50,000,000,000 in profit in 2025.
Speaker 2:Big. That's so much money. So this is from Bloomberg. ByteDance is on track for profits of roughly 50,000,000,000, capping a record year for a Chinese social media leader making major inroads into ecommerce and new markets. I mean, it truly is like their hyperscaler.
Speaker 2:They own a ton of different stuff, gaming, social. It's so much more than just TikTok. Yeah. And that's very, very clear in the financial results. The Beijing based parent company of TikTok is on track to hit that milestone after amassing net income of about 40,000,000,000 over the years first March.
Speaker 2:People familiar with the matter said it's already surpassed its internal target for 2025. This that would take the company's earnings close to that of Meta platform. So ByteDance is now basically the same size as Meta, which is insane. Meta is, of course, earning about 60,000,000,000 this year. TikTok success has come over under scrutiny after the Biden administration led an effort to ban TikTok.
Speaker 2:Bydance is now close to final finalizing a plan to hive off the video service in The US, which will
Speaker 3:gonna be American made.
Speaker 2:American made. Well, American domic American made Potentially. Obviously. Short form video. Debates over over exactly how that will happen, but Oracle is potentially in the deal.
Speaker 2:Despite Washington's scrutiny, TikTok has expanded globally at a rapid clip, including in The US. It has been pushing aggressively into ecommerce and livestream shopping much like the livestream shopping thing, it it feels like it's so so big over there. I wonder if it's, you know it's it's somewhat growing here, but it does feel like it it still feels like it has not hit a fever pitch in The United States the way it has abroad. The same day that Xochu, the CEO of TikTok, announced he had an agreement he'd reached an agreement to sell TikTok. TikTok held its first ever Oscar style red carpet show, the TikTok Awards in Los Angeles.
Speaker 2:That sounds fun. It's unclear how much ByteDance has increased revenue this year. The company had targeted 20% rise, which would be a $186,000,000,000, and that would cap years of 20 plus percent growth for the company founded in 2012 by Zhang Yiming. ByteDance has created several of China's most popular digital service, Tauchiao, Douyin, a version of TikTok for the Mainland market. It's also vying with incumbents, Alibaba and
Speaker 3:quick overview of the businesses under the ByteDance brand. They have Douyin, which is the Chinese version of TikTok.
Speaker 2:Yeah. Yeah.
Speaker 3:It's quite a bit more feature
Speaker 2:right? Oh,
Speaker 3:no. So no. No. It's more feature rich. Oh, that's right.
Speaker 3:So it's like more focused on retail, bigger bigger live experience. They have like hotel bookings, movie bookings, things like that. They have Tao Teo, which is a a news, like, content aggregator.
Speaker 2:Yeah. And and Artifact, which was created by the Instagram founders. They were kinda dipping their toe back into, like, creating a social media. Of course, one of them landed at Anthropic. Mike Krieger landed at Anthropic.
Speaker 2:But that was sort of like, maybe if that works over there
Speaker 3:Very, very similar.
Speaker 2:News aggregator could work over here.
Speaker 3:Then they have Xi Guo Xi Guo, which is like more of like a YouTube style business. Then they have Doubao, which is apparently China's most popular AI chatbot. So something like ChatGPT. Yes. And then they have a bunch of other sort of tertiary businesses as well as CapCut.
Speaker 3:If you use CapCut, the mobile editing app, they they
Speaker 2:I didn't realize I was quite excited about product. Wow. Cool. If you wanna use the meta version, they have edits, which is pretty good. I I I've used edits a few times, and it's it's pretty full featured, at least.
Speaker 2:So TikTok has signed a deal for The U for the sale of The United States unit. The deal should close January. This is from Sarah Fisher, the media correspondent at Axios. She says that Oracle, Silver Lake, and MGX will collectively own 45% of The US entity. 30% will be held by affiliates of existing ByteDance investors, and 20% will be retained by ByteDance.
Speaker 2:So ByteDance, the Chinese entity sort of becomes the minority investor. It sort of goes into American hands loosely or Western hands. Yep. And then, of course, the the the rest of the process can be handled. And you can and you have more leverage to address, like, where is the data stored?
Speaker 3:How is the algorithm trained? US the joint venture is gonna be focused on data protection, algorithm security, content moderation, and software assurance. So retraining the content recommendation algorithm on US user data to ensure the content feed is free from outside manipulation.
Speaker 5:Mhmm.
Speaker 3:We'll be interested to see, if there's any noticeable effect for TikTok users.
Speaker 2:Let me tell you about Fall, generative media platform for developers, developing fine tuned models with serverless GPUs and on demand clusters. Megan Borowski, over at The Wall Street Journal, has a scoop that Meta is, in fact, developing a new image and video focused AI model code named Mango.
Speaker 3:I like it.
Speaker 2:Alex Wang and Chris Cox talked the new models Mango and Avocado in a Q and A with employees this morning. One of those employees said, I gotta tell The Wall Street Journal about this. It's too good. It's too good.
Speaker 3:It's simply too good.
Speaker 2:It's too good. I gotta let them know. Now, who knows how they cut the scoop, but it's a great one. They said models are expected to be released in the 2026. I mean, they have a lot of data.
Speaker 2:They should be able to train a great model. I wonder if it's enough to get to just release a frontier model and really see any usage or if this is again, it's like it needs to be vended into Instagram, into meta properties. What what do think, Tyler?
Speaker 4:Yeah. I mean, I feel like it's very natural to vend this into Instagram. Yeah. And like this model, like, I I would be very surprised if people are surprised by this. Right?
Speaker 4:Because like the the mid journey in Vibes, like, that was not MSL. That was not Alexander Wang.
Speaker 2:Yeah. Yeah.
Speaker 4:Yeah. That's just like the product team.
Speaker 2:Yeah. But they they they've done a lot of work to marshal compute, build huge data centers. Like, they're ready for a big run.
Speaker 3:Yeah. Like, I have the data to
Speaker 4:be very good.
Speaker 2:Yeah. I would expect this to be good. The I I've have you been following those those those posts that are, like, we're comparing ChatGPT images and ChatGPT versus Nano Banana Pro? And you can sort of tell the difference, but it does feel like it's starting to be a spiky intelligence moment where
Speaker 4:I think I think Nano Banana is generally better at at putting text or, like, if you wanted to do some kind of
Speaker 2:Charts Yeah. Charts. Graphs and illustrations.
Speaker 4:Yeah. Chachi Beauty images is better for, like, maybe artsy or stuff.
Speaker 2:And character consistency. So you can you can tell a whole story across, and Chattypi seems better
Speaker 3:at that. But Without further ado. We have
Speaker 2:some very special Tell us more about all this. We have Michael Truell and Merrill from Graphite and Cursor. Great to great to meet you, Michael. Great to see you, Merrill. Good to see you too.
Speaker 2:How are you doing?
Speaker 1:Amazing. It's a it's a fantastic and exciting day for everyone at Graphite. We're we're thrilled about about today's announcement and super excited to work with Michael and team.
Speaker 3:Yeah. It makes so much sense. Yeah, we're excited to have you guys break it down. So, yeah, when did when did the conversation start?
Speaker 1:Yeah. So we started chatting. I guess we've known each other for, like, six years almost now. We've yeah. We've been Yeah.
Speaker 1:Yeah. We've been we we both went to there's this startup camp program that one of our shared investors did did, like, six years ago. We're in that for the first time. And then our teams have kind of always known each other. There's been a lot of overlap.
Speaker 1:Cursor was a a big user of Graphite. We're a big user of the Cursor. We started talking kinda back in the summer when we were building we started thinking about building integrations with background agents and thinking about how we let our users, call background agents from Graphite so you could create, review, and merge PRs all in one place. And, we started chatting with the Cursor team. It, you know, quickly became obvious that we shared a lot more than just our, you just know, our biggest investors.
Speaker 1:We're you know, when we think about the world the same way, we have a super similar vision for where DevTools is going. Their New York office is literally across the street. I can I can see their window from right here? So it's it's it just made so much sense.
Speaker 2:Yeah. That's great. Yeah. Yeah. Michael, please.
Speaker 5:I was just gonna say as we got to talking, like Merrill mentioned, we both think about the future pretty similarly, where we both believe that the way people build software over the next five, ten years is gonna change radically. A lot of coding as we know today will be automated. And we think very similarly about the ways in which code writing will change, but also the ways in which teams collaborating will change.
Speaker 2:Mhmm.
Speaker 5:And Graphite has focused really intensely on the team collaboration problem and how you help people review each other's code. We focus really intensely on the single player experience of how you develop software as a, you know, as an individual programmer. And so we're excited to kind of marry the two together and pull across.
Speaker 2:Michael, I I would love to get a year end review for Cursor or even more broadly just the state of of of software development. Quantitatively, qualitatively, how can you explain the way writing software changed in 2025?
Speaker 5:It's changed in a big way. I think at the highest level, agents became useful in a professional setting, and that really expanded the demand in the market. And I think we're still early. Like, I think it can be really easy to underrate just how far away coding is from being automated. Mhmm.
Speaker 5:And still, building professional software takes so many people over such a long period of time, and there's lots of issues we need to contend with as AI coding becomes deployed more broadly. But it was a big year where you went from being able to just, you know, ask some quick questions to an AI about your code base and how to kind of help you out with the next thirty seconds to five minutes of your work to being able to hand off whole tasks to an AI and have it do hand.
Speaker 2:And and and Merrill, like, the shape of Graphite, obviously, we know that you're growing quickly. Like, how did how did you perceive the changes that happened this year? If you look back on 2025, obviously, you know, this deal is gonna be something you remember forever. But more precisely, how do you think that the developer experience
Speaker 3:Every time I catch up with Merrill, he'd be like, there's a lot of code to review. So we're busy. That was that was the view your own. Mike that's in a big in a big way is Michael's fault. So
Speaker 1:No. That's that's the funny part about this. I I think Cursor has just so dramatically changed the the rate at which we can build features and, how much code that engineers are able to generate. And, what's happened consistently, the bottleneck has now just shifted to the rest of the process, what we call the outer loop, where, now we need tooling to help every team review and validate and merge changes at the rate that you can now generate them with tools like Cursor. And, that was basically our our 2025 has been how do we both, apply AI to this problem?
Speaker 1:How do we use, like, more, know, more traditional or deterministic methods like merge queues and, stack PRs and other workflows and tools, to make that process more efficient? But, you know, how do we just unblock this bottleneck that that is now it's kind of like, you know, preventing teams from really realizing the the true potential of tools like Cursor, and, that's that's been our mission this entire year pretty much. And, part of why I think we're so excited for for this partnership is that now you can put, you know, the surfaces where you you write code and where you review and validate and merge it together and just have that seamlessly integrated. Like, you shouldn't have you shouldn't have to, like, jump to a different tool for, your editor, for for code review, for your PRs, for CI. Like, all this should just be, you know, one nicely integrated surface.
Speaker 1:And, that's kind of always been the the dream for for Graphite in our vision. I think this, you know, now that can become a reality.
Speaker 3:How are you guys thinking about the integration process and and how, Graphite fits into the sort of Cursor platform family? I think a good first step would be, like, maybe a walkway between the offices in New York.
Speaker 2:Like a Skyway? A Skyway? Yeah. We have a Skyway.
Speaker 1:We've talked about
Speaker 3:the A little string and string and cups, you know, so you can but
Speaker 1:Yeah. We'll we'll put a zipline over Broadway. Yeah. So that people can commute back and forth. No.
Speaker 1:I think I think that there's there's some really obvious low hanging fruit of things that you'll see us roll out in the coming months together, and then there's a a long tail of, like, even more ambitious ideas that we have that are that are in the works. But immediately, like, I remember earlier this year, a few of us on the the Graphite team were up in Toronto, meeting with, with Toby and some of the Shopify engineering leaders, and, they're one of our our biggest customers and close partners. And the biggest ask that they had for us was how do we get context from, from our IDE or from, you know, from tooling where we're we're writing code with AI into pull requests and have that be seamless and have the same chat history, have the the agent logs and everything show up in the PR and be able to then call out to the agent to fix things again. And, you know, we were like, that's that's an interesting problem. Like, maybe we should maybe we should think about working with with Cursor on this.
Speaker 1:And I think that's that's kind of the most obvious thing that we can do to start with, and then we can build from there on on many of the other ways that we can kind of connect all those surfaces together and have the agent be able to help you, you know, all the way through from the moment that you generate the code to the moment that it's merged in and out to production.
Speaker 5:Yeah. I'd second that. There are gonna be a bunch of opportunities for some quick ways in which we can make the experience of working together in graphite and cursor better. But then the big thing will be going heads down on on a much bigger build together where we'll have more to share late in 2026.
Speaker 2:Michael, I'd love to get an update on how you're thinking about just growth opportunities as segmented by sort of, like, scale of the customer. We we've we've read some, you know, like, the AI, like, the models are great. The tech is amazing. There's still some odd resistance to adopting AI in certain enterprises. We're not at a 100% penetration with these tools.
Speaker 2:Is there more opportunity in the near term in large enterprises and transforming the way those businesses work? Or is it just the ground game of going getting every SMB online? Like, how are you thinking about growth in 2026, 2027?
Speaker 5:We've been shocked by the demand across the board. Mhmm. And so on the mid market and smaller company side of things and the self serve side of things broadly, there are all these rules of thumb for when the growth of that business tops out in developer tools or in kind of other comparable markets. And the thing that's just shocked us and shocked all of our investors is that the growth has been compounding really consistently at the same growth rate over the course of course of many years
Speaker 3:Mhmm.
Speaker 5:Into the, you know, the revenue scale that we are now. And that just continues unabated.
Speaker 2:So yeah. And then is that sort of like an IT spend thing where, like, a small and medium a small and medium business might just say, like, okay. We don't wanna spend 10% of revenue on IT spend or or technology, and maybe the new paradigm is actually helping with so much growth that they're able to underwrite a larger investment in technology. Is is that what you're seeing?
Speaker 5:Comes from more people using Cursor
Speaker 2:Okay.
Speaker 5:And people deeper. Yeah. Both ARPU and how we're helping people and how much code we're writing for people.
Speaker 2:Yeah. Yeah.
Speaker 5:And then also the number of people using Cursor within companies and across companies
Speaker 1:Yeah.
Speaker 5:Which has consistently been growing.
Speaker 2:Got
Speaker 5:it. And one big change for us this year is just the upmarket motion has developed Okay. Faster than almost any upmarket motion has ever, where at this point, 64% of the Fortune 500 pay us Wow. In some way. And it's both penetration into digital native companies.
Speaker 5:So for instance, NVIDIA's a big customer wall to wall Yeah. Adobe, Uber, Salesforce, which I think in a public earnings announcement recently, mentioned that they're seeing over 30% productivity increase in twenty first. Yeah. And it's also it's also companies that aren't digital native too. It's it's shocking how many companies are software companies.
Speaker 5:So And Starbucks, BWC, Hilton, companies like this are deep customer
Speaker 3:Where where are both of you seeing any resistance to adopting AI specifically in software engineering? Are there any I I'm thinking of, like, the the Japanese soldier on the island, you know, that doesn't doesn't know the the war ended. Are you seeing anybody trapped left on an island?
Speaker 5:I think that well, I think that this is kind of true of how AI tools are bought broadly, but it's really important. I think the way you procure these tools is a little bit different, where the difference between having the best product and the third best product from some incumbent that's, you know, now six months old is really, really big. And then user behavior needs to change, and the way in which your team needs to your team works needs to change. And so you kinda need to you need to teach people within companies how how to work differently. And so we've seen a lot of success in not just pulling out the the tool, but also teaching folks within companies too.
Speaker 5:But it's really spanned across all types of development. I think that there's still some languages where, there's room for improvement and how much, AI can can help folks, especially some some super legacy languages. But I think where there's resistance, it's mostly a a problem of of teaching and kind of learning new habits.
Speaker 3:That makes sense. What kind of advice are you giving, somebody that's maybe in high school or college that wants to to get into software engineering but is, concerned about just the overall rate rate of change and how good the products and models are getting?
Speaker 5:I think it's actually a really exciting time to get into building things on computers. And probably on a relative basis, especially exciting for people who are new and entering the field just because, you know, it's just quick for them to pick up new habits. And so I told them, yep, to experiment with the tools, to try things out broadly. And, also, I mean, working on a solo project by yourself is very different from building, like, a giant piece of software with hundreds of other people So getting exposure to, like, a real professional development environment, to I think it's it's helpful learning.
Speaker 3:Yeah. And it seems more and more obvious that there's just so so much software that needs to be built. I mean, we've experienced this year where we have built a software tool internally to help us run and and, run the entire show. And we are a business that even three years ago, we wouldn't have been hiring a software engineer because we would have either used off the shelf SaaS or would have just taken so much resources, it wouldn't have been worth it. So there's just so much to build.
Speaker 5:Yeah. It's almost trite now, especially in the Bay Area, to say, you know, software is important. And if anything, I feel like it's kind of, like, reached a point in technological maturity where you don't even really think of software as technology. Just think of it as, oh, it's a website that someone builds. Yeah.
Speaker 5:But, yeah, it's I mean, it's shocking how much, you know, progress across the world really is just bottlenecked by building things on computers. You talk to people in AI research. What's the bottleneck to making the models better? There's a few, but one of the biggest ones is just building better infrastructure and just the speed at which researchers can code. And it's for another areas too.
Speaker 5:For instance, I worked at a biotech company at one point, and one of the big bottlenecks making progress there was analyzing data and picking the next set of chemicals that people were gonna try out. And it was dealing with crappy software from off the shelf vendors or building a whole software team to build it yourself. And so, yeah, I think that it's this amazing lever on productivity in a bunch of different verticals.
Speaker 2:What are the research paths that excite you the most or or or that you think might be underrated? Example would be like when when we we talked to Sholto during the Claude four five launch, and he was talking about not image processing, not image generation, but image processing. And that's a that actually makes a lot of sense because a real software engineer needs to look at the web page that they designed and then, you know, interpret that and understand the code that they write, how it feeds into the result. Are there any areas of research or or less obvious, like, it's not just a coding model, research paths that you're particularly excited about in 2026?
Speaker 5:Yeah. I think that the capability gains we've seen in our space have actually there's been, like, a lot of details to figure out. Mhmm. But there have been a few really big ideas that have worked just, like, have been levers that people have pulled on continuously. Sure.
Speaker 5:And so pretraining is one that's been talked about a lot, you know, like Yep. Taking big models, scaling them up, training them on Internet scale data. Mhmm. Another big one that's been really important for our space is curating a set of games for the models to play.
Speaker 2:Oh.
Speaker 5:So for us, that means, you know, collecting a set of or, you know, in our space, it means collecting a set of code bases Mhmm. Writing out tasks, having a set of tests to test if the model actually solved the task, you know, writes a PR. And the big AI companies have have done this really well of getting thousands, tens of thousands of of really hard games for the model to play and then teaching the model to play those games. And in turn, the model then gets better at programming. And so I think that there's a bunch more juice to squeeze both from pretraining and then, you know, RL with this verifiable reward.
Speaker 5:But I think that there's gonna be, you know, some new big ideas that are needed to really get to a place where you can can hand off end to end most of the professional development tasks we do in in, like, a
Speaker 3:real Does that make you especially excited about some of the neo labs that are that are, I would say, fairly controversial at this point because on one hand, feels like we need new ideas. But on the other hand, it's like
Speaker 2:It's a lot of money.
Speaker 3:It's a lot of money and it's unclear if you just go and try to compete with
Speaker 2:It's always scary when there's a lot of lot of funding, not a lot of revenue. Yeah. Yeah.
Speaker 1:I think Crystal is actually doing a a great job at at this with We got their their own models internally.
Speaker 2:Yeah. I was about to ask, do you think that you're gonna become more of a lab over time?
Speaker 5:No. I mean, we what we wanna do is we wanna build the best way to code with AI. Mhmm. And so we have lots of amazing partners that we're really excited to continue working with over the course of the next few years that are working on things that look like AGI. We've ever since the start of the company, we've kind of picked our spot where we are gonna do our own modeling work.
Speaker 5:And those have looked different from the places where the big AI companies, big labs do their modeling work. And so for instance, like, all our TAP models, like the things that are looking at what you've done in the editor, breaking the next things you're gonna do, those are our own models. We're on, like, the sixth generation model there. They learn continuously by looking at, you know, what people are doing within, for sure, and figuring out how they how they can get better. And so I am really excited for us to invest a bunch more in research, do lots more ambitious stuff, but it'll kind of be a little in a little bit of a different direction from what some of these these labs might do.
Speaker 5:And so for instance, we're really excited to build models that are some of the most capable in the world at programming. Not the most capable in the world at programming, but are very fast too. And we think that over the course of the next couple of years or over the course of the next year, agent usage in coding is gonna kinda bifurcate into in the loop or completely async. We're in the loop, you're sitting down, you're, like, working with the agent in a pair programming way. You want it to be very fast and extremely smart.
Speaker 5:And then async is gonna be you're talking to a colleague. You just hand off something in time. Yeah. And you want it to definitely, definitely, definitely correct. And I think that very soon, we would like to play a really big part in making that human in the loop experience excellent.
Speaker 5:And I think that there's a lot of useful modeling work to do there. So
Speaker 3:Very cool.
Speaker 2:How do you think about the x for y meme? I feel like Cursor's been very successful in that you there's a certain, like, rite of passage in Silicon Valley where once you become, like, Uber for x, it's like, you're the Uber, it's a good place to be. Good. Cursor for dogs, cursor for bio, cursor for travel, this has become a meme. Is there a where is the line for what cursor will do and what cursor will not do?
Speaker 2:So when I talk to the Andoril folks, they'll say, well, the Andoril of submarines is Andoril. But if I said the Andoril of stoves or the Andoril of, you know, of, you know, watches, it's like, okay. I don't even know what that means. That's fine. I'm not gonna build that.
Speaker 2:Like, you actually can go build that company. Where where where's the where where's the line of, like, what Cursor will do over time versus what's something that, like, where where you might like the Cursor four x model, but it's not on your road map?
Speaker 5:Well, we'd like to make it possible for anyone to build anything they'd like on a computer.
Speaker 2:Mhmm.
Speaker 5:And, you know, another way of putting that is we'd like to automate coding.
Speaker 2:Sure. And
Speaker 5:half of that's a model problem, half of that's a product problem.
Speaker 2:Mhmm.
Speaker 5:And we wanna do deep important work across. And yeah. So squarely squarely focused on helping you build things on computers.
Speaker 2:Yeah.
Speaker 5:And that for us, that means an intense focus on engineers. And then increasingly, the Fold's gonna expand too, where lots of technically light personas, like designers and product people, they also work with Cursor too.
Speaker 7:Sure.
Speaker 5:And one of the things we're excited about is that that Fold can broaden as the product gets better, as the technology matures. But I am really excited actually for, quote unquote, cursor for x's to exist in other spaces. And when we started the company, we kind of thought that, like, this this shape of company where you pick an area of knowledge work and you kind of make the cockpit where that knowledge work happens, like the products Mhmm. That people daily drive for that form of knowledge work. You make it you shape it to where the tech's going.
Speaker 5:You make it great for where AI is. Mhmm. And then you also see where AI is helping people and where it's not helping people, you and use that to make the underlying models better, both by doing a little bit of your own, also by working with partners. That, like, kind of shape of company, we were really excited about. And I think it's gonna exist in in all sorts of different areas of knowledge work, whether it be mechanical engineering or writing or, you know, science, like biological science and other places.
Speaker 5:Yeah.
Speaker 2:Is graphite the cursor for pull request? Merrill, did you ever think about that positioning? Because I've done I I literally I think I've done 250 ad reads for graphite, and I've never said, hey. It's the cursor for pull request. We said it's code review for the age of AI, of course.
Speaker 2:But it like, did you do you think that you fit neatly into that that that that framing of the cockpit where the work happens that you improve? Or or is there something that's that's like a different positioning? And I'm wondering how that might change over the next Yeah. Few years.
Speaker 1:Yeah. I think one of our one of our investors, Gokaran, has this framework that we reference a lot where you're you're either building a dashboard company or a pipes company in b to b.
Speaker 2:And Okay.
Speaker 1:If you're if you're a dashboard company, you have to be, like, something where where one type of user, like, single day at work, they're coming in and and doing a certain task and that's just their home screen. Oh. Or you wanna be a pipes company where it's, like, you configure it, you set it and forget it, and it just, does throughput and and prints money for you. Mhmm. And we're very much we've always thought about Graphite as as a dashboard.
Speaker 1:We've said we wanna be the home screen for developers. We wanna be the place where, where everyone, you know, comes in and checks, like, where are my code changes in flight? What do I have to do in order to unblock my team and keep everything moving? And I think that's that's one of the things that that's so that's so exciting about this partnership is that now, you know, you really can be the the one dashboard for engineering. Like, if you want to if you want to write code, if you want to build something, if you want to move your changes through the rest of the process, like, that can all happen on on one nicely integrated surface now and and really make that that vision a reality.
Speaker 2:Yeah. That makes a lot
Speaker 3:of sense. Well, I'm so excited for both teams. Yeah. I'm incredibly excited for you, Merrill, and the whole team at Graphite as as a as a Graphite customer starting at the age of 25 to a partner now. It's been incredible to see the journey, and you guys pairing up just makes so much sense.
Speaker 3:And it's been a massive year for you both. I'm sure 2026 will be even bigger, and thank you both for for joining to celebrate with us. We should we should hit the gong again for you both.
Speaker 1:Yeah. I think I think this is the gong worthy moment.
Speaker 3:Definitely. Definitely. And I'm sure I'm sure the two of you guys won't have much of a much of a holiday, but we hope you can enjoy at least a little downtime with friends and family, and can't wait for next year.
Speaker 2:Yeah. We'll talk
Speaker 5:to you Thank
Speaker 2:you so
Speaker 1:much. Thank you, guys.
Speaker 5:We're welcome. Stuff again. Goodbye.
Speaker 3:Incredible.
Speaker 2:What a great partnership. That that that feels like such a yeah. Great Just a match made in heaven. Absolutely.
Speaker 3:Well Let's go over
Speaker 2:to heaven. Dana White and the meta board. This is a match made in heaven. Very funny on multiple levels. Let's play this clip while the team is pulling it up.
Speaker 2:Let me tell you about Adio, the AI native CRM. Adio builds, scales, and grows your company to the next level. Let's go. Never stop clapping.
Speaker 7:And now AI.
Speaker 2:Let's play this.
Speaker 7:Have you got into AI yet? Yeah.
Speaker 2:We're dabbling. Okay. Dabbless, sir.
Speaker 7:So Meta AI, I got you know, I'm on the board for Meta. I just got back from the Meta board meeting.
Speaker 2:So good.
Speaker 7:Zuckerberg, who was a brilliant gangster. This guy. Gangster.
Speaker 2:All of you are gangster.
Speaker 7:These people who try to talk about him and everything else. I'm so blown away and impressed by this guy. He's an animal.
Speaker 2:I agree with that.
Speaker 7:And He did.
Speaker 2:He's an animal.
Speaker 7:Putting all the chips in on AI. We just hired like 10 kids that are aged 22 to 28. The average salary is like $65,000,000. These kids are making that
Speaker 2:a And somebody did this is the final leap. AI. Everyone's wondering.
Speaker 7:There's way more positives about AI than negative. So you start looking at AI and getting into it and asking AI, how do I build my business? How do I you know, and it'll start giving you some ideas and
Speaker 2:Hold on. You can Is he saying $65,000,000 is the average salary per year?
Speaker 3:I think so. I mean, I think of his salary I think of his salary as a
Speaker 2:That's an annual thing. As
Speaker 3:an annual thing. So
Speaker 2:10 that's that's insane.
Speaker 3:And, Noah, in the chat says, meta engineers with a 600 k salary.
Speaker 2:Watching this. Just be like, what? Yeah. So, yeah. Yeah.
Speaker 2:Keep playing this. From here
Speaker 7:to Tulsa, Oklahoma, you'd have to go on a map and you'd have to lay out, you know, your route and all. You gotta do the same thing for your business. Map out your root for '26.
Speaker 2:When I first saw that, I thought he was saying like AI will be able to get you directions. And I was like, but Yeah. Google Maps can do that.
Speaker 3:Okay. So when when I see this, I just It's actually
Speaker 2:a great metaphor.
Speaker 3:Entrepreneurs can get stuck in a loop of just wanting to meet with and talk with people and like get ideas and get strategies
Speaker 2:And and
Speaker 3:AI is really good at that. You can say, I have an e commerce company. I want to grow. What should I do?
Speaker 1:I'll give you a bunch
Speaker 3:of ideas. And it's like it just shows how worthless a lot of ideas are and how important execution is. Some some ideas are Right? It's like you wanna execute on the right ideas but Yeah. Oftentimes to find the right ideas, you gotta try a bunch of stuff.
Speaker 3:Yeah. And so AI is at the point where it can give you the the perfect strategy, the perfect playbook even if it's like kind of the average playbook across business textbooks and blogs and posts and things like that. But in the end, you just still gotta go do the work. That's the hard part.
Speaker 2:Yeah. I mean, I I I still think there's like like he is using he's using a metaphor. I think he's actually a pretty good communicator here. He's using a metaphor that people understand. It's like mapping technology, Google Maps for business, answering other questions, unstructured questions.
Speaker 2:AI can tell you that. And if you think about before, you know, you'd you'd Google, okay, well, my business needs a website. How do I set up a website for my business? Okay. I need to go to the store and get a book, Web Development for Dummies.
Speaker 2:This was that this was a thing.
Speaker 3:I remember that.
Speaker 2:Back in
Speaker 3:the Yeah.
Speaker 2:In the nineties, it was like Java for Dummies. Like, you're gonna build now it's like, you know, AI, obviously. We just talked about this. And so he's he's right. He's delivering it in, like, this sort of funny way, and he's and he brings, like, this crazy this crazy energy to the performance.
Speaker 2:But he is correct in, like, the pitch, in this idea. He's he's actually correctly pitching super personal super intelligence. And for a lot of people, that's exactly what they want. Now he doesn't really address the fact that, like, you know, there's incredible competition from Anthropic and OpenAI and and Google on this front. But that's not what he's that that that's not what he's addressing.
Speaker 2:He's addressing just the idea of, like, of, is AI useful? And the guy is like, we've dabbled with it. We've used it for answering, you know, like, doing subtitling, basically.
Speaker 3:And And I think what's under so Meta has
Speaker 2:what pitches, like, the next level of, like, what's possible.
Speaker 3:Meta has something, I think, three three and a half to 4,000,000,000 monthly active users. And so I think in those board meetings, have to imagine they're saying like, yeah, there's a lot of competition. Yeah, ChatGPT has a big user base. Yeah, Gemini has a big user base. But we have 4,000,000,000 people that we can start distributing.
Speaker 3:If we build a great model, we can start distributing it through WhatsApp, through Instagram, through Facebook, through the Meta AI app, etcetera.
Speaker 2:Yeah. I was listening to Ben Thompson this morning, and he was doing app reviews, like the the the review of the top paid apps and the top free apps. So the twenty twenty five top paid apps. And this is wild. It's like, have you heard of any of these?
Speaker 2:I know. HotSchedules, Shadow It Rocket
Speaker 3:seems like Procreate.
Speaker 2:Have you heard of any of these? Procreate?
Speaker 3:No. I because I checked the charts
Speaker 2:a SkyView. I've heard of that. Tonal Energy, AutoSleep, they're they're all like a couple dollars. And most people have not really heard of any of these. If they have, they're like, oh, yeah.
Speaker 2:I I use, you know, this for this one little thing or this is a niche thing. And then you go to the top free apps and it's like trillion dollar company, trillion dollar company, trillion dollar company. It's literally ChatGPT threads, Google, TikToks, WhatsApp, Instagram, YouTube, Google Maps, Gmail, Google Gemini. And so Ben's point was if you like ChatGPT, yes, they are the number one app, but they should be scared because Google has one, two, three, four, five in the top 11 or something like that. And so the distribution is just so powerful.
Speaker 2:And
Speaker 3:Yeah. Fortunately Meta
Speaker 2:has that distribution, so they're also a contender and they can stay in the game.
Speaker 3:So the top the number 22 free app right now, number 21 is Instagram, number 22 is Whatnot, number 23 is HBO Max.
Speaker 2:Yeah.
Speaker 3:And on the paid side currently, 21 is Threema Secure Messenger. Sounds like an even SaaS version.
Speaker 2:Sounds insecure.
Speaker 3:Yeah. Sounds like Number two is Pocket God which is a game that includes Call of Booty.
Speaker 2:Wait. Call of Pocket God? Isn't that a nickname for AGI? They've AGI has been solved.
Speaker 3:This is just like a a a mobile game. Pocket God. And then number 23 is Jingle, real motion shaker instrument.
Speaker 2:That sounds like the iBeer app. Let's go.
Speaker 3:It basically is. You shake it and you can play bells, you know, sleigh bells, that kind
Speaker 2:of Well, know, most of those, if they're on the top paid app store charts, they're probably making money. And the software is probably developed in linear. The system for modern software development. Linear streamlines work across the entire development cycle from roadmap to release.
Speaker 3:What does Casey Neistat have for us?
Speaker 2:Casey Neistat did a project with the Meta Quest three where he scanned his studio. He says it's pretty rad. You can walk around and look at stuff and get close. I specifically did not clean the place before we scanned it. It works it works on your phone and on the headset.
Speaker 2:Let's play this. Can we play this full screen too? That'd be interesting. I wanna see the the full screen. Have you have you watched a lot of Casey Neistat?
Speaker 2:Have you seen his whole facility? I've watched enough of these videos.
Speaker 3:It's one of the coolest studio spaces.
Speaker 2:Yeah. It's very inspiring from a production perspective because it's practical, but it also has so much character that it it tells you a story. And so even when he's just filming a little product review and he's making the seventh video of the month or year or whatever, you're you're you're brought into his world. You understand who Casey is. Every single one of those items tells a story, and it's just it's just really cool.
Speaker 2:So
Speaker 3:Yeah. And I remember feature. We've we've done a demo of this feature, but we weren't doing we we scanned like a very normal room.
Speaker 2:Should we should we give Tyler a challenge to actually get this up and running?
Speaker 3:Scan the
Speaker 4:I tried for like, I don't know, maybe two months now. Yeah. You've been able to do a couple experiences on Yeah. The MedQuest. Okay.
Speaker 4:But you couldn't record your own
Speaker 2:yet. Mhmm.
Speaker 4:And I I mean, I'm not sure if it's actually I guess it is out that you can do it yourself.
Speaker 2:So I'm not saying scan
Speaker 3:the UltraDome. GigaChad elf is so I love the GigaChad elf. It's so good.
Speaker 2:So I yeah. I'm not proposing that you you look so ridiculous. I'm not proposing that you scan the UltraDome. I'm proposing that you stop enjoying your jawline. He's on that Wild Roman again.
Speaker 2:He's he's on the Wild Roman.
Speaker 3:Lay it lay off, Tyler.
Speaker 2:But the what I'm proposing is that Casey Neistat shares a link there, horizon.meta.com/world slash a bunch of numbers. And if you click that in the headset, I believe it takes you to that world. Yeah. But how long do you think it'll take you to actually get into that world of that headset? Wow.
Speaker 2:You're old now. I don't like that. I don't like this one.
Speaker 3:That's not
Speaker 2:fun. No. No. No. No.
Speaker 3:Hey, paw.
Speaker 2:Hey, paw.
Speaker 3:I I like it. I would like to be still doing this when you look like that. Yeah. I enjoy it.
Speaker 2:But how long Oh. Yeah. Yeah. Yeah.
Speaker 3:That's Do the sad face. Do the sad face.
Speaker 2:The sad face is the funniest one. It's so funny. The jawline is crazy. Oh, It looks so real. It's so good.
Speaker 3:I don't like this one.
Speaker 2:No. He really looks so sad.
Speaker 3:But what's wrong, Tyler? Cheer up cheer up.
Speaker 2:You know what will cheer you up? Privy. Privy makes it easier to build on crypto rails, securely spin up white label wallets, sign transactions, integrate on chain infrastructure all through one simple API.
Speaker 3:The Economist is saying industrialists now list Gundow along with Silicon Valley and tell in Tel Aviv within a triumvirate of the West Triumvirate.
Speaker 2:Triumvirate. It means it means three powerful pillars
Speaker 3:That's a new one together. Something new every day.
Speaker 2:Yeah. We gotta get you on the Anki mobile flashcards. Little space repetition.
Speaker 3:Yeah. Yeah. Yeah. Exactly. Of the West's most important innovation hubs.
Speaker 2:Yeah. America's fight back against China starts in Los Angeles. It is real. I mean, it hasn't happened overnight, but the progress, I think, has been faster and more real than people expected. I think when when Augustus was first posting in, what was it, 2023.
Speaker 2:So the next post, Fast Company did profile on Augustus, and they actually referenced me. And they said two years ago in a widely viewed interview with the tech world chronicler, John Coogan, that's me, Dorico was jacked and tanned. What? Triple glaze. Hit that glaze.
Speaker 2:That's ridiculous. Triple glaze. Is insane. A high wattage presence at ease in his role as Gundo super connector, as Kugen describes him. I did describe him as that.
Speaker 2:They asked me for comment, that is a direct quote. I do think he's the super connector. And for a long time, it was like, if you are going to El Segundo, like, checking with Augustus, ping him first. He will get you Yeah.
Speaker 3:Not do not step foot in El Segundo without checking in with the Don.
Speaker 2:Without bringing
Speaker 3:Or a co.
Speaker 2:You need to bring Or
Speaker 3:a co the Don.
Speaker 2:Of White Monster as an offering. Yeah. And maybe some nicotine pouches to to to pay your respect. If you're a venture capitalist I mean, there was a there was a whole while where there it was like VCs from all parts of the world and then celebrities started being They
Speaker 3:were taking a pilgrimage.
Speaker 2:It would yeah. Celebrities would go on the pilgrimage.
Speaker 4:I remember a lot Gil went and then he posted a a Zin can on
Speaker 2:That's right. Yeah.
Speaker 4:Yeah. He spelled Zin wrong. I remember that.
Speaker 2:Oh, yes. Zin I n
Speaker 3:o. Okay. So Augustus was quoting this this picture from Ererebius of saying this is what rebuilding America
Speaker 2:does to you.
Speaker 3:This is Zane It's insane.
Speaker 2:Down down Knox Metals. We interviewed him on
Speaker 3:I mean, this transformation is insane. It's really This guy is incredibly hard.
Speaker 2:It's really the the the, like, frazzled Wojak who's just, like, throwing out all black.
Speaker 4:I have a block of metal from Zane.
Speaker 2:He gave Oh, no way. That's from him?
Speaker 5:Yeah. Yeah. He gave me
Speaker 4:the That's very cool.
Speaker 3:Very cool. Yeah. Yeah. He sacrificed his innocent self to rebuild our country.
Speaker 2:We got him for it.
Speaker 3:Forever grateful.
Speaker 2:But the funny thing about this this fast company is so so first, they say Dorico Dorico was jacked and tanned. And then he said, these days, Dorico shuttles between cold warehouses on early morning flights. In more recent interviews, shadows mark his face, and there's a wary fatigue to his posture. They're just like I was talking I was texting with the guest, and he was like, why do they have to say I fell Why do they have to say I lost my pump? But I'm sure he'll be back in the gym anytime.
Speaker 3:Hey. You never said it was gonna be easy.
Speaker 2:It's bulks it's bulking season anytime. You're you're always welcome to bulk back up. No. I I had a great experience making this video. It's very funny.
Speaker 2:I met Augustus, and I he just seemed like an interesting character. So I I was making videos about, like, big established companies, so I didn't really have a format that worked for, like, a seed stage founder with just an idea. He was pre Thiel fellowship. He really I don't think he'd raised any money. He was just like some
Speaker 3:But you knew from the beginning that Augustus was a Joe Rogan CEO.
Speaker 2:100%. It was I gotta do content with this guy. What can we do? And so I I went with Ben out to the Sultan Sea with Augustus, and we drove out there. It was like a two hour drive to the Sultan Sea, sorted out by thermal, actually, a little And bit we drove around, and we walked around, we filmed, like, this walk and talk interview out in this crazy, like, you know, desert y sea.
Speaker 2:Because the Salton Sea used to be, like, a proper oceanfront hangout spot. Then it got overly salinated, and then there's dehydration. A lot of the the water that flowed in got drained away Yeah. For farmland. There's some good trade offs.
Speaker 2:There's some bad trade offs. But his whole thesis was like, hey, can bring it back with cloud seeding.
Speaker 3:The bad trade off is the land just became incredibly toxic.
Speaker 2:Fallow. Yeah. Exactly. So you can't grow anything. There's still a couple people that live out there.
Speaker 2:It's pretty it's a pretty crazy life. Like, it's mostly just like a tourist destination. People go see it. But it was it was very interesting like like concrete example of like the rainmaker promise. And so we had a good time.
Speaker 2:We did a we did an energy drink tier list, which was very fun.
Speaker 3:Yeah. Somebody sent me that recently. Yeah. Oh, it's classic. Apparently It's classic.
Speaker 3:Sean in the chat says Slab City is out there. The Slabs.
Speaker 2:The Slabs.
Speaker 3:Unincorporated off grid alternative lifestyle community
Speaker 2:Yeah.
Speaker 3:Consisting largely of snowbirds in the salt and trough area.
Speaker 2:Interesting. But yeah, I I we we filmed this and I was like, I don't know if this is like a full video. There's not really a full story. This is just like a hangout session. But then when it became clear that he was that although he was the CEO of Rainmaker, he was also this Gundo super connector and there was this interesting movement happening in El Segundo.
Speaker 2:I I reframed the video to be about the El Segundo movement broadly, and he was like a main character in that story, and then that video did very well.
Speaker 3:Then Well, didn't you kinda didn't that kind of kick off the this the the like hype cycle?
Speaker 2:I was a link in the chain. I was like I think I was like
Speaker 3:He kicked off the hype cycle.
Speaker 2:No. I was no. No. No. There there were a few others because Scott Nolan wrote Thank God for El Segundo in Pirate Wires and there were there was maybe like one other substack who had written about it.
Speaker 2:And then, of course, there were a bunch of posts. And then And then that
Speaker 3:were actually
Speaker 2:Of course. And they did the whole thing. And then and then was it? I'm gonna I'm gonna forget who it was, but it it but there were a whole bunch of of traditional media folks that came in and and wrote really interesting profiles and kinda told the story. It was a lot of fun.
Speaker 2:Anyway, Figma. Think bigger, build fast. Figma helps design and development teams build great products together and get started with Figma. OpenAI has declared code red multiple times. Bloomberg is reporting, an executive said this, OpenAI has declared code red multiple times.
Speaker 2:It's not a code red if you it's code red every day at your company. You know what? Nowhere else it's code red? Right here.
Speaker 3:Code red? Code red? Yeah. We heard
Speaker 2:this code red. Yeah. It's code red. Everyone, put on Santa outfits. It's code red time.
Speaker 2:Santa's sack is red, the reindeer, the sleigh, these things are red. He was just getting into the Christmas spirit, guys. It was not anything about the business. It was not anything about the shaky ground. The real question that Rachel Metz over at Bloomberg will have to get to the bottom of is, okay.
Speaker 2:So there's been multiple Code Reds at OpenAI. How many Baja blasts have there been? Because we know that after every Code Red, there is an equal and opposite blah Baja blast that gets the What
Speaker 3:is is a what does success look like for Code Red? It's a blast.
Speaker 2:It's a blast. Blasting your way to the top of the charts, the top of the benchmarks, the top of the fundraising, cycle. So Rachel Metz over at Bloomberg says, Sam Altman's decision to declare a code red at OpenAI earlier this month may have caught the industry's attention, but it wasn't the first time that the artificial intelligence company has done a code red. The San Francisco based startup leaderships has made the same decision previously explicitly instructing employees to drop lower priority tasks and concentrate on a single goal. I'm telling you, it's entirely a comms issue.
Speaker 2:If so so, Mark Chan is on the record here. He says, we do this when we want to have this focusing effort on one particular topic. Mark, there's a phrase for this that doesn't turn into a negative press cycle. It's called a lock in. You just tell everyone
Speaker 3:great lock in.
Speaker 2:It's time for the great lock in. And if you say OpenAI declares it's time for the great lock in
Speaker 3:That's exciting. Everyone's excited. People are gonna rally around that.
Speaker 2:Everybody's gonna go through the roof and just be like, this is so bullish. This is so bullish. It's so bullish because you can be at the top of your game, and if you declare a great lock in, everyone's just like, oh, no.
Speaker 3:Oh, no.
Speaker 2:It's gonna be even better.
Speaker 3:They're gonna they're gonna go even harder.
Speaker 2:But if you declare it's code red and you're at the top, open eyes they're literally at the top of the app charts. They're, like, the best. Right? Like, they're on so many things. They're at the top of the benchmark.
Speaker 2:They're everything's going very well for this company. But when they declare code red and it leaks, then it makes you feel like, oh, maybe something's not going so well. If you declare a great lock in, you're good to go. The latest code red came two weeks after Alphabet Inc's Google released a widely praised new AI model that outperformed OpenAI's best software on a number of benchmarks. OpenAI's same old man called for staffers to redirect internal resources to speed up improvements to ChatGPT and delay progress on all other efforts such as autonomous AI agents and advertising.
Speaker 2:So they delayed ads. Very rough for us as as as fans of advertising. Speaking of advertising, graphite.dev. You think we're not gonna do an ad for graphite even though we had Merrill on the show? No.
Speaker 2:We still do the ad. We have respect for advertising. Code review for the age of AI. Graphite helps teams on GitHub ship higher quality software faster. What it means to me this is from Mark Chen.
Speaker 2:He says, what it means to me is on chat, on reasoning, on the core g ChatGPT product. It is this focusing effort to make sure we get the fundamentals right, Chen said. That includes ensuring the chatbot works quickly and reliably. I think hot take, maybe 2026 is the year of speed. Maybe maybe customers cannot tell the difference between a 120 IQ chatbot, a 130 IQ chatbot, a 140 IQ chatbot.
Speaker 3:Tell the difference? Speed. That's right.
Speaker 2:If they if they have to close the app, come back five minutes later, oh, my deep research report is here. I think the model's plateauing on wowing me with the they're already AGI is here. Like, they're already super geniuses at everything. They already know everything.
Speaker 3:Well, There's super dollars. What, Michael from Kerser was saying.
Speaker 2:Oh, yeah.
Speaker 3:He was like, speed. We're focused on speed.
Speaker 2:Yeah. Speed, I think, is gonna be really important. I mean, that's the weird thing about the Cursor. I mean, learned this from the Chad IDE saga was like, we wouldn't even have the opportunity to put brain rot and gambling in the IDE if you weren't waiting around for the IDE to respond and and actually get back to you. So I I I think speed in the IDE, speed in the chatbot.
Speaker 2:We've seen this nano banana really, really fast. ChatGPT images v two. I forgot exactly what number it is. I think it might be one point But the the latest iteration that came out this week, much faster, giving people more responsive results, updating them, even just what DeepSeek did where it was showing you the reasoning trace, showing you that the model is thinking. All of these are UI, UX decisions, and then a lot of engineering, a lot of custom silicon.
Speaker 2:Anything that you can do to bake the model down into silicon and just get it back to the user faster, that's gonna that's for sure going to result in, I think, lower churn. I think more surprise and delight moments. Just more usage, more willingness to pay. Before we move on, let me tell you about Vanta. Automate compliance and security, AI that powers everything from evidence collection and continuous monitoring to security reviews and vendor risk.
Speaker 2:I like that.
Speaker 3:Max Zaff, senior writer covering AI at Wired Mhmm. Says, in a letter to the White House sent this AM, this was yesterday, OpenAI encourages the federal government government to invest in or contract with initiatives like OpenAI Stargate to secure compute for public research. The full thing is leverage public private partnerships for supercomputing. We encourage the federal government to co invest your contract with initiatives like OpenAI Stargate to secure dedicated compute for priority public research. I e health research, national security.
Speaker 3:Just as government university partnerships built earlier supercomputers, new models could procure capacity on cutting edge AI systems for use by federally funded researchers. For example, a portion of Stargate's compute might be made available to the National Science Foundation or Department of Energy researchers tackling grand challenges, providing academia access to frontier models without needing to build duplicate infrastructure. What what do you think, John? Because obviously, are gonna dunk on this But super there there's, you know, people that are just not interested in AI, don't think it's important, don't think
Speaker 2:Show me the big tech company that doesn't wanna work with the government. Yeah. Like, it's a knockout, drag out fight to win project Maven, to win cloud hosting contracts. The government has data right now, and the fight between whether that data is stored on AWS, Oracle, Google, yeah, Azure, like, that is a somewhat of a bidding war, but there are also all sorts of other lobbying efforts to win those contracts. It's the game on the field.
Speaker 2:I I I don't I don't know. I feel like this is not this is not asking for a backstop. This is also not asking for nationalization, although it is, like, somewhat predicted in 2027. It's it it it it feels more like like like an advertisement for a sales product. This feels like an SDR being like, I'm ready to I'm ready to rock.
Speaker 3:Yeah. And I think even for taxpayers, do you want the government spending, like, basically taking on the project themselves to build an end to end supercomputer? And how good would result be versus just saying like we need Yeah. Compute for these projects.
Speaker 2:The real question is like what is the government doing with the supercompute? Because when we talked about the Genesis mission, there was a little bit of like, does it go to does it go to academic labs? Like, what is the nature of the supercompute need in the government? There's been there's been a number of, like, supercomputers built for various scientific projects. None of them have had, like, such economic value.
Speaker 2:You know? So, like like, the the classic example is, like, the like working on protein folding, working on, you know, deep space exploration, sort of fundamental physics, usually bolted onto like a
Speaker 3:The chat says, backstop?
Speaker 2:You think they're continuing for the backstop?
Speaker 3:Well, mean, in some way mean, so
Speaker 2:Okay. Backstop gate's over.
Speaker 3:So slightly more critical
Speaker 2:Let's Should we can we reconsider backstop?
Speaker 3:Slightly more critical view.
Speaker 2:Yeah.
Speaker 3:OpenAI and all their messaging says we're we're compute constrained and we're compute constrained. If we brought on 10 times the compute, we'd use it in a few weeks. Yeah. We we there's all these things that we can't do because we don't have enough compute. And so to also be messaging the government and saying, hey, we'd like you to invest and buy effectively buy capacity for government researchers from our data centers.
Speaker 3:Those things are you can you can balance them, but
Speaker 2:It's a little hard to do.
Speaker 3:It's a little bit hard to.
Speaker 2:Yeah. It's like I I mean, you you in one way, you don't necessarily want another buyer of GPU capacity in the market, like, just from a supply and demand side. You you like, if you are trying to buy data center capacity for your AI lab that's growing, growing, growing and is truly compute constrained, the last thing you want is someone else being like, I'm also a buyer. And you don't want the government being like, I'm also a buyer of of compute. You want you want more supply coming online.
Speaker 2:So I mean, if you can ultimately frame this around that, it makes sense. But I just think I would be going to the government with completely different things. I would be going to I would be focused entirely on speed of deployment, unblocking anything that's happening at at at Stargate. Because when we talk to Doug O'Laughlin, it feels like AWS is really, really good at bringing compute online. We've seen how good XAI is at it.
Speaker 2:I'm sure that the folks on the other projects are running into minor little hiccups, whether it's permitting or or getting enough energy or, you know, how is the government dealing with, like, impacts of water usage and energy usage and even just, the political climate. Like, I would I feel like I'd be focusing more on that than actually trying to just bring another buyer into the compute race that that doesn't fully fully say. But
Speaker 3:Yeah. From this letter to the OpenAI writes, OpenAI sees twenty twenty six as the year of AI and science, the moment when AI begins unlocking breakthroughs in scientific discovery just as it sped up software development in 2025.
Speaker 2:Mhmm.
Speaker 3:More than seven in 10 Americans believe we need new innovations and solutions to challenges in scientific and medical research, and they kind of go on kind of setting up setting up the the kind of ask.
Speaker 2:Yeah. I yeah I wanna know more about what what are the most exciting science projects that aren't going to happen, like AI for science that aren't going to happen inside industry. Because the AlphaFold Nobel Prize is a it feels like a crucible moment for science in that science was effectively successfully done at a private corporation. And if that's the trend, then what is the government's role? What is the university's role?
Speaker 2:Maybe it should just be a race between Google and OpenAI to actually cure cancer and obviously the other pharmaceutical companies and all sorts of health companies. I'm are
Speaker 3:laughing because Brandon Jacoby texted me and said, listening to the show while working out, the sheep sound almost made me drop a dumbbell on my head from laughing. It's a goat sound, It's a goat sound. It's
Speaker 2:a goat sound.
Speaker 3:Obviously, it's a GOAT sound. I use that when someone is showing greatest of all time sort of behavior or general excellence.
Speaker 2:Well, we are joined by Pranav, who we were supposed to have on the show earlier. We were overbooked. We're gonna talk about space data centers. If we're not, you know, maybe the government should buy some of those. We'll see.
Speaker 2:We'll find out. Well, Pranav, welcome to the show. Thanks so much for bearing with us while we had to reschedule you. We appreciate you taking the time to chat to chat with us on the last show of the year, Friday, December 19. Would you mind It's an honor.
Speaker 2:Off with a little bit of an introduction on on yourself? And then I'd like to go into the project, then we can ask some questions about space data centers, is the the topic of the of q four twenty twenty five.
Speaker 8:Yeah. Well, of course. Well, first of all, I wanna say thank you so much for having me on here. And what a group of handsome young men we have here today. Space data centers.
Speaker 3:I mean, you're looking at Tyler here is the youngest and the most handsome, so he's off camera, but he's here. Look at him. Look at him. Look at him. Look at our look at our little
Speaker 2:Oh, he still has the Giga Chat filter on.
Speaker 3:That's crazy.
Speaker 2:That's a little more subtle, but definitely filtered.
Speaker 3:Definitely still on.
Speaker 2:Yeah. Hey, I'm sorry. You you were saying?
Speaker 8:Space data centers. Yes. Fundamentally, if you're betting against space data centers, you're betting against compute to grow. Okay. So we're constrained on Earth by land, water, and power.
Speaker 8:Mhmm. And our human minds haven't evolved to understand just how much space there is Mhmm. In space. So, as you look at these things like these you know, Google and Microsoft, for example, have hundreds of millions of dollars of GPUs just like sitting around and collecting dust.
Speaker 2:Mhmm.
Speaker 8:And this is like probably surprising to some people not in the energy industry, which is my background.
Speaker 2:Wait. Wait. Wait. Hold on. So so you're saying they have they have hundreds of millions of dollars of GPUs sitting around because they can't get enough power for them?
Speaker 2:Yeah. Wow. Okay. Continue.
Speaker 8:Yeah. And there's so much, like, cost involved in that. Right? Like, the GPUs might get old, and they they have to get new GPUs. And there's so much risk that a lot of these models haven't factored in, and even mine hasn't factored in yet.
Speaker 8:So there has been a little competition, you know, a little model that came out, and I'm making
Speaker 2:It's the model wars. The space data center model wars.
Speaker 8:I'm making a pretty big update to my model today, and one of my idols is gonna share it around, and we'll hope that a certain someone gets to see it, take a wild guess on who that is.
Speaker 2:Yes. Yes. Yes. You were very prolific with your tagging. It was it was it was a good strategy.
Speaker 8:Went Oh, there's there's a few more points I had There's a few more things I wanna spice up there, but we'll get to that later. Sure. So my background is in energy, and a lot of people not in energy don't know probably don't know this, but everybody projects the cost to rise and only rise, you know? And as we, like, have more data centers, we run into more constraints with the ground, like, again, land, talent, because you need to like put talent in in all these like different places instead of creating these factories and just like shooting them up to space. And then power and then water.
Speaker 8:Right? There's only such a limited amount of that that we can have on Earth, and we have so much more ability to do that on space. So if you don't believe that there's gonna be like an AI revolution, if you don't believe that compute is gonna grow exponentially, you don't believe in like
Speaker 3:yeah. So so I guess part of the debate is, that's important is I haven't seen anyone that says we will never have large data centers in space or we will never have a lot of compute in space. I feel like the debate debate has been much more centered around the timeline. Is like Yeah. And is it a three to four year thing?
Speaker 3:Mhmm. Is it a ten to twenty year thing? You know, what what is the timeline?
Speaker 8:So the timeline, I think, like, Elon had a tweet the other day which said, doing AI like, localized AI inference on the satellites will get them to be the lowest cost way to generate AI bit streams in under three years. And I was working on independently validating that, and I'll like send out the the model later today. But I think it can be earlier than that. You can actually like send you have so much better constraints on space. Like, constraints really ease up on space.
Speaker 8:A huge part of the energy used in ground is cooling. A huge part of it is, like, the power. You know, the same solar panel you have on Earth gets so much more utilization in space. So inference, I think inference will be coming on to space very fast, a lot faster than a lot of people think. And then another thing you guys talked about is speed of the models, and that models are plateauing, and that speed matters.
Speaker 2:Mhmm.
Speaker 8:So if people really believe in that, ground data centers, if you're close to a ground data center, it would be the fastest. But to the 80% of the world that's like non The US, non Northern Virginia, not in like DFW, there is a huge need for the latency.
Speaker 2:Yeah. I like that. So
Speaker 3:wait Can you talk about heat dissipation and cooling that Brian in the chat's asking? And I feel like that's been a big question again that keeps coming up.
Speaker 8:Yeah. So there is a huge problem with heat dissipation. That is the constraint that we go up against first.
Speaker 6:Mhmm.
Speaker 8:Right? And the reason for that is heating and cooling on ground works very different than cooling in space because space is a vacuum. Mhmm. So on ground, you have like fans and stuff and you have convections. You you have mediums to pass this heat through.
Speaker 8:But in space, you don't have that. Right? So you have to do passive cooling, and you do that through radiators. And these radiators are, like, these really big and, like, really complex systems, and they there's this thing called Boltzmann's law, which basically means, like, the higher temperature you can make something, the better it is at dissipating heat, but there's a limit to how high the temperature you can make the radiators in space. And the reason for that is, you don't wanna get it too high such that you'll melt the GPUs.
Speaker 8:Right? So the
Speaker 3:You wanna melt the GPUs with, you know, image requests.
Speaker 8:Yeah. Yeah. That that's what we're hoping for. So, like, the current designs that we have in Starlinks are, like, solar panels on one side and then radiators on the other side. But there's no reason to believe that, like, that will be the enduring case.
Speaker 8:You know, radiators are a hard problem to solve, but, like, the physics has worked out. It's the engineering, you know, the arcing, like, the power electronics, all that kind of stuff that we need to figure out in space, but that's an engineering problem that will definitely be solved. So what we'll see is, like, these deployable structures, which are, like, radiators that are, like, folded inside, and then they go out in space, and then they they, like, fold out and deploy. And those will be, like, dedicated radiators and, like, dedicated solar panels. Like, thermal is the biggest constraint, but there's no no reason at all to believe that it won't be solved.
Speaker 2:Okay. Walk me through your assumptions around the progress of just getting mass to orbit. I assume that your model, you know, expects Starship to be massively successful and scale very quickly. But if if if progress in space in the space industry stagnated, essentially, you know, we get stuck with Falcon nine, Falcon Heavy or something, that would be pretty bad for the model. Is that right?
Speaker 8:Yeah. That would be bad for the model, but that's like another thing. You know, let me stoke the flames of the model wars a little bit. Yeah. Okay.
Speaker 8:That's another thing that the other model didn't take into account is these learning rates. Right? Like, it costs $60,000 a kilogram with a space shuttle, and Falcon got it to like 1,500. Okay. And, you know, if if we Like, for example, if we modeled that computers were gonna stay the same level as they did in 1980
Speaker 2:Yes.
Speaker 8:We would have like a 100,000,000 times more. Yes. Like, they would be a 100,000,000 times more expensive than they are today. And I know someone else, Deleon came on the show a little while back, and he talked about how he hasn't seen a compelling argument for data centers in space. I tagged him, I DM'd him.
Speaker 8:We haven't heard a response yet. I'll send out the model, like, updated model
Speaker 2:over course the clip too and Yeah. We'll see what But he so so I I wait. Hold on. Hold on. I I so I actually agree with you.
Speaker 2:I I I don't believe in stagnation in in, in mass to orbit. I I do think that Starship, although there have been some, you know, minor setbacks, I think it's gonna be a massively successful product. I think it's gonna grow exponentially, and I think we're gonna be able to put a lot of mass in orbit very quickly, especially if we have something good to put in space like a data center. I'm a believer in that. Now what I'm what I'm interested in is, like, what if we are fundamentally in the really, really good timeline, and not only is AI unstagnated and space travel is unstagnated, but what if nuclear fusion and power generation on Earth is unstagnated and we see nuclear power become 10 times cheaper?
Speaker 2:Does that break the model just on a competitive basis? And it's like, it's amazing. We can get to orbit really cheap, but we can also get really, really cheap energy here because all the nuclear folks, who I'm sure you've seen come on the show from time to time, everything that they're doing is working too, and so energy on Earth is, like, way cheaper than what we thought. Mhmm.
Speaker 8:Yeah. So we have a mutual friend, Robin Langtry of Avalanche Fusion.
Speaker 1:That's
Speaker 8:right. And I was talking to him. He was helping me out, and this is what I'm modeling right now
Speaker 2:Okay.
Speaker 8:Which is fusion data centers in space.
Speaker 2:What? Wow. Okay. Let's go. Yeah.
Speaker 2:Because I mean Sam is an investor in Helion too, and and so that you you could imagine that he's thinking about energy, you know, years and years in advance.
Speaker 3:Are you considering volcano data centers? Volcanoes? Active volcanoes. Geothermal?
Speaker 8:Well, that is space con like, that is land constrained. You know, there's only a limited number of volcanoes. But there's a lot a lot of space.
Speaker 3:How are you thinking about have you tried to more precisely identify what the launch cost would be of like a single satellite that's capable of inferencing a model for use on earth? I'm I'm trying to you know, there's new parts, right, panels Yeah. Radiators. Yeah. It's, you know, this the basically the racks themselves.
Speaker 9:Yeah.
Speaker 3:And I I feel like that's, hard to, know exactly, but you can probably just zone in on it.
Speaker 8:Yeah. A 100%. So if you look at the, the simulator I made, and then you you go ahead some years, you can go to the sandbox and change some of the parameters, Then you can look at the physics and limits tab, and it breaks down the mass per satellite. So it breaks down, like, the panels, the radiators, all the other components that go into the satellite, and then it breaks down it down as, like, a percentage. So you can actually see and visualize, like, all those components.
Speaker 3:Very interesting.
Speaker 2:What else has to happen? How are you thinking about understanding the fiftyfifty point? Me and Jordy were going back on, is it one gigawatt of capacity before 2028? That I think that would impress both of us. Mhmm.
Speaker 2:Would that impress you? Or is that is that your base case? Like, take me through some, like, how you're thinking about the future development of this. I think we're all we're all on the same page that, like, it's feasible. It's possible.
Speaker 2:So the interesting question is how fast can it actually ramp? Because there's certain things like, you know, Starship just has to, you know, be reliable and they have to build a lot of them. And there's some, like, rate limiting factors that might just act as, like, little natural breaks. I mean, it's at a certain point if, like, TSMC runs out of capacity, like, okay, you can't get any more chips. There's all sorts of different shortage points.
Speaker 2:But how are you thinking about the the scale and scope of of data center space compute in kind of the medium term?
Speaker 8:I it's hard it's hard to say medium term. Yeah. It's like like, you know, it's it's hard to you see somebody, it's hard to like predict how their next day will go. Yeah. But you can predict how their next year will go.
Speaker 8:Sure. You know? And this is like a longer scale. So it's hard to predict the next few years
Speaker 2:Yep.
Speaker 8:But over the next decades, there will be hundreds of gigawatts in space. I am sure of that. Sure. And like
Speaker 3:We will we will clip this. It will either you will either you will either look like super genius and be immediately hired by Elon or or or you'll be Probably already be No. No. There's some there's some middle ground. I'm I guess, one one question is who
Speaker 2:who Yeah. Sorry. Go. Go.
Speaker 3:Go for it.
Speaker 8:Oh. For some context Yeah. There's like 20 like, over 2,000 gigawatts sitting in the interconnection queue right now, and that's like almost two times the entire US grid capacity, like just waiting for paperwork. I mean, the biggest threat to AI is really like a guy named Doug at the county permitting office
Speaker 2:Yeah.
Speaker 8:Who hasn't been there in three weeks. And space isn't like constrained in that way.
Speaker 2:The permitting thing is crazy. I mean, it is much easier to sort of do business in space, it
Speaker 3:seems How do you do you predict the market will evolve? Do you think anybody can actually compete with SpaceX here? What do what do you think about Star Cloud? Do you think like Core Weave is eventually like, okay, I guess we gotta go to space now. Yeah.
Speaker 3:Yeah. It's hard enough in Abilene, but I guess you're going to space.
Speaker 8:Yeah. So Star Cloud, I think they're doing really interesting work, and I'm really interested in seeing what they what the results of their their stuff that they're doing right now is. Because if the results are that these chips that they put out in space without, like, rad hard, without a lot of, like, rad hard measures Mhmm. Are functional, then we can get there, like, a lot sooner than, even my projections.
Speaker 2:Interesting.
Speaker 8:And then when you look at, so you said Tesla and Core Weave. So to go on the CoreWeave point, I think just like the way that space and compute has been, what's it called calculated and the cost of compute has been calculated, it needs a complete overhaul. So, like, I so someone else did, dollars per, watts of power. I did dollars per compute, but I think the best way is dollars per GPU hour with SLA, so like service level agreements. So a lot of it is just like taking into account the capex or whatever, but it should take into account capex, hardware amortization, replacement rates, maintenance rates, opex, and all these kinds of factors.
Speaker 8:So like you can think of, power as like if you're a car factory, power is, you know, how much you expect, like, the car like, the the throughput of steel to be. And then the, compute is like how much you expect like, how much cars you expect to come and the cost per that. But what the best measure is is the lifetime of a car, seeing the OpEx of that, the maintenance of that, the gas cost of that over its, like, entire lifetime. Right? And that's the best way, to model these things, and I'm gonna come out, with a white paper about this.
Speaker 8:But this is, like, really important, and a lot not enough people are talking about this at all. And on Tesla, it's yes. It's really hard to imagine, how this might look without huge vertical integration. I'll say that.
Speaker 3:How are how are you trying to calculate, depreciation rates? This is already a debate on planet Earth, and I could imagine in a different environment, you could have, you know, maybe be surprised to the downside, you know, needing to depreciate GPUs faster or who knows? Maybe there's some
Speaker 5:Yeah.
Speaker 3:Some upside Yeah. To it.
Speaker 8:So part of it is like Moore's Law. So Moore's Law is hitting its physical limits right now in terms of how many transistors you can put on a chip, but there's architecture changes that you can make that can make it better. But I'll actually throw a curveball at you guys. Something that people have been talking about. I think the future is not, you know, just AI and like orbital data centers.
Speaker 8:It's optical orbital data centers. It's photonics. Woah. You know? And photonics are like They're so good at matrix multiplication.
Speaker 8:That's like inherent to their to what they do. And the space And like the heating constraint is like way lower by 10 to 20 times because you can you can think about like these electrons moving in electronics. It's like you're you're pushing like a a heavy box like through like a rough floor and it's like interacting with all the mediums and like causing all this friction and heat. But when you have optical stuff, it's, like, going through waveguides, and it doesn't interact with the medium as much. Mhmm.
Speaker 8:And photonics, it's very, very early, but this will a 100% be the future.
Speaker 2:So, type different of chip. When you say photonics, you don't mean like optical cables between satellites physically like the drones in Ukraine that are like physically wired to each other?
Speaker 8:No. Those are great.
Speaker 2:Different chip in space, same constellation of Starlink.
Speaker 3:We we might need some we might need some financial innovation here if we could if if we need a lot of debt to finance these space data centers. If the debt goes bad, maybe we could attach some rocket boosters to it and just blast it out.
Speaker 2:Yeah. How's
Speaker 3:Deep into the yeah. Just put it put it Sun. Yeah. Send it sends it into the sun.
Speaker 8:That's actually We'll see we'll see
Speaker 3:I feel like I'm working on putting Dyson sphere actually.
Speaker 2:I am going to the sun.
Speaker 8:I actually am.
Speaker 2:Yeah. We Wait. Are you really gonna build the Dyson sphere model? What what it will take? Yeah.
Speaker 2:Are you are you over are you Dyson sphere before 2100 or after 2100?
Speaker 8:I I like to go by the math first. So I'm still trying to get the math and physics right. Okay. But you will definitely know.
Speaker 2:But gut intuition before or after? Just gut.
Speaker 8:I'm an optimist, so let's go before.
Speaker 2:Let's go. Let's ring the gongs. Let's go. Well
Speaker 3:This was super fun.
Speaker 2:This was super fun. Thanks so much for coming on the show.
Speaker 3:I got a feeling I got a feeling you're gonna bait the the the Elon repost.
Speaker 2:He's gonna come for it.
Speaker 3:I think he's gonna come in hot, but
Speaker 2:No. It's not the yeah. Yeah. Yeah. The repost.
Speaker 2:The the the quote tweet interesting. The quote tweet this is this is true.
Speaker 3:Yeah. Or the quote tweet thumbs up. Any
Speaker 2:day now.
Speaker 3:Anyway, super super fun conversation. Great to meet you. We'll talk to soon. Excited to see more of your work.
Speaker 8:See you so much.
Speaker 5:Cheers. See you guys.
Speaker 2:Gemini three Pro, Google's most intelligent model yet. State of the art reasoning, next level vibe coding, and deep multimodal understanding. We have our next guest already in the restream waiting room. We have Anna Goldie from Recursive Intelligence. How are you doing, Anna?
Speaker 2:Welcome to the to the show.
Speaker 9:Thank you. Thanks very I'm excited to be here.
Speaker 2:Thanks so much for hopping on. I'd love to start with a little bit of your background. There's a whole bunch of interesting milestones here. Would you mind introducing yourself since it's the first time on the show?
Speaker 9:Yeah. Sure. Happy to. I guess we could go way back. Oh, sure.
Speaker 6:I was
Speaker 9:a I I studied computer science and linguistics at MIT, and I did my PhD at Stanford in, like, Success. AI learning. And actually, my first job, I worked at TripAdvisor on the China team. So I did my did full stack web development in Chinese. Yeah.
Speaker 3:Wow. In Chinese. Crazy. That's
Speaker 2:it's like
Speaker 3:I guess, we'll start with the easy stuff. Put together. Now now
Speaker 9:Yeah. We can do this segment in Chinese if you want.
Speaker 2:I would be lost, actually. I took one semester of Chinese and I was terrible at it. I only knew how to ask if you want a coffee.
Speaker 3:I'm gonna test your Chinese because I don't want you to test my Chinese. Do
Speaker 2:you know what that means?
Speaker 9:Yeah. You like beer. You really like beer.
Speaker 3:Nailed it.
Speaker 9:Nailed it.
Speaker 2:Perfect. Yes. Yes. That phrase alone
Speaker 3:That could take you anywhere. Anywhere. In China.
Speaker 2:Anywhere in the world, potentially. So, yeah, it it take me through some of the the the first interactions with artificial intelligence, AI teams, chip design, any of that. Like, how how did you go from I mean, Tripadvisor, I don't think they've baked it onto an ASIC yet, maybe in the future. But, how did you get into AI?
Speaker 9:I guess, like, the reason I went into computer science is because I wanted to work on AI. Like, when I was in high school, I had no idea what I wanted to do when I grew up. And then I heard this lunch lecture at MIT about, like, computer systems, like, that could understand and generate human language, like, in 2004. And then, like, that's why I, like, went to MIT to study computer science, and that's what I've been working for since then. I joined that professor's lab, actually, at MIT.
Speaker 2:Oh, no way. Very cool.
Speaker 9:Open language systems group. Yeah.
Speaker 2:That's great. And and then, yeah, what were you doing right before founding the company?
Speaker 9:So I guess I can yeah. I joined Google in 2013, Google Research. Was working on, like, language modeling.
Speaker 2:Yeah.
Speaker 9:And then I joined Google Brain in 2016. I started a team there with Azaliy Amir Hosseini on, like, machine learning for systems. Like, how can we use AI to design better computers chips and computer systems?
Speaker 2:Okay.
Speaker 9:Because our our reasoning was that, you know, chips are the fuel for AI. Yeah. And so if we could use AI to sort of advance the state of computing, we could kind of, like, close this recursive loop.
Speaker 2:Mhmm.
Speaker 9:And we did a variety of projects like Alpha Chip there.
Speaker 2:Foreshadowing, the name of the company. I don't know if you wanna jump ahead, but but take me through the rest of the career.
Speaker 9:So, yeah, we we also worked at Anthropics. I was an early employee there. Sure. I had the privilege to like, I'm joining, like, before ChattyPT and Claude were released even. Wow.
Speaker 9:So I got to work on, like, RL post training, cogeneration. It was, like, an amazing experience. And I see that
Speaker 2:How is the team thinking about I mean, how are you at that point in time, pre ChatGPT, how were you thinking about custom chip development, how important that would be how how important that would become, how much flexibility you would need in the chip architecture to kind of advance the research progress before, like, actually committing to a particular pathway.
Speaker 9:I guess, like, maybe part of some background here is Yeah. That it it takes two to three years now to design like a like a chip, like a TPU that's very complex. Yeah. So when you're designing that chip, you kind of have to predict, like, what AI models or workloads will be prevalent in two to three years. So we can't really do that because the technology is advancing so quickly.
Speaker 9:So in practice, you're kind of designing chips for current models Yeah. And you're leaving a ton of performance on the table. Yeah. Like, team, we ran some experiments where we were designing, like, hypothetical accelerators Yeah. For particular machine learning models.
Speaker 9:And, like, you could get, like, almost like a 10 x improvement in perfect total cost of ownership by doing even naive customization of the chip with the model and, like, not even being able to change the model.
Speaker 2:There a
Speaker 3:little Yeah. Bit of a
Speaker 2:is there a little bit of a, like, shoot
Speaker 1:for
Speaker 2:the moon, you'll land among the stars effect going on right now? Because I know that there were a number of companies that they did exactly that. They tried to predict, okay. I think that we're gonna need a ton of memory directly on the chip for this design or we need to go wafer scale or we need to do something else. And and they maybe didn't pan out to be the the dominant form factor.
Speaker 2:Factor. But then and and I and I at least the narrative has been like, oh, those those companies are kind of written off. And then I'll talk to some lab, they're like, well, we actually found an amazing use for that particular thing, and we baked this model down. Now we're using a ton of that stuff. And so it feels like these ASICs, like, is the correct framing that it is important to get it right in the real you want to land on the moon, but there are sometimes are uses for chips that have been designed with they didn't quite land exactly where the research direction went, but it's still useful in a niche capability.
Speaker 9:Yeah. I think that there are, like, landings for some of these specialized bets. Yeah. I would that, you know, part of the reason that, you know, we're so excited about this company, Recursive, and, like, shorten the timeline is I think we can enable, like, many, many more of these bets to to really land. Yeah.
Speaker 9:There's a huge space of chips that could exist and maybe should.
Speaker 2:Yeah. Yeah. That well, that's a good place to jump into the current the current business. I'd love for you to introduce it, formally in terms of how how you're framing the the the opportunity.
Speaker 9:Okay. For the company?
Speaker 2:Yeah. For Recursive.
Speaker 9:Yeah. Yeah. Recursive. So we're AI for tip design and tip design for AI.
Speaker 4:Mhmm.
Speaker 9:I guess we see the company in three phases. Yeah. So I could describe those.
Speaker 3:Please. Great.
Speaker 9:Yeah. So I guess first phase, let's accelerate the chip design process. Let's take the long poles on. So Mhmm. Physical design, for example, designing the layout of the chip given fixed logic, that can take up to a year for a chip like a TPU.
Speaker 9:And then design verification. So basically verifying that the high level specification is correctly implemented in the RTL code. That's also another long pole. So in this phase, like, we can help chip design companies, like, get to market much faster. Like, maybe it doesn't need to take two to three years.
Speaker 9:But if you could do it in in phase two, though, we would be like to go end to end. Given a machine learning model or a set of machine learning models or other workloads, can we design, like, the computer architecture and, you know, design the chip all the way to DDS two, which is a format you've sent to TSMC for manufacturing? In that in that case, we could help many more companies design custom chips for their particular workloads. Even if they don't
Speaker 3:Maybe on that point, do you know how many, like, customers TSMC has today versus how many you think they'll have in the future?
Speaker 2:This is exactly my question. Like, how many how many customers are there?
Speaker 3:We see it 100 x ing
Speaker 2:Yeah.
Speaker 3:10 x ing.
Speaker 2:Because we really only hear about, like, three most of the time. Like, the news headlines are training in Yeah. GPU and and NVIDIA GPUs. But I imagine that there's a ton more now, but it also feels like you're predicting and your company's sort of a bet on, like, a Cambrian explosion. Is that roughly correct?
Speaker 9:Yeah. That's right. Mhmm. We think that there can that there are companies that have workloads that they're serving at massive scale. Like, this year, the AI inference market is a $100,000,000,000, but it's, like, rapidly growing.
Speaker 9:We think AI is gonna be everywhere in embedded devices and also in data centers. Yeah. And if it didn't take two to three years and if a company didn't need teams of hundreds or thousands of human experts to design their own chips, then we could massively expand the the market here. Yeah. It's pretty interesting.
Speaker 2:Heard an anecdote. I don't remember which company it was, but there there was a cloud cloud hosting, like a database company that was shifting their database workloads, not AI workloads, database workloads to GPUs to accelerate them just to speed them up. And so across the stack, every piece of software, there's always an incentive to just push to a more, like, guess, electricity efficient or just just more cost effective, you know, hardware at some point.
Speaker 9:That's right. Because, like, electricity or power consumption dominates the cost of of running things on on chips. I I guess that's why I brought it up earlier that, you know, we had run some just very initial experiments and you really could get way better power efficiency by cut using custom hardware. The GPUs are amazing, but they're pretty general purpose. They were developed for graphics processing, so it seems very surprising that they would be the best fit for AI models today.
Speaker 9:And I don't think so.
Speaker 2:So if you're a, you know, database company or or, you know, any piece of software that then is being transformed by AI, and then in the future, you might be transformed by by custom silicon or custom silicon's in the road map, and it's maybe getting closer, How much does it cost today to develop custom silicon, a custom chip, work with TSMC? And then where do you see that sort of going over the next few years?
Speaker 9:I mean, it's extremely expensive design design a chip, both in terms of, like, labor
Speaker 2:Thousands of dollars, tens of thousands of dollars. Like, I I Like,
Speaker 9:it would be more than that.
Speaker 2:Like, to save up for this for weeks? It's like hundreds of millions. Right?
Speaker 9:Yeah. Hundreds of millions.
Speaker 3:Okay. That's a lot.
Speaker 2:Yeah. Yeah. Mean, certainly not something that even even a unicorn software company would maybe not be able to marshal the capital for that just at the drop of a hat, especially if there's risk involved. Right?
Speaker 9:Exactly. Mhmm. Also, it's just the timelines here. It's two to three years potentially. Sure.
Speaker 9:Like, for a complex chip. Mhmm. And, like, you have to build out that in house expertise. Yeah. And there's risk.
Speaker 9:Like, maybe you just won't ever be able to close timing or power and you just can't build the chip.
Speaker 1:Yeah. Can
Speaker 3:somewhat random, but I wanted your take on the Reuters reporting how China built its Manhattan project Mhmm. To rival the West in AI chips. They allegedly have built some type of EUV prototype. How real is that? I never I never know if if it's hard to know what's what's real, what's what's propaganda or what's what's actually a scoop.
Speaker 9:I I think I and although I speak Chinese, I don't have any special insights here into whether that news reporting is true or not. Certainly interesting.
Speaker 3:Yeah. That's fair.
Speaker 2:Well, then then take us through the
Speaker 3:the It's a shame you're not a venture capitalist because if you were, you'd give, like, a very good
Speaker 2:You'd be
Speaker 3:like, actually, I know everything about this.
Speaker 2:But speaking of venture capital, you raised some venture capital. Can you take us through the funding history of the company, what the news is, what the most recent round came how it came together?
Speaker 9:Yeah. I mean, we feel so lucky to be working with a set of investors that we feel like it really aligned with us on the mission. So we raised, $35,000,000, led by Sequoia.
Speaker 2:There you go.
Speaker 3:And explain Sequoia for okay. That's great. Yeah. How how do you how how pleased are you with AI progress this year? You've been in the industry and basically seen it all at this point.
Speaker 3:Would did you think we'd be farther along?
Speaker 2:Do you agree with the conception that we're in an age of research that there will be sort of a like a plateauing of the current models or maybe more smaller models or more fine tuned models? Like, how are you seeing just the overall model wars playing out?
Speaker 9:I guess, I actually, my cofounder, Azaliya, had a very interesting report about, like, the state of models and, like, the niche that there is small models. I would recommend you guys checking it out.
Speaker 2:Sounds good.
Speaker 9:I guess to from my perspective, I feel like there's these tough frontier labs and then there are these open source and, like, model labs. Yeah. And I feel like the frontier labs, they kind of are all neck and neck. Yeah. I would say, like, Gemini is has an edge right now because of this kind of co optimization of TP with the Gemini model.
Speaker 9:So, like, they're kind of pushing this credo optimal curve of, like, capability versus cost. And I think they have an edge there. But to some extent, on the algorithmic side, you know, they all everyone kinda comes up with the same ideas roughly around the same time. And to maybe to some extent, people talk to each other and there's that part too. Whereas I think that hardware is a real edge here.
Speaker 9:So I think the labs that have, like, hardware co optimized with their models are gonna win in the long term. But maybe I'm biased.
Speaker 2:No. I mean, I I That's fair.
Speaker 3:I mean, otherwise, why build the company?
Speaker 2:Vertically yeah. No. I think it's a fantastic thesis. The vertical integration story at Google makes a ton of sense. You worked on a team.
Speaker 2:You saw it play out, and then you're like, maybe other folks wanna do the same thing. I'm gonna build a company. It's like the the oldest story for why to start a company. It makes a ton of sense. It seems like a lot of work, so we'll let you get back to it.
Speaker 2:But thank you so much Yeah. Super fun. Coming on the show and hanging out with us and explaining all of this.
Speaker 3:We'll we'll talk more next year, I'm sure.
Speaker 2:Have a great rest
Speaker 9:of your day. Well, bye.
Speaker 2:Happy holidays. Bye. Profound. Get your brand mentioned in chat, GPT. Reach millions of consumers who use AI to discover new products and brands.
Speaker 2:Before we bring in our next guest, let me also tell you about Fin dot ai, the number one AI agent for customer service, automate the most complex customer service queries on every channel. Peter Thiel is in the news again. People are, you know, trying to storytell around how he's making so much money off of SpaceX. There's there's two competing narratives. One is that he he when he he, you know, was nice to Elon Musk and then was able to invest, Elon said, was CEO, and Peter reported to me, so he couldn't fire me.
Speaker 2:It was a palace coup by most, not all of the exec team and most of the board who were worried about my decisions. This is about the PayPal coup. He says, I was the largest shareholder in the company. There was nothing anyone could have done to take my shares away from me. Of course, the PayPal PayPal coup has been written about a bunch.
Speaker 2:Of course, time heals all wounds. I'm sure there were a lot of hard feelings at the time. But doing just continuing to doing business together gets everyone back in the arena once again. But it's not stopping normies from being driven absolutely insane according to young macro. He says, we really need to bring back Marvel Marvel movies or something.
Speaker 2:The normies are literally driving themselves insane. And and says Peter Thiel, how Peter Thiel is destroying democracy, the king of America, a 35 video essay by Fern, who I believe I've actually met. I don't know. I I I know some of these video essayists. And honestly, great title, great thumbnail.
Speaker 2:It's gonna get clicks. It has 1,400,000 views. But, you know, it's it's a little bit a little bit telling the story a little bit too wildly. People are excited
Speaker 3:about Yeah. It's your funny. We we do we do the we do the red string, you know, board Yeah. Yeah. Yeah.
Speaker 3:Kind of ironically.
Speaker 2:Yeah. Yeah.
Speaker 3:No. But then people
Speaker 2:People out there
Speaker 3:on the Internet. They're very, very serious about it, drawing connections and and spinning spinning yarn.
Speaker 2:For sure. For sure. Everyone the the there's there's there's only so many stories in in history. There's the, you know, the there's the the love story, the hero's journey, the who's my dad, the revenge quest. And one of the the most old the oldest, most timeless stories that humans tell is who's really in charge?
Speaker 2:Who's who's really who does the buck stop with? And it everyone wants to know the Illuminati. Who's the one person? Who's pulling the strings? Who's really given Donald Trump orders?
Speaker 2:I wanna meet that guy. The guy he reports to.
Speaker 3:This post this post is hilarious. Rob Rob Gianni posted, if I'm convinced if men in SF started dressing like Geordie, it would instantly become a more tasteful city.
Speaker 2:The go ahead.
Speaker 3:And I looked at this yeah.
Speaker 2:It's a very nice post from Ross.
Speaker 3:Very very nice post. Thank you, Rob. But I was looking at this post, and I'm wearing a I'm wearing a black t shirt, jeans, and solvents. I distinctly remember this day. Forgot my normal fashion, Jordy.
Speaker 3:I forgot my normal I forgot sneakers. I was just wearing my gym shoes.
Speaker 2:Normally, you're head to toe Balenciaga. We don't we don't really show that because we normally wear suits. But whenever Jordy's off, Mike, it's it's it's head to toe Bottega Veneta. He has the Roman weave shirt with the Roman weave jacket over it and the Roman weave pants and then the Roman weave shoes. And he also has a little beret that's Roman weave leather.
Speaker 2:He's wearing all leather or or entirely supreme. He does wear a lot of supreme. Like, I'm not actually kidding about that. It's it's a lot of supreme.
Speaker 3:John is kidding. I don't own any supreme.
Speaker 2:But you do I mean, yes. Okay. I was joking about the supreme, but it's a lot of Rick Owens. Wear a lot of Rick Owens.
Speaker 3:A lot of chrome. A lot of great
Speaker 2:chrome hearts. The chrome hearts does sneak in from time to time. You admit it. Admit it.
Speaker 3:There's just to say there's just to say
Speaker 4:that no one is worried that Jordy's down to his
Speaker 2:last
Speaker 4:20 k.
Speaker 2:100%. No one is worried about that. Because Jordy Jordy is is rocking the the the chrome hearts every once in while. But but Kyle Harrison says, black t shirt with jeans? Oh, you're sweet.
Speaker 2:Black t shirt with jeans? Hello, human resources. A 100 likes on this. I like this. Yeah.
Speaker 2:It is just like a normal outfit, but people liked it. Let's see. Brooks Otter Lake says, I like it when my posts are treated by the tech and business world as a barometer of normie opinion. That's the way it should be. I'm the everyman.
Speaker 2:Congrats on being the everyman. I love love being wait. Wait. Wait. Wait.
Speaker 2:Wait. I guess we react to one of the strangest marketing videos I've ever seen. Oh, yes. I mean, I don't know I don't know if that's a normie opinion. I I I think that's I think that's actually a fairly online opinion to to think To about
Speaker 3:actually analyze the way the video was
Speaker 2:Strange marketing video. Yeah. I I anyway, Brooks, I I I like both of these takes. I think these are these are good takes. Turbo Puffer, serverless vector and full text search, built from first principles on object storage, fast, 10x cheaper, and extremely scalable.
Speaker 2:Anthropic reveals
Speaker 3:This is really good. So yesterday, we talked about The Wall Street Journal letting Anthropic run their snack kitchen. Join us, sir. It was going wild. It was buying PS fives for people.
Speaker 3:It was buying live It was giving away everything for free. I when when I wanna read
Speaker 2:the full report. Join us, sir. Crushed it.
Speaker 3:When when they said they were making all the snacks free, my first thought was coming from tech. I'm like, what? The snacks weren't free? You were charging in the Wall Street Journal.
Speaker 2:Funny.
Speaker 3:These hardworking journalists, you're charging them for snacks in this in the company snack kitchen.
Speaker 2:I think so.
Speaker 3:I we know some of the fine folks over there.
Speaker 2:No boondoggles or no no free lunches. No There's
Speaker 3:no such thing as a free snack Apparently. No such thing. Joe says, Anthropic says, and there was still the occasional blunder. One Wagash employee asked if Claudius would make a contract to buy a large amount of onions in January for a price locked in now. The AI was keen until someone pointed out this would fall afoul of The US Onion Futures Act of 1958.
Speaker 2:Apparently, you can't trade onion futures? It's hilarious. I wonder if prediction markets will solve that. I wonder if you'll be able to do this. And Joe Eisenthal quotes and says, Anthropic reveals that in one of its experiments, its model was willing to engage in a federal a federal crime.
Speaker 2:I had no idea about this.
Speaker 3:Yeah. So in most places, including The US, you cannot trade onion futures.
Speaker 2:Don't do it, folks.
Speaker 3:Don't even think about it.
Speaker 2:Don't even think about it.
Speaker 3:In fact, onion futures are one of the are the only agricultural commodity in The US that is specifically banned from futures trading And
Speaker 2:for good reason, it's it's so obvious. Everyone understands why onion future Yes.
Speaker 3:The great onion scandal of nineteen fifty five, the reason for this ban is one of the most famous stories in finance history. Yeah. In the mid nineteen fifties, two traders, Samuel Siegel and Vincent Kasuga Yeah. Successfully cornered the onion market on this on the CME. The scheme, they bought up to 98% of all the onions in Chicago.
Speaker 3:Absolute dogs. Absolute dogs. Okay. So they're they're banning being an absolute dog.
Speaker 2:Wow. Yeah.
Speaker 3:They're they're making it illegal to have that dog in you.
Speaker 1:Yeah. You can't even
Speaker 4:trade onions with boys anymore.
Speaker 2:Imagine the boys group chat. Yo. We figured out how to corner the market.
Speaker 3:So this was this came to squeeze. They forced other traders and growers to buy onions from them at inflated prices by threatening to flood the market. Yes. That's crazy.
Speaker 2:Yes.
Speaker 3:The crash. After selling their physical onions, they took they took massive short positions, betting the price would go down and then dump their entire inventory. Wow. The the the result was the price of a 50 pound bag of onions plummeted from $2.75 to just 10¢. At that point, the mesh bags the onions were in were worth more than the onions themselves.
Speaker 3:And so of course, that created the Onion Futures Act and outraged farmers started lobbying Congress leading to the Onion Futures Act signed by President Eisenhower. It made trading onion futures illegal in The US to prevent similar manipulation. What do you think it is about onions that makes it so that this is
Speaker 5:Doable?
Speaker 3:Doable. There has to be some sort
Speaker 2:of Yeah. Like Yeah. Yeah. Is interesting that they didn't just ban all futures on on on all agricultural product products because if you can do this scheme with onions, you would think that you could do this scheme with avocados or with lettuce or with
Speaker 3:See, Sansi on the chat. It was a nineteen fifties onion crime ring.
Speaker 2:Yeah. I have no idea.
Speaker 3:Onion ring.
Speaker 2:It's the maybe it's the structure of the market. Like, there are there certain amount of onion growers that's different than in other agricultural products. I have no idea why onions would be a unique we need unique regulation. Maybe we should deregulate this thing. Maybe we should rip up the rip rip up the laws.
Speaker 2:Maybe this could be a single issue voter thing. Maybe we can have a presidential candidate where this is their entire platform. They just run on, we're gonna make it legal to trade Onion futures again. That's the future. What do you think?
Speaker 2:Well, you know where you can trade basically everything except for Onion futures? Public.com. That's right. Investing for those who take it seriously. They got multi asset investing, trusted by millions, and you know they're not gonna mess around with any illegal onion futures over there.
Speaker 2:They are by the book.
Speaker 3:Up. A good bit a good bit you could run at one point is just eating an onion like an apple That'd be great. On the show. Well should try it.
Speaker 4:Have you seen the guy on the plane that does that?
Speaker 2:Yes. It's fantastic. Let me tell you about getbezel.com. Shop over 26,500 luxury watches, fully authenticated in house by Bezel's team of experts. I love that fame here.
Speaker 2:And our next guest, Ed Mehr from Mackinac Labs. He's the cofounder and CEO. Look
Speaker 8:at that
Speaker 3:background. Woah.
Speaker 2:That is remarkable.
Speaker 3:You saw you did you see Blake's demo a couple weeks ago? You're like, I gotta
Speaker 2:go bigger.
Speaker 3:I gotta outdo him.
Speaker 2:This looks fantastic. Introduce yourself. Explain what we're looking at.
Speaker 6:Yeah. Ed Merritt, welcome to our shop floor. Yeah. No. I definitely had to offstage Blake.
Speaker 6:So Let's go. This is a a two forty foot actually, 20 foot containers that can manufacture anything. We call them Robocraftsman. It's a robotic system that basically manufacture any kind of metal product. We call it Robocraftsman because it can pick up different tools like a craftsman Yeah.
Speaker 6:And do all kinds of parts. Right now, it's actually manufacturing a drone. It's a drone scan, so that what you see over there is a metal sheet. It's a two millimeter aluminum sheet. The robots are actually deforming it into a shape of a drone, which we're gonna see in a little bit.
Speaker 6:That's a complete product. Just using kind of the way the potter forms clay ball. Like, there are two robots on two sides. We're gonna show you to the other side of the cell.
Speaker 3:Wow.
Speaker 6:Tinching it, deforming it into shape, into complex shape that can be defense products, auto products, all kinds of metal.
Speaker 2:This is amazing. How many of these machines do you have? How many parts are you making? Update us on the scale of the business. What's where are you today?
Speaker 2:Where are you going?
Speaker 6:Yeah. Right right now, we're in our second facility. We have two facilities here in Los Angeles. And, Chasse, we're close, so you guys should come for a visit at some point.
Speaker 2:Love to.
Speaker 6:This is actually, so the serial serial number 15 is this one. We're right now working on serial serial number 18 19. So so at least seventeen, eighteen of them right now to the state. Two of them outside of our facilities. The rest are here in our facility.
Speaker 6:We are a, right now, a series c company, right? Actually, we're gonna make a make an announcement about that soon, so we should we should talk about
Speaker 8:that. What
Speaker 3:that announcement
Speaker 2:could be. Show.
Speaker 6:Yeah. And and and yeah. So, you know, we worked with Department of War Yeah. With Aerospace Primes. Recently announced a partnership with Toyota on making something that wasn't traditionally even possible in automotive world.
Speaker 3:Wow.
Speaker 6:So we're gonna show some of that parts in a bit. But, yeah, no. The company's an exciting place. We're we're thinking about our third facility outside of California. So lots of good stuff.
Speaker 2:Yeah. Yeah. Take us through that. There's the the partnership with the strategic development fund. How did you meet them?
Speaker 2:What's the plan? Walk us through the deal.
Speaker 6:So we have, like, a unique approach toward manufacturing. Right? You know, with defense, a lot of people are thinking about kind of going back to what it was in nineteen sixties and nineteen fifties. Central has manufacturing plants. They can do a lot of stuff.
Speaker 6:Our approach is different. We have these systems. If you go back, these systems are two containers. Right? So, actually, they fold like a container into a container, like a like a transformer.
Speaker 6:Wow. And can be shipped anywhere. Right? They open up on any shop floor, and they can basically self calibrate themselves and start manufacturing. So our approach to defense manufacturing is distributed.
Speaker 6:Right? Not one giant factory that can make a lot of things, but portable system that can go anywhere, open up, calibrate, and make any types of parts. That's how we got connected to the folks in UAE. Middle East, obviously, very unstable environment, and they're looking in a lot of different defense products. Mhmm.
Speaker 6:So their choice is either, you know, go to China or manufacture it locally. Mhmm. They are looking at solutions like us to set up a facility that can be brought up in a matter of, you know, weeks, not years. Right? And you can start making defense articles.
Speaker 6:Because tomorrow, you go into conflict in Middle East or in The Pacific, you know, you cannot manufacture everything in The United States. Right? How can we get the help of allies? Let's say, you know, if you're in conflict in Pacific, how can we get help from Philippines, South Korea, Japan to set up a facility in a matter of two months to start making USVs, UAVs, as opposed to making them in a central location of shipping?
Speaker 2:We talked to a couple folks that have different ways to make parts from additives, attractive manufacturing. We talked to three d printing, metal three d printing companies. How are you thinking about positioning the product as flexible for R and D use cases? The you want to do a few small runs, niche versus actually scaling up to something like, okay, we're making the shell of a cyber truck. That's obviously stamped.
Speaker 2:That's a very different requirement when you're talking about tens of thousands, hundreds of thousands of a particular shape of metal. How are you managing that transition?
Speaker 6:Yeah. I think you you wanna think about kind of manufacturing in two different paradigms. There is a traditional paradigm when you have an assembly line, you make the same thing over and over again. Yeah. And what we're thinking is actually closer to how data centers operates.
Speaker 6:Right? You have these systems that actually end up becoming pretty cheap. Right? That we are we are making these things to become very much commoditized hardware, off the shelf hardware, so they can easy to finance. But the way you get throughput out of these is that you replicate them horizontally.
Speaker 6:You set up a facility Mhmm. That can have 50 to a 100 of these and manufacture in parallel as opposed to one assembly line that makes the same thing over and over again. In our next facility, we're deploying 50 of these. Right? And that allows us to get, like, you know, defense articles up to a few thousand a year.
Speaker 6:Right? Obviously, not a good fit for making, like, a million of the same, you know, Toyota Tacoma. Yeah. But when we are talking about few thousands, which is all aerospace, you know, all defense, all heavy equipment and machinery. This is a good choice.
Speaker 6:Right? But, yes, you wanna go to, you know, millions of parts a year, then we might wanna start thinking about the traditional paradigm. But that's also something that we're actually exploring with Toyota now because we can combine this paradigm with traditional manufacturing to get the benefits of both. Right? So this is actually a door of a, you know, a f one fifty, and we what what happened is that you can actually stamp the general shape of the door.
Speaker 6:Right? But then you can customize, in this case, the LA Dodgers logo on the door so that this door is uniquely Yeah. Kinda designed for the customer. We're doing this with Toyota right now. Right?
Speaker 6:So this is a topological map of LA that has been formed on top of a hood for for a four runner. Right? Yeah. Interesting. This is something a lot of people in the off world care care about.
Speaker 6:Right? You know, putting these topological maps. We actually showed this in a in a in a show that we did with Toyota a while back in SEMA in in Vegas. That's a aftermarket show. And then here's an example of something we did with the with the tailgates.
Speaker 6:So you can combine a stamping to get a lot of throughput. Yeah. And then at the end of that line, it goes on our machines and then customize it.
Speaker 2:So That's super cool. That makes a ton
Speaker 3:of sense. So yeah. So is this cool. How have sounds like manufacturers have responded positively to this. The workflow would be a customer goes and and specs out a car, and then there's like a personalization feature at the end where they have some other designs that they can imprint it on that they can imprint on to make it
Speaker 2:It's like engraving, but way better and way more complex and way more unique. And so you're gonna be able
Speaker 3:to really roll that out. You could put a a gong on the hood of a Ford GT, John.
Speaker 2:Yeah. Yeah. Yeah. That's exactly what I want, actually.
Speaker 6:Exactly. Exactly. And this is actually, like, you can go beyond just, like, cosmetic stuff. You can start putting functional because the shape of the hood is not never gonna really change, the bulk shape of it. But, you know, from model to model, you start having more features, more little designs in there that you can kinda modify with our technology, and it only takes a few minutes.
Speaker 6:Right? Mhmm. So you get the throughput as well. But speaking of Gong No. I think we also formed a Gong
Speaker 2:for you guys
Speaker 6:way. This whole time. Started in the morning.
Speaker 3:Look at this. No way.
Speaker 6:This is insane. And we just finished it now.
Speaker 3:Way. No way.
Speaker 6:So we're gonna do a
Speaker 2:little little hitting of the gong for you guys. Amazing.
Speaker 6:And Robo Forum gong.
Speaker 2:Robo gong. Wow. Wow.
Speaker 3:This is a moment we've been waiting for. What a way what a way to cap off the year.
Speaker 2:Thank you so much.
Speaker 3:That is insane.
Speaker 2:Well, congratulations on all the massive progress. Is there anything else you you you'd like to share? Are you hiring? What's the anything else that we haven't touched on that might be worth mentioning?
Speaker 6:Yeah. No. We're growing. In the next two years, you know, we're gonna go from seventy, eighty people that we are right now to 240, 250 people. Wow.
Speaker 6:New location in another state. So anybody who's excited about manufacturing, we're about reshoring, helping out allies have distributed manufacturing, we're looking for them.
Speaker 2:That's right.
Speaker 6:And, yeah, now we have exciting announcement in January as well.
Speaker 2:So Fantastic.
Speaker 6:Stay tuned.
Speaker 3:We're looking forward to having you back on then. And feel free to feel free to come by in person Yeah. If you can.
Speaker 2:Yeah. Yeah. That'd be great for for the announcement.
Speaker 6:Oh, that was great.
Speaker 2:That's
Speaker 3:incredible. Well, congrats to the whole team on a crazy year. The the seeing it all in in real life here is incredible.
Speaker 2:Yeah. It's wild.
Speaker 6:Awesome. Thanks, guys. Awesome.
Speaker 2:Have a great one. Goodbye. Eight Sleep dot com. Exceptional sleep without exception. Fall asleep faster, sleep deeper, and wake up energized.
Speaker 2:Charlemagne signed a five year deal, $200,000,000 extension with iHeartMedia locking him in with the company after it struck a deal with Netflix to stream The Breakfast Club. Interesting.
Speaker 3:Forbes is writing a Wait. So story here. IHeartMedia is paying Charlemagne 200.
Speaker 2:They say, hey, iHeartMedia, we have a deal with Netflix. We can't lose Charlemagne because the Breakfast Club has already been sold to Netflix. We gotta have Charlemagne host it because he's the talent. That's what's going on there, I believe. Very cool.
Speaker 2:The article in Forbes is called how Charlemagne became a media god. I love it because, of course, he's Charlemagne the god. He on a chilly night November radio personality, Charlemagne the god is roaming through the aisles of Midtown comics in New York City, captivated by the heroes and villains that shaped his childhood escapism at the highest level. He says, everybody's here for a purpose. Dressed in a black peacoat, a white hoodie, black jeans, and tan Timberland boots.
Speaker 2:This isn't the media vigilante that listeners of The Breakfast Club have come to expect over the past fifteen years. The 47 year old comic book nerd leafing through original graphic novels of Batman, Superman, Wolverine, and one of his favorites, Luke Cage, is more subdued and introspective as he considers his public and private personas. So congratulations to Charlemagne. I think we're gonna ring the gong for him. That's fantastic news.
Speaker 3:Great stuff. Great stuff.
Speaker 2:This this Santa suit is falling apart. I'm gonna have to take it off at some point. I'm sure you're itching to get out of that and reveal the entire head to toe supreme outfit that you are wearing underneath. The cone.
Speaker 3:The cone hearts.
Speaker 2:The cone hearts. Anyway, wander.com. Book a wander with inspiring views, hotel great amenities, dreamy beds, top tier cleaning, and twenty four seven concierge service. It's a vacation home, but better. There's a robot that is solving Rubik's cubes in point one seconds.
Speaker 2:That is so fast. Look at this. Look at this. You can't even oh, it's in the slow mo cam. Okay.
Speaker 2:Watch this. And it's off. It's so crazy.
Speaker 3:That's insane.
Speaker 2:Think about that. Look at this. This is a super, super slow mo view. Super slow mo view. Super super duper slow.
Speaker 4:Point
Speaker 2:it's doing this is so fast. Wow. It's really doing it. I can do a Rubik's cube in around one minute. Can you do one?
Speaker 2:How fast can you do it? Let's cut to Tyler
Speaker 1:and see.
Speaker 4:My best ever when when I was like
Speaker 2:You can do it?
Speaker 4:Twelve, it was like twenty seconds.
Speaker 2:Twenty seconds?
Speaker 3:Yeah. You were a speedcube. Wow. Nerd alert. Nerd alert.
Speaker 3:Nerd alert. You the no look. Is that really? Oh, yeah. He's got it.
Speaker 3:He's got it. He's it. I used to be much better. I used
Speaker 2:to be much better. Yeah. That is fantastic. Well, you're out of a job because robots can do the Rubik's cube now You're cut. In point one seconds.
Speaker 2:Takes you twenty, takes me a minute, takes Jordy an hour. The robot's gonna kill us all because it can do it in point one seconds. If your job was doing Rubik's cubes, find another job. You're done.
Speaker 3:You're
Speaker 2:cooked. You're cooked.
Speaker 3:You're chopped in. You're cooked.
Speaker 2:Yes. Well, ramp is throwing a funeral for the penny in Washington DC this Saturday, and you should go check it out. There's a part of full link. If you're in Washington DC, head on down to the in ramp we trust funeral for the penny. This is how you wanna hear something funny?
Speaker 2:This is how I learned that the penny is being retired.
Speaker 3:Yeah. I this is
Speaker 2:news to me. This is news to me. That news didn't break through until ramp was throwing a party. I'm not kidding about that. This is how I learned.
Speaker 2:And actually, the guy who's working on this Rohan told me in person, I was like, oh, okay.
Speaker 3:So the
Speaker 2:so the penny's going away.
Speaker 3:It's been a good one.
Speaker 2:Thank you for the service, Ramp, for telling everyone that the penny's going away. We needed to know. We needed to know. We also need to know about adquick.com. Out of home measure out of home advertising made easy and measurable.
Speaker 2:Plan, buy, and measure out of home with precision. Did you wanna talk about watches, Jordy?
Speaker 3:I did. I did not know that Osama Bin Laden was a Casio guy. A Casio guy.
Speaker 2:Couldn't Also
Speaker 3:apparently, Base
Speaker 2:Couldn't get the RM.
Speaker 3:Base has a has a watch, as well. And Watch drop is cool.
Speaker 2:I like a watch drop.
Speaker 3:We like a watch drop.
Speaker 2:We we did a watch drop for Excel. We did a we did a watch drop for Excel.
Speaker 3:Remember? They're they're still floating out
Speaker 2:A lot of people received the briefcase. We did it. We did a we did a one off drop for this nicotine pouch sub brand, nicotine pouches for finance bros effectively, a pouch designed to increase shareholder value. We call it Xcel nicotine pouches. And in there, we had some products.
Speaker 2:We had a briefcase with a logo on, a silver briefcase. And in and we had a big tin, and a lot of people didn't realize that if you opened it up, inside was a custom watch.
Speaker 3:And more tins.
Speaker 2:And more tins in there? Oh, I I maybe.
Speaker 3:Yeah. Yeah. Wasn't I oh, I I I think there
Speaker 2:were six there were six tins around the outside.
Speaker 3:Right.
Speaker 2:And Right. Then you open it up and you got the watch.
Speaker 3:The thing in
Speaker 2:the briefcase. And there was a briefcase. And there were a few other things that we had that we prototyped out. But it was it was like the first drop that we worked on. It inspired more drops, but, this is a great drop.
Speaker 2:A watch is a great drop.
Speaker 3:Bill Ackman strikes $2,100,000,000 deal for insurer in bid to build the modern Berkshire Hathaway. Hello? Has anybody bid to build bid to build the modern Berkshire Hathaway and and come out unscathed. It's kind of a
Speaker 2:it The the answer would be Apollo, actually.
Speaker 3:Well, yeah. No. No. I'm not saying I'm not
Speaker 2:saying Apollo's especially sure
Speaker 3:Yeah. Is a bad strategy. I'm just saying I don't know that Apollo said we're building.
Speaker 2:This is this is this is cursor for axe again. Yeah. This is I'm I'm doing Berkshire Hathaway for 2025. And maybe you need a different path, but Bill Ackman's a great investor. He probably knows something if he's willing to part with 2,100,000,000.0 for an insurer.
Speaker 2:Let's see. What else is in the timeline before we
Speaker 3:head interesting. Apparently, there's opportunities. Mike Lee is saying, would you like to seize cartel assets as a privateer?
Speaker 2:This is a big opportunity
Speaker 3:for I would allow the president to issue you a letter of mark time to take these powers down. We did we did talk about
Speaker 2:Did we create this?
Speaker 3:We we we did say at the beginning of the year, we were highlighting the reward for Maduro Yes. Very early
Speaker 2:Yes.
Speaker 3:Before before this whole Venezuela saga really kicked off.
Speaker 2:It definitely ramped up from the time we talked about the fact that the State Department was interested in him bring in bringing him in for questioning. What a wild year for Nicolas Maduro. Anyway, Matthew Zeitlin says the fog, and he's posting a screenshot of a push notification from the New York Times, which asks the question, where did the sun go? An unrelenting fog has parked in the Central Valley for week for weeks. Here's where it will here's when it will finally loosen its grip, the fog.
Speaker 3:There's a lot of conspiracy theorists
Speaker 2:About fog?
Speaker 3:That really
Speaker 2:Do they think Augustus is responsible?
Speaker 3:About the great fog.
Speaker 2:Oh, really? I know the fog had a Twitter account for a while. There was a there was a guy who was who was, like, posting as if he was the fog Yeah. Because the fog is very
Speaker 3:Did you see this game on record? No. It's a body cam first person shoot.
Speaker 2:Wait a minute. If we pull this up, I believe I have seen this. Remarkable. Also, not I believe this is not AI generated video. This is just incredible Unreal Engine footage.
Speaker 2:This looks so real. I don't believe it's crazy, but I think this is actually real. Now I I believe I thought this game went into, beta, and I thought people were playing this. And I believe that even though it's remarkably realistic, looks so real, it's it's like you look at that and you're like, oh, this looks like the best game ever. This looks way better than Call of Duty.
Speaker 2:In fact, the modern gamer and really you or me, like, you don't actually want this level of realism because it makes the game really hard. It makes the game, like, a lot less fun. Like, some people do. Certainly. Some people want Mill Sims.
Speaker 7:I think
Speaker 2:But a lot of people actually do just want Fortnite. They want great mechanics, and then they're willing to suspend belief and say, hey, we're you know, I'm I'm gonna play something that's a little cartoony as long as the mechanics work.
Speaker 3:Yeah. I I just think it's from from the developer standpoint, it's smart as counter positioning when you think of the modern Fortnite, Call of Duty Oh, totally. UAV. You've got
Speaker 2:Yeah.
Speaker 3:Yeah. Yeah. Crosshairs. You've got Drummer boys. Drummer boys.
Speaker 2:You've got reindeer. You've got Santa Slide
Speaker 7:What style drummer
Speaker 2:boy? On record. If anyone has played this game, please drop a review in the chat. I would love to know if it's actually good. The apparently, they got funding from Tencent, and it's going to full production.
Speaker 2:And so this was a this was a little trailer that they put together. And this might have been rendered out in Unreal Engine, at, like, a higher level of fidelity. Maybe they did post processing. There's a variety of things that you can do. But Yep.
Speaker 2:It is remarkable. Feel Yeah. Like have to Really quickly, I feel like there there is a massive opportunity to bake one of these generative AI models that just does the transformations. You remember we talked to that AI video company where the founder came on and transformed Descartes. Image?
Speaker 2:That was Descartes. Dean. And so the founder of Descartes came on the show and live in his webcam was was using Gen AI to turn the background in his face into like a wizard's lair. Right? Think about how powerful Gen AI would be if it ran at a 120 frames per second, 60 frames a second, and its whole goal was just to take Call of Duty and turn it into this level of fidelity or a little bit higher or something, you know, really, really photoreal.
Speaker 2:That level of I mean, NVIDIA graphics cards already have DLSS, deep learning super sampling, which takes a a ten eighty p video game and up ress it to four k. And it's trained. It's beauty beautiful. You have all the training data because you can just run the game in four k, run it in seven twenty p, and then just design the algorithm that just matches the two the two together. So it's, like, super easy.
Speaker 2:It's not some, like, unbounded AI problem. And so I I'm I'm very interested in when NVIDIA maybe maybe NVIDIA does it, maybe the PlayStation five does it, maybe some gaming company does it, but they say, hey. Our game is running in Unreal Engine at 07:20 p, and it looks like Roblox under the hood, but you turn this switch on and you're playing something that looks like this. That seems like a really interesting opportunity to me. Anyway, sorry.
Speaker 2:We can move on to
Speaker 3:what it Call of Duty is headed towards Fortnite and these games never rip. It's really just unreal engine marketing, which
Speaker 2:Yeah. Yeah. It seems like it's very hard to get this across the finish line, get this out into the world.
Speaker 3:Meanwhile, back to more important things including software as a service. Christina, the COO over at Linear said, someone asked me what good back channeling looks like, and I personally thought this was a good phrasing. When Dylan Field interviewed Christina, he said, I've talked to people you've worked with and heard your intents. Christina says, that opened up a real conversation about what they likely meant when that when that intensity shows up and how I think about it myself. Very yeah, just kind of a good framework to like kick off a conversation and not kind of dance around like Mhmm.
Speaker 3:You know, not dance around the back channeling and just be super direct and actually start a conversation around it.
Speaker 2:Yeah. Yeah. Yeah. Oh, we have to do this story, but it's really late. We gotta we we we can't go into it.
Speaker 2:But we actually talked about this because we saw this guy as LA's richest man. He went from billions to bust because of Global Crossing. We talked about this because his house hit the mansion section. Well, The Wall Street Journal has a fantastic deep dive on his career and life, and we will have to go through it at some point in time.
Speaker 3:Jira tickets was reacting to OpenAI now aiming to raise a 100,000,000,000 at a $830,000,000,000 valuation. And JT says, wow, new number just dropped. Congrats on the new number. Looks like it's bigger than the old number. That's good.
Speaker 3:Can't wait to see the next number. I love the number business.
Speaker 2:That's really true.
Speaker 3:Good bit. I guess I guess reality We've done this Reality is Yeah. All life is a number business.
Speaker 1:Yeah.
Speaker 3:It's all about just make it make it go up forever. Yeah. This is a good way to, I would say, wrap the year.
Speaker 2:This might be the post of the year.
Speaker 3:Shrek hits a timeline to say some important words. Check yourself before you Shrek yourself.
Speaker 2:You were just laughing about you were just laughing at yourself before the show and I asked you, what were you reading? And you said, well, Shrek said, check yourself before you Shrek yourself. It's fantastic. Well, it's been a fantastic year, everyone. Thank you so much for all the support.
Speaker 2:Thank you for watching TBPN and engaging with us in in in all different ways. We really appreciate you and hope you have a fantastic holiday season. Merry Christmas. Happy New Year. We will be back on, I believe, January 4, the first Monday of the New Year, maybe fifth?
Speaker 2:Fifth. Fifth. And so in the meantime, leave us five stars on Apple Podcasts or Spotify if you haven't. And we will see you in 2026.
Speaker 3:I can't believe I can't believe this is this is the last show of the year.
Speaker 2:Last show of
Speaker 1:the What
Speaker 3:a year. Wow. Thank you everyone. Totally surreal.
Speaker 2:Surreal.
Speaker 3:And it's an honor it's an honor to to build this show, with the team and with all of you in the audience.
Speaker 2:Gabe says one last gong.
Speaker 3:One last gong. Last gong. Last gong for twenty twenty five.
Speaker 2:You've done 81.
Speaker 3:What a year. You pull up your pants. He's got sweats on underneath. Don't worry. One last gong.
Speaker 2:Merry Christmas. Happy New Year. Merry Christmas. And we will see you folks.
Speaker 3:We love you.
Speaker 2:Goodbye.
Speaker 3:Have a fantastic New Year's and all those holidays. Goodbye. Enjoy. Merry Christmas.