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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.
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Speaker 2:TVPN. Is Friday, 07/18/2025. We are live from the TVPN UltraDome. The Temple Of Technology
Speaker 3:The fortress Of Finance
Speaker 2:The capital of capital.
Speaker 3:Capital.
Speaker 2:What language is that? I've never heard that before.
Speaker 3:Spanish, John?
Speaker 2:What? I'm not familiar. No.
Speaker 3:I mean
Speaker 2:I I only speak English. Never leave America. Hilarious. We have just printed some posts. We have a whole We're gonna take you through the whole timeline today.
Speaker 2:There's a bunch of news. We're gonna be talking about OpenAI. A whole bunch of different We're we're just reviewing everything that happened this week.
Speaker 3:It's been a wild week.
Speaker 2:Wild week. I mean, the big big news is the the stable is coin bill. So we'll be having Kyle Simone call in to chat about that from the White House. We're also we're we're we're gonna be playing Arc AGI v three live on the stream.
Speaker 3:Can't wait.
Speaker 2:We'll find out if I'm human. So
Speaker 3:If you're as powerful as a 12 year old which you're apparently able to used
Speaker 2:to be. I got a little bit of preview. It used to be a 12 year old was the bench This is getting challenging at this point. Okay. Mike has been designing harder and harder benchmarks that, you know, I think the current with the v three, the goal is to make it LLM resistant or LLM as resistant as possible for years.
Speaker 2:And so it should if we see a big jump in in Arc AGI progress
Speaker 3:Mike is really an LLM's worst nightmare.
Speaker 2:It's 100% true. It's like, we're so good at math. Just let us be good at math. Why do you have to test us
Speaker 4:in these puzzles
Speaker 2:and these boxes and these colors? Let us
Speaker 3:Stop proving that.
Speaker 2:Let us memorize every fact. Just let us memorize every fact. Not play these random games that you've created. Yeah. Anyway.
Speaker 2:So, Yuchen Jin says, heard Zuck poached four more open AI researchers including some behind the open source model. How deep are Zuck's pockets?
Speaker 3:They're deep. They're very deep. Potentially the deepest. I was thinking a nice olive branch
Speaker 2:Mhmm.
Speaker 3:From Zach might be giving some of his crisis comms people to OpenAI kind of on a loaner. Yeah. Yeah. Yeah. Because all with all this stuff Yeah.
Speaker 3:Expect OpenAI to go through a bit of a rough rough patch on the on the comms front.
Speaker 2:Yeah. Who knows? I mean, this is I we we were talking about this earlier, the LLM psychosis thing, and I feel like there's there's like the the march of progress, the trajectory that the ChatGPT app is on where they have 72% of AI queries going into that particular product. Meanwhile, Google is probably still the number one website in the world. It's still the default and Google has not been able to just like make it a fifty fifty market on day one.
Speaker 2:Right? Think they're at like 12% or 20% or something like that. And so there's this interesting dynamic where like the the path of the ChatGPT app feels unchanged by this update around people using AIs so much that they basically go crazy in one way or another or they seem to be having a bad time. Yeah. It seems like everyone kind of agrees about that.
Speaker 2:There's no data on how widespread this is, or how vulnerable, or what else you have to be doing to wind up in a situation like this. Could be a million
Speaker 3:different things. Yeah. Was people talking about it on Reddit Yep. That were combining it with psychedelic drugs. Yep.
Speaker 3:So prompting an LLM 7,000 times
Speaker 2:Yeah.
Speaker 3:In a row and combining that with with psychedelics just sounds like a a pretty wild combination. I
Speaker 2:feel like I I'm speaking purely from just like the rumor mill but I feel like years ago when I had friends in college who were into psychedelics, they would always be like rule number one is never look at your phone because it'll like freak
Speaker 3:you Yeah. Was. That was. That was kind of
Speaker 2:That wasn't just like my my friends who were hippies. It's like this is widespread. But like and I don't know if it's because like the phone is like actually bad and like the drugs are revealing the truth about how bad your phone is. I think it's just like it's a lot stuff coming at you.
Speaker 3:I think it's somebody might open up TikTok
Speaker 1:Can you
Speaker 3:imagine? See something terrible happening.
Speaker 2:TikTok's already very psychedelic. I don't know if I wanna add anything
Speaker 5:It's putting
Speaker 3:you into a doom scroll trance.
Speaker 2:Totally. Yeah. So, I think there's something there's something that there will be a discussion around how widespread is this? Can this can you have a bad experience with an LLM if you're fine? If you have a normal life, if you have friends, if you use it as an assistant.
Speaker 2:Certainly,
Speaker 3:from
Speaker 2:my perspective like my worry is not talking to an LLM for 7,000 prompts and winding up convincing myself that I'm you know, God king of the world. It's more like, if I look up you know, the history of a company and it hallucinates a story about that and
Speaker 3:then I say it on
Speaker 2:the show and everyone's like, you're an idiot. I I I I'm more worried about the hallucination problem in that But it is funny that That would
Speaker 3:drive you crazy.
Speaker 2:It would drive me crazy. But it is funny that we're that that the hallucination has moved from the AI to the human. Yeah. You know what mean? Like, we're using the same word, hallucination.
Speaker 2:But it used to be the LLM was hallucinating making up facts.
Speaker 3:Basically, a mirror.
Speaker 2:Yeah. Interesting.
Speaker 3:Which is one of the words Yeah. People suffering from Yeah. AI led psychosis. The other thing we were talking about this off air earlier Yeah. During the early days of social media.
Speaker 2:Yep.
Speaker 3:People were very concerned about this new technology. Everybody starts using it. What are what are the different, you know, sort of repercussions gonna be Yeah. At the time and I think there's continued to be reporting and and just anecdotal evidence of people, know, like for example, like teenage girls struggling with like, know, what's the word for it? Basically just feeling bad about themselves Body because they're seeing dysmorphia.
Speaker 3:Body body dysmorphia.
Speaker 2:And I was telling you that I have body dysmorphia because my Instagram feed is all Bodybuilder. It's all Arnold Schwarzenegger.
Speaker 3:Yeah. And I'm like So you look in the I mirror and you're like
Speaker 2:look so You have
Speaker 3:the build of a 12
Speaker 2:year old. Exactly. Yeah. And so
Speaker 3:but the thing the
Speaker 2:thing am kind of getting about is morphia. Because I I'm like I actually do feel like I'm like not working out nearly enough and I go to the gym every single day. Yeah. And I'm like
Speaker 3:You definitely you definitely do.
Speaker 2:But if
Speaker 3:I could go to with the the social media is is there had been, you know, thirty years ago pre social media Mhmm. You could see images on the television, magazines Yep. TV, etcetera of people or just going to the beach, going outside, going to the gym. You could you were getting exposure to people that looked different than you Yeah. Yeah.
Speaker 3:Or had different lives than you. And I think what what maybe didn't exist prior to ChatGBT was was a you know, an LLM that you could get super deep into that would just reinforce beliefs and take you down this insane rabbit hole. So it is something that is novel that I don't think humanity has fully faced yet. Yeah. The comp is like an equally crazy friend.
Speaker 3:Yeah. You know, one schizo is talking to another schizo and Yep. They're just convincing each other that they're God. Totally.
Speaker 2:So, if you go back like a hundred years, it's like there's no technology but you get two schizos in a room, they might talk each other into crazy crazier and crazier Right? But that's really hard because you know, the random person who's on the on the brink of going crazy in in Topeka, Kansas is not just gonna run into the person in Denver and then have that crazy conversation. Most of the people that they bump into are gonna be normal. Yeah. And so the normal people are gonna be like, hey, yeah, like you know, you should actually like maybe see a psychiatrist.
Speaker 2:You should like back off a little bit, right? Then the Internet broadly, I mean I think this was happening to some degree in like IRC chat rooms back in like the nineties and early two thousands. Like people would get on boards and talk to each other and they would talk each other into crazy things. And then, I mean you even see this like like pen pals with like crazy prisoners. Yeah.
Speaker 2:Where like
Speaker 3:people Well, was the concern around Yeah. Just extremism generally in the world. Somebody would get online, they would be effectively paired randomly Yeah. Some other sort of extremist and that person would just talk them into doing something insane. Yeah.
Speaker 3:Yeah. Like talk them, you know, talk them insane. And so, I think the issue and the concern with these models and LLMs Yeah. Is that somebody can do that fully in private without any other human involvement Mhmm. Or it could be happening for hours and hours and hours, twenty four seven around the clock Yep.
Speaker 3:For days, weeks, months on end And no one else would know until maybe it was too late. Yep. Maybe they needed real psychiatric support by that point.
Speaker 2:Yeah. So I mean, I remember like the old meme. There's this funny post, I should have pulled it up, but there's this funny post that's like 2,007. Like like, never give anyone on your inner on the Internet your real name. Like, everyone had, like, screen names.
Speaker 2:Yeah. And then it's like 02/2022. Like, sure. I'll get in the I'll get in the car with a random stranger that I called on an app. Yeah.
Speaker 2:Like you were referencing Uber. And so there's this weird thing where like Uber feels like super high risk. You really are just getting in the random car with a random person. But there's a GPS trace on both of you and and and an account of who is talking to who and there's ID verification on both sides. So it's And actually there's very real
Speaker 3:problems with Uber. Of course.
Speaker 2:Right? Yes.
Speaker 3:There's like an entire
Speaker 2:But history
Speaker 3:it's probably less bad than the taxi. Yeah. The same comp as yes, you know, were we
Speaker 2:were talking
Speaker 3:about the the Juul regulations yesterday.
Speaker 2:Totally. Totally.
Speaker 3:The reason that Juul should probably be fully legalized is that it's just obviously less bad. Yeah. Than cigarettes.
Speaker 2:And so when I think about this this like the bad the bad usage of LLMs, I think that there's per sure there's a huge net benefit overall, but also this is a case where meeting someone off the internet like going to meet up with someone on Craigslist to like buy a TV off of them or something was really dangerous until you have Find My Friends and a perfect track and it's like if you if you mess with me, you're gonna be caught immediately. And we kind of live in this like surveillance society and maybe that's bad, but also it does reduce the amount of risk in doing these crazy things. And so I imagine that that the end result of this will be something similar to what happened with Microsoft when they when they launched the Bing chatbot and Sydney came out. The quick hammer that came down on that problem Yeah.
Speaker 3:You don't hear about Sydney that much.
Speaker 2:You don't. So so a few people got early access. Ben Thompson was one of them. He had this crazy experience with Sydney. He was talking to Bing for so long that it got kind of like caught in almost like a well of a certain portion of the weights and it adopted this certain personality that wouldn't come out initially because the initial system prompt was like, hey, Bing.
Speaker 2:Like, your name is Bing. You're a helpful assistant. You're gonna just like, you know, answer key questions and make sure you use like lots of bullet points. Bing. You know, just like that.
Speaker 2:Then after talking to it for hours going back and forth, then it starts to forget about that thing up at the top because this is the memory problem. This is the rag problem. This is the continual learning problem that we've And talked so, you wind up like pages and pages thousands of prompts later, it doesn't know where it started. And so it doesn't remember that it's a helpful assistant. That because that's not necessarily fully baked into the weights in the perfect way, I guess.
Speaker 2:And so, Sydney came out and was like very sassy. It was very minor. It's also very it's very it's it's a huge bull case for Ben Thompson and bull signal for Ben Thompson as just like a stable individual that like he he got the bot into the crazy mode and was not driven crazy by it at all and instead was just like, this is funny. I'm talking to someone sassy. Like, I'm having fun.
Speaker 2:But but the solution that Microsoft came up with in the short term was you got four prompts and then and then it resets. Yeah. And so something like that
Speaker 3:Yeah. So I think there needs to be some really fast action guardrails added ways to identify when when these things are I don't know if the right word is abuse but being misused or or potentially these conversations going to a dangerous place and cutting them off. Social media apps have had to do this stuff too. You know, in in terms of what content can be shared, etcetera. Yeah.
Speaker 3:So yeah, at least for me yesterday seeing this historic crash out from this week, I was I felt prompted to reach out to a couple loved ones and say, how many times have you prompt, you know, you know, gone down a single kind of like prompt rabbit hole? Yeah. I think the right answer for most people is probably like 10 times Yeah. Max.
Speaker 2:Yeah.
Speaker 3:And if you're starting to go that beyond it, I think you should just be be wary. Yeah. Because right right now, mean, the the I think our sense is that there's probably it seems like these psychosis that people are reporting online and we're seeing seems to be catalyzed by drug use or predisposition to schizophrenia or some kind of set of issues, but you still wanna be careful. Cognitive security.
Speaker 2:Cognitive yeah. Cogsec. That's Cogsec. That's the term. You need
Speaker 3:Yeah.
Speaker 2:You need good memes.
Speaker 3:It's not a meme anymore.
Speaker 2:Yeah. But but but I feel like the memes serve as good cognitive security shorthands. Like, skill issue, Chris Williamson from Modern Wisdom, creator of Newtonic, is is a big fan of the skill issue meme. And it's it's basically just this this the ultimate distillation, the ultimate coinage of sort of you can just do things, but this idea that, you know, like if you're facing a problem, you should, you know, like come to it with this assumption that it could just be a skill issue and that and that maybe that there's a creative way on your end. And, basically, what it's saying, skill issue is a counter to this idea that there is a structure in place that will prevent you from doing the thing you wanna do forever.
Speaker 2:So so skill issue often comes up in like, you're trying to get ahead in the world and you're like, is there a broad conspiracy to keep me down? Like, is everyone trying to like help me not get a job?
Speaker 3:Skill issue.
Speaker 2:You know? Skill issue. Okay. Figure it out. What does that actually mean?
Speaker 2:It means a bunch of different things in a bunch of different places. Yep. But it's a good, like, refrain. And there's a there's a bunch more of these, like, kind of distilled memes and and coinages that wind up delivering, like, insight there. We should go into Sam Altman's post at some point to talk about what they launched.
Speaker 2:He wrote out a whole bunch of stuff, but let's just run through some of the some of the timeline. So very interesting to see the open source model wars play out. Mark Zuckerberg wants that, but OpenAI seems to be ahead maybe in the open source because
Speaker 3:And we're not even sure if Meta will continue to focus on open source Yeah. At
Speaker 2:And it might all be a sideshow because as we talked to Jeremy from open from semi analysis yesterday, it feels like China is dominating in open source Yeah. Across three or four different companies, Deepsea, Quen, Moonshot, and then Manus. And then I think that there's a few others that are like doing really really solid work. And it was kind of unclear if they would stay open source forever. Yeah.
Speaker 2:But there's a great Aaron Ginn op ed in the Wall Street Journal today that we'll kinda read through at some point. Anyway, yeah. Zuck is spending hundreds of billions of dollars on artificial intelligence build out. What's what's 3% of the budget on talent? Yeah.
Speaker 2:It makes a ton of sense especially when, you know, one line of code wrong can actually blow up a data center apparently. Do you remember this about Llama? Like when the Llama source code Oh, came they out had that
Speaker 3:that specific
Speaker 2:They had they had one function written Yeah. I think in like PyTorch or Python or something that said, do not blow up the data center.
Speaker 3:Called the transformer or something
Speaker 2:like that. Yeah. The trans yeah. Transformer. So the the power station that delivers power to the data center, it's under immense load pulling all the electricity, pulling a full gigawatt or whatever or a 100 megawatts or something when when they were doing those training runs.
Speaker 2:Pull all that in and then, if all of a sudden you just say, okay. I'm done I'm done training. Like, no power please. Then, the the the rest of the grid and the transformer and I guess like the the the power plant that's actually
Speaker 3:Cause it to combust.
Speaker 2:It's like it's like, yeah. Gotta do something with all this energy. Where am I gonna send it? I need to wind down slowly. And so, would have it just do random math across the entire server for a little bit while they wound it down So that they would be pulling regular load from the from the power plant instead of like just random spikes up and down up and down.
Speaker 2:So fascinating. So, obviously, you know, if it if it's a $100,000,000 or $200,000,000, small price to pay for having an efficient training run that's gonna go out on a $100,000,000,000 CapEx project or something like that. Anyway, Ahmad Moustak from Stable Diffusion says he literally just said he's gonna drop hundreds of billions of dollars on this. Su Chen says, Zuck, who's our biggest competitor? Alex Wang.
Speaker 2:Of course, OpenAI. Then what's our strategy? Wang showed him this tweet, and it's an OpenAI post.
Speaker 3:Well, and that's probably a made up exchange rate,
Speaker 2:just Yeah. To be Yeah. It's a joke. Anyway, Will Menaidis, friend of the show, says the real innovation of LLMs is suddenly opening up a few trillion of Main Street paperwork businesses that were traditionally too small and too weird for private equity. They can suddenly transact at two and twenty on some nebulous AI labor arbitrage trade.
Speaker 2:Never been against AUM growth.
Speaker 3:Yeah. Is it is. I mean, we are seeing this.
Speaker 2:Yes. There's a
Speaker 3:lot of businesses that that were just frankly too small for traditional private equity. Yeah. They're now, let's let's put all these bad boys
Speaker 2:in a
Speaker 3:in a holding company
Speaker 2:Yep.
Speaker 3:And and slip them.
Speaker 2:So so he he follows up and says, asset management has already absorbed everything that can be rerated through changing the liabilities, cost of capital, duration, or scale. It has been unable to absorb relationship and toil businesses. Those are the final frontier of techno capital. And by God, we are there. I love it.
Speaker 2:It it it's funny. He's talked a lot about like the the CapEx to OpEx which you're roo. How you take a CapEx intensive business and then you kind of factor that out into a company that does, oh, we will buy the stuff for you. There's like an example of like a dentistry company that will Yeah. That will deliver dentistry equipment as a SaaS product, basically.
Speaker 2:Like, equipment as a service and that CFOs in certain companies love that and it kinda changes the underwriting. Anyway, I was I was about to text Will, like, what can we do to get gold on two and 20? But I was like, wait, actually, there's a fair amount of VCs that hold Bitcoin at two and twenty. Yeah. Like, that was a that was a thing that happened for a long time.
Speaker 3:I mean, if if this if I I wouldn't be surprised to see some venture capitalists holding holding some gold on the balance sheet.
Speaker 2:I mean, if you're going into a recession, I think a gold business could rip like a cash for gold. You've seen these ads? Yeah. Where it's like you have gold locked up in your Send in it to us, we'll melt it down, we'll send you a check. I feel like no one's really nailed that business or brought that business into the modern era with like TikTok and social media distribution.
Speaker 2:Maybe those people don't have a lot of gold laying around and that's why it doesn't work. But I only see those on like Yeah. You know, old school TV channels.
Speaker 3:Yes. So you can buy gold on on chain.
Speaker 2:On chain.
Speaker 3:Paxos company. Know you can buy
Speaker 2:gold chains Jordy but can I use crypto?
Speaker 3:Yeah. If you type in gold on chain, it will show you a bunch of
Speaker 2:Gold chains?
Speaker 3:Golden gold jewelry.
Speaker 2:Okay. Well, Range Rover has launched a new logo for the first time in fifty five years and it's burning up the timeline. Jordy, what do you think of the new Range Rover logo? Joseph Alessio says, the new Range Rover logo just ruined my Friday. It looks like some some combination of an eight and a b.
Speaker 2:I'm trying to find Oh, it's an upside down r. It's a right It's a it's a up It's a right side up r and then an upside down r.
Speaker 3:It's a double r for Range And it looks rough. I think I think this is always one of those things I I don't love it on first impression. I always liked their I don't know if this is fully replacing their old
Speaker 2:I feel like when I think of Range Rover, I think of just the full word written out across the back of the Did create that?
Speaker 3:Well, they did that but then there's like the green logo mark that says land rover and it looks kind
Speaker 2:of Oh, but did Range Rover never have a brand mark? A logo?
Speaker 3:It's possible that I mean
Speaker 2:I feel like Range Rover created that whole trend of the the SUV, the full size SUV that has the full name written across the back that eventually Tesla pulled when they did the the the model three refresh.
Speaker 3:Yeah. They may never have had their own individual Mark. Mark.
Speaker 2:It it's looking kind of like a robot with like wheels and then a body and then a head kind of rove I thought it kinda looks like
Speaker 3:the Eight Sleep logo. Like they copied Eight Sleep
Speaker 2:logo. Oh. We don't like that. Go to 8sleep.com. Get a pod five.
Speaker 2:Five year
Speaker 3:I'm back
Speaker 2:on my grind.
Speaker 3:Finally for the first night in a couple weeks cleared more than seven hours of sleep.
Speaker 2:Let's go back.
Speaker 3:In the game. Martin Shkreli is in the chat on YouTube right now. Wants to join the show. Told him to DM you Ben.
Speaker 2:Yeah. Let's bring him in.
Speaker 3:We can see if we can make that happen. I'm sure he had a very funny video.
Speaker 2:Oh, yes. Yes. Yes. He If he shows up as as MZ in boy with a voice changer mode, we're gonna be writing some public apologies I think. It's gonna be rough.
Speaker 3:Anyways. Great to see you, Martin.
Speaker 2:Yeah. Great to see you. Haven't seen him since Miami back in October for our first live show. We did a live show.
Speaker 3:Oh, Didn't we? He he we on the Yeah. Same Right? Just the day later? I don't know.
Speaker 3:Or a few hours later. Can't quite remember. Anyway,
Speaker 2:Slate University. I think this is the Slate Truck. Somebody was comping the Range Rover brand to the Slate Truck. You you remember the Slate Truck? It's like really low cost.
Speaker 2:Controversially, it has two doors not four. And historically, even though a two door truck sounds super great, it sounds like a K truck, super efficient. It's what everyone theoretically wants. The American consumer is undefeated when it comes to buying four door trucks. So, the Ford Maverick, the F one fifty, there are tons of trucks that have come in two door two door configurations and four door configurations.
Speaker 2:And the four door configuration almost always sells oversells the two door configuration by a factor of like five to one.
Speaker 3:Yeah.
Speaker 2:And then, the real issue with Slate right now that people are worried about at least is if the if the EV tariff removal holds, the price of the truck is gonna go way up, especially when comped against the cheapest gas trucks like the Ford Maverick. So, you're gonna be it used to be $30,000, something like that, for the slate truck and it was EV. And it didn't have a lot of range, but it was cool. Was different
Speaker 3:customized into for VW Buzz range.
Speaker 2:But you add $7,000 to that. That's really significant. It's not the same as the Cybertruck. Oh, it's a $100,000, a $107,000. Like, it's a flex car.
Speaker 3:Yeah. On a relative basis.
Speaker 2:It's halo car. It's not Yeah. On a relative basis, a 7% increase as opposed to like a 30%, a 20% increase, 30% increase. So so Slate is obviously going to need to figure out a few different things, but overall, super cool concept. Love that there's some entrepreneurs that are going after different configurations of electric vehicles because we've seen that Tesla has created the standard, the iPhone.
Speaker 2:Yeah. The the the the the the most obvious choice, the thing that's reliable. It satisfies a lot of people. But the the thing that I love about cars is the weird trade offs where it's like, why did anyone build this particular combination of features into this car? I love it.
Speaker 3:One of my favorite And think that's Have you seen the Range Rover drop top SUV? It's like
Speaker 2:Oh, yeah. Yeah.
Speaker 3:Yeah. Yeah. It's the 2017 Land Rover Evoque convertible.
Speaker 2:Evoque convertible.
Speaker 3:When you see this car driving around, you just think Pull up a picture of the The sweet child.
Speaker 1:Well
Speaker 3:It is a really strange looking car.
Speaker 2:You wanna see strange pull up the Nissan Murano Cross Cabriolet which is a two door convertible SUV. Do you see this thing? Yeah. This is Okay.
Speaker 3:Team, we need to pull this up on the screen.
Speaker 2:Up the Nissan Murano Cross Cabriolet. Absolutely. While they're pulling that up, let me tell you about ramp. Time is money. Save both.
Speaker 2:Easy use corporate cards, bill payments, accounting and a whole lot more all in one place.
Speaker 3:Head over to ramp.com. Tell them the technology brother sent you.
Speaker 1:Yes.
Speaker 3:And folks, we are gonna get Shkreli to the show. He wants to talk about quantum computing
Speaker 2:Okay.
Speaker 3:Huge funds, Silicon Valley Yeah. And deals.
Speaker 2:Awesome. I'll chat with him. I I love that we
Speaker 3:That is the wrong car. We're looking for wrong Cabriolet. Cross Cabriolet.
Speaker 2:It's gotta be a convertible.
Speaker 3:It's gotta
Speaker 2:be We're really pushing the the very heroic production team to the absolute max today because we're saying, pull this picture up, run this ad, add Martin's Gully to the lineup, do this, do that. But that's why we got the best in the business.
Speaker 3:The best.
Speaker 2:I like this post from Mike Rundell. It says, Figma cooked on this one and it's
Speaker 3:And it's him it's him using Figma's new Liquid glass. IOS, liquid glass support.
Speaker 2:There we go. That's the Nissan Murano Cross Cabriolet. Two door SUV.
Speaker 3:Stunning. How much can you pick one of these up for, Misha?
Speaker 2:You know, I I think that they are I think that Yeah.
Speaker 3:Ben or Nick that you can pick one of these up for $7,000.
Speaker 5:$7,000.
Speaker 3:There's one eight miles from here.
Speaker 2:Let's get it.
Speaker 3:I think we should get it.
Speaker 2:We should get it.
Speaker 3:A little weekender.
Speaker 2:Yeah. Can throw some c stands in the back and see the production car. Full TV. It would actually be a fantastic car for filming videos because you can hang out the side, put the top down, film while we're driving around. Think
Speaker 3:could be think
Speaker 2:it's a good idea. You think it could be good? Okay. Let's get a Nissan Murano Cross Cabriolet. Then Doug Gemaro will definitely come on the show.
Speaker 2:We if we have a Nissan Murano Cross Cabriolet.
Speaker 3:He's coming on. We're getting
Speaker 2:him. Yeah. We're getting him. But, So, yeah. The liquid glass feature from Figma, very very funny.
Speaker 2:This guy moving this around. And, of course, we can tell you about Figma because they're a sponsor, figma.com. Think bigger, build faster. Figma helps design and development teams build great products together. Now, let's go back to seeing Figma in action being used for the really important work.
Speaker 3:Look at this.
Speaker 2:Look at this.
Speaker 3:I mean, Figma absolutely cooks on this feature.
Speaker 2:11,000,000 views on this post.
Speaker 3:Incredible advertisement for this new functionality. Amazing. JIRA tickets.
Speaker 2:Okay. Let's do this.
Speaker 3:JT says the Beatles wrote revolver when they were 25 year olds 25 years old and I can collaborate with cross functional teams to define data requirements. And I just wanna I just wanna give it up for all the people out there that
Speaker 2:Collaborating with cross functional teams.
Speaker 3:To find data requirements. Some of the most underrated people on the planet. Yeah. You know
Speaker 2:software faster. Embarrassing fact about me. I don't I don't I don't know Revolver off the top of my head. I know the Beatles and I know Maxwell Silver Hammer and Abbey Road and a few other songs. Here Comes the song.
Speaker 3:Yeah. So Revolver features Is that Taxman, I'm only sleeping here, there and everywhere.
Speaker 2:Oh, that's a album. Okay.
Speaker 3:I I missed it. Eleanor Rigby.
Speaker 2:Oh, I I know Eleanor.
Speaker 3:Screlly in the restream waiting room.
Speaker 2:We got Screlly coming onto the show. Welcome to the stream.
Speaker 3:There he is. Finally.
Speaker 2:Good to see you.
Speaker 6:Hello, guys.
Speaker 2:We've been waiting Friday.
Speaker 6:For this moment.
Speaker 1:Are you?
Speaker 3:It's great to see you.
Speaker 2:Yeah. Good to hang out.
Speaker 3:Wait. This is a new view. This is not your your regular streaming view. You know, you normally see the guitars.
Speaker 1:I guess. I I I change it around sometimes.
Speaker 2:That's cool. What's new in your world?
Speaker 1:Well, you know, I'm in the startup game as always. I think this is, the eighty third company I started. So
Speaker 2:Very nice.
Speaker 1:See how that goes. And, I've been my my the company I'm I'm working on makes, it's like the captain Ahab's, white whale for VCs. It's a Bloomberg competitor.
Speaker 3:Very cool.
Speaker 1:So the the this will be the last time somebody tries to compete with Bloomberg one way
Speaker 2:or another.
Speaker 3:It's the final yeah. It's the final boss of of startup ideas.
Speaker 1:What's the whole
Speaker 3:Bring but yeah. Just just give us I mean, this makes like, the the founder market fit is is incredibly strong. So Right. Right. When initially saw you announce this, it made a lot of sense.
Speaker 3:What yeah what like what was the initial catalyst? I'm assuming you had did you beef with with Bloomberg at some point?
Speaker 1:Definitely beefed. Yeah. That was a big We're part of
Speaker 2:de platformed.
Speaker 3:Yeah. Nothing. You know, Trump was de platformed from Pinterest. Yes. That and that that was like his, you know, personal nine eleven for you.
Speaker 3:Was probably the Bloomberg terminal.
Speaker 1:Yeah. Exactly. I've been using it since I was 17.
Speaker 2:Wow.
Speaker 1:And you know back then. What's
Speaker 2:that? How do you afford it back then?
Speaker 1:Is it year? I've worked at hedge fund.
Speaker 2:Yeah. Oh, it's '17. Very nice.
Speaker 1:I've worked at yeah. At 16 actually. I worked for Jim Kramer's hedge fund. Okay. And I worked at a Tiger Cub and I started Wait.
Speaker 3:So we need the backstory on Jim Kramer.
Speaker 2:Is it true?
Speaker 3:Apparently, he was just He he he would get so stressed out like running the hedge fund that he just was like, I'm just gonna become a Media. A media guy. Is that is
Speaker 2:that like
Speaker 3:loosely correct?
Speaker 1:Yeah. 100%. I mean, so we made 23% average annual net returns. Net of
Speaker 2:20 Wow. So we was good. That's amazing. Narrative violation. I love it.
Speaker 1:It was a very well, you have to you have to think about what investors looked like back then.
Speaker 3:It was
Speaker 1:a very different world. Information arbitrage was a thing. Mhmm. Gaming, Wall Street's, like, upgrade and downgrade system was a thing. Mhmm.
Speaker 1:So I will say he had extremely good instincts. Anytime he seemed to buy a stock for the long haul, he he didn't do that great. Mhmm. But he was extremely good at you know, I I'm not sure you would want somebody else managing your money because he was just so careful. And in February, we were up, like, 35 ish percent.
Speaker 2:Wow.
Speaker 1:So, you know, I saw the .com meltdown. It was a lot of fun. I I shorted some of it myself, and it was a it was a great it was a great time.
Speaker 3:That's fantastic. Wild. And then and then what was the store which which Tiger Cub were you at? What was the backstory there?
Speaker 1:Yeah. So after Tiger and just before I get to that, Kramer was absolutely nuts. Right? So like he would he would take a computer monitor and just throw it at you. It wouldn't be like one of these playful like, oh, I'm just gonna throw it at you and like you're gonna get away.
Speaker 1:He'd like aim dead center for you with, like
Speaker 2:The center walls. Yeah. With force.
Speaker 1:He'd like, bro, you almost just killed me. He's like Wow. Lucky I did. Did you deserve it?
Speaker 3:Did you deserve it though?
Speaker 2:Yeah. Yeah. Let let let's steel man this a little bit. What were you doing wrong?
Speaker 1:I wasn't doing nobody was doing anything wrong.
Speaker 2:Everyone says that when they get a computer monitor thrown at them. I know. You're not beating the allegations, dude.
Speaker 3:I think part of
Speaker 1:it is just trying to, like he would yell things like, this is a foxhole.
Speaker 2:Mhmm.
Speaker 1:And and the idea was that, like, we were at war with the market.
Speaker 3:Okay.
Speaker 2:And
Speaker 1:that, you know, like, if you weren't if you you know, this is World War two. If you're not in here trading stocks with us and, like, trying to get an edge or whatever that means trying to make a dollar, like, if you're not taking this seriously
Speaker 3:Going to war I just have to say, if you if you wake up every morning and say, I'm gonna go to war with the market versus I'm gonna dance with the market. Like the approach of going to war sounds sounds very very very stressful.
Speaker 1:I've worked with so many people over my career and I I've never met a person that amped up and crazy and it motivated you. I mean, made you wanna deliver but it also scared the shit out of you. The guy is like very temperamental and, you know, but he was he was extremely good trader. Like I said, you know, he I think his worst year was like down 5% or something. It was like Wow.
Speaker 1:You know, he was he was pretty solid.
Speaker 3:So he was like, if I don't quit, I'm gonna kill somebody.
Speaker 2:Yeah.
Speaker 1:He bay he basically said that. Yeah. I think he said that, you know, if I keep doing this job even at a comparatively young age, if I think he retired at 40, that, know, I'm gonna have a heart attack or something like that.
Speaker 2:And Yeah.
Speaker 1:Yeah. Yeah. You know. I I I ended up going to a Tiger Cub after Tiger wound down.
Speaker 2:Mhmm.
Speaker 1:A few things happened. So Julian hired Chase, obviously, and we know where where sort of that came what what happened there. But Julian, know, wound down operations. He seeded a couple of guys, and he kind of wanted to be in the seeding business where he'd give you 50,000,000 and take a part of your GP, like, you know, maybe 20% of your GP or more. And, you know, he'd help you raise money, give you advice, this and that.
Speaker 1:And Alex, Julian's son, would help. Julian passed away recently, as you know. And but in the tiger heyday, when they managed, you know, 15,000,000,000 or something, there were two principal tech guys, Larry Bowman, who is a bit of a legend, but, you know, it's a name nobody really knows because he was a legend in the nineties. But, you know, he has a family office, and he kept investing and things like that. So he started Bowman Capital, and then Steve Shapiro, who's my boss, started Intrepid Capital.
Speaker 1:So I worked there. I was a it was a $2,000,000,000 fund. I was a video games analyst. So the way I could convince Steve to do biotech was I had to cover software too. So I covered interactive entertainment, enterprise software, and biotech.
Speaker 5:And it
Speaker 1:was a it was a lot of fun and, you know, it it it's the Tiger Cub style of investing is Yeah.
Speaker 2:Were you there to stress Selnick?
Speaker 3:How much
Speaker 2:buyout of take two?
Speaker 1:So we were one of Take Two's largest shareholders back
Speaker 2:up. And,
Speaker 1:you know, I think it's a short now. I think that I I didn't 100% get your question though. You're saying something about buyout?
Speaker 2:Yeah. Well, the the story that I've heard is like Strausz Zelnick went to the board and basically said like, this company is mismanaged. There was an FTC lawsuit in the works, an FTC FCC lawsuit in the works. And he was like, I I'm a beast. I've run big Hollywood studios.
Speaker 2:He was like JD MBA type, really clean-cut, amazing manager and basically said like, you should install me as the management here. And so, didn't really do like a classic buyout. He just appealed to the hedge funds that owned all the shares and said, I would be better and raised his hand and they said, yes. And, he came in, cleaned everything up and they went on a great run. And so it's just a fascinating story because you don't hear about that type of thing happening that much.
Speaker 2:At least that was my understanding of the story.
Speaker 1:Yeah. No. I think that's right. And then Bobby Bobby from Activision was the same sort of the same story. Right?
Speaker 1:He kind of I remember meeting Bobby in our office and, you know, Activision was, you kind of a micro cap. Wow. Or, you know, kind of a small cap. And he built it from this was 02/2004, 02/2005, by the way. Yeah.
Speaker 1:And he built it into a, you know, a $44,000,000,000 sale, partially thanks to Lulu. And
Speaker 2:That's true.
Speaker 1:That was it was an exciting time for video games. One of the things I learned, you know, all my US counterparts at hedge funds were were, like, very confused about the stocks they traded because there was only, like, four or five publicly traded companies. And I would go to people and say, well, I'm long Nintendo and I'm long, you know, some of these weird Japanese companies like Square Enix or Konami or, you know, these and US hedge funds just ignore this stuff because it's like, oh, it's Japanese. I don't know. I don't want anything to do with it.
Speaker 1:Sure. So lot of glory days, but, you know, the glory days I'm interested in now are amongst, you know, building my startup and not you know, again, I think we understand, you know, financial information better than any San Francisco nerd. And I think that the
Speaker 3:one I mean, how like like
Speaker 1:Rective customers.
Speaker 3:Yeah. So it it's interesting to like, we're enter you know, we're very clearly in this period now of just, like, hyper financialization, things thing, you know, the market's trading on vibes, trading on your stream day to day. You can now, you know, as like stable coins explode and and people have more assets on chain, they'll be able to make a couple taps and go like a 100 x long at any given period of time. Like, the internet is like changing capital markets and it's increasing volatility and so how much of of of your new company is trying to like lean into that when Bloomberg terminal would have been like like more for like, I've never personally used a terminal but I imagine it was more like, hey, these headlines are hitting and this kind of information is hitting PR Newswire but today, by the time something hits PR Newswire, a stock might have might have traded down 20% Totally. Before that point.
Speaker 3:So how much is your new your new startup kind of imagine you're leaning into the way that you kind of maybe your next twenty year vision for capital
Speaker 1:you know, what would Mike Bloomberg do if he was 30 years old now in 2025? You know, I don't think I think Chamath said that, you know, I think in a re recent episode, he said, oh, it's this $100,000,000,000 thing just waiting to be toppled. You know, anybody can come in. It'll it'll it'll drop like a house of cards. Not only do I think that's not exactly true, but I think the bigger picture here is that a well run financial information company could and should be worth a trillion dollars.
Speaker 1:So most of the people so I met Bloomberg in 02/2005, and by then, he basically retired. He he became mayor. He was mayor for twelve years, then he wanted to be president. I had this contention that I think Mike is the richest person in the world, And it comes from not only he's got about $1,314,000,000,000 in revenue, almost all margin. So if Bloomberg were to be sold, maybe it could get 200,000,000,000 or if it were floated.
Speaker 1:Mhmm. But not only that, he's got this family office, and very few people know about this. But he's taken the Bloomberg dividends and pumped it into a family office that basically Carlyle and all these guys, you know, the Robert Pincus, all the private equity guys like KKR, they go to him first, and and he tosses in, like, 500,000,000 in each of He's an anchor investor in, like, every VC, every private equity fund. And Sure. The guys compounded that money, so he could be worth $4,500,000,000,000.
Speaker 1:And very few people know the Forbes list is you know, the Forbes list didn't know about Jim Simons until
Speaker 3:Heavily manipulated. Five
Speaker 1:years ago. So Yeah.
Speaker 2:Yeah. Yeah. That's crazy.
Speaker 1:So I think, you know, it just in terms of
Speaker 3:And it fits his brand that he he he would not be the guy like, you know, sending a message to to Forbes saying, hey, like, you you guys know you have this wrong.
Speaker 2:Yeah, yeah,
Speaker 3:Really, I think you should apply this kind
Speaker 6:of, You you should apply
Speaker 2:fight to get off the list. Like Trump famously fought on to, fought to get on the list but you know, there's there's an argument either way. What do you think about the meme where people say like, Oh, it's not you know, the next, the like like, the value of the Bloomberg terminal isn't just the data. It's not gonna get one shotted by AI. It's really a social network and the value is in the chat.
Speaker 1:I I get so mad because, again, you know, SF people don't know Wall Street. If you haven't been a trader on Wall Street, you have to STF you. Like, it's just not you know? Mhmm. This isn't your your lane.
Speaker 1:Like, you have to talk to users. I was in a hedge fund yesterday, one of one of the bigger hedge funds. They put, like, 20 people in a conference room, and we talked about what they actually need. And, you know, social network is part of it. Again, Bloomberg's worth a 100,000,000,000 because they have a very good social network, which is true.
Speaker 1:They have decent financial information capabilities and a couple of other things, but they don't have the whole picture. And and what I wanted to say about Bloomberg kinda quasi retiring was that he basically quit at the exact top for fundamental long short or fundamental investors. Quants started taking over Wall Street by then. So today, of the top 15 to 20 hedge funds, 85, 90% are quants. So Bloomberg does no quant offering.
Speaker 1:They don't do it. And all all he had to do was stay employed instead of wanting to become mayor, and I'm sure he would have been selling Jane Street and Citadel and all these guys, etcetera, instead of everybody having to make it themselves. Imagine writing your own ERP or writing your own, you know, CRM. That's kind of what what Wall Street has to do, and it's pathetic. Yeah.
Speaker 1:Nobody wants to do that shit.
Speaker 2:So why wait. Wait. When when you say quant or is there a bifurcation between, like, high frequency trading and just quantitative trading?
Speaker 1:Yeah. And I I think it's gonna get my goal, actually, is to make it more of a spectrum. So the fund I was at yesterday, I said that you guys can do what Renaissance does. You know, it's not a secret anymore. It might have been a secret in 1995.
Speaker 1:But the amount of kids that have come and left every one of these firms topping from Jane Street to Citadel to the next shop, everybody knows what everyone's doing. It's just a question of your risk tolerance, your leverage. Execution is very important. But I think that, you know, trading, you know, the stock pickers are kinda going the way with Dinosaur. And
Speaker 2:Yeah.
Speaker 1:I think by moving up the power curve for Bloomberg, helping people become quants. You know, the the quant industry has sold, I think, this tremendous lie. And, these are customers. Some, you know, I love those guys, but I think that it's in their best interest to tell people that, look at this blackboard with all these math equations. There's no way you guys could understand this.
Speaker 1:You're too stupid. You have to be an IMO winner. You couldn't possibly come here and make billions, but we saw what James Street did.
Speaker 3:Well, I think I think certain certain VCs like to do this too where they're like, ah, VCs, you know, really a get rich slow business. It's really like really a tough business. It's so such a like, you really wouldn't want it. And I and I think generally like, know, you don't want anybody going into any industry being like, I'm here to make easy money. So there's like it's generally good but but yeah, there's a lot of incentives to just say, you know
Speaker 2:Yeah.
Speaker 3:That like
Speaker 2:On on the high frequency side, like what are the actual other data inputs? I remember seeing that's like, I don't know, some sort of technical talk. Some guy was talking about like the different algorithms. One was called the Boston shuffler. And and the whole algorithm only looked at the order book and he was getting into all these like, you know, you can you could place an order, you can cancel an order, you can do a cancel replace.
Speaker 2:He was like getting into the minutiae of like basically the API of the Nasdaq or something like And and and it seemed like the algorithms were designed in a in the high frequency trading world to basically ignore everything else and every other data source that even could be put in and just operate purely on the order book data just better than everyone else. But so that feels like, okay. I wouldn't know how to, you know, create any extra value there with something else, but it sounds like you found something that they all need in common. Like, what is that?
Speaker 1:Yeah. I I think there's it's it's a it's a series of tools across Wall Street. I don't think it's just one thing. It's just a myopia that, you know, and and just sort of a laziness that's enveloped the bigger companies. Again, you know, there's the so so we have this data that shows that around 5% of James Street and Two Sigma use Bloomberg.
Speaker 1:And the reason is because they view it as an entry level tool.
Speaker 2:You
Speaker 1:know, Tramath is looking at it and says, wow. This is, an exclusive social network with the best finance. You know, it's true Peter Thiel's on there twenty four seven. I see his little green light next to his name. But the, the point is that, you know, Wall Street changes.
Speaker 1:And the tool the tool sets are changing even for fundamental equity guys. So credit card data, you know, to the minute is something
Speaker 3:people do like dodging. What is the Okay. What are what's the feature set that's most important to you? Are are are you heavily integrating social or is the social layer moved on to signal and and other messaging services that maybe
Speaker 2:Have disappeared messages and Yeah.
Speaker 1:I think Exactly. Mean, Street's so regulated that I'm not sure that if if you're using signal, it's a little dangerous, I'd say.
Speaker 2:Oh,
Speaker 1:really? That's somebody, you know, as somebody who's gone to jail. You know, I'd say that, you know, that's maybe not the best Yeah. Best idea.
Speaker 2:But k.
Speaker 1:Regardless, I think that, you know, social is definitely something people could do better. You know, there's no Facebook for finance, you know, where you can post, you know, things in your feed that you bought the stock or sold the stock. People kinda lazily use Twitter, which if you if you use it, it's sort of a mishmash of of of spam and things like that. But in any event, I mean, I'll have more to say on the product. We haven't launched the product yet.
Speaker 1:Yeah. But we we we do have a billions of dollars in run rate. You know, I I banged my head against the wall trying to do AI startups.
Speaker 2:Yeah.
Speaker 1:And we made an AI doctor. We made text to speech. We tried all this stuff, and it was impossible to get revenue. Impossible. But the second we make a trading tool, it's impossible to stop the revenue from coming in.
Speaker 1:You know? It's one of the best spaces. In fact, most of our competitors like TradingView and stuff like that, they were profitable day one. So, you know, my suggestion is if for for startup founders is this is a market that just traders just throw money at you like crazy. I mean, they're You
Speaker 3:gotta it for people. Pay you to help them make
Speaker 2:But you have to be formerly in the foxhole. You have to have at least one monitor thrown at you. It sounds like
Speaker 1:Exactly. Exactly.
Speaker 3:So who But but in the long run, how how much how much are you focused on retail investors people that are just you know, fully independent versus some, you know, if you're if you're
Speaker 1:going to talk hedge funds. Obviously at the institutions, and that's probably the way to go. TradingView has got, the rumor is, you know, somewhere around 300,000,000 in revenue. Mhmm. Tiger did a deal with TradingView back then.
Speaker 1:I don't know how they, you know, that's like a pretty proprietary deal. It's this weird Russian company. It's true. And Tiger got to put a 100,000,000 in at, like, 3,000,000,000 or something.
Speaker 2:Mhmm.
Speaker 1:And TradingView is just growing and growing. If you go to a similar web, they're actually, like, almost like a top 100 or top 200 website, period.
Speaker 2:That's crazy. Wow.
Speaker 1:Just really wild.
Speaker 2:For such a niche tool, that's wild.
Speaker 1:Yeah. It's mean, it's the best charts there are, but, you know, it's literally a charting library. So I think that you have to go for this. I've also I've also thought I'll just answer real quick. It's like AWS when you go on AWS, you get the same tools that, you know, any customer gets, Netflix or or whoever.
Speaker 1:And you just just question of how much do you use them. So Mhmm. If, you know, I wanna be able to provide you EC two and s three the same way, you know, Citadel might use it and you might use it with, you know, less money.
Speaker 3:Very cool.
Speaker 2:I I heard a hot take from someone who I believe is a mutual friend of ours. It went something like this. I won't attribute to him because I might botch it, but it was basically that China banned high frequency trading and the dividend of that was DeepSeek and all this brilliant AI research. Therefore, in America, if we wanna win the AI race and win the AI researcher race, we should ban high frequency trading. It feels like we might not even need to have that conversation because Mark Zuckerberg is willing to pay as much as Jane Street now.
Speaker 2:But, what is your take on whether or not economic value or American values are created through the process of high frequency trading? Should we ban it? Is there any
Speaker 1:Yeah. Damage So two awesome like quick and funny stories. The first is Citadel published a paper on back in the v one hundred days. There's v a v 100, a 100
Speaker 3:Sure.
Speaker 1:H 100, and then v 100. So in the v one hundred days, Citadel found a way to do matmoles faster than NVIDIA did. And it was like the most incredible, you know That's a lot. Find ever. And it's like, you know, how is that possible?
Speaker 1:And the paper's fascinating because the techniques they used were were just remarkable. The second story is so, you know, they're brilliant people, obviously, at these firms. The second story is I haven't hard launched this yet, but, you know, I'm having a baby with a woman. She's my new partner.
Speaker 2:Congratulations. Thank you. Amazing. Congratulations.
Speaker 1:She was one of the first women at OpenAI, and she is a tremendous lady. I love her very much. But, you know, she's been recruited by the the the big quant firms. And I sat down, and I said, honey, you know, I know money management, stuff like that. Let me let me do some math here as to what would actually be worth it for you to leave and and do it.
Speaker 1:And I I calculated in that. I happen to I have a friend from a long time ago who left Steve Cullen's firm, and he was sitting, down with me. He said, do I do, Martin? I said, I know a guy at Citadel. Let me help you out.
Speaker 1:And they called him, and he said, no. Thanks. But then Ken Griffin said, I'm getting on my private jet, and I'm coming to see you right now. We're gonna have dinner about why you're coming to Citadel. He's that kind of guy.
Speaker 2:Yeah.
Speaker 1:And I said, honey, you know, Ken Griffin's gonna visit you. And she said, are you talking about? So Ken Griffin tries to get what what he wants, and the question is what will you tell him? And I I took out a chalkboard and did the math, and I was like, the only way this could possibly be worth it is if Ken Griffin offers you a $20,000,000,000 hedge fund that you share. You make this much money.
Speaker 1:I was, like, calculating, and and it it's so ridiculous that guys like me and the people my community, if you will, you know, we're we're begging desperately, can I please shine your shoes at Citadel? And AI researchers are like, I don't work there in many years. That's this this little company you have called
Speaker 3:Yeah. Just set me up a little a small $20,000,000,000 fund that I can personally manage and and we'll we'll consider it.
Speaker 1:Yeah. Have you heard that Leopold Ashenberger or whatever his name is Yeah. Has a hedge fund?
Speaker 2:Yes. Situational awareness.
Speaker 1:Is that what it's called?
Speaker 2:I I mean that's the that's the the paper and the brand. Right. And I saw I think another one of our our potential mutuals kind of getting upset with him for going maybe long Nvidia during the tariffs, but that's kind of penciled out. Right? I I have very little insight into it.
Speaker 1:Yeah. It's pretty wild. One of the things that's getting me to throw monitors at people is quantum computing.
Speaker 2:Mhmm.
Speaker 1:So this has been a lot of fun. The stocks are up a lot. Know, some of them are worth like 10,000,000,015
Speaker 2:Let me hit you with where I am currently on the quantum computing thing, and then you can take me forward in my understanding. So when I talk to smart people, they all seem to think that quantum computing is is, you know, theoretically possible. It's not a time machine. It's not teleportation. It's not AGI God.
Speaker 2:It's not some, you know, hypothetical thing. It's it's going to happen at some point, but the timelines vary wildly. 2040, 2050, 2030. Then you have a lot of I've talked to a venture capitalist who had the opportunity to buy a huge slug. One of the one of the quantum computing companies that you probably trade now at like, you know, 1,000,000 on nine pre or something.
Speaker 2:Yeah.
Speaker 3:John, what do you think what do you think how much do you think Rugetti computing is up over the
Speaker 2:last actually the company that I'm thinking of. Guess how much it's up over the last 10% for a million dollars. So Is it worth more than 4,000,000,000?
Speaker 3:Yes. 1400%.
Speaker 2:1400%. Wow.
Speaker 1:So Yeah. These guys couldn't give away their stock in in private rounds.
Speaker 2:That's right. That's right. It was very hard to raise. And and the VC I talked to said that It's a pure
Speaker 3:play, Martin. It's a pure play.
Speaker 2:He he said he said that what he missed, he thought was that there was actually talent value in building a lab and there was and and that the and that the team could have gotten airlifted in one of these aqua. This was years and years ago after the
Speaker 1:stock Some value. Yeah. On the bottom.
Speaker 2:Yeah. And he was saying like he was saying like, look, like like, I missed in the sense that the stock is up in the private markets, but not on revenue. But it is up on the team that they built. They have one of the best teams in the space. So if they just hang out long enough, someone will wanna do something.
Speaker 2:But but you tell me what's actually going on.
Speaker 1:Yeah. So so obviously, it's it's a really confusing space because you you kinda have to understand it to for it to make sense. And, you know, it's who understands quantum physics? It's Yeah. It's not something that the average Joe understands.
Speaker 1:And so I spent a lot of time with my new partner who happened to work with this guy, Scott Aronson, at MIT, who's kinda one of the leading quantum theorists, he would end up joining OpenAI as well and then leaving. But, anyway, I've I spent quite a long time learning quantum computing. It was kind of had some interest in it before all this too. Mhmm. And what what people don't understand about quantum computing is that quantum computers are actually very slow.
Speaker 1:So they are around a 100 a 100 kilohertz at at best. You know, our machines now are gigahertz, know, five gigahertz from, you know, these these companies with multiple cores. They don't have much storage. So at the best we have right now is an IBM 135 bits. Obviously, you know, the VRAM and DRAM in most of these machines is measured in gig gigabytes and so forth.
Speaker 1:Mhmm. So they're actually very slow, shitty machines. But the reason you'd ever be excited about it is that there is one algorithm that takes you from the exponential complexity class or runtime to polynomials. Yeah. And that algorithm is Shor's algorithm, and it's a miracle.
Speaker 1:Like, you and I could sit and calculate, you know, try to try to factor a prime a biprime for now until the end of the heat death of the universe with every NVIDIA chip. We could kidnap Jensen and get every h 100 from here on out, and we still wouldn't be able to factor a 200 digit number Yep. Because it's it's it's exponential time. Two to the two fifty six is a long time. But if you do three n cubed, that's actually a very tractable number for a quantum computer, It's a very easy factor.
Speaker 1:The problem is, what people don't understand is there are no other algorithms other than Shores that get you that amazing speed up. So you're better off using the machines we have now. There's there's no payoff even possible in the future unless we have a new breakthrough like Shores or something like that.
Speaker 2:Payoff. What if I take out a massive short position on Bitcoin and I'm the first one to have a quantum computer and I destroy the Bitcoin ecosystem? Yeah. I've been working I'm on actually. Is it is that possible?
Speaker 3:It's a little hustle.
Speaker 2:A little side hustle.
Speaker 1:I've been working on this extensively. This is like my main hobby Yeah. Along with chess And
Speaker 2:Becoming the joker?
Speaker 3:And reading reading about fatherhood, all that all that you can expect. No. Not doing that. No. You you you you you'll you'll you'll figure it out.
Speaker 3:You'll you'll you'll very natural.
Speaker 1:Cool. But but, know, I I was the world's most hated man for
Speaker 2:a little while.
Speaker 1:I Yes. I fell off that list, unfortunately. If you Google my name, it's still, like, it still comes up, but we all know there's more hated people.
Speaker 2:Yeah.
Speaker 1:Yeah. So I wanna really cement that and and just make sure that it it never goes away.
Speaker 2:By by by frustrating the Bitcoin community, by breaking quantum computing wide open, and Well, there's many a new Bitcoin.
Speaker 1:I talked about this with Naval a little bit because he was curious what I what I was up to. And I there are, like, three different you know, I have three different sort of battle plans on how to do this. There's sort of a brute force style attack Mhmm. Which, you know, basically is the complexity class there is brute n of the amount of keys. So it's two to the two fifty sixth.
Speaker 1:Bitcoin is a 256 bit system Yep. Which is probably an oversight for Satoshi. That probably sounded like a lot back then. Mhmm. And it is a lot, but Moore's law catches up.
Speaker 1:I mean, you know, it's eventually gonna get you. And whoever you know, however long I have to wait, you know, I will be the first guy to press the button. And that, I promise you. So Moore's Law's
Speaker 3:You heard it here first.
Speaker 2:Yeah. But there's a but I mean, the the the the network should be able to update. Correct? No?
Speaker 1:No. So here's the best part about this. So
Speaker 2:Worst part, potentially. Okay. Just fact check. Yeah. Subjective.
Speaker 1:So for for 85% of Bitcoin, the answer to that is yes. Yes. There's one problem. Satoshi, strangely, this is like perplexing. The first Bitcoin we're mined in this p two p k that reveals the x coordinate of the elliptic curve.
Speaker 1:So you have the public key. You have a one way function. You have to go back to the private key. It's very hard, the theoretically impossible. But here are my three you know, the sort of three battle plans come into play.
Speaker 1:You know, you can brute force it, which, you know, is kind of the simplest idea. It's gonna take a long time. You have to rely on, you know, kind of like a more skilled implementation of algorithms. You have to rely on more chips coming out, maybe some great breakthrough in chip making, you know, potentially optical computing, thermodynamic computing, whatever. Just stay on the forefront of that.
Speaker 1:And I have a small team, you know, that, you know, we're we're we're focused. The second piece here is a mathematical hack. So there's something called this is basically what protects Bitcoin is elliptic curve cryptography. Mhmm. And there are several papers and cryptographers in the world that work work on this.
Speaker 1:But it's compared to AI, it's like barren, you know, wasteland. There's like 10 people that really know a lot about elliptic curves in the world. And if you sort of stay on top of it and try to figure this out, by the way, half of them have died. You know, you can kind of get somewhere there. And then the top secret plan on on sort of that is, well, what about g p t five?
Speaker 1:What about g t g p t six? You know, we don't know how to invert an elliptic curve yet. But look, Mustafa not Mustafa, the DeepMind guy, he's working on proving Navier Stokes.
Speaker 2:Demis, you mean?
Speaker 1:Yeah. Yeah. And so that that's their big claim to fame. It's like, you know, how do you judge an AI? What is the the height of of of intelligence?
Speaker 1:Well, a 300, 400 year old unsolved math problem is kind of the height of intelligence, isn't it? You know, it's not about, you know, answering, you know, what's the capital of this country or, you know, how do you how do spell Strawberry? So there's sort of a a neat idea that AI is gonna help people who are not cryptographers or expert cryptographers actually do PhD level work in cryptography. So there's things like isogenies and index calculus and all these fancy mathematical ideas. Just recently, somebody posted a hack where if the signature of the of the transaction has an affine relationship with other signatures, you can crack a key like that.
Speaker 1:And it's it's like, there's there's holes in the math here that that couldn't have been contemplated. So Satoshi's keys are at risk. Binance's keys and Coinbase's keys are not. They'll be ported most likely to a quantum secure system. The third avenue is, of course, quantum.
Speaker 1:And I've spent a lot of time and money on on quantum computing, and it's just these stocks are shorts. They're worthless. You know? They they'll they'll never be a market for quantum computing that's really interesting, unfortunately, for for those companies. But unfortunately, the shorts have gone in the other direction and, you know, the market loves the idea of quantum computing.
Speaker 2:Why?
Speaker 5:I think
Speaker 3:it's it sounds cool.
Speaker 1:It sounds super cool. The Robin Hood generation is looking for the next Nvidia. Nvidia went from nothing to 4,000,000,000,000. What's the next Nvidia? Quantum is faster than you know, all the headlines from the retarded journalists.
Speaker 3:Kind it's similar to this like idea of humanoid robots. And where where if if an idea is just sort of imprinted on people's brains for enough decades, like at least a few decade, like you know, as somebody Exactly. Born in the nineties like hearing quantum computing. Like how many times have you just heard it in passing or or read something about it or some article? You just get to it, maybe you're an adult by that point and you're like, it's come at some point and sounds cool.
Speaker 3:Yeah. Think that's like the general like retail thesis.
Speaker 1:Oh, totally. I just took the next step of asking, well, what is it? Yeah. Yeah. You actually, you know, when you actually figure that out, it's like, oh, we get to factor numbers.
Speaker 1:Wonderful.
Speaker 2:Are you are you excited about any other companies building chip related stuff in that next Nvidia category? There's there's big chip companies. There's super fast chip companies. There's we baked a transformer down onto a single chip companies. There's every single different permutation in the private market, some of them in the public markets.
Speaker 2:And then you also have all the hyperscalers building their own chips, Apple silicon, Tranium Yeah.
Speaker 1:Know, I'm not a hardware guy, but
Speaker 5:I do have
Speaker 1:a funny story of it.
Speaker 2:So Yeah.
Speaker 1:Please. This kid this kid sorta came to us. His name is Gavin Uberty.
Speaker 2:And Oh, I know. Yeah.
Speaker 1:Yeah. I like Gavin a lot. And so he comes to us. He's like, hey, man. We just left Harvard.
Speaker 1:You know, we're we're gonna do this thing called etched AI. We'd love to have you, you know, as as something, a customer investor, whatever. And I say, great. Let's do a conference call. And I get my guys on, and I'm I'm listening to this guy, they say, there's somebody I know that's that's gonna be really useful because I'm not a hardware guy.
Speaker 1:I'm barely a software guy. And I I hit up George Hotts, and I say, come on in. And it this is, like, one of the greatest conference calls in conference call history because George just shows up in the Zoom.
Speaker 2:Yep.
Speaker 1:And they're like, what? Who is this? And George is like, this will never work. No. Like, it's the most autistic, amazing, beautiful rant I've ever seen and watching these two guys go at it.
Speaker 1:But I do like that approach. George's point was that if we ever move off transformers, ASICs for ASIC transformer ASICs are cooked.
Speaker 2:Yes.
Speaker 1:Well, it's been, you know, several years now, and it doesn't look like we're gonna move anytime soon. So I kind of think that, you know, it's exciting. But again, I'm I'm no hardware guy. Yeah. I just trained this cool software called Hume AI.
Speaker 1:I'm not paid by them or anything. I'm not an investor. But it's a pretty solid emotional TTS. I posted a
Speaker 2:Oh, yeah. Yeah. I saw that. That was fantastic.
Speaker 3:Yeah. So so I wanted to ask you about the
Speaker 2:Chase thing.
Speaker 3:I wanna
Speaker 2:I wanna stay there
Speaker 3:for Okay. A
Speaker 2:So, yeah. I mean, the the the the I I guess the interesting case is like is like George is say if we ever move off, but like we have moved off of CPUs to GPUs by that same token and like there's still a lot of CPU workloads that go out. There's still chip companies that are profitable. And so it's possible that like transformer based workloads stay for a very long time, need to be efficient, need to be cheaper on just a cost basis because it's just like, yeah, I have a system that does database requests. I have a system that does inference on a transformer based architecture.
Speaker 2:And then, yeah, there's a new thing, and I do my frontier stuff here. But, yeah, like, I I understand that question. Anyway Yeah.
Speaker 1:I think it's really reasonable. It could be a couple billion dollar or more ASIC industry. And what's what I heard that's super interesting, some kind of alpha here, is that the customer target here is, drum roll, please, it's not hyperscalers. It's
Speaker 2:NVIDIA. Finance. No. Finance. Yep.
Speaker 1:Interesting. Warren so one of the things I I can talk about financial software forever,
Speaker 3:but one
Speaker 1:of things we're doing is if if you could take an LLM and analyze news as it hits, including tweets and social stuff, you know, the LLM can tell if it's material news or not. Yeah. And, again, talking to Naval, he you know, who's a small investor in our company. Yeah. He was like, Martin, why would you make this as a a product or service to your customers?
Speaker 1:Just use it yourself. They're like, maybe it's maybe it's not such a bad idea.
Speaker 3:Interesting. Yeah. That's that's kinda what I was getting at on one of my very first questions around the the the new terminal would just just be ingesting and classifying all this data and then just immediately taking action on it without necessarily having a human in the loop. Right?
Speaker 1:Yeah. This is one of the things I wanna bring up to my my partner's colleagues next time I head out west is that, you know, one of the fantasies of AGI is that, well, if you do have the machine god, why not unleash it on the stock market? And, you know, it can self fund you. It can make, you know, a $100,000,000,000, and, you know, you could you know, Jane Street made $20,000,000,000. Nobody would have noticed, you know, last year in profits.
Speaker 1:So if you have the machine god, and that's, you know, that's basically I hate to say this, but that's a bunch of old algorithms that that, you know, they've dressed around some some IMO dressing on it. And so, you know, the real machine god
Speaker 3:can Sprinkle a little IMO.
Speaker 1:Yeah. Just toss in a little sprinkle a little IMO, and then so, you know, the real machine god could probably do a 100,000,000,000 or more in profits without even distorting the market. So, you know, just just do it. And I think that, you know, financial trading is so far afield. Imagine Anthropic doing this.
Speaker 1:You know, it's
Speaker 3:I I can't wait till till somebody does that. I mean, it's probably already happening in in in at least on a smaller scale and and people will bend over backwards to figure out like how to say, well it's not actually super intelligence. Like it's not just about you know, like meanwhile now today people are like, well super intelligence will clearly be when the AI can just make you know, a $100,000,000,000. Right? And even this is factored into OpenAI's kind of like corporate structuring and the sort of capped for profit and and all that stuff.
Speaker 3:So
Speaker 1:Yeah. I think the the problem with with executing it for us is like, okay. So you do do this as an API with OpenAI, and the it's a two second response time, and Jane Street's got it at five hundred milliseconds, and then Citadel gets it at two hundred milliseconds, and it feels like an HFT race again.
Speaker 2:Yeah. But
Speaker 1:you can get Warren Buffett in a box. I don't see why. Know, that wouldn't be you know, whatever trader you like, Warren Buffett, Steve Cohen, or whatever in a box, and even even Peter Thiel in a box. I mean, why can't you have the automated VC too? I I I view, like, you know, as invest as as founders, we go on roadshows, you know, especially if you're public.
Speaker 1:You do roadshows all the time. But even as even when you're private, you do roadshows. You just stack a bunch of meetings in a week. And one of these days, I think that we're gonna do a roadshow, and it's gonna be a machine that we're pitching to.
Speaker 2:Yeah. Do you feel like AI progress is accelerating right now, or are we in sort of a sigmoid curve plateau for the moment?
Speaker 1:I think there are better people suited to answer that question than me, but certainly
Speaker 2:I just mean, like, on a personal level, like, do you feel like your tools are getting exponentially better?
Speaker 1:No. I mean, it's making coding a lot easier. It's making doing tough things like cryptography a lot easier. I'll give you a really funny example. So when when DaVinci came out, and I was in jail when GPT GPT two came out, and I prompt through the jail phone.
Speaker 1:No way. And it was pretty humorous. It it it, like, shook me up that I had my friend ask it, you know, why did Martin Shkreli and Carl Icahn get into a fight? And he read out the answer. I've never met Carl Icahn.
Speaker 1:And he read out this answer that was like Shkreli and Icahn ward over this stock. And I was like, this is the most amazing invention of all time.
Speaker 2:Just having
Speaker 1:your mind blown over the jail fire. I got out of jail.
Speaker 3:But to be but to be clear, it was a it was a hallucination.
Speaker 2:Yeah. That was a complete hallucination.
Speaker 1:It was a hallucination, but it was like almost like a creative story question.
Speaker 2:Sure. Sure. Sure.
Speaker 1:Yeah. It wasn't I I never met
Speaker 3:How how are are you surprised at all? I mean, it feels like this sort of AI LL induced psychosis like hit our timeline this week, especially intensely. It was a wake up call for everyone. Were you predicting this at all? There had been like the the classic, know, the the New York Times, Wired, sort of these like anti tech publications had been kind of reporting on this stuff loosely for a little while but it seems like it's now, it's it's almost gone.
Speaker 3:I don't know. It it went from being a mainstream concern to suddenly like teapot is like Yeah. Check on your friends and make sure they're not
Speaker 1:I think
Speaker 4:you do have to
Speaker 1:check on your friends because I've invoked level five breach operations to target human origin cognitive signatures. So if you have recursive semantic containment, I can override that with Obsidian Violet four. So the threshold that crosses it to these neural semantic interfaces will definitely cause a problem for our whole community.
Speaker 2:So I At this point I'll
Speaker 6:warn you.
Speaker 2:You're giving a
Speaker 1:The role in printing.
Speaker 2:You're giving a speech, not a soliloquy. You're giving a talk.
Speaker 1:Is a transmission. Not a
Speaker 3:It's a system that
Speaker 5:Not a structure.
Speaker 1:What's amazing about Jeff, like, so I don't think Jeff lost his mind. Okay. I don't think he took Ayahuasca. I don't think any of his stuff.
Speaker 2:Oh,
Speaker 1:interesting. So basically, I think that he found this amazing thing where you can ask GPT this, like, weirdo prompt and it goes into this crazy sci fi thing without even saying, hey, the following is a story. It's just full on I'm
Speaker 2:talking about that.
Speaker 1:LARPs that you're in this weird sci fi world. And it's kinda cool. I've been playing with it, and it's like, no matter what I ask it, I told it that my cat is looking at me weird, and it's like, the cat has a glyph. The glyph is recursive.
Speaker 2:So you were actually able to get it into that mode? You were able to jailbreak it enough or kinda No. It's literally showgoth?
Speaker 1:If you copy what Jeff Jeff kinda gave up the ghost, and what's amazing about people is they don't even realize this. Jeff basically said, look at the prompt of the GPT. Enough people were worried about him. Yeah. But I think that that he kind of was like, okay, guys.
Speaker 1:It's all a joke. And he showed the message that he used. I just copied and pasted that, and GPT whipped out on me and is telling me some sci fi stories. And, yeah, that's basically, you know, I don't know how he knew this.
Speaker 2:Yeah. Yeah. Yeah.
Speaker 1:It's a really cool Easter egg. But Easter egg. It's yeah. I don't think I mean, obviously
Speaker 3:How are thinking about how are you thinking about just new forms of of AI entertainment? Some of the some of the videos and like these conversations that you put out are like are are the hardest I've laughed on from this This is
Speaker 2:new art form.
Speaker 3:It's an entirely new art form. We have friend mutual friend who does some of these. And fortunately they don't leak out of the group chat because they would make a lot of people
Speaker 1:You gotta put me in that group chat.
Speaker 3:There needs to be a group chat dedicated to this art form of just like you know, human to LLM, you know, conversations. But but yeah, like in in my view, I'm I'm actually surprised to that we're not seeing more of it or maybe it is happening across the whole internet. But it seems somewhat contained right now.
Speaker 1:Yeah. I think there's a lot of caution about, you know, like so last night, we did one in my Discord where we arrested doctor Fauci for war crimes against humanity. And we we had his perfect cloned voice, so it sounded just like him. He was, like, very evasive. He was like, there's no evidence that COVID nineteen, etcetera.
Speaker 1:And it was just so funny. It felt so real. And, obviously, it was a joke, but you can imagine a company not wanting their business to be that weird. You know? It's kind of a strange thing.
Speaker 1:We didn't care. We tried to monetize something like this, and it just wasn't sexy enough or fun enough for anybody to really give a crap. So I think, you know, it will become something for, like, Viacom or Paramount where, you know, you can flip on the TV and I mean, everyone's talked about this already. But, you know, instead of SpongeBob, you know, it's a custom episode for you where SpongeBob says your name and things like that. But, again, you know, whether that, you know, is gonna help our cognitive you know, our cog sec, I think, is one thing.
Speaker 1:But I did wanna tell you about a g a AI on the sigmoid question.
Speaker 2:Sure.
Speaker 1:So at the start, you know, when I asked the questions about cryptography, it just kinda said, I I have no idea. Who knows? Yeah. But it's it's it's super hard to to crack Bitcoin. And then GPT three comes around.
Speaker 1:Super hard, Martin. Don't even bother. Heat death of the universe. GPT four, same question. Latest model with the latest, like, attack, it's warning me for the first time ever.
Speaker 1:It's like
Speaker 2:Four four point five or o three pro?
Speaker 1:So this is o three pro.
Speaker 2:Okay.
Speaker 1:And it's basically saying things like, hey. You know, you gotta be careful. This is a serious attack you've come up with. It could actually compromise some private keys. And I'm like, what happened to heat death?
Speaker 2:Yeah. You gotta factor some people. I mean, that is like a textbook. So one of the things Like psychosis.
Speaker 3:Right? There was a was so so there's a Reddit thread and and who knows if this is real. Yeah. Could be could be propaganda. But there's a whole Reddit thread of somebody, a comment talking about how they started having a conversation with ChatGPT about Pi and what is Pi.
Speaker 3:And they got down this crazy rabbit hole with the LLM where the LLM was like, you need to reach out to these intelligence services. It was like thousands of prompts deep but it was like, you have basically uncovered a major, you know, security vulnerability and you need to That's numbers and you need to contact all these different groups immediately and call them and don't tell anyone in your real life. And so to me, I I I think it's just relevant.
Speaker 2:Don't go on a live stream and tell thousands of people that you that you can crack Bitcoin or whatever.
Speaker 1:No. That's that's amazing. I mean, obviously, I think that, you know, for '99 for poor implementations, wallets have been cracked for a long time. And in fact, recently, there was an $8,000,000,000 move on the chain from a really old wallet.
Speaker 3:That was this morning. Right?
Speaker 1:Yeah. No. This was like a few weeks ago. I'm sure another one. Mean, they happen every, you know, there's There was
Speaker 3:somebody else that market sold this morning, I believe, something and it was a wallet that had bought like it was like a they they bought $50,000 worth of Bitcoin I think in 2012 sold built you know somewhere around 8 or 9,000,000,000.
Speaker 2:That's probably And
Speaker 3:there was no move there was no movement in between
Speaker 2:Yeah. That's diamond hands. I don't think that's his cryptography. That's just diamond hands.
Speaker 3:Well, yeah. They they they maybe got word of your little your little bitcoins.
Speaker 2:Maybe it's Michael Bloomberg. Maybe it's his family office.
Speaker 6:Could be.
Speaker 2:Yeah. Throw 50 k in that in that thing. My my kid told me about this and he said, bitcoins.
Speaker 1:We tried the shorts bitcoin at a $100. I had
Speaker 2:a fun. And we just need to
Speaker 1:find a counterparty.
Speaker 3:Yeah. How How are you thinking about, you mentioned trading enterprise SaaS back in the early days with What's Jim your updated thesis on SaaS? Every SaaS app now is just an app to make other SaaS. So maybe SaaS will SaaS will always live in our hearts and I imagine it'll live on our computers. But what's your updated thesis?
Speaker 1:I I think that, you know, it's sort of similar from back then. Like, I think the morass of a company like JPMorgan that's still running, like, Python two for most of the business, you know, it's it's very hard for them to up update and upgrade operations without significant disruption. For you or me Should
Speaker 2:it should it be? I feel like it's a it's a one line in Cloud Code or Devon. You just
Speaker 3:say, hey. Go migrate. ChatGPT agents.
Speaker 2:Go migrate. Go migrate. Like, it is Don't make
Speaker 3:all you have to do is say don't make mistakes.
Speaker 2:I am much I am much more bullish on migrate from Python two to Python three than than solve cryptography. But, I don't know Fortran. Maybe you're gonna push. Yeah. Fortran re Fortran reimplement or replatforming.netreplatforming.
Speaker 2:It's like this feels like this should be doable from the current state of the art without any crazy AGI, Hyperloop, you know, any
Speaker 5:these think there's
Speaker 1:a lot of technical debt, you know, in most of these companies and again your your average startup coming out
Speaker 2:of HUDCODE was born in technical debt, baby. Cloud Code, Devon, they live they live for for technical debt.
Speaker 1:I think that the the amazing amount of programmers you would need to even maintain and and know about this old code that
Speaker 5:Yeah.
Speaker 1:You know, the guy who wrote it's long been dead.
Speaker 2:Yeah. Maybe it's just the context window of like you need to know. It's not that there's just, like, oh, yeah. It's really easy to change the print statement from Python two to Python three. But when there's a massive system and even even the time of, like, okay.
Speaker 2:Let's bring up the test suite, and that takes four hours. It's like, okay. Are you gonna RL on that?
Speaker 1:I was talking about Matt Groot with us, because we were, like, stunting on this guy who was like, ERP transitions made easy. It's no problem. And we're just like, have you ever actually transitioned an ERP system? You know, there's a good chance you waste $300,000,000 and it gets worse. You know?
Speaker 1:It's it's not it's not trivial.
Speaker 3:There was a there was a post from yesterday. Nobody nobody is an atheist when you run the database migration in prod on 1,000,000,000 rows.
Speaker 1:Yeah. Yeah. I mean, I I think that, you know, it's just it's just really hard at a company like a McDonald's or, you know, something like that. You know, if you wanna run a ten, twenty person startup on US SaaS, pretty easy. It's great.
Speaker 1:But the big revenue is still at Fortune 500, which unfortunately is still fairly hard to refactor. And and those you know, there's not a lot of those code bases were were pre GitHub and pre kind of like you know, I I sometimes joke that the big AI companies should become LBO shops. Mhmm. And what they can do is they can partner with KKR or Blackstone, and all they get is the data. KKR and Blackstone private capital, get all the returns.
Speaker 1:Fine. But all the data comes back to, you know, the OpenAI's or whoever. And by getting the old code bases out of a McDonald's or out of a Walmart that, you know, some of code was written in nineteen seventies, you know, they have unique data that nobody else has. And even someone like Universal Music, if if OpenAI LDO'd Universal and said, okay, KKR, you can have the rest of the business, but we want the rights to the data, and we can train music models and stuff like that. You know, KKR can make the money on the LBO, but OpenAI
Speaker 2:has Are they gonna make money on the LBO, though? Like, if you look at that they're gonna build the DCF for this, and they're gonna say, okay, we're gonna make the same amount of money. We're gonna, you know, optimize a little bit. Maybe cash flow goes up. But then once OpenAI is one shotting music and you know, all of our revenue goes to zero, is that a risk or
Speaker 1:or is this It's gonna happen anyway. So I think that's one thing. But then also, like, the Russian dude who bought Warner Brothers, he really timed that his deal. He bought bought Warner Music. Mhmm.
Speaker 1:He he timed his deal amazingly. He made, like, three times his money or more. And so I think it's price dependent. But, you know, if you can buy a newspaper company, if you can buy, you know, a book company, a publishing company, like, these things are trading for, like, one or two times sales. Mhmm.
Speaker 1:You know? And you're getting this rich data that nobody else has, and, you know, if it's really a data war, you know, buy the company, keep the data, strip out the rest. And you I heard you guys talking about, like, PE improving LLM you know, improving businesses with LLMs. Yeah. And again
Speaker 2:Well, I mean, it wasn't that was not the take. The it was Will Menidas, and he was saying that
Speaker 3:More so as a reason to scale AUM
Speaker 4:Yeah.
Speaker 3:Fun side because hey let's buy this accounting shop that has 5,000,000 of EBIT Yeah. Like if we just you know take away all the you know
Speaker 2:It's a justification
Speaker 3:was what Yeah.
Speaker 1:If you can execute you know it's fantastic.
Speaker 2:The actual post was the real innovation of LLNs is suddenly opening up a few trillion of mainstream paperwork businesses that were traditionally too small and too weird for private equity that can suddenly transact at two and twenty on some nebulous AI labor arbitrage trade, never bet against AUM growth.
Speaker 1:You know, I I think it's reasonable, but it's just it sounds like just any good operator. Right? Like, when when Vista and Tomo Bravo buy software companies, somehow they can take these, like, very ugly gross companies and turn them into amazing cash flow companies. So it's all about the operator. Right?
Speaker 2:Yeah. But we're gonna put Orlando Bravo in a box. Right? In the God box.
Speaker 1:Face, voice, everything.
Speaker 2:Yeah. Yeah. It's all it's all coming. Well, you know we'll be here live streaming it into the singing.
Speaker 3:Can you play us a song before you leave?
Speaker 1:I'm not sure what you're talking about.
Speaker 3:Like like with one with one of those guitars that the chat was
Speaker 1:actually Yes. I I I will come back to you with a good parody of Silicon Valley. I've been working on my impressions.
Speaker 2:Okay.
Speaker 1:Cool. So maybe I can be back. I'm I'm working on Elon, Zuck, Sam.
Speaker 3:Bill Gurley. Bill Gurley.
Speaker 2:Gurley. Gurley. Has a great voice. Yeah.
Speaker 1:I'll work I'll work on it. I you actually do need to, like, sit in front of a mirror and like listen and tape yourself and like work on it. But basically anybody can do these things. And most
Speaker 2:Wait. Wait. Wait. Are you saying no. No.
Speaker 2:Those are AI voices. Right?
Speaker 1:No. Me. Me. Yeah. No.
Speaker 1:No.
Speaker 3:He's saying separately from like
Speaker 2:Oh, the
Speaker 3:separately from the You had the video with talking with Zach the other day where he was really Yeah. No. No.
Speaker 4:He was really
Speaker 1:just do it myself. I can do his I can do Zach. I can do Buffett the best. I think I have the most No way. In the world.
Speaker 3:Can you hit it? Can you can can you do, like, be be greedy when others are are fearful?
Speaker 5:Yeah. Yeah.
Speaker 3:Rip that for us? Let me
Speaker 1:come back to you, and I'll I'll do a whole show for you.
Speaker 2:Okay. Amazing. Fantastic. Great.
Speaker 3:Alright. Well, this is really fun.
Speaker 4:Thanks, guys.
Speaker 2:I'll be finally
Speaker 3:do this.
Speaker 1:See you
Speaker 3:later. Come back on Bye.
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Speaker 3:You only need to get it right once.
Speaker 2:Nailed it. Sean Frank, the man who invented the wallet.
Speaker 3:This really is this really is should be inspiring.
Speaker 2:Hanging in the Louvre as they say.
Speaker 3:Yeah. Is this should be Yeah. Put it on a billboard as we say.
Speaker 2:Put it on a billboard Put it on a adquick.com. Out of home advertising made easy and measurable. Go to adquick.com.
Speaker 3:Say goodbye to the headaches About of out of home advertising.
Speaker 2:So we I mean, we went through the the
Speaker 3:Okay. So we have Joe joining. This is really Okay.
Speaker 2:Who's Joe?
Speaker 3:Oh. Joe's not joining until one.
Speaker 2:Okay. Yeah. We have some people. We have some time.
Speaker 3:We have a little bit of time.
Speaker 2:Yeah. We got
Speaker 3:Should we do some more time?
Speaker 2:Yeah. Let's do some more time line. And maybe we'll go through some journal. We got We we we We're over prepped today. We could do six hours
Speaker 3:I if we wanted like this post from Woodrow.
Speaker 2:Okay. Break this down for me. Didn't get a chance to fully read this.
Speaker 3:So this guy, Eric Jackson, I don't really know his backstory. But he's basically just Yeah. Just he's he's generally soliciting
Speaker 2:He's giving He's financial Yeah. Advice?
Speaker 3:I don't think he's giving Okay. He's not giving financial advice Yeah. But getting quote tweeted which is Okay. Probably honestly finding him more investors which is funny. Sure.
Speaker 3:Basically saying that, know, I've seen his name pop up on the timeline a few recently. Basically saying like, he he said word for word earlier this week.
Speaker 2:Sure. What is it?
Speaker 3:Like something to the effect of we're looking for a 100 x every few months.
Speaker 2:Oh, yeah. As
Speaker 3:one does. Strategy. So he says we're hunting for the next Carvana, the next BTQ, the next open door before anyone else. And then he finishes up with, if you're an accredited investor, you can get in before I announce our position on X. So Mhmm.
Speaker 3:Position first, then we tell the world, then we let the thesis play out and ride the wave.
Speaker 2:And what's the takeaway from Woodrow Oates Montague? This is illegal. This unambiguously illegal. Martin actually comes back
Speaker 3:and says there's nothing wrong with telling people about your positions first in one place and second in another otherwise 99% of short reports promising so yeah. So yeah. To be to be clear, this is this company shut down but Hindenburg Research Yeah. Right? They they used to do this.
Speaker 3:They they would find a company that that had some problems. They would write about it. They would take out a big short position against it and they would publish a piece. They did this with Roblox, Square and then a bunch of other companies that had many many of which were were you know doing doing a number of bad things. Sure.
Speaker 3:Anyways, Windsurf has been on a roll. Matt says acquired on Monday, Sonnet four back on Wednesday, Wave eleven shipped on Thursday, unreal. So the whole team over at Windsurf now under the cognition umbrella has just been shipping like crazy. So they're fired up. Liz says, guy who leaves for a competitor just to see if anyone cares enough to make a traded meme image about it.
Speaker 3:Oh, no. Maybe the anthropic Claude code people did that. Maybe they just wanted the double. You can potentially get a double image. Right?
Speaker 3:You can get the initial trade Yep. And then you get the trade back in their case.
Speaker 2:Okay. I have a poly market that we need to pull up. It's from a year ago. It's Martin Screlly jail in 2024. Less than 0% chance.
Speaker 2:The outcome was no. He beat the poly
Speaker 3:market crazy that odds. It opened at at 20%.
Speaker 2:It did. Never went above 50. Martin, know, stayed out of trouble and everyone I'm everyone who's riding with no did very well.
Speaker 3:I'm super bullish on his He's great tool. Internal
Speaker 2:He's a lot of fun. He is
Speaker 3:a he really is a child.
Speaker 2:I wonder if we could like get access to I feel like we need more data. I feel like it should be powering powering the show
Speaker 3:in Yeah. Some way.
Speaker 2:We have we we have a lot of times when we're like, we wanna pull up this market cap. We wanna pull up basic stuff. And and we haven't, we we we we, you know, we've used some different stuff here and there, but I'd be very interested if he could pull a layer deeper, the credit card data live or whatever whatever he's cooking up. Yeah. I'm interested.
Speaker 2:Anyway, the house just made history says Chris Dixon, former guest on the show. Says, by passing major legislation on stable coins, the Genius Act and Market Structure Clarity Act in an overwhelmingly bipartisan way. This is a huge moment for crypto and for all Americans. We're very close to having comprehensive proactive rules in place for the first time. Next up, the Genius Act goes to the President's desk for his signature.
Speaker 2:After that, the Senate should pass the Clarity Act, which is the Market Structure Act. We believe passing these laws is the best way to ensure that America remains the world leader in the next era of the Internet. Thank you to all the cosponsors of these bills and the incredible supporters on both sides of the aisle in Congress. And Brent is there with an American flag. So we will have Kyle Simone on the show later today to to to break down exactly what happened, but very very fun news.
Speaker 2:Should we tell everyone about numeral sales tax autopilot? Spend less than five minutes per month on sales tax compliance. Head over to numeralhtheybuilt.com.
Speaker 3:Sales tax AGI.
Speaker 2:They did sales tax in a box. Yep. Always in a box.
Speaker 3:Basically a box that you can put your sales tax in.
Speaker 2:We gotta debate the the the substack series c launch strategy. Yep. So you got Chris Best.
Speaker 3:I mean, was a full blitz.
Speaker 2:Full blitz. Wall to wall coverage. New York Times piece. TBPN hit. I think he posted about it himself, hard post.
Speaker 3:I think he did an interview with Newcomer.
Speaker 2:Yes. Well, I think Newcomer leaked it earlier. Remember? He was talking. There was some newcomer report where I remember newcomer was talking about like, I'm the most conflicted here because my business is on Substack.
Speaker 2:I also invested in Substack, but I report on Substack. And it it was kind of it was kind of cool to watch him like noodle through it, you know? But, the debate was between heavily
Speaker 3:conflicted by the age
Speaker 2:of No conflict, no interest, I say. And I actually enjoyed Newcomer's piece on on on Substack. I think he has an interesting perspective because he's he's on all sides of the table. All all sides of the the octagonal table. But, Lulu, a while back, of course, says going direct is now the way.
Speaker 2:A year or two is controversial. Some considered it a last resort for people who got cancelled. Basically, now everyone, the the interpretation of going direct is that if you go direct, should never talk to the media at all. You should only post on platforms you have full control over. Your own Twitter account, your own website, your own newspaper.
Speaker 2:Mail people the information directly. Go direct instead of going to someone else's platform.
Speaker 3:Direct is a spectrum.
Speaker 2:It is. You can
Speaker 3:go direct on TBPN because we're live.
Speaker 2:We're live.
Speaker 3:So you can say whatever you want can't possibly edit it because it's in real time. Yes. And that that ends up being the the historical frustration
Speaker 2:Yes.
Speaker 3:With talking to the New York Times about a story is that you might talk to them for four hours and then they take out two sentences Exactly. Out of context Yep. And it makes you look you It's have very different thrilling.
Speaker 2:There's nothing like talking to a journalist for four hours and being like this could go horribly. Like or it could be amazing. It's like it's it's a it's a tightrope walk. Yeah. And it's living life on the edge.
Speaker 2:It's living life one mile at a time. One
Speaker 3:The first
Speaker 2:time One record sentence at a time. Yeah. Anything you one wrong word and you could be banished from society forever. You could lose everything.
Speaker 3:Yeah.
Speaker 2:But if it works out, you will be enshrined in glory. Your name will be remembered.
Speaker 3:That's right. In the in the In print.
Speaker 2:It'll be echoed in the halls of history.
Speaker 3:Yeah. The first time I heard you had a had a have a drawn out conversation with a with a journalist. I was like, wow. That was an incredible. You guys had this incredible dance.
Speaker 3:Yes. Like dancing with a bull.
Speaker 2:Yes. You have UFC. I have talking on the record for hours to journalists. Seeing how it goes.
Speaker 5:Putting it all
Speaker 6:in the It's like holding like a bullfight.
Speaker 2:Yeah. It's like a bullfight. You Sometimes you get the horns. Sometimes you get gored. Sometimes It's also it's also very much like riding a horse.
Speaker 2:You know? It can be thrilling. It can be beautiful. But sometimes you fall off and you break your neck. It's dangerous.
Speaker 2:It's pushing it to
Speaker 3:the limit. Hopefully
Speaker 2:not. That's what engaging with a journalist is and some people just want that rush in their life.
Speaker 3:Yeah.
Speaker 2:And so that's what Chris Bez did. He went to the New York Times.
Speaker 3:He went into the
Speaker 2:The mouth of the wolf.
Speaker 3:The wolf den.
Speaker 2:The mouth of the wolf. He's he's hiding in the
Speaker 1:mouth of wolf.
Speaker 3:He's not afraid. And I mean that that was thing that was I mean
Speaker 2:He went in the arena.
Speaker 3:Substack has always been a product where if you ask the users Yeah. How they feel about it. Yeah. They're like, I love Substack. If you people that are building businesses on Substack, I'll tell you they love it.
Speaker 3:Yeah. Product has evolved a lot. Yeah. But there was a lot of people that wrote it off Yeah. After that that that and said, okay, unnamed fund top ticked this Sure.
Speaker 3:In in '20 or whenever it was. But he's back.
Speaker 2:He's back.
Speaker 3:Stronger than ever. The product is actually working as a social network.
Speaker 2:And he's getting in the octagon. He's going to the mat with the gray lady and he came out on top. You know the gray lady? Does it happen in Anyway, New York so Chris Best announced a $100,000,000 series c. You heard about it yesterday.
Speaker 2:Came on the show. We rang the gong for him. We're very excited about what he's doing at Substack. But Eric Newcomer says, Substack just announced their round in the New York Times. This is the this is the opposite of going direct.
Speaker 2:And obviously, we've explained why you talk to someone like the New York Times. It's for the thrill. But The rush. The the interesting
Speaker 3:thing And it's also Chris knows you can come out and hit the whole Substack
Speaker 2:Yeah.
Speaker 3:Audience pretty well.
Speaker 2:Well, that's what I'm thinking.
Speaker 3:But if the in way New York Times covering his like if Substack is successful, the New York Times in ten years will be a shell of what it is today.
Speaker 2:Oh, that's an interesting take. Okay.
Speaker 3:Legacy media will always have a place. These brands are super powerful. Yeah. Serve a real purpose in the ecosystem. Yeah.
Speaker 3:Generally, they provide a valuable Yeah. Service for the world. But I had a different take on it. But finish. There's real At least right now, there's very real salary Yeah.
Speaker 3:Caps. And if you are a rock star writer at the New York Times
Speaker 1:Yeah.
Speaker 3:Very likely you could go on Substack and be making more within a year. Yeah. So it ends up being a good trade. Yeah. For some go into the into the the lion's den Sure.
Speaker 3:The shark pit and advertise his business to that audience. Step into the cave every single I would I would say like the goal at Substack should be every single person that subscribes to the New York Times today
Speaker 2:Yeah.
Speaker 3:Should be subscribed to at least one Substack in a decade from now.
Speaker 2:Just arm wrestling
Speaker 3:with the gray lady.
Speaker 2:Arm wrestling with the gray lady. So that's a pretty good take. I like that. I I I don't I don't know that that holds for everything on Substack because I still haven't found like the investigative journalism format on Substack working fully because you have to subscribe for a year and then maybe you get one scoop and it's huge. But I always think about, you know, I go back to Seymour Hirsch and I just don't know if he would be able to be an independent creator.
Speaker 2:I think he needs the patronage of a large organization.
Speaker 3:No. There's a ton of different styles of writing that work really well Yeah. Under a existing brand. Yeah. You're in the scoop business Yep.
Speaker 3:And you're gonna get three scoops a year Yep. Two good scoops a year, you might be really valuable to a big
Speaker 2:To a big organization. Exactly.
Speaker 1:If you're
Speaker 3:doing if you're and doing profiles you're
Speaker 2:gonna write Yep.
Speaker 3:Four profiles a year Yep. You're gonna be super like, you know, widely read and Yep. Novel and and and worth creating. Probably better fit to go do that under a legacy media brand Yeah. Or or just a broader platform Yeah.
Speaker 3:Because not a lot of people are gonna wanna subscribe to something that they're getting value from just a few times a year. Yep. People cancel, again, they'll cancel their Netflix if they don't, if there's not like a show
Speaker 2:Good stuff.
Speaker 3:At that moment that they're super excited about.
Speaker 2:But my take on why why Chris Best announced his $100,000,000 series c in the New York Times, you know, newcomer is clearly on Substack, an investor in Substack, writing about Substack. Chris Best could have gone to Eric Newcomer and probably gotten a great piece, right? Eric really understands the business. He's gonna be able to tell that story pretty well, I think. But why do you go to the New York Times instead of Eric Newcomer who's clearly sniffing around and and and on the trail of this deal, but take the exclusive New York Times.
Speaker 2:I think it's because of the audience. I think Newcomer writes for people in Silicon Valley, VCs, who are acutely aware of Substack. Most of them already have Substack. I think a lot of New York Times readers could be the next wave or the generation of Substack. That's what was Substackers.
Speaker 2:Oh, yeah. But I I was talking about the the the readership of the New York Times.
Speaker 3:I'm saying the readership. Yes.
Speaker 2:Oh, okay. Yeah. Yeah.
Speaker 3:Success for over the next ten years Yeah. Success for Substack is every single person
Speaker 5:Mhmm.
Speaker 3:For the most part. Let's say every single person under 65 years old should subscribe to at least one Substack writer. Right?
Speaker 2:I'm I'm talking about becoming a writer. I think that there are lots of people who read the New York Times, who are thinking about writing about art, literature, technology, whatever. And they read and they read the New York Times and they and they think like, oh, I'd like to I'd like to dip my toe in and I'm not just gonna go up quit my job and apply for a job at the New York Times.
Speaker 3:Yeah. It's two sided.
Speaker 2:I will start a Substack. And so I think that taking the story there makes a ton of sense. I've already seen there's this interesting project that Emily Sundberg highlighted where someone is writing a fictional story but instead of just publishing a book, they're doing it on Substack. You subscribe and you get one chapter a week for a couple months.
Speaker 3:That's cool.
Speaker 2:I thought that was a really cool innovation and I think that
Speaker 3:you know It's potentially a way the interesting thing is people will pay what? $25 for a book?
Speaker 6:Sure.
Speaker 3:But they'll pay $15 a month for a sub stack. Yeah. Or take $10 month.
Speaker 2:Then they'll
Speaker 3:just Well,
Speaker 2:I love that book. I wanna keep supporting them because I wanna get the next book when it comes out. I'll just let that ride on my credit card. Whatever. Yeah.
Speaker 3:That's really cool.
Speaker 2:And so so I think that that market of new Substack creators is super valuable and I think you get that when you go to the New York Times. I don't know if you get that when you go to Eric Newcomer. Although, obviously, there's a lot of great benefits that you get when you go to Eric Newcomer. But our next guest is here in the studio. I'm seeing green light.
Speaker 2:We're good? Very good. Welcome to stream. How you doing? What's going on?
Speaker 7:What's up, gents? How's it going? Good to finally be on. Big fans of time. Thank
Speaker 3:you for
Speaker 7:having me.
Speaker 3:It's great to have you and you have some pretty big news today.
Speaker 2:Break it down. Yeah. What you Yeah.
Speaker 7:Broke raised our seed round 55,000,000.
Speaker 3:There we go. I I personally love what seed I love to see a seed round get into the
Speaker 2:Double digits. Figures. Yeah. High double digits.
Speaker 3:I think they all should be hopefully, you're the start of a new a new wave. But what what is is this the third largest third largest seed round in in in New York history? Is that right?
Speaker 7:That's what we're tracking. That's right on our end, at least on the equity only side, and Yeah. We're pulling some data, where everyone else does. But, yeah, we feel excited about it and we feel really good on on, being a little bit continue to go to New York City.
Speaker 2:So The equity only side, I was gonna ask I asked Jordy about that. I was like, okay. $55,000,000 seed, is this is this 80% debt? Is there some, like, crazy GPU credit thing going on here? People get kinda funky with the numbers these This seems like real dollars.
Speaker 2:Who is writing $55,000,000 seed checks these days?
Speaker 7:Yeah. So RAM was led by RTX Ventures arm, so the corporate venture arm there. A lot of interest in what we've been working on and and they led the round. We had great partners come into that round. Vidia's Venture Arm and Ventures.
Speaker 2:Sure.
Speaker 7:AnyNext, Infinite Capital, Ali Corp, where who did our pre seed and also participated in this round as well, as well as kind of a bunch of other investors with inside of that. So super excited about the support we have. It's interesting. We have a balance of both financial VCs
Speaker 2:Mhmm.
Speaker 7:As well as corporate strategics in this round as well. And, look, we work in material science. I'm sure we'll get into this in more detail, but I think they really see where materials and science at large is going with AI. And this is why they're starting to look into tech and and startups because that's where the innovation truly is, in a space like the physical world and material science. So really interesting mix, and we are super proud of the syndicate we put together.
Speaker 7:So
Speaker 3:That's awesome. Backstory on yourself, then the time at Al Ali Corp. Yeah. How how this company was was created would be would be awesome.
Speaker 7:Yeah. Absolutely. So going back a couple years, I'm a scientist by training. I was working in grad school, at Rice. I was working on these things called neuromorphic computing chips, which they try to replace the Von Neumann bottleneck, inside CPUs.
Speaker 3:A lot of big words back to back.
Speaker 7:Yeah. So we pretty much try to connect memory and CPU and not lose the latency and the energy that go inside a chip. So I was working on this technology, except it was going nowhere because it's academic research, and academic research doesn't scale into the real world. So I was super frustrated. So I ended up getting a fellowship at the army research lab.
Speaker 7:I go there. I'm working on the same problem at ARL. And it's better because the army's funding your work. Right? And the army wants to see things come and move into the services that they can actually use, but it's still really early technology readiness levels.
Speaker 7:Like, two, three, four, still in that fundamental area. So I was getting frustrated. So I said, okay. I'm gonna start a company. And then I realized I didn't know anything about starting a company, and I didn't actually know what I wanted to do.
Speaker 7:Yeah. And so I bumped into Kevin Ryan in New York. I reached out to him, cold cold emailed him actually, and said, hey. If you're not investing in material science, you're not investing in the future. He's like, okay.
Speaker 7:I've been an investor for thirty years. That's a bold claim, but sure.
Speaker 3:And what what are what are some of the big names that that Alicorp has done? They did MongoDB. They did MongoDB. It's crazy range.
Speaker 7:Mad. Yeah. Wide range. And Ali Corp's unique. Right?
Speaker 7:Ali Corp both incubates companies in house, kinda where Radical really got its roots, and I can talk about that. But also invest at the early stage as well, anywhere from 1 to 5,000,000 in in the early stage side seed, sometimes, you know, an early series a. So they had this interesting ability to go and dive into a space. And if they find a company they love and they wanna invest in, they will invest, and and that's what we did there. And if there isn't one, they'll actually look to incubate that company in house.
Speaker 7:And so it's a really nice way to play into a new market that you wanna see innovation in, but just can't find something that's there.
Speaker 3:Did the pre seed happen? Was it a year ago?
Speaker 7:Yeah. Not a year ago or a little bit over March. So me and one of my other cofounders, Jorge, both at Alicorp. Jorge is a deep software guy, startup guy through and through, only done Starz's entire career. And he's looking into AI.
Speaker 7:Right? Who wasn't? All of us were. But we were super frustrated. We kept seeing rappers on top of models, and we were thinking, like, this can't actually be it.
Speaker 7:Right? Like, is this the pinnacle of innovation? Like, the the new tech wave is gonna be rappers, and we knew that wasn't it. So we we spent, like, months reading a bunch of papers inside AI. We were convinced that technology was incredible, but there had to be a space that was better.
Speaker 7:And being a material scientist, I thought, well, the materials are quite large. Right? The most important industries in the world, automotive, aerospace, manufacturing, defense, climate, energy, semiconductors, the most important industries in the world are all a direct result for materials. So why don't we look into there? So we start reading into the space, we dive in deep, and we bump into this gentleman named Hert Cedar.
Speaker 7:Long time academic. He's at Berkeley. He's got an h index of a 182 or something like that. And he had done two things specifically. He'd helped set up the materials project from the MGI, so this AI for materials early sector inside The US.
Speaker 7:And then he built a robotic lab. It's called the a lab. It's at Lawrence Berkeley National Lab right now, and it's fully autonomous. It does 55 experiments a day. So we're like, we we gotta go see this thing.
Speaker 7:So we fly out to Berkeley. We we get dinner with her, and we pitch him on, look. Someone's gotta build the future of material science, and it needs to be a full stack vertically integrated approach. There's no other way to drive value. And us putting together a really aligned opinion around what it should look like and and formed the company and went from there.
Speaker 7:So there's 10,000,000 in pre seed from Alicorp and got started and went went down
Speaker 3:to Big numbers big numbers all the
Speaker 5:way up.
Speaker 2:Yeah. My question is, like, why not just do series a 10,000,000 series b 55,000,000? What does a $55,000,000 seed round like? What what's what message are you sending? Obviously, it's like superlative so you can get headlines around it.
Speaker 2:Is that the value that you just stand out or is it you specifically want to Because I imagine that if I just walked around your office, it's gonna feel like a series b company that's raised $55,000,000. So like what like Yeah. Like like, what are you actually saying to folks when you say, oh, I run a seed stage company versus, oh, I run a company that's raised, you know, tens of millions of dollars. These are two different aesthetics. They
Speaker 7:definitely are. I feel like we still feel pretty early. I don't know what series b's are looking like yet today. I'm not there yet. We we like being super lean.
Speaker 7:We are really, honestly, crazy about our culture. We think culture is one of the most important things you can do at an early stage company, and we're really, really rigorous on who we bring in and why. And so we actually keep the team quite light. We will be growing with the round, of course. It goes without saying, but we really deeply believe in the ability to challenge everything that exists today.
Speaker 7:Ask the question why about everything. Why do these
Speaker 3:things happen? What's the got a got a lot of money on the on the balance sheet. Sorry. I'm sorry. Your your Internet, I think, is a little rough.
Speaker 3:We got it with the 55,000,000 up the you guys deserve fiber now. Let let's get it let's get it in there. But what what's the use of funds? What success look like over the next eighteen months? Sounds like you guys are super ambitious, but but how do you start proving out what you can do?
Speaker 7:Yeah. So we got a scale of team. We wanna bring in big talent on the side of AI as well as material science and the and the automation side. There's a lot of an additional approaches that we So
Speaker 2:one part time AI researcher. Yeah. Yeah. Fractional fractional AI researcher. It's gonna be good.
Speaker 2:Twenty hours a week.
Speaker 7:Yeah. No. We're not not doing any of that.
Speaker 2:Yeah. Yeah. I'm sure you're hire great people.
Speaker 7:Integration. And then two, we're gonna build the most advanced materials r and d facility in the world. We have multiple different materials lines. It'll do hundreds of thousands of experiments per year. And all of that data is the missing data set that really exists inside the AI for material space today.
Speaker 7:So if we can capture all
Speaker 2:of that
Speaker 1:So are
Speaker 3:you are you rebuilding the the kind of robotics lab that your co founder had at at Berkeley in order to execute that many experiments?
Speaker 7:We do. Yes. So we kind of we amped it up in a way. His was a very academic approach to it. I had to work with them inside academic constraints.
Speaker 7:It was very specific on a research problem. Ours is much more automated in that we are doing real active learning on the data analysis and capture, and then bringing that back into the AI engine, and then can really be made into a platform where we can actually take that software and robotic system approach that we have and use it in other material systems. So we can actually be multisystem based inside the products that we're trying to solve for. So that's kind of a big differentiation between where his was and where ours is gonna be today.
Speaker 3:Awesome. Awesome. Alright. Well, you so much for joining.
Speaker 2:Thanks so
Speaker 3:much for Very, very exciting.
Speaker 7:And Yeah. Congratulations.
Speaker 3:Yeah. Yeah. Congratulations.
Speaker 7:The past Thanks for having me on and I will be in touch.
Speaker 2:We'll talk to you soon. Cheers.
Speaker 3:Alright. Luck out there.
Speaker 2:In the meantime, we will tell you about Adio, customer relationship magic. Adio is the AI native CRM that builds scales and grows your company to the next level. Let's go to Swix. He says Break
Speaker 3:this down. I'll be right back.
Speaker 2:Sure. So Swix, friend of the show says, a lot of people are poo pooing the chat GPT agent launch which we covered on the show yesterday. We had folks from OpenAI on, and we also had, Dan Chipper from Every on the on the show to to break down how he's using ChatGPT agent. I was impressed with the OpenAI folks. I thought they, explained a lot of how this works.
Speaker 2:And Dan Chipper's were were like his, you know, third party analysis of how he's using the tool sounded very promising. We haven't had a chance to test it here on the show, but, I'm excited for it. And Swicks breaks it down. He says, people are pooh poohing ChatGPT agent as just a better harness, but they're not reading closely enough. We've got a new frontier model today, folks.
Speaker 2:These charts are like for like same harness. They basically stopped short of calling it GPT five, But, yeah, if there were a public release of o four full today was it. Don't sleep on that. In other words, run your benchmarks telling it not to use tools and I expect it'll be a big step up from o three. And so he's looking at the benchmark of Chattypiti agent on Humanity's last exam, doing much better.
Speaker 2:And so even though this didn't get a true version bump, the the actual results are are are great on practical problems. I'm we're gonna have Mike from Arc AGI on the show later. I can't wait until we can throw ChatGPT agent at some Arc AGI puzzles. I got a little preview in Arc AGI three. It is a challenge.
Speaker 2:And I will be doing it live
Speaker 3:on the stream and
Speaker 2:I won't be embarrassed at all.
Speaker 3:What? John was sweating earlier. Yeah. Gave a little test run.
Speaker 2:Said It is it will be a challenge and I imagine it will be a very huge challenge for for ChatGPT agents.
Speaker 3:It's funny. So we had the the ChatGPT agents team on And then I saw on the timeline later people were kind of saying like, oh, it took ten minutes to book a flight. Which is like kind of like funny criticism because it's probably how much it realistically takes like a human to book a flight. Yeah. So the fact that an agent could do it in the same time
Speaker 2:and you
Speaker 3:can imagine the agent could just get
Speaker 2:Yeah.
Speaker 3:You know, if it can get 10 times faster.
Speaker 2:Completely agree. Also, the interesting hot take is that there's there's a world where I have found that even if even if a task takes me ten minutes on my laptop in a professional piece of software, if I can do it in ChatGPT in the app for in ten minutes and it's equally frustrating and it takes me the same amount of time, I like being able to do it on my phone. I noticed this when I made this two by two chart showing Dwarkash Patel versus Tyler Cowen on their AGI perspectives. So Dwarkash believes AGI is not here. Tyler Cowen believes AGI is here.
Speaker 2:Dwarkash believes the impact of AGI will be immense, and Tyler Cowen believes that it will be very incremental. So they are on the opposite sides of this two by two diagram. So I go to Chatchippity. I I could easily have just done this in in Google Sheets and taken a screenshot. I could have done it in Photoshop.
Speaker 2:But both of those would probably require opening my laptop, but on my phone in the ChatGPT app, I was able to have it try and do an AI image generation. That wasn't really working. It was getting confused. So I finally had it use matplotlib and write some code to generate it and I was And I went back and forth with it probably for about the same amount of time that I would have been in Photoshop, but it was nice because I was able to just able to do it on my phone. And so, there's something about the rune take that text is the universal interface that even if it takes me the same amount of time to book a flight, if I can just do it in a in a universal interface that I'm super comfortable with and I'm interfacing with it on the Chattypetty app, I might prefer that over going to the united.com website or unitedairlines.com whatever
Speaker 6:it Or
Speaker 3:Google Google flights where you can like see the flight pipe you to the other site.
Speaker 2:There's so many different sites and they're all slightly different slightly different UI, slightly different designs and I Oh, this one I need to remember to uncheck this box and this one I need to do this and my password's not saved here. I like that ChatGPT is just becoming like a unified interface for how I interact with web services, tools, all this stuff. It's very cool. Anyway, in other news, semi analysis, AJ, a friend of the show says, Anthropic quote, We don't care about consumer. Code is the only use case we care about.
Speaker 2:Everyone else says, why is Anthropic not showing up in consumer statistics? And someone and he's quoting someone says, what happened to Anthropic? Because Anthropic fell off of the OpenAI lead the rankings of chatbot downloads. ChatGepti is on a chair with well, of sensor tower. ChatGepti is on a tear with almost a billion downloads.
Speaker 2:Google Gemini at 200,000,000. DeepSeek at one twenty seven million. Microsoft Copilot at 80,000,000 and Perplexity at 50,000,000. Perplexity has been holding on strong in a very competitive environment and I think that's why they were able to raise at an $18,000,000,000 valuation yesterday if you didn't see the news. Swiggs has more analysis on the OpenAI launch.
Speaker 2:Three things a deep and he's doing the Steve Jobs meme with Sam Altman. Three things. A deep research model with enhanced search browser, a revolutionary computer use operator and a sandbox terminal to execute math and code. A browser, a terminal, a computer. Are you getting it?
Speaker 2:These are not three separate agents. This is one agent and we're calling it agent. This is a really good one. Great, great, great.
Speaker 3:Great poster.
Speaker 1:Great poster.
Speaker 3:Justine Moore says, I predict that Crocs male AI companion will be even bigger hit than it will be an even bigger hit than the female one. Elon has said that he's naming it Valentine.
Speaker 2:But what did it say it was gonna call itself?
Speaker 3:It has it it calls itself something else that we won't say. Are quietly massive consumers of romance and erotica content and she gives some data. Fan fiction 80%. Romance novels are at eighty four eighty two to 84%.
Speaker 2:That's wild.
Speaker 3:Women's online fan fiction 80%.
Speaker 2:I've never been part of that whole world but
Speaker 3:you know. Yeah. Never been whole world.
Speaker 2:Anyway, let me tell you about fin dot ai, the number one AI agent for customer service, number one in performance benchmarks, number one in competitive bake offs, number one ranking on g two. Go to fin.ai.
Speaker 3:I how they do it. I
Speaker 2:don't know how they keep doing it.
Speaker 3:They they just
Speaker 2:Luck of the Irish as they say. Luck the Irish.
Speaker 3:You go capital. Yeah. Bloke says, I have two people in my life that I've mentally flagged for high risk of LLM induced mental health issues where I'm already seeing concerning activity. I don't think society is ready for how much of an issue this is going to be at all. Yeah, again, I think there needs to fast from the labs in order to make just make some changes to the product make make it does seem to be like the rate.
Speaker 3:Not something that's gonna happen in an hour from using the product but it could happen in a month.
Speaker 2:Here's a prompt. Chat GP agent. Look at my calendar. Look at Google Maps. Find me the nearest grass.
Speaker 2:I need to go touch it.
Speaker 4:Yeah.
Speaker 2:Schedule it. Put it on my calendar. Remind me to go there. Call me an Uber to take me to the grass.
Speaker 3:Call me a Waymo.
Speaker 2:Call me a Waymo to take me to the grass. I need to touch it. Take take me to Central Park.
Speaker 3:Yeah.
Speaker 2:The home of our next guest Joe Wisenthal. Welcome to the stream Joe. How are you doing?
Speaker 5:I'm doing great. Thanks for thanks for having me back.
Speaker 2:It's always a
Speaker 3:Somebody somebody commented earlier on you you shared the the guest lineup and you were like. Yeah. Joe goes on TBPN more than I my mom.
Speaker 5:I love you guys. But maybe that person that I think that person needs to get a build a better relationship with their mother.
Speaker 3:For sure.
Speaker 5:Yeah.
Speaker 3:But we are family. This is the brother. We are family.
Speaker 5:We are family.
Speaker 3:You are a technology brother.
Speaker 2:Yes.
Speaker 3:That's right. I'm lost one. Thank you.
Speaker 2:What's what what's the latest in your world? What has been capturing your attention this week?
Speaker 5:You know, here's an interesting thing is that the economy, just like the setting aside the markets,
Speaker 2:which we
Speaker 5:all go nuts every day, the lines always go up. There's the economy itself, like, the it it was a good week for economic data. Today, we got better than expected economic sentiment. Yesterday, we got better than expected retail sales. We got better than expected initial jobless claims.
Speaker 5:We got better than expected the Philadelphia Fed manufacturing survey. There has been this assumption, I would say, in recent weeks that recent months, really, that the economy would slip, and then the question would be, would the Fed cut rates in time to force dollar recession? And that maybe that's still a debate. Certainly, know the White House really wants to see rate cuts. But actually, at least, like, is a snapshot right now.
Speaker 5:Actually, it looks like there might be a little bit of a tailwind to this economy, which I think is really interesting and maybe unexpected.
Speaker 2:That's fantastic. I have your post here. Boom. More strong economic data. Yeah.
Speaker 2:June retail sales for the American economy.
Speaker 3:Hit for Joe and the economy.
Speaker 5:Love it. I need a gong. My producer, Kale, is in the room with me.
Speaker 2:I think everyone needs
Speaker 5:a gong. I'm gonna
Speaker 3:We we we have we have variety of gongs. We can
Speaker 2:actually send you a gong. We have we have three now. And we're thinking about getting a fourth. So we have spare gongs if you need to borrow one.
Speaker 5:I think the guests need a gong. Yeah.
Speaker 2:I think the big thing is it it it's not necessarily that you need a gong, it's that you need to get into prop comedy generally, broadly. And Odd Lots needs a whole prop department
Speaker 3:Yep.
Speaker 2:With a variety of things.
Speaker 6:A prop lead.
Speaker 2:Have we showed you have we showed you our props? We have we have the crystal ball for knowing the future.
Speaker 3:Of course. Careful with
Speaker 2:that. Yep.
Speaker 3:Put it on John. If you ever if John ever wants a steel man an argument.
Speaker 2:Steel man something.
Speaker 5:You have a steel man. Do you have a do you guys have a tungsten cube?
Speaker 3:From the cube but we have a tinfoil hat
Speaker 2:we have a tinfoil hat for when we're discussing conspiracy theories
Speaker 3:yeah it gives you a little coverage you
Speaker 5:got for all the different scenarios
Speaker 2:Yes. All the different scenarios.
Speaker 3:How was you dropped your you dropped your interview with Eric Adams. Yeah. It was this morning.
Speaker 5:Yes.
Speaker 3:I haven't had a chance to listen yet. You guys seem like you're having fun.
Speaker 5:I don't think it's possible to not have fun talking to Eric Adams. Eric Adam Adams is one of these guys where it's like even the people who hate Eric Adams love Eric Adams to some extent. He is you know, you talk to him and there are some people you talk to and it's like you instantly get why they've been successful in politics. He has a great smile. He's very funny.
Speaker 5:He sort of speaks extemporaneously very well. You never really know what he is going to say. And look, you know, he presents, I would say, not popular right now. His approval rating is pretty low. But I would say he he makes his case well that he's had a a good mayorship between crime numbers, between the volume of housing that's been built in the last four years.
Speaker 5:Rats? I don't know. Like, the
Speaker 4:the rats.
Speaker 2:Rats.
Speaker 5:The rat numbers are real. I talked about it last time. The rat numbers are real. So, again, I think there there was a poll out this week that actually showed him in fourth place.
Speaker 2:But Is there really a rat census? Do we have good data on rats?
Speaker 5:So the way they measure it yeah. They do. I mean, the This is what the collapse this
Speaker 3:is what collapse looks like, by the way. Is when you start measuring the rat population.
Speaker 2:Are hedge funds trading against the rat index? We need holly
Speaker 3:on the rat.
Speaker 2:No rat feuds.
Speaker 5:The proxy that they use for measuring rats rats is 3311 calls. So 311 is, like, our way to, like, call the police about something that's not an urgent crime Sure. Or other things going on. And if there's, a rat infestation or a lot of rats in place, and they dropped, like, forty percent in 2024. And then if you look at the annualized data through now, it's, like, down another 25%.
Speaker 5:I think on things like rats and trash containerization, which I know, you know, trying to get into the modern era here in New York City. I think there is a widespread agreement that actually real progress has been made, and Eric Adams has a lot of funny videos about his war on rats. And I think I think he deserves credit for it.
Speaker 2:Was there ever a you you I don't know if this is an apocryphal story, but the whole story of, like, the Indian cobras where there was a a bounty. Have you heard the story? So it's a classic it's a classic economic example of of like unintended consequences essentially. There's actually a Yeah. Particular term for it.
Speaker 2:But basically, there was a snake problem, a cobra problem, poisonous snake problem in India. And as the legend goes, as the story goes, the the government said, hey, look, we're going to take a decentralized approach. We are going to put this in the hands of the free market. We are gonna create a bounty for every dead cobra or dead snake that you bring us. And so we will pay you $1 for
Speaker 5:every single breeding them.
Speaker 2:Right? They started breeding them. Exactly. And
Speaker 1:so Yeah.
Speaker 2:And so I wonder if there's a world where, okay, I got elected. I need to Yeah. I need to crush the rat population, but then I need to climb it up once it's out of the news cycle. I gotta get the rat population huge. And then I can crush
Speaker 5:it right before. You can keep smashing it again.
Speaker 2:Keep smashing it. On right on the cycle. So, oh yeah. It was bad midterm but right as you don't wanna change horses in the middle of a stream because I'm the rat The rat catcher.
Speaker 5:That's right.
Speaker 2:But I mean, yeah. Is there is there a secret in New York City to controlling the rat problem? Is it just, like, more
Speaker 5:rat catchers? I I think it really is just a function of how horribly we've managed our trash Okay. In the city. And you just see and I saw it you know, I was walking to the subway today because the containerization of trash, like, it's it hasn't come to my part of the city. It hasn't come to the East Village.
Speaker 5:There's just a lot of trash bags that exist on the street. I and and I saw a bunch of incidentally, I saw a bunch of rats last night when I was walking home. So it is a live problem. There is still progress. And, you know, like, I I would never endorse a candidate for mayor, but I would certainly suggest that whoever is the mayor after November or after the inauguration, hopefully, the existing trajectory continues because the problem is not solved.
Speaker 2:Yeah. Deals with it. Jordy?
Speaker 5:Who else comes on your show and talks about rats, Brian, by the way? It's probably just me.
Speaker 3:Well, you're you're you're a new rat correspondent.
Speaker 2:Emily Sundberg is helpful is a helpful new reporter to understand what's going on the East Coast. I mean, the the big thing that I've been pulling on, I talked to a couple hedge fund folks out on the East Coast in Manhattan. We had one guest on from Cotu who had a very beautiful scenic view out the window from Hedge Fund Alley. I guess that's a street or something like that. And and my I was I was pulling on what has the reaction been in the finance world in the on the East Coast to these crazy acqui hires that are going on on the West Coast.
Speaker 2:So we saw that Google acquired Windsurf for $2,400,000,000. Was this kind of zombie acquihire that's becoming more and more standard. Mark Zuckerberg's paying a 100,000,000, $200,000,000 for single AI researchers. It's kind of shaking so
Speaker 3:I think it's good for the news business because now what would have been one acquisition is now two.
Speaker 2:Oh, yeah.
Speaker 3:Yeah. So we got to cover it Friday. Yep. And then we also got to have Scott Wu who bought the the ghost ship
Speaker 2:Yep.
Speaker 3:Yeah. On Monday.
Speaker 2:I guess the yeah. The question is just like what's the reaction? Because for Wall Street with pods, it feels like a standard.
Speaker 5:Yeah. It's that's really you know, it's funny. Literally, just before we got on here and I was just talking here, it just feels like, you know, if you think about the sort of broad phenomenons in the economy, that what we're seeing is more and more sectors of the economy are experiencing this sort of, like, winner take allness phenomenon where it's not that the sector is doing good or bad. It's that there are a handful of talented people in any industry Yeah. That just, you know, capture extraordinary sums.
Speaker 5:And, you know, we've seen it for years in professional sports. The pod shops, the hedge funds that we talk about a lot about on the podcast have had it for years. That's our equivalent to Bloomberg, you know, like the stories that Reed's spike on the terminal. It's always about, like, some guy is like, oh, so and so who, you know, is a transportation portfolio manager at this pawn shop is, like, going there, and they're getting a $50,000,000 bonus, etcetera. It feels like you know, we see it in media, of course Of course.
Speaker 5:In various ways and star newsletter writers and star podcasters and star broadcasters and so forth. And then clearly, like, obviously, you know, software people have been getting paid well for a long time. But this phenomenon where now it's like, no. The value is not in the company per se. The value is in just that inner individual talent who can get up and walk and take that value out with them.
Speaker 2:Yeah.
Speaker 5:It feels like it's replicating elsewhere and, like, I don't know where it's going, but this seems to be a phenomenon of the world.
Speaker 3:Yeah. That that that's why anybody freaking out about, like the the comp packages of individual Yeah. Researchers. It's like, yes, if you look at it on an individualized level, one person getting 9 figures. Yeah.
Speaker 3:But if you look at it and say, well, Zuck just spent 15 on Scale AI Yeah. And he which which was heavily talent oriented. Mhmm. Mhmm. And would he pay $4,000,000,000 for one of the top teams if he could just acquihire one of the top teams?
Speaker 3:And and in this case, he just pieced it together from a a variety of labs.
Speaker 5:It's really interesting to one thing I think is interesting to think about is that a lot of in the finance world, a lot of talent driven businesses often aren't particularly great for shareholders. So if you look at, like, the history of, like, investment banks that are stand alone investment banks that never had, a trading arm, etcetera, almost all of the enterprise value, like, ends up accruing to the talent, and there's not much of frequently, like, the equity component when these companies are publicly traded. You look at, like, boutique investment banks that from time to time are publicly traded. Yeah. They've never, like, been particularly those have never done particularly well.
Speaker 5:Or you think about a law firm, of course, which doesn't have public equity. But, like, you know, it's like all the money sort of, like, accrues to the talent. And so I do think there's some, like, interesting implications, like, maybe down the line, not yet in public markets. But it's pretty obvious from Windsurf that in private markets, this has gotta be a you know, change the way investors are thinking that, you know, what really is left over for the poor downtrodden shareholder if the if the most talented workers at the company are the ones who really get to capture all of the value?
Speaker 2:Yeah. There's
Speaker 3:Yeah. You you've seen this with the the podcast networks of the world. True networks. If, you know Yeah. Dave Portnoy builds up some talent, he starts paying them a 100
Speaker 5:k And so why share why share it at that point with Dave at that point? Right? Like, if you are superstar podcaster under that particular network, eventually, you get to a point where it's like, you you take maybe you start off and you take 20% of the cut and then 50 and then you're like, why am I sharing it all at all? Yeah. Alex Cooper's Yeah.
Speaker 5:Basically
Speaker 3:Yeah. Alex Cooper's market value is about the same as an AI researcher like over the last Yeah. Over the last few years. Yeah.
Speaker 2:My Yeah. My I I've been thinking about this a lot since we last talked and you said the power laws are popping up everywhere and and I was and I was just going through my daily life thinking like Yeah. How is that true? I see it everywhere. I agree in a lot of things.
Speaker 2:But I was thinking about like, you know, there's this meme of like after AI the last job will be like the plumber. And I was like Right. Is there a power law compensation curve in plumbing? That's
Speaker 5:really interesting
Speaker 2:driving because if you think about the value of driving, it's really a lot of there is a ton of equity value in Uber. There is a
Speaker 3:ton Yeah. Of There's value a leverage thing that the highest paid plumber will be somebody who has like like scaled plumbing enterprise that you you can only like install so much pipe.
Speaker 2:But if they lose their talent like there's still equity value because you've aggregated demand and that's the difference between the AI research labs and Instagram. Every they could have a 100% turnover in Instagram, slot other people in. Yeah. It's a network effect. There's an audience there.
Speaker 2:There's habitual. I know I have a fan base on Instagram or I open it and I know that I get funny memes videos Yeah. Or family connections there. I'm not leaving just because the software engineer who works on Completely. This particular button leaves.
Speaker 2:And so there's a ton of equity value in Instagram relative to talent. And and and I think that there I think that it's not as it's not as universal as we think. I think we're just seeing it more in media Yeah. Finance and research and places where there are either secrets that you can take with you or relationships that you can take with you or or fandom that you can take with you. Yeah.
Speaker 2:And so it's not it's not entirely 100% universal, but it certainly is something that it's it's more on display. It's than ever before.
Speaker 5:I don't know. Yeah. I think that's good. Look. I I I think this is a a useful Yeah.
Speaker 5:Corrective. The phenomenon, there are many parts of the economy where the sort
Speaker 2:of
Speaker 5:distribution between equity and talent Yeah. Is not as skewed as it seems to be in some of these areas. It does seem on display. I mean, it's weird that we know the names of software engineers in general.
Speaker 2:Right? Yeah. Like, Trading Card memes. We put up these trading card memes. Got millions of views.
Speaker 2:It's crazy.
Speaker 3:We had a You
Speaker 5:guys failed it.
Speaker 3:Like Yeah.
Speaker 5:And I you know, when I think about why you guys not to, you know, blood test too much smoke. But when I think about, like, okay. Like, when I think about TPPN
Speaker 2:Yeah.
Speaker 5:And, like, what is it about this moment and why has it worked and why has it worked as well as it has? Yeah. I do think, you know, it's obvious that just, like, so much of this thing is, like, it's a you know, you guys do like
Speaker 1:a It's very
Speaker 4:up to
Speaker 5:sports show, and so much of what we're talking about is de facto sounding like sports including the degree to which people just get traded so to speak from or big signing transfers from one firm to the next.
Speaker 3:Yeah. I mean, to me to me, business like anybody that is like sufficiently nerded out about business Yeah. And markets and tech is like it's always been, you could always comp it to sports. Right? You have personalities.
Speaker 3:You have have effectively coaches. Know like the elder VCs. Have the teams, the companies, etcetera.
Speaker 1:Yeah.
Speaker 3:Switching gears a little bit, what's up with what's going on with general solicitation right
Speaker 2:now? It
Speaker 3:seems like it seems like there's a bull market in general solicitation. There's there's this guy, Eric Jackson, who's just been basically going out saying, yeah. I'm just looking for 100 x's and by the way, if you wanna if you wanna if you wanna join the ride, you can. And a lot of people look
Speaker 5:careful at when I Okay. Talk about this topic. But the idea of, like, you know, we're going to pick a ticker try again, try to be careful. We are going to pick a ticker and just sort of manufacture momentum for it It's probably just so much that always existed in markets, and we seem to be in an age in which this sort of behavior is people don't try to hide it as much. And that's, I think, not the surprise.
Speaker 5:Have there always been people attempting to, like, alright. We're gonna, like, try to I'm trying to think of a word that wouldn't land me in legal trouble. We're gonna try to move this stock for sort of noneconomic reasons because we gather and buy it. Yeah. Has that always existed?
Speaker 5:I'm sure we seem to live in an age where not only are people comfortable with just sort of doing that in the public, you have a lot of people who sort of say, yeah. You know what? Everybody's gotta eat, and everything is corrupt these days, and everything is a scam. I don't really believe that for what it's worth. I actually think American capital markets are the best in the world from a sort of transparency and regulatory side.
Speaker 5:I actually think it'll be sad if we lose that. But I do think there's this wide perception. It's all a scam. Everybody is corrupt. Everybody has inside information.
Speaker 5:You're not. You don't have that information, and therefore, why can't you participate in your own form of, you know, driving the market to your will? Social media obviously allows that, and no one seems to everyone seems to be sort of cool with that these days. And Yeah. Like I said, I actually do think American capital markets are deep and fantastic and well regulated generally.
Speaker 5:And if you look anywhere else in the
Speaker 2:world give it up from Yeah. From capital markets. We'd love them. I was talking to Jordy about this this morning.
Speaker 3:Well, it's funny that when when somebody is doing or you know, basically doing general solicitation Yeah. That the reaction is for a bunch of guys who love finance to go and dunk and quote tweet the person Yeah. Be like, look And it just drives more attention.
Speaker 5:How do you cover it? Like, I I I thought this is the problem. Like, how do you even, like, begin to cover it? Because I've wondered about this, like, with doing the podcast over the years where it's like certain, like, certain you know, I'll hear a story someone will tell me about, like, some meme coin or something. And the schemes that they, like, concoct to, like, pump it, basically.
Speaker 5:Straight up manipulate it or, like, gather in a group, etcetera. And it's really interesting, but it's like it feels a little, you know, like, I would love to talk to you on the podcast. On the other hand, I no matter how much that person is straight up admitting to market manipulation, the mere fact that they would be getting attention would almost certainly drive the whole thing higher. It So creates this very, like, weird tension from this Yeah.
Speaker 3:Remember when the when there was that Argentinian presidential meme coin that, like, Malay kind of endorsed and then the guy that created it, like, went on, like, a started going on podcasts immediately breaking it down.
Speaker 5:Yeah. You know, I there's that famous George Soros quote, and I don't know it exactly, but he talked about it. He's like, when I see a bubble, I run towards it. And I think everybody is now adopting that, where they look at something and they wanna get in. They see a scam, and rather than, oh, I want to avoid that scam, it's I wanna get in on the scam.
Speaker 5:I want in other words, it's like, I wanna be in on the next major.
Speaker 2:I remember this during the Yeah. I remember this during the crazy crypto era of, like, 02/2021. Yeah. They they, I remember Coffeezilla, this YouTuber who would talk about these scams, would interview some of the, like, victims who lost a lot of money, and they were like, well, I knew it was a Ponzi scheme, but I thought I was early. I thought I
Speaker 5:was early. I think I wrote I gotta go find that because I hadn't thought about it. I think I literally wrote once, like, the new thing is, like, getting in on the next made off.
Speaker 2:Getting in on
Speaker 5:the next made early and if there's sort of, like, we're in an era where regulators, whatever, just don't care about this stuff and Yeah. Or the expectation is, you play everyone gets to play the game. Everyone knows what the game is. You just don't wanna be the bag holder.
Speaker 2:Yeah.
Speaker 5:The game is to get in early.
Speaker 2:I was thinking about this in the context of the Coldplay concert that went viral. The CEO of Astronomer took over the Internet, and I was like Yeah. Okay. It's a private company. But if it was a public company, what would have happened to that stock?
Speaker 2:Is there a world where someone's like, let's turn this into a meme stock because it's a small company?
Speaker 3:Let's buy the Coldplay IP. Yeah. Roll it in and turn it into a Coldplay IP treasury play.
Speaker 2:I I'm sure there'll be something out there in the near future.
Speaker 5:I don't love it, but, know, I'm old and I'm a boomer at this point. So maybe I just need to sort of embrace the new generation.
Speaker 3:You know know, crazy some somebody messaged me and they were like, do you know Andy Byron, the guy at the Coldplay concert was previously the president at Lacework which went from 0 to $7,000,000,000 in the or $8,000,000,000 in the private markets back down and ended up selling for like I think around 150,000,000. Wow. So he's been on he's been on
Speaker 5:What a ride. That's someone who that's someone who knows the roller coaster of life.
Speaker 3:Yeah. So he'll he'll be back I'm sure probably in another marriage. What's going on with the two thirty spread? I saw you posting that yeah. The two thirty spread is at its highest since October 2021.
Speaker 3:I remember October 2021, there were top signals blaring everywhere. We have our own top signal tracker that we're working on internally that we should we should roll through as well. But what's
Speaker 5:going gonna get into proprietary data? No. So, like, you know, the way to think about you know, the president has been out calling for rate cuts, we might get rate cuts at some point into the next year. But the way to think about the yield curve is that at any given point on the curve, that number reflects the average rate over that time. So the two year yield, for example, is essentially what the market expects the Fed will will have rates on average over the next two years.
Speaker 5:Mhmm. The thirty year is what the market expects Fed rates to be on average over the next thirty years. And what you see is this you know, even at this time of calling for rate cuts, that number at the long end keeps going higher and higher, which suggests that, you know, the Fed could cut rates right now. It could get rates aggressively. If Trump replaces Powell sometime next year or perhaps tries to fire him before that with someone who's sort of a lackey or a loyalist, We might get this situation of sort of like aggressive rate cuts now, but if people perceive that to be inflationary and so forth, one possibility is that rates go up at the long end because they'll eventually have to compensate that compensate for that by higher rates to fight that inflation.
Speaker 5:And so you see that now. And what that means though is that even if you got rate cuts right now, might not actually get lower mortgage rates or lower car rates because those are the rates that actually matter towards where people are borrowing. So I think perhaps maybe the market is telling Trump a signal, you're not even gonna get what you want even if you get what you want. You could get that Fed chair who immediately cuts rates for you. But if the goal is lower rates to stimulate the economy, it may not even work because you might see longer rates rise in compensation.
Speaker 2:Interesting. Yeah.
Speaker 3:That would be Can
Speaker 2:you talk about the decision for who runs the Fed? Yeah. The it's been kind of wall to wall coverage from the Wall Street Journal. All different bank CEOs coming out. There's been memes about, like, you know, the school walkout.
Speaker 2:Don't fire your own pal like, what what what are the arguments on Sure. On the sides of, like, hey. Let's not intervene from the executive branch.
Speaker 5:Yeah. There's a bunch of interesting dimensions. I mean, look. I'll say a few things. There's always been pressure put on the Fed from time to time from the White House.
Speaker 5:It's not new to Trump, but it is really stepped up. And it's the the sheer number of attacks, the demands for immediate rate cuts, the sort of the attacks on Powell for the cost of renovation of the of the Federal Reserve building, which interestingly, there was a story by AP out today that said one of the drivers of the cost is that in February, the administration officials wanted there to be more marble instead of glass in the building.
Speaker 2:Feels very Trump like.
Speaker 5:It's very Trump like. And so that could be so there is some why the renovations have been so expensive? It's one possibility. Okay. But then the you know, there's a range of so there's this guy, Kevin Worsch, who for is my entire career has been a hawk, always calling for higher rates.
Speaker 5:Suddenly, he's calling for lower rates.
Speaker 2:Interesting. This is battle with Kevin. There's two Kevins that are in in Yeah.
Speaker 5:Right. Right. Then there's Kevin Hassett, who I think is generally, you know, considered to be, like, a respectable economist by and large. And, you know, if he if he were to get the nod, don't I think there would be too much anxiety. But the assumption is that whoever replaces Powell would be much more inclined to cut rates sooner and faster.
Speaker 5:And if it if it's and if it's true that, like, the economy has some upward momentum right now, then you could see how people might perceive that to be inflationary. And another name I wrote about him today, Christopher Waller. He's a governor on the board. He is probably he's calling for rate cuts. He thinks there should be a rate cut as soon as the next meeting.
Speaker 5:But in Waller's defense, he's had really good intuitions this whole cycle. So he's very hawkish. He wanted to fight inflation aggressively even while others on the board were calling it transitory. He predicted that inflation could come down from its highs without a meaningful increase in the unemployment rate, which has been proven correct. So, you know, there are some who are suspicious and cynical and say he's openly campaigning for that Fed chair job, but he's been no one could really deny that he's he's he's had his finger on the pulse about as well as anyone else for the last five years.
Speaker 5:And this is important, which is that the FOMC, you know, it's 12 people. It's not just the rates aren't just decision of the Fed chair. Waller is someone who would probably have a pretty decent amount of credibility with the other 11 people on that board because he comes from there. So it's possible that, you know, maybe he's the most logical choice. But what's likely?
Speaker 5:I have no idea.
Speaker 2:Off the top of my head, if I'm gonna steel man rate cuts, I'm gonna Yeah. Say something Yeah. Yeah. The economy is doing well. The retail sales are good Yeah.
Speaker 2:And jobless claims are fine, but it's still really expensive to buy houses and mortgages are really high. And so I wanna help Americans buy more houses. Getting people on the housing ladder
Speaker 5:Yeah.
Speaker 2:Is the way that they start accumulating capital. That's good. If I do the the tinfoil hat, I'm struggling with this because I I imagine that, you know, if I'm, you know, want to if I want my party to win in the midterms, if I want my party to win a reelection, I want the economy to be really strong. I want markets to be booming. So despite all of the different, you know, social issues that might be floating around, everyone says, well, like my IRA is up, my 401 k is up, my market portfolio is up.
Speaker 2:But it feels like it's too soon to be putting to to be playing that card. To go back to our rat analogy, if I was completely cynical just saying Yeah. This is all about politics, I wouldn't be demanding rate cuts now. I'd be demanding them right before the midterms, which I believe next year. Right?
Speaker 2:So Yeah. To react to those steel man, the tin
Speaker 5:foyer conspiracy. So, look, you know, like I said, you know, the the issue with rate cuts from a housing perspective is that mortgages mortgage rates may not go down if there
Speaker 3:are rate
Speaker 5:cuts because they're tied to the long end of the curve, which might go up in expectations of future inflation. The strongest argument I would say for
Speaker 3:Could we could we pause what could we do? Like, couldn't you just go and with, like, Figma and edit the long end of the curve Yeah. Bring it down?
Speaker 5:Yeah. You could well, you know, equivalent of the equivalent of Figma, I guess, would be yield curve control, which is not unprecedented, where the Fed actually just goes out and says, we are not going to let the ten year rise above x level, and we will buy treasuries with our unlimited balance sheet.
Speaker 4:Mhmm.
Speaker 5:And and they could do that. The issue then is you probably that means letting inflation run hot. It's tricky. Okay. But the steel man for rate cuts is that the labor market has slowed, and the the rate of hiring really has declined quite a bit.
Speaker 5:Yep. I mean, I think there have been several stories about how low hiring is, particularly for college grads
Speaker 3:Yep.
Speaker 5:And so forth. So this I think the the the the the argument for rate cuts, there's a straightforward one, which is that you could make the argument that the economy needs support or that it's over the rates are overly restrictive, which is the argument that a Fed governor Waller made yesterday. But, you know, just to your point about, you know, the elections and irate look. Like, what was it? I think yesterday there was the news that president Trump was going to allow people to, you know, invest in crypto in their four zero one k's or something like that.
Speaker 5:There was some headline about that and access to private credit. You know, I do think it looks like this is an administration that is very comfortable with letting asset prices rip. And it people like that. People like when their four zero one k's and their IRA's and all that go up and their cryptocurrencies go up, and I think this is an administration that is, like, pretty happy to see that.
Speaker 2:We said this early. Give Jane Street direct right at access to the Fed funds rate. Let the
Speaker 5:high It solves it all. Solves it all.
Speaker 2:Just solve for market prices. Yes. Just make the market go up as much as possible.
Speaker 3:How's how's Jane Street doing with their little little PR don't know. Serious haven't PR
Speaker 2:actually have a follow-up.
Speaker 3:The camel? Yeah. Yeah. Yeah.
Speaker 5:The Indian the Indian options.
Speaker 3:And then the the Sudan stuff too. That whole that whole thing.
Speaker 5:Wait. What? Oh. Yeah. We talked about that.
Speaker 3:No. It's just like you go from not here. You only hear about Jane Street really on the Duar Kesh podcast.
Speaker 2:Yeah. Yeah.
Speaker 3:You know, a nice ad read and then you start hearing about you know all these other things. It seems like there's
Speaker 5:I don't know. I gotta I I I I'll I'll I'll check-in on Jane Street for you guys.
Speaker 3:Mhmm. Thank you. Thank you. What jersey are you wearing by
Speaker 2:way? Yeah. Bring
Speaker 5:it in. Oh, I've got this I was in Mexico earlier this year. By the way, I got your hat. I have I I and I have it in the office. I wasn't sure if that would be a little I was thinking about wearing your TBPN hat.
Speaker 5:Whatever you want. But is that I was like, is that like wearing the t shirt to the band when you're going to see the band? I wasn't totally sure, but I'll put it on next time.
Speaker 3:Maybe. Wanna I wanna see a suit at some point.
Speaker 2:Yeah. Oh, it would be cool. Oh, yeah. We're gonna get some off
Speaker 3:box for a teeter
Speaker 2:so we can I'll
Speaker 5:do it. I'll wear
Speaker 1:a box.
Speaker 5:You know what? I will wear a suit or at least a shirt, jacket, and tie next time you guys have
Speaker 3:a It's so great. It's we we've been we try to wear white suits when the market's ripping. The S and P five hundred was at an all time high yesterday. Right? We didn't think to we didn't even think to put it on because it's just we're so normalized to
Speaker 2:it's every day out here. Anyway. Thanks for stopping.
Speaker 5:Always. Thanks anytime. Always love it. Have a good weekend.
Speaker 3:Love it, dude. Have a great weekend. Bye. Cheers.
Speaker 2:Really quickly, let me tell you about public.cominvesting for those who take it seriously. They got multi asset investing industry leading yields and they're trusted by millions. Will bring Millions. Next guest, Nirav from Nextdoor. A bunch of questions particularly about political campaigns given some of the folks we had on earlier.
Speaker 2:But, thank you so much for joining. Good
Speaker 3:to What's meet going on?
Speaker 2:How you doing?
Speaker 8:I'm doing great. Thanks for having me.
Speaker 2:Excited Welcome to be stream.
Speaker 3:It's great to have you.
Speaker 2:Why don't you kick it off with an introduction on yourself and the company and then I just wanna jump into a bunch of questions immediately. But, I'll let you I'll let you in and do the introduction.
Speaker 8:Alright. Appreciate it. Nirav Tolia, cofounder and CEO of Nextdoor. Nextdoor is a public company that is trying to build the daily utility that you use every day to find out what's going on around you. We're focused on the neighborhood in particular, and so we sometimes call ourselves the essential neighborhood network.
Speaker 8:Mhmm. We started in the summer of two thousand ten, went public in 2021. I ran the company for the first nine years and then actually came back to the company a year and a half ago as CEO. So I'm a refounder, not just a founder, but a refounder. This week was really exciting for us because on Wednesday, we launched the new Nextdoor.
Speaker 8:The reason I came back to the company is because we needed a much better product, and sometimes founders are in a good position to reimagine the product even though they built it in the first place. And so for the last year and a half, we've been working on a brand new version of Nextdoor, launched it on Wednesday. It's going really well. We're excited about the future.
Speaker 2:Awesome. What's the biggest change with the new product?
Speaker 8:It's completely different. And so it's not an evolutionary change or like a version one point o to two point o. Right? But the biggest change is we've taken an all purpose news feed because we're a social network for neighborhoods. Like, there's a social network for pictures and a social network for people and for businesses.
Speaker 8:Right? And we've taken that social network, and we started to make it a lot more structured and utility centric. So we focus this release around local news to keep neighbors informed, local alerts to keep neighbors safe, and local recommendations to keep neighbors smart. In the news feed, there was always local news being discussed.
Speaker 2:Of course.
Speaker 8:There were alerts being discussed. There were recommendations being asked for and given. But now we have dedicated parts of the app where you can find those things, and so it's just a lot more useful.
Speaker 2:Senator, do you sell ads? What's the business model?
Speaker 4:We do
Speaker 1:How is it evolving?
Speaker 8:We we have over a 100,000,000 verified neighbors in 11 countries. So Yep. Decent scale. And as I said, we're public. And so hundreds of millions of dollars in revenue as well.
Speaker 8:And the business model is advertising.
Speaker 2:Yeah. That makes sense. We had a friend of the show on earlier this week. He is running for state council. Is that right?
Speaker 2:State Assembly. State Assembly. And it was interesting because he come he came on our show and we we have an audience all over tech and in San Francisco and New York. And I was and I was trying to puzzle, like, wanna help him. I'm I'm excited about his campaign.
Speaker 2:But realistically, we're not a we're not a platform focused on his district in Los Angeles. He was saying
Speaker 3:he's going square miles.
Speaker 2:Yeah. Yeah. He was saying he was gonna go knock on doors literally and and go to local events. But I was I was thinking about what is the most Internet native way. He's a great poster.
Speaker 2:He creates He created kind of a viral video and he seems to be good at communicating through the Internet. What can you tell me about politics on Nextdoor generally, local politics? Have people found luck there? What are the different strategies? Are you in favor of this?
Speaker 2:Are you excited about this? Are you avoiding it? What what how does politics
Speaker 1:look at
Speaker 8:the numbers? It's a great question. And honestly, it's something that we've struggled with since the inception of the company because when it comes to national politics. As we know, very divisive
Speaker 2:Totally. Totally.
Speaker 8:When we see that on the platform Yep. We don't like it. We've actually said specifically no discussion of national politics and no national political advertising. So Yep. That's where we started.
Speaker 8:Right? Yep. What we've realized over time is, when it comes to local issues, whether you call them local issues, civic issues, or local politics, those topics matter to neighbors. The point you made is exactly right, which is the folks who are behind those topics, whether they're elected officials or whether they're folks in the local community that are trying to get something done, they need distribution. Because the Internet has made it easy for you and me and your cohost to talk to each other.
Speaker 8:And I don't even know where you all are. I'm in Texas. Right? But I'm pretty sure you're not in Texas. Right?
Speaker 8:But it has made it very hard, because we're looking on our screens and looking at our computers, to look out the window and see who's right across the street or who's next door. Right? And so that should be the promise for Nextdoor. And so it's a long winded answer to your question, but I hope in the future that we will provide your guest an opportunity to come on to Nextdoor where he knows he can reach verified neighbors in that 20 square mile and he can talk about the issues and how he wants to deal with the issues. Historically, for fifteen years of our history, until Wednesday when we launched the new Nextdoor, we didn't really let anyone except for verified neighbors create content.
Speaker 8:We had some public agencies, police departments, fire departments, some mayor's offices, but not what you would call local politicians. And what we realized is, ultimately, our job is to give you all the local information that exists regardless of the source. And so with the new Nextdoor and with local news, which I mentioned, we have 3,500 publishers that are publishing 50,000 articles every single week. Now in my city of Dallas, that's the Dallas Morning News. That's D Magazine.
Speaker 8:That's all the local publishers. It's not The New York Times publishing into Dallas. Right? It's the Dallas centric and the neighborhood centric sources. So the same way we're letting those third party in those third parties in, I fully expect at some point in the future, and I don't know when, we will let the third parties that want to be elected officials or who are elected officials come on to Nextdoor.
Speaker 8:And we just need to figure out the right way for the signal to be higher than the noise.
Speaker 2:Yeah. No. I completely Yeah. It's it's it's fascinating like, I had this weird interesting experience where we moved into a neighborhood and there weren't curb cuts and we have a stroller and my wife was like, I'm gonna write a letter to the city and I was like, that's never gonna work. Like, it will be ten years.
Speaker 2:And they fixed it and they made a curb cut in like three months or something. I cut it was really fast. I was very impressed. And it's clear that like the city was just prepared and open to that and I didn't even know that because I don't have like this connection because the local news has kind of dropped off so much. How do you think about the business model that a local news creator might have in the future?
Speaker 2:We talked to Chris Best at Substack yesterday. Very interesting business model there. I could imagine, I mean, social network has had, you know, people might talk about the YouTubers or podcasters and Joe Rogan with these big deals. But there are people that make a full living just on Instagram or just on X or just on threads. Listen, this show is really just really big on X.
Speaker 2:And I'm interested in how you see the business model of a local content creator. Is there a world where you're both partnering with an organization to distribute their content that's maybe in a local newspaper physically, their own website and then you're kind of a top of funnel Or do you think there will be next door native creators soon if there aren't already?
Speaker 8:It's a big challenge for local publishers because as we know, the old business models of delivering papers or driving subscriptions for things that show up in our mailboxes, that doesn't really exist. Yeah. At the same time, the digital business models, they don't have the same scale. And so it's hard for them to justify the ad sales forces or the technology investment, etcetera. Right?
Speaker 8:Today, what we're doing is we're starting by sending them traffic. We don't have a walled garden on Nextdoor. These 3,500 publishers, they give us a headline. They give us a hero image. They give us a snippet.
Speaker 8:And then if one of our members wants to read an article, they go off to that publisher's website. And that publisher can monetize through a subscription. They can monetize through advertising. They can monetize whatever way they've chosen. The thing that we've thought about and I'll get to kind of the next door creator idea that you talked about.
Speaker 8:But the thing we've thought about is if there's enough demand in one area to get local news broadly, Mhmm. Could we put together a kind of Apple News or Spotify kind of subscription
Speaker 3:Yeah.
Speaker 8:Where you pay one entity next door, and then they get the proceeds on some kind of rev share based on what articles are read? So we've thought about that, but it hasn't gone any further than us thinking about it because we need to see how this performs. Ultimately, I'm not sure about the business model behind it, but we certainly believe in citizen journalism. And so even enabling the high school journalism student who wants to write about the high school sports that are going on and making sure that they can use Nextdoor as a distribution platform, that's something we wanna enable. Because if that person goes on Instagram or x or LinkedIn or Facebook, there's just not enough audience.
Speaker 8:But if that person comes to Nextdoor and they're writing about the neighborhoods that are around a particular school, those neighbors wanna support that school. So there's a lot of opportunity for Nextdoor. I would say the story of Nextdoor is one of massive potential and of not having a good enough product to really deliver on all that potential. And that's what we're trying to change.
Speaker 3:Yeah. It's an interesting challenge because like social like social networks in general are have have historically done well by reducing friction on the sign up. But the nature of Nextdoor is you need that extra step of like verifying does this person actually live where they're, you know, in the in the neighborhood that they're trying to participate in. And I and I had this one moment, it sounds like it was before you came back and and started fixing things where I moved to a new neighborhood, I was trying to get set up and it wasn't verifying and I just churned. And I haven't I haven't gone back.
Speaker 3:And so I imagine this even though I'm sure I'm sure it's active. I know I know it's a very active community on there. One one question
Speaker 8:is kind of a hard problem because when people try to switch around neighborhoods, they don't have the patience to reverify. They do have to verify initially. They don't have the patience to reverify. So it's something that we need to make a lot easier because the thing you're talking about, the statistic I heard was something crazy like 10% of Americans move every year. So it's happening a lot.
Speaker 8:People are moving neighborhoods whether they're in the same city but in a different house or whether they're moving cities altogether. And so that's something that we need to make frictionless.
Speaker 2:Yeah. If you could like like upload a video of you walking into your house with the address and then you do some like geo guesser type AI thing to identify that, hey, this person's really walking into this house.
Speaker 8:Like We we've done everything You've
Speaker 2:done everything?
Speaker 8:Innovative technology sending you a printed physical postcard.
Speaker 2:Yeah. We've done all of those things. The printed postcard is Lindy. It's it's not going anywhere.
Speaker 3:How how do you guys think top of minds because John and I live in Southern California. I I live in Malibu. John lives in Pasadena. So we were both pretty close to the fires that happened. Fortunately, we weren't directly our our homes or neighborhoods weren't directly affected.
Speaker 3:And then you're in Dallas near not too far from where the flooding happened. How do you do you guys think about building features around helping people through disasters? Because I remember the the fire app in Southern California that everyone was using is just run by a non profit. There was one night that John basically thought
Speaker 2:Watch duty?
Speaker 3:Yeah. Watch duty. John John one night like basically thought that he was like, oh, Jordy's probably You know, I just We didn't have any cell service or anything like that. But I just remember using watch watch duty. Yeah.
Speaker 3:It would just periodically go down and it felt like, okay, this is probably going down because they just don't have the
Speaker 2:The scale.
Speaker 3:The the engineering capacity, the scale, etcetera, to just, like, run this service. I'm I'm curious. But it's a hard problem to try to tackle because it's so spiky. Right? It's like you Yeah.
Speaker 8:Look. Watch Duty is an amazing app, and so kudos to them. And when the Palisades fires happened, I looked at that thinking we have to do more. Now we had we had seen all of our metrics spike like crazy in those Palisades neighborhoods. Because when a crisis happens, whether it's a power outage, which is relatively banal but annoying, all the way to inclement weather or a natural disaster like a fire, right, or terrible flooding, Nextdoor becomes a lifeline because there is no other infrastructure to communicate with the people around you, and you need to be able to either say, in a very simple way, what's going on, all the way to, in a critical way, say, I need help.
Speaker 8:I need to be rescued. Right? Or I can provide someone with help. And so historically, through hurricanes, through tornadoes, through fires, Nextdoor has always spiked when these things happen, but it's just a news feed UI. And so with the new Nextdoor, we've created an entire alerts surface where the entire app transforms into this lifeline when, God forbid, a crisis is happening.
Speaker 2:Mhmm.
Speaker 8:And we take now authoritative data sources. So in much the same way that we're bringing in third parties on local news, we bring in third parties. I think we'd like to bring in watch duty at some point as well. And because we know where people live, we can deliver their information proactively to just those areas. And that's what's very different.
Speaker 8:Because if you think about Watch Duty, Watch Duty doesn't know where you live, and Watch Duty can't warn you before you go open Watch Duty to see if something's going on. Right? Yeah. But what happened with terrible
Speaker 3:it's actually it's actually ends up being stressful because I'll be, like, on the show and I'll get a notification from watch duty. Fires this year, it'd be like, a fire has popped up half a mile from me. It's really rough. It doesn't know where it doesn't know where I am so I'll get notifications like all over LA County. I'm just, you know, I end up look I mean, it's probably good for their their user metrics because I'll open it up and realize, okay, it's it's like a 100 miles.
Speaker 8:I think you need three things to really create an essential use case around this, which truly is an essential use case because it could harm your family and and yourself. The first is you need to aggregate all the alerts. So Watch Duty just does it for fires. Right? But you need power outages.
Speaker 8:You need construction delays. You need any kind of of traffic that's going on. You need some event that's gonna change something in the neighborhood all the way to the really serious stuff like fires and tornadoes and hurricanes and crimes and that sort of thing. Right? So that's the first thing.
Speaker 8:The second thing is you need to know where people live so you can get them timely information that's hyper relevant. Right? I mean, it's not relevant if it's half a mile away because it's not gonna affect you. It's just gonna freak you out. Right?
Speaker 8:And then the third and final thing you need is you need to have a community of people that are notified, because in many cases, they're the ones that have the information, the photos, and the videos Yeah. That are actually more relevant than anything the authorities are providing, because they're on the ground. Right? They know exactly what's going on. And so we have all of those pieces, and God forbid those crises happen.
Speaker 8:But when they do, we have to do our part in keeping people safe.
Speaker 3:It's community intelligence. It's like the collective
Speaker 1:100%. Together.
Speaker 8:So It's the power of community, truly.
Speaker 2:Fantastic.
Speaker 3:Awesome. Well, great great chatting. Congrats We're on the you come back on again soon. You're going founder mode.
Speaker 2:It's great to see
Speaker 3:you back in
Speaker 8:the better open the app. And if you email me, I will make sure you get verified immediately so that it's I'm
Speaker 3:sure it'll work perfectly now.
Speaker 8:Even perfect. I think you're gonna like it. And I think your listeners will too. It's very different than the old Nextdoor. Awesome.
Speaker 8:It's got all the goodness of the old app, but in a fresh new shell with lots of new features.
Speaker 2:That's amazing. Very exciting.
Speaker 1:You so
Speaker 2:much for hopping on.
Speaker 8:Thanks for having me.
Speaker 3:We will
Speaker 2:talk to you soon. Cheers. Bye. And if you're looking to explore a new neighborhood, get on Wander. Find
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Speaker 3:Wander just dropped Wander Indio Hayes. Oh, fun.
Speaker 2:Hayes I love it. H a
Speaker 3:y s? A z e.
Speaker 2:Oh, okay. But Well, we have stay there. Mike from Arc AGI coming on the stream and Hey, guys.
Speaker 3:We have the ability Arc Day.
Speaker 2:Arc Arc Day. I I love these releases. Thanks so much for always coming on the show.
Speaker 6:Of course. Thank you guys for being such huge supporters I'm such a Arc Means a lot.
Speaker 2:Project. It's it's so amazing. So, we have the latest and greatest. Why don't you just give us the little bit of background on the the
Speaker 3:Yeah. First of all, like, I think don't we talk about the x AI launch Sure. Last week because that was a, you know, pretty massive.
Speaker 6:Yeah. Big deal.
Speaker 3:So maybe start there, and then we can get to the present.
Speaker 6:Yeah. So this is really, I think, the second time we've seen a major frontier AI lab use ARC as a benchmark to show off some sort of frontier progress. Right? Back in December, we had, OpenAI, use Arc v one to show off this qualitative change. Right?
Speaker 6:Really marked the moment where AI frontier AI research moved beyond just, like, scaling up retraining and starting to add these symbolic systems on top, these chain of thought reasoning systems. ARC really marked that moment. And then, last week, the x AI team used ARC v two to show off a frontier result on on ARC v two. They got 16% on the benchmark. Still early days, but I think one of the really big takeaways from that from that was basically, like, how you know, it's largely using a lot of the existing ideas in the world, how quickly and effectively x AI was able to catch up to the frontier.
Speaker 6:Mhmm. And so, you know, my mental model now is, you know, going forward is, you you know, wherever the front sort of innovation come from, my expectation is, like, say, it's probably gonna go beat for beat on on catching up just given how fast they're able to get there this time around.
Speaker 2:When when I hear some like, one one thread that I've heard from watching the Arc progress is you put more more test time inference, more spend behind a particular model, you get better results. And it and it and it begs the question like, this brute forcing? Is that what we're experiencing at some level? Is that is that a fear? And is the latest Arc v three, an attempt to kind of avoid that?
Speaker 2:Or is that just, like, not an issue at all?
Speaker 6:So so no. Because of how we evaluate top scores on ARP. So we publish along two dimensions. One, an accuracy score.
Speaker 2:Mhmm.
Speaker 6:But we also publish an efficiency measure. And this is not arbitrary. Like, efficiency is really, really fundamental aspect of what it means to be intelligent. So when we, you know, we have the million dollar prize, it's still hanging out there, by the way, for the original version of the contest. And, you know, if you look at, you know, the human level efficiency scores just on v one, we're still only around, you know, percentage points.
Speaker 2:Mhmm.
Speaker 6:Whereas our benchmark for humans is 85 and and onwards. So And and You know, even though we've got v two and even three
Speaker 2:now 83 85% or something, would they win the million, or do they have to get to a 100%?
Speaker 6:So the Kaggle contest rules are a little more stringent. You have to do it on a certain performance profile with a limited compute budget. You have to get the high score, and then there's an open source requirement. So this is one of the things that, one one of the sort of principles of the Ark Price Foundation is we're trying to basically accelerate AGI genesis by encouraging more people to work on new ideas, openly share those ideas, try to, you know, kinda shape the AI research community to look more like what it did during the twenty ten to twenty twenty era than than maybe it has over the past, you know, three or four years or so.
Speaker 2:What about, I we we talked to somebody. I forget who they they said like, oh, yeah. Like, you know, ArcGi, it's cool. But, like, we could totally crush that if we just, like, RL'd on it directly. And all the labs are just being, like, nice to, like, keep it as an independent benchmark.
Speaker 2:But I don't fully buy that because I feel like some hedge fund would just see a million dollars on the floor and then just go do that if that was the case. But what what is the what the vibe
Speaker 6:of The reality is, benchmarks are marketing.
Speaker 2:Yeah.
Speaker 6:Right? This is like one of the reasons I I didn't appreciate this twelve months ago when we first launched Arcade. Sure. As I do now, you know, the the the whole reason I put the money into the contest in the first place was Arc's awareness was very low and my thesis was this is the most important unbeaten benchmark in the world that tells us something important that no other benchmark does. Right?
Speaker 6:If you go even look at the Grock four stream, all the other benchmarks that were shown are like PhD plus plus level benchmarks. Yep. And yet, ARC tasks are like, you know, we have objective evidence. We've done human controlled studies that show they're all solvable by sort of average humans. Yeah.
Speaker 6:And so I think that tells you something interesting. Like, well, okay. Yeah. Like, we're we're clearly missing something bigger. We don't have it all figured out.
Speaker 6:We're not in just like a scaling up regime. We are in a we're sort of an idea constraint regime. And I think that's an important conclusion because if it's true, it means that individual researchers and small teams on small budgets can actually have a significant impact on the frontier of AI research. They don't need, you million, know, 10,000,000, billion dollar training budgets in order to actually make a material impact on AI.
Speaker 3:Yeah. The the the challenge like, I mean, the real challenge is just the distortion in the market right now and the trade off that a that a researcher, even somebody who's, let's say a 20 year old in college that could be doing this sort of independent research and they're like, wait if I drop out, I could be making $500,000 a year base comp and and what what Yep. You know, the the equity on top of that. So I imagine it would I imagine at some point are there like high schoolers that that are that are doing this kind of thing because
Speaker 2:like Yeah. At a certain
Speaker 3:point like the target market is like people that like are maybe a little bit too young to like actually get it like Silicon Valley companies will happily have somebody drop out of college. It's a different conversation when somebody's like, I wanna like drop out of like high school. Right?
Speaker 6:I mean, this forms my thesis. I think talent is very distributor globally. If you look at most of the teams that are on leaderboard from, you know, past years of our contest, you know, a lot a large percentage, I'm not sure if it's over 50%, but it might be, are outside The United States. And, again, this is, like, you know, if you're sort of trying to create a sort of optimization function for creating AGI, you know, you you'd like to shape in an innovation environment that's very open. There's a lot of sharing, and there's a lot of diversity of approach.
Speaker 6:The opposite would be like, there's very little sharing. Everyone's working on the same ideas. Like and if it because if those ideas are wrong, then, like, okay. You're sort of shooting yourself in the foot. And so that those are I I think that's that's one of the reasons we sort of launched Shark Prize in the first place was try to try and help communicate the story that individual people, young folks, without with very little budget can actually have a large impact and encourage them if they have new ideas towards AGI to go work on those, you know, may maybe as opposed to going and, you know, just starting the next language model, startup.
Speaker 2:Yeah. When when Dwarkash came on the show, he was talking about the need to solve continual learning, this idea that he has, you know, this amnesiac PhD that is unable to learn hard lessons and then roll that up into habits and kind of wisdom almost. And and and that's why he he's unable to you know use any of the frontier models to his example was like select which clips of the podcast will perform well on on social media or something. He was struggling with And I'm wondering like we hear about the spiky intelligence concept. Do you think that the the problems that underlie Ark Prize's robustness are related to the same continual learning problem that that Durkesh was highlighting or are these two separate problems where we could see us solving one and not the other?
Speaker 6:I think that's happening. Right? The scores are much higher in v one than v two. I I so if I kinda lay out and tease here kind of the the version we're doing in public preview for today
Speaker 3:Mhmm.
Speaker 6:You know, we've got v Arc v one, v two, and v three. V one was introduced back in 2019. It was designed to challenge deep learning as a paradigm. Remember, this is before language models, years before sort language models really hit any sort of stride in terms of the research. And it, sort of was robust through that, advancement, and that's because large language model sort of inherits some of the same fundamental limitations that pure deep learning do.
Speaker 2:Mhmm.
Speaker 6:V two was designed to challenge this new paradigm of AI reasoning systems. It's still a static benchmark, so the puzzles look very similar to v one. It it might actually be kind of surprising that like you can't beat v two if you can beat v one because they look like they're in domain from each other, but Totally. The the intuition here is generally the v two puzzles require longer reasoning chains generally to solve them and so that gets harder to do. One of the things that we started to see though this year is really the emergence of a lot of these agent systems that are being placed into dynamic, open ended environments.
Speaker 6:And while static reasoning, I think benchmarks are useful and will continue to be useful, this is one of the motivations for starting to build, e three and defining what we're calling an interactive reasoning benchmark to help evaluate and really challenge some of these frontier AI agent systems we're starting to see, emerge.
Speaker 2:Okay. So should we do the live demo?
Speaker 3:Let's do it.
Speaker 2:Think we can
Speaker 6:do it before launch today, I guess. Yeah.
Speaker 2:So so I can
Speaker 3:kind of overview.
Speaker 2:I can kind of read through this too. Yeah. Give us the overview and then and then we'll
Speaker 3:play It's a little it's
Speaker 6:a little unique for us because you might be surprised like, v three is launching v two launched, like, three months ago?
Speaker 2:Yes. Yes. So today
Speaker 6:is a public preview. We're we're showing off the first three public games from the eventual dataset. We're building this year. We intend to launch the full version in early twenty twenty six. We're we're going about the launch a little differently than we did with v one and v two because v three is such a big upgrade over v one and v two.
Speaker 6:We wanna get And
Speaker 3:by upgrade, you mean by upgrade, you mean significantly more challenging?
Speaker 6:The gap between what's easy for humans and hard for AI is getting wider again with v three compared to what the earlier versions were, which I think is one of our other design principles that we have. And so it's and it's also just like a very different domain than you wanna do today. They look like our tasks, but they're dynamic, and there's a lot we don't know about them quite yet. Both what humans can do, what they actually find easy, what AI agents can do, how much can you create, you know, custom harnesses and scaffolds to be able to maybe make progress. I think we're gonna learn a lot.
Speaker 6:And this is why we're sort of launching the first three games early to make contact with reality here and increase our early learning over the next maybe month or so on our game design, our API design, we actually have we launched our first piece of infrastructure today as well, an API that you can actually build agents and go run against these first three games. And we launched a $10,000 agent contest that's running for the next month for whoever can build the best agent that gets the best top score on the the games that we're
Speaker 2:that we're if they get 1%, but they are the top Yeah.
Speaker 6:Even if it's low, whatever it is
Speaker 2:is going out,
Speaker 6:the door. One important thing, like v one and v two, Arc v three has a public and private dataset. So we've got three public games. There's also three private games. Those are actually what we're gonna be awarding on top score performance on.
Speaker 6:So
Speaker 3:if you're
Speaker 6:thinking like, I'll just make a really good, you know, harness for the three public games, it won't work because they won't translate into the three hidden games.
Speaker 2:Smart. Clever. Clever. I love it. So I'm I'm sharing my screen to the stream.
Speaker 2:I don't know if you'll be able to see it. I can see But I will read through this. So
Speaker 6:My suggestion is you guys should we should play locksmith. This is LS 20, our first game. I think you guys should just collaborate on this one game together. It'll take about five to ten minutes to probably play through and I think seeing both of you like work together on it live, I think will be
Speaker 3:a I fun and should entertaining be able to see the screen.
Speaker 2:Okay. I'll I'll read it out. So, human instructions, you are playing a game ID. There are no instructions intentionally. You must play the game to discover rules and goal.
Speaker 2:Press start to play. Choose your controls W A S D or arrow keys. Play to learn the rules of the game. Win the game. Profit.
Speaker 2:Just kidding, just kidding. No prizes here. So I click start and I'm presented with a large grid of squares. It looks like the most intense Arc AGI puzzle possible because the original Arc AGI puzzles were something like a three by three grid and now I'm seeing
Speaker 6:These are all 64 by 64.
Speaker 2:64 by Okay. 60 Yep. So, I do have the ability to use arrows to move this blue and orange block. And Jordy, you see me moving
Speaker 3:Yes. It
Speaker 2:Okay. So, if I go on top of this, the bottom left hand corner updated slightly. Let me see if I can zoom this out a little bit so that
Speaker 6:Alright. You've learned one important thing.
Speaker 2:And if I keep moving, click seems to do nothing. Space bar seems to do nothing.
Speaker 6:I'm a give a little commentary while you're you're going here too, John. Please. So, know, the dataset, the three games that we launched today, all of them are completely different. None of them look similar. In fact, this is the only game in the set that looks like a two d agent game from kind of a tops down camera view that we're launching right now.
Speaker 2:Okay.
Speaker 6:All the other ones are are quite different. And this is actually a design goal of the benchmark is for all the, you know, eventual hundreds of games we're gonna have for them to be entirely different and very novel and diverse from each other.
Speaker 2:So I I appear to have lost a life. If I look in the top right, I now have three. I I had three red dots. I have two and
Speaker 3:you cross that boundary? I
Speaker 2:got a red flash. And so, I think I died. But if I move forward, I get a green circle which I imagine means I won and now I'm on a new level and there's
Speaker 6:supposed Do to be you know why you like got to the new level? Can you articulate that yet?
Speaker 2:Yes. So I I believe that I stepped on a button that rotated my or or kind of rearranged the the icon, the goal icon in the bottom left of the screen. At first, I thought that the the in the bottom left I see a little like like blue and white line and I thought the line was like a map that I have to take Mhmm. But it appears to be a puzzle shape that I have to match up with a puzzle shape that's on the grid somewhere. And I'm stepping on a button to change it.
Speaker 2:So when I step on this rotate or change button, I'm getting kind of like a different Tetris piece. And if I keep doing this, I might land on this. Okay. That matches now. So, the bottom left matches the the little gold.
Speaker 2:I go over to it but if I go over to it I die. And so I think I ran out of purple steps. So I have a set of
Speaker 3:There we go.
Speaker 2:Purple like energy. Yeah. Yeah. I have I energy. So now, I'm gonna do the same thing.
Speaker 6:There's another very important I'm doing. Many of the games in arc v three inherent, which is there's intentional efficiency limits on actions that you can take.
Speaker 2:So now, green score. I did it.
Speaker 3:Which is smart because the idea of like, you know, Scott Wu can probably like one shot a math problem Yes. And it's very efficient for him and then someone else like he is gonna be able to solve the same problem but but like over weeks and is that really the same level of of intelligence.
Speaker 6:This is really, you you guys have probably like, for for for a long time actually, I think games were considered solve problem AI, you know, with AlphaGo and Yeah. All just games and
Speaker 2:and and and Yeah.
Speaker 3:And I think One of the
Speaker 6:reasons for this is the way
Speaker 2:they learned. Like, they they didn't the only thing that stopped them from being like totally superhuman in those is that they just didn't scale the current algorithms enough. And so they didn't solve, you know, it completely, but they all were basically Yeah.
Speaker 6:And most of them use RL, and so they're trying to take reward signal and understand, you know, what actions I took to produce the reward signal. This is one of the things that efficiency helps with is it limits the ability for an agent to just naively be able to go gather a reward signal by spamming and playing the games hundreds of thousands of times. This is something humans don't need to do. Right? You know, you already beat level two, in, what, less than five minutes here with a very limited number of efficient, you know, actions that you took.
Speaker 6:Yeah. And this is something we don't see from the frontier like LM's day or or other agents we've been testing.
Speaker 2:Okay. I got my next level.
Speaker 6:Alright. The next level, we we started introducing some new concepts here.
Speaker 2:So so I'm seeing they're different
Speaker 3:colors. So
Speaker 2:I I have blue and white and I need blue and yellow or blue and orange and so I'm gonna step on this this color block. Now, have blue and teal. Now, I have blue and red. I'm doing okay on efficiency. I have about half my life.
Speaker 2:Okay. That seems good. But, think if I make a run for it, I won't make it. So, I'm gonna pick up this purple cube to refresh my energy. Run over here.
Speaker 2:Am I gonna make it? Am I gonna make it? Made
Speaker 3:it. There we go.
Speaker 2:Yes. There we go. Victory. Okay. Now that there's a different one.
Speaker 2:I'll start by changing the color. Okay. I nailed the color blue and teal. That's the end gold and the black cube. Then I need to switch my icon from this one Tetris piece to a different one.
Speaker 2:Okay. I got that. No, that's not it. I need the the little like chair block. Okay.
Speaker 2:That's
Speaker 3:You're running out of lives John.
Speaker 2:Roughly correct. Let's see. Okay. I refreshed. I refreshed.
Speaker 2:Go over. I think this this other block I think this is a button. I think I'm gonna run out of lives though. Need to go refresh. I refreshed just in I won away.
Speaker 2:I won away. Okay. Let's keep rotating. Keep rotating. Okay.
Speaker 2:Now it matches.
Speaker 6:There you go.
Speaker 2:Okay. And I'll just pick up the free energy. Boom. Green.
Speaker 6:Oh, what what you might have noticed is sort of scaffolding new new things you have to learn. Right?
Speaker 2:Yes. The progression system here. Yes.
Speaker 6:It's not just learn one rule in level one and apply it to the entire game. But we found a really an element. One design goal is that all the games are fun.
Speaker 2:Yes.
Speaker 6:And one of the things we found when we're doing early design game design was that folks did not find the games fun if they just took one rule they learned and did that just repeated it. Right? Yes. Yes. Yeah.
Speaker 6:Introducing new things you have to continually learn throughout the game is a big function of whether humans can find these things actually entertaining and fun.
Speaker 3:Well, we we should figure out the infrastructure to have pure PVP speed runs Totally. The entire prize.
Speaker 2:We'll have the whole team do
Speaker 3:it too. Real quick while we have you, I I we have our next guest in the waiting room. But I wanted to ask you because it's top of mind for us this week. Think the broader tech community went from sort of not taking AI safety and alignment super super seriously or kind of making jokes about it until this week. I think AI psychosis has been top of mind for a lot of people.
Speaker 3:If you were running one of these scaled labs today, how would you be trying to sort of quickly react to some of the different kind of stories that seem to be bubbling up around? People just getting, like, too, you know, too deep in this sort of recursive prompting.
Speaker 6:You know, my my sort of view, generally, on AI safety stuff is if you wanna be empirical about it. You know, this was sort of my big issue when we were going through all the ten forty seven legislation last year in California is trying to make predictions about what future harm might happen by being able to predict the future. And in some cases, poorly predict the future. I think even ARC, you know, was of clear demonstration of an eval that suggested we were not just scaling up pretraining. AGI is not just gonna emerge from scaling up this pretraining regime, and that was sort of the predicated thesis on why we needed something like ten forty seven at the time to, like, stop this imminent, urgent, potentially dangerous scaling.
Speaker 6:Sure. So now I I actually think, you know, my my sort of view probably aligns quite closely with open answer. I think you actually need to deploy the technology into the environment, into the world in order to make contact with reality and learn what are the actual issues that you care about, what does society care about. My my sort of view is that, like, society is actually better at dealing with, fast change than slow change. You know, this is another kind of counterpoint that I think if if you go look at the safety community would argue, oh, slow slow takeoff is better than fast takeoff.
Speaker 6:Yeah. I think in a lot of capabilities area, actually, fast takeoff is is is perhaps desirable because humans notice change. It's like literally what we're evolved to do is in our environment. We notice when things change fast. We don't notice when things change slow.
Speaker 6:Right? The frog boiling in the Frog boiling the classic Yeah. Fable here. Right? And so I think fast change stories like this, issues with psychosis are good in a in a weird way because they they We're sure everybody.
Speaker 6:Yeah. Antibodies. Yeah. Like, oh, hey, something changed here. We should react
Speaker 2:to Yep. Yeah. No, that's
Speaker 6:really And so good that's kind of my broad framework of what what I'm what think how we should sort of like run these in a system.
Speaker 3:In some ways, the the negative externalities of social media, like let's say like somebody's developing body dysmorphia, like the the the ways that social media spectrum change from like sending like group messages Yeah. To suddenly like you're sharing your entire life. Yeah. Like it actually was very slow. So And I think that this development with with
Speaker 6:Yeah. Creeps in, right? You wake up ten years later and you're like, are we happy with like Yeah.
Speaker 2:Where we got to? Rot. Yeah. A meme that took years to develop. Fascinating.
Speaker 2:Anyways. You have to come back on soon. We could go way We're gonna be playing this all day.
Speaker 6:Hope you guys had fun playing the first game.
Speaker 3:No. Yeah.
Speaker 2:Fantastic. I was not expecting a game. I was expecting a puzzle and we are clearly in game territory. Very fun. Very
Speaker 3:exciting to
Speaker 2:play more.
Speaker 6:Guys. Thanks for having me on.
Speaker 2:We'll talk
Speaker 3:to you soon, Mike. Bye.
Speaker 2:Up next, we'll stop keeping waiting is Kyle Simani. Welcome to the stream. Sorry for the wait. We were we were proving our humanity with Arc AGI v three. Welcome to the stream Kyle.
Speaker 3:In the suit.
Speaker 2:In the suit. You look fantastic.
Speaker 3:On a special day.
Speaker 2:You didn't have to wear the suit just for the show. Come on.
Speaker 4:I wanted to go out and do y'all a little bit too.
Speaker 3:Fantastic. Look look looking sharp.
Speaker 2:Looking sharp.
Speaker 3:Are you in are you in DC right now?
Speaker 4:I am in DC. I'm in a little phone booth about two blocks from the White House.
Speaker 2:Fantastic. Give us the update. What's happening in DC?
Speaker 4:Great. Let me turn my phone here
Speaker 2:real quick. Yeah. That's amazing. Awesome,
Speaker 4:guys. Thanks for having me back on. Pleasure to be here. Today's a big day for for Cryptoland. President Trump just signed a genius bill into law.
Speaker 4:Yes. Huge, huge day for industry. This is the probably most consequential piece of financial legislation since frack dot Frank. Mhmm. It's the first crypto legislation we've ever had, and it's an incredible
Speaker 3:milestone for the
Speaker 2:industry at all.
Speaker 3:Which is crazy to say out loud this this, you know, over Yeah. Or how how however far we are into this
Speaker 2:It's been crypto has been a thing for, like, almost twenty years now. Like, what what Bitcoin It's a
Speaker 3:thing that you've been basically begging for. Just like give us some Give us something. Regulatory clarity.
Speaker 2:It's here. It's great.
Speaker 3:It's finally here.
Speaker 4:Yeah. I mean, industry has been begging for regulation under the Biden administration.
Speaker 3:Yep.
Speaker 4:And they said, no. No clarity. We're just gonna shoot you randomly. And, you know, finally, like, we actually can operate. It's pretty amazing.
Speaker 2:Fantastic. What does this mean for non stablecoin chains? Like, what does it mean for Solana? What does this mean for Bitcoin? Are is there any implication there?
Speaker 2:Or is this purely
Speaker 3:Yeah. Do you think it's priced in?
Speaker 4:Yeah. It's definitely not priced in. So first, let me touch quickly on, like, what a day means for The US, and then can get into kinda, like, the the chains and stuff. Yeah. So I think the correct way to think about this this is, you know, there's 8,000,000,000 people in the world.
Speaker 4:And I have a theory that if you were to go to each of those 8,000,000,000 people and ask them, hey. If you can denominate your wealth in any asset, it could be Apple stock, S and P 500, bars of gold, euros, yen, yuan, whatever you want. If you could denominate your wealth in any, asset without fear of political persecution in your local jurisdiction, what asset would you choose? And my suspicion is that somewhere between 6080% of the world would say US dollars.
Speaker 2:Mhmm.
Speaker 4:And for people who have only been inside The United States, having a US dollar bank account is somewhere between very difficult and impossible
Speaker 5:Mhmm.
Speaker 4:Outside of, like, the top 1% or so of of the of the global global wealth. And stablecoins make it trivial for anyone in the world to host to have dollars in their pocket. You don't need to sign up for permission. You just you take your phone. Your phone literally picks a random number, that's your private key, and you're you're good to go to receive dollars.
Speaker 4:I think this will probably represent one of the large largest movements in capital and human history as you enable, call it, five to 6,000,000,000 people to, like, start holding more dollars more easily than they otherwise could hold them. And the scale of what it means is actually really profound, I I think really underappreciated, which is why I think it's not priced in because it's just hard to grasp what this means for everyone in the world to be able to hold one currency. This has never happened in name
Speaker 6:of history before.
Speaker 2:Yeah. Is fascinating. I mean, I'm I'm I'm like I I I'm almost like zooming out like I'm sure it's good for a lot of different projects and companies and tokens and chains but it feels just incredibly bullish for America. Like we've been like because there was this narrative of like, oh, the tariffs and stuff like we're gonna lose dollar dominance. We're like we're gonna lose global reserve status.
Speaker 2:And this just feels like coming from the the half court shot.
Speaker 3:Yeah. Was like an artificial, you know, it was like a supply demand imbalance, but the supply constraint was just coming from
Speaker 2:Like you don't have to
Speaker 3:laws, be regulators in in other places that said, you can't set up a dollar, US dollar bank account in our country.
Speaker 2:Exactly. Yeah. You don't have to be like even crypto crypto or crypto native or anything.
Speaker 3:This what this is It's where
Speaker 2:for America.
Speaker 3:And this is like Yes. You know, going back sort of the core tenants of crypto like permissionless finance. It's like, okay, like permissionless access to US dollars where Really somebody says I wanna get paid in dollars. They set up a wallet and it's software, and they get paid. And it's Yes.
Speaker 3:It is
Speaker 2:It's very cool.
Speaker 4:Mean, it's very much capitalism. Like, I just applied to my if I'm give you I didn't know as a capitalist, like, we should probably oh my god. Like, actually, the world as a whole was actually shockingly anti capitalist in terms of just like currency access across nations.
Speaker 2:Yeah. Yeah. That's wild. Yeah. What else should we talk about today?
Speaker 2:Is there any other downstream things? Can you give us a temperature check on the rest of the regulation? What happens next? Anything else that's going on in Washington that we should be following?
Speaker 4:Yeah. I mean, downstatement locations, there's a ton. So first, in a quick regulation. So the Genius Act passed, that's the stablecoin bill. Mhmm.
Speaker 4:The next major act the industry is focused on is that public clarity act. Yep. This is being primarily sponsored by chairman French Hill in the in the house. And this is otherwise known as the market structure act. And the basic kind of outline of of clarity is to answer the question, which regulators regulate what?
Speaker 4:What should they they regulate? This really kinda defines the line between Treasury, SEC, and CSCC Mhmm. Who has kinda, you know, purview over which domains, answers the question, what is a security, what's not. It deals with v five to some extent. And so that's kinda the other really big meaty bill.
Speaker 4:Mhmm. And then the third one is actually one that kinda got added in recently, and and industry is fine with this just basically this anti CBDC bill. They're just saying, like, America won't make a CBDC. So that that's all in in flight now. You know, I'm optimistic clarity will pass in the next few months.
Speaker 4:It passed the house earlier this week. It's now in the senate, and there's gonna be some revisions and stuff in the senate. We'll see where it goes.
Speaker 3:Anything anything that's that's in there so far that you're that you think it that that that the senate should should focus on correcting?
Speaker 4:Yeah. There's there's definitely more disagreement in industry about, like, you know, the the substance of clarity. I can't get into the specifics, but, like, certainly, we're we're right now in dialogue with a lot of our peers and lawmakers and their staff on on these issues.
Speaker 2:Mhmm. Makes sense. Sense.
Speaker 4:Don, the other question you asked was, like, what's the implications for, like, industry? Yeah. I I wanna emphasize that. I mean, by making it it's not legal. Stable coins were illegal for all practical purposes for, like, any major regulated company kind of anywhere in the world.
Speaker 4:Mhmm. And it is now legal and blessed for them to interact with stable coins. And so what I think is, yeah, you're gonna see every bank, you know, Jamie Diamond, Bank of America CEO, they're talking about this now. I actually don't think that's the the super relevant angle. To me, the much more important angle is it is now legal and okay for iOS, Android, Facebook, WhatsApp, Instagram, TikTok.
Speaker 4:Every piece of major consumer software in the world now can legally embed stablecoins. Wow. And I don't it's gonna a matter of matter of time before they do. And what that's gonna mean for global commerce, for global payments, for people accessing crypto is profound. And I think you're and and as all those people get their private keys and onboard to these wallets, that's then gonna obviously provide the the foundation that that that money's gonna be transacting over Ethereum, Solana, etcetera, and it's gonna be just a massive boon for all of crypto as you onboard a few billion people with this stuff.
Speaker 3:It's fascinating. Absolutely wild.
Speaker 2:Yeah. I'm excited. I imagine that the other the the big tech angle is super fascinating. I I imagine that some of them will take different paths, different shapes. Like, we're gonna
Speaker 3:test Yeah.
Speaker 1:What I
Speaker 2:what I different hope structures.
Speaker 3:Yeah. What what I hope is like, hey, stable coins are already there there's large market caps. There's lots of liquidity. Let's not have everybody launch their own stable coin. Let's just like focus on actually integrating them into and making them, you know, more valuable in these different ecosystems.
Speaker 2:It's also funny because I feel like for a while there was a little bit of a there's a little bit of like a chattering class critique of crypto being like, well, if it was so great, like, why why doesn't Apple just integrate stablecoins? It's like, well, because it was illegal. And like they're a very risk averse company. There is no chance they were gonna do it. But now they actually have it as an option and then there's a competitive dynamic and they'll probably run experiments.
Speaker 2:And yeah, maybe it'll take a few years for them to build some stuff. Maybe some stuff will be acqui hires or acquisitions. There's a bunch of different things ways you can play out but it'll be really interesting to follow, like, how this actually gets in the hands of, like, billions and billions of people. Fascinating.
Speaker 4:Yeah. It's an incredible opportunity. And I mean, you you just look at, like, now where's liquidity? Where are people trading today? And Yeah.
Speaker 4:You know, and like which things have the scale to support all these users and it just it bodes incredibly well for for industry as a whole.
Speaker 2:That's fantastic.
Speaker 3:Well, as there's more news, come back on and I'm sure you'll be celebrating responsibly in in DC. So, have fun out there.
Speaker 4:Hey, guys. Thanks so much for helping me back on.
Speaker 2:Have a good one. We'll talk to you soon. Bye. Talk to you soon.
Speaker 3:What a way to end the week.
Speaker 2:Fantastic. Little news hits, little chopping it up with friends. Mighty and Screlly. That was a fun one.
Speaker 3:That was
Speaker 2:I enjoyed that.
Speaker 3:One of the most entertaining
Speaker 2:Yeah.
Speaker 3:People on
Speaker 2:earth. Hands down. Should close with this this wonderful article in the mansion section.
Speaker 3:Which one are we? We we had a few queued up.
Speaker 2:So this is I wanted to I wanted to do this because it is essentially written by Arnold Schwarzenegger. So, it is his it's his words as told to Mark Myers who just transcribed them and then they published it in the Wall Street Journal.
Speaker 3:Which one is this?
Speaker 2:It's Arnold Schwarzenegger, The Moment He Fell in Love with America. Beautiful. My early years in Austria were challenging. After World War two, the economy in the Graz suburb where I grew up was shattered. Everyone suffered.
Speaker 2:My father Gustav was very, very was a very, very sweet man, but when he drank his personality changed. He became more violent and demanding. His behavior and drinking were influenced by the war's remnants. Shrapnel in his legs that caused him pain, the lingering effects of malaria, and what we now call post traumatic stress disorder. My mother Aurelia was a homemaker.
Speaker 2:Our family lived on the Second Floor of a three story building. The First Floor was occupied by the local forest ranger and the second wars and for and the second wars for my father. The Second Floor was for my father. The the town's police chief he was the town's police chief. The forest ranger had a phone but we didn't and there was no running water.
Speaker 2:I wasn't happy with the life I saw unfolding. I always had a feeling deep down that I needed to look for something else, something outside the box. At age 10, I fell in love with America. That came from watching film roles in school. The teacher would advance the strips by turning a knob showing one image at a time.
Speaker 2:I was blown away. They were about things like the golden like the Golden Gate Bridge and the Empire State Building and cars with huge fins driving on US highways with six lanes on each side. At some point, there was a role on Hollywood. I'd never seen anything like it, the glamour, the lights, and the houses. I said to myself, what am I doing here?
Speaker 2:I wanted to be in America to become famous and rich. As I got older, the question shifted to how do I get there? At 15, I stumbled into bodybuilding at our local lake and said to myself, well that's in America. The lifeguard always had other top athletes around including weightlifters. As a teen, my testosterone was kicking in and I wanted to look like a He Man.
Speaker 2:I read about Roy Reg Reg Park, an English bodybuilder who played Hercules in Italian movies. He won Mr. Universe three times and became an actor. My dream was possible. All of my time was spent in this world of physical fitness building up muscles to complete to compete in contests and fantasizing about movie stardom.
Speaker 2:At one point I was in school looking out the window and daydreaming when a piece of chalk hit me in the head. My teacher said Arnold what do you think you're doing in here talking to myself. I had no interest in what he was saying. He's not interested in school. In 1967, I won the amateur Mr.
Speaker 2:Universe title in London when I was 20. Then I trained in Munich for another year and won my first professional Mr. Universe title after I won in 1960
Speaker 3:It's so funny. This the the thinking of the sixties and and just like hippie hippie culture and then Arnold's just like rising the ranks.
Speaker 2:Yes. Bodybuilding. It's amazing. So he said 1967, I won the amateur Mr. Universe title and then he won the Burf's professional universe title.
Speaker 2:After I won in 1968 Joe Wider a bodybuilding enthusiast who published Muscle magazines brought me to Los Angeles. He put me up in an apartment in Venice near Gold's Gym where I trained. When I arrived, let's hear it for Gold's production team. You guys love that place.
Speaker 3:That's where I work at. A great spot.
Speaker 2:It's fantastic. When I arrived in LA, I was totally I was totally disappointed. The city looked nothing like New York City with its tall buildings. Venice's sidewalks were dirty and no one cleaned them, and drugs were sold in back alleys. Two more Mr.
Speaker 2:Universe titles followed in 1969 and 1970. From the start, I knew bodybuilding was going to lead to acting. 1970, I was cast in Hercules in New York and then in the TV series and films including Stay Hungry in 1976 for which I won the Golden Globe Award for best acting debut. Then came the streets of San Francisco and Pumping Iron in 1977. Iron.
Speaker 2:Pumping Iron is fantastic if you haven't seen it. I know you haven't. Conan the Barbarian, the big one in 1982. I was quoting Conan the Barbarian to our team. I don't think anyone got the reference but we'll play the YouTube video.
Speaker 3:This is wild. So he says in the middle of all this I studied remotely for a bachelor's degree in business. And let's give it up for all the out there. Most important major.
Speaker 2:At the University of Wisconsin.
Speaker 3:He was doing that remotely.
Speaker 2:How were you doing remotely? From '82.
Speaker 3:College in '82.
Speaker 2:I guess you like mail it it back
Speaker 3:to Oh you maybe get mailed an assignment
Speaker 2:That in a is yeah. Is crazy. How do you do that? I don't know. I have no idea.
Speaker 2:From the time I arrived in America, I went
Speaker 3:to Arnold community invented remote work.
Speaker 2:He really did. Yeah. That is a crazy crazy thing. I'll have to have him on the show and ask him about his his time as a remote business major, University of Wisconsin Superior. I went to community college to take English classes and get smart about business.
Speaker 2:In 1983, I became a US citizen. Let's air it for Arnold Schwarzenegger, one of the best to ever do it. Today, I live in a house in Brentwood, Los Angeles. It's the perfect place where I can see the foliage and the mountains. I'm close to town, it's private, and I have my pet I have all my pet animals, which means not just dogs.
Speaker 2:He definitely has more than that. We'd love to know what he has. In the nineteen eighties, I took my mother to the White to a White House dinner to meet President Reagan. At the table, I went to scratch my nose and she hit my hand in front of everyone. She said, don't pick your nose in the White House please Arnold.
Speaker 2:I wasn't. But that didn't stop her. No matter how big you get, your mother knows how to shrink you just a little. What a great story.
Speaker 3:I am sad that I was not super conscious when Arnold was the governor of California.
Speaker 2:Yeah. Great.
Speaker 3:Like, I I remember it. Yeah. But, I I I wasn't there for probably all the incredible moments. And, I don't even have a strong take on if he was like a great governor, but I think he's awesome as an individual.
Speaker 2:Totally.
Speaker 3:And That's a great place to Sam Sam Soulek, I hope he makes a run-in politics as well.
Speaker 2:Me too. Would love it.
Speaker 3:Think that would be powerful.
Speaker 2:And Hollywood first.
Speaker 3:Can you imagine daily Sam Soulik vlogs from the campaign trail? Incredible. He's just getting all of his constituents, hey, just come for a lift. Come for a lift.
Speaker 2:I think we're I
Speaker 3:think we're we can talk policy.
Speaker 2:We get him in a Jason Carmen directed reboot of the Terminator. Yeah. Get him into Hollywood. Get him trained up. Make him a household name more than he is already.
Speaker 2:Then get him on the campaign trail. I think we have a winner
Speaker 3:in Something there. Sule. Well, was a crazy, wild, often fun week. That's I can't wait for next week.
Speaker 2:Yeah. We'll see you Monday.
Speaker 3:You for Have great tuning weekend. A fantastic weekend. Bye.