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TBPN is a live tech talk show hosted by John Coogan and Jordi Hays, streaming weekdays from 11–2 PT on X and YouTube, with full episodes posted to Spotify immediately after airing.
Described by The New York Times as “Silicon Valley’s newest obsession,” TBPN has interviewed Mark Zuckerberg, Sam Altman, Mark Cuban, and Satya Nadella. Diet TBPN delivers the best moments from each episode in under 30 minutes.
You're watching TBPN.
Speaker 2:Today is Thursday, 04/09/2026. We are live from the TBPN UltraDome, the temple of technology, the fortress of finance, the capital of capital. Have a great show for you
Speaker 1:folks. Getting a little worried Monday. Not a lot of fundraisers going on. Sure. I was looking at the schedule
Speaker 2:Yeah.
Speaker 1:And I was thinking, is it over?
Speaker 2:It's
Speaker 1:And today, I'm happy to report that we're back. Andrew Dye is coming on from Elorean, raised a $55,000,000 seed round. We got Kesava coming on with a six 38,000,000 series b. We got a $170,000,000 series c later and then a $100,000,000 series e. And then a nice little mango seed Yeah.
Speaker 1:From the Enclave team to to cap it off. But really fun show today. We got Saagar Enjeti from Breaking Points, our friend over there coming on. We got Joe Weisenthal. Yeah.
Speaker 1:Wise and tall. And then CZ from Binance. Yeah. Who is releasing Freedom of Money, detailing Binance's rise to crypto evolution and of course his US legal battle.
Speaker 2:Memoir. And I'm excited to talk to Joe about the who is Satoshi Nakamoto and I'm also excited to talk to CZ about who he thinks Satoshi Nakamoto is. You would imagine that he's in a position to potentially have a good good take on that. Anyway, there is a ton of AI news. Andy Jassy released the 2025 shareholders letter.
Speaker 2:Amazon is known for fantastic shareholders letters dating back to 1997. I thought he did a good job of sort of resetting the AI narrative. There's this AI Lab horse race going on. Of course, we've been covering it all week. Anthropics Mythos preview and Project Glasswing launched on Tuesday, quickly followed by news today that OpenAI also plans to deliver a model with advanced cybersecurity capabilities to key Internet infrastructure providers.
Speaker 2:And there's this debate going on over how and when these models will roll out. I think this is going be an ongoing trend. I don't think cybersecurity is the last model capability that will be slowly delivered to key companies first. Cybersecurity is a perfect fit for powerful coding agents. And people have been digging into exactly how some of these zero day exploits, some of these bugs and vulnerabilities were discovered.
Speaker 2:And it makes a ton of sense that if you have a model that's fantastic at coding, it can basically try every single coding exploit, try new coding exploits across a huge number of open source packages, submit pull requests and generally harden the Internet infrastructure that we all rely on. So in general, it seems like the rollout Mythos, although people are disappointed because they want to play with the latest and greatest model, even if it's very expensive, it seems like it's having a positive effect and should be a bit of a white pill for containing powerful models, having them have proper impacts, having them have a positive impact on the American economy, on our security, on all these different things. I do think I wouldn't be surprised if we see something similar happen in biosafety. Now the biosafety AI research loop is a little bit longer because you might have to go to the lab. It's not entirely existing in a computer, in a virtual machine that you can spin up and just brute force reinforcement learn against.
Speaker 2:But you can imagine if a model develops capabilities, in the next run, maybe in middle of this year, If a model becomes powerful enough to design a harmful virus or something like that, you would want the lab that creates that model to deliver that to the scientific community and companies that can protect the population against the development of new harmful biological viruses, just like we're protecting the Internet against cybersecurity viruses. And so I'm not exactly sure where this all goes, what the other 10 steps are, but in general, it seems like there's going to be a pattern of a powerful model becomes capable of doing something that it makes sense to share with the particular community that can defend against that new capability and then make and then the entire community needs to make sure that that capability is carefully under control before releasing a version of that model that can still you know, in the biosafety example, like you still want a model that can help you learn about biology, learn about how viruses are made, how they mutate. This is important for education and augmentation of the of scientists from, you know, high schoolers all the way to professionals.
Speaker 2:But the most advanced technology, it makes sense to put it in the hands of people that can actually take a real have a real impact on that immediately before rolling it out broadly. But Andy Jassy sort of zoomed out and was stepping back from the horse race because Amazon's a partner with basically everyone in the ecosystem and has their own models. And so he shared this shareholder letter zooming out on the state of AI, the state of Amazon's plans, and he shares a bunch of very interesting anecdotes about his personal life. So we should read through some of this. He says, when I graduated from college, wanted to be a sportscaster.
Speaker 2:After sending my resume reel to many small markets around The United States and only getting two nibbles, I settled on doing sports production at a major network. To make extra money, I coached my former high school soccer team and worked at a retail golf store. Six months later, a college classmate convinced me to interview at the consumer products company where he worked, and I spent three years as a product manager there. I left that job to try some of my own businesses. After deciding these businesses weren't my calling, I tried short stints at sales and investment banking before going back to grad school and ending up at Amazon three days after my last final exam in May 1997.
Speaker 2:Not exactly a straight line. He says AWS followed lots of squiggly lines too. And of course, Andy Jassy is the, by and large, the creator of AWS. That was his major project during his tenure. Founder.
Speaker 2:Yeah. Deserves so much credit in, building that business. The original vision included storage, compute, payments and human intelligence. They had a product called Mechanical Turk where you could go and dispatch a specific task. You would have to build sort of a web UI, but it was the original sort of data capture tool.
Speaker 2:But it could also be used for little things like manual translation tasks. People weren't really using it for customer support tickets, but
Speaker 1:Data labeling.
Speaker 2:Data labeling before you really needed mass data labeling, but it was that type of business. And there was always a question when Scale AI started like, is this just Mechanical Turk? Is this business process outsourcing? Obviously, that went on to a fantastic outcome with Meta. But it became a different thing and quickly moved towards what we see in the expert networks and data collection that's much more nuanced than a single task on demand.
Speaker 2:But AWS, this was in the vision. And they wound up pulling away from that and sort of refocusing. So Andy Jassy says, Some of those, e. G, storage and compute became linchpins in AWS. Others didn't.
Speaker 2:Others didn't succeed. We initially we didn't initially plan a database service. And when we built one, our first attempt to fail to get traction, went back to the drawing board and built new relational and non relational databases, which have resonated well and become core to millions of AWS applications. When we launched EC2, our compute service, it was a single instance in one availability zone, Linux only, with no auto scaling, load balancing, block storage or private networking. Over the time, we added those capabilities and hundreds more services, and you see that when you go into the AWS dashboard.
Speaker 2:It is chock full of different products. AWS was initially attractive to startups. Companies like DoorDash, Dropbox, Pinterest, Slack, and Stripe were among many that built their businesses on AWS. Pundits said that enterprises and governments would never use AWS. Wait.
Speaker 2:What is going on here? I am
Speaker 1:Out of order?
Speaker 2:I'm out of order here. Let me find the actual link on here and I'll stop reading from the paper because I printed the
Speaker 1:right here.
Speaker 2:So he says pundits said enterprises and governments would never use AWS for anything substantive. But in 2008, Netflix, which was delivering DVDs in the mail for almost a decade at that point, decided to move all of their applications to AWS. Then came big commitments from GE, Intuit and others. And eventually, the CIA chose AWS as their partner to build their classified cloud. Growth came fast and furious.
Speaker 2:And as it accelerated, so too did our capital expenditures, CapEx, with dilutive with a dilutive impact on free cash flow. And so he's starting to make the case that there's this trade off between free cash flow and CapEx, and this will come back when he talks about his plans for taking advantage of the AI boom. So he says, at our first at at at our 2014, more than twelve years ago, AWS operating plan review, the discussion started with a senior leader at the company musing, tell me why we're doing this business. Like, why are we doing this? It was confusing and it was very different from being an online bookstore and then eventually the Everything store.
Speaker 2:But it felt it felt different, but then eventually it started working. So he says AWS has worked well for Amazon, but a straight line, not really. There's a bit there's a band I like from New Zealand called the Beths. Have you ever heard of the Beths? No.
Speaker 2:We gotta listen to the Beths. They've written several excellent records with thought provoking lyrics. I eagerly await new releases. And when their latest album dropped last summer titled Straight Line Was a Lie, it made me think how prescient that expression is. Most long term endeavors do not follow
Speaker 1:Top songs are generally considered to be future me hates me and expert in a dying field. Interesting. And little death.
Speaker 2:What what yeah. I'm gonna listen to the Beths on the drive home today.
Speaker 1:He says Any any Beths Sound off in chat? The in the chat?
Speaker 2:The so he see he he's he's reflecting on his career and the twists and turns in building AWS. He says, most long term endeavors do not follow a linear straight line up and to the right. Progress jumps around. It'll zig up, then sometimes stall or zag down or force you back to the starting line. Sometimes it feels like you're running in circles, but the path is rarely straight.
Speaker 2:That's because the world is complex and new technology, business model invention, competitors, global issues, or people and cultural shifts can come into play. When we're in the middle of some of the biggest inflections of our lifetime, e. G. AI, robotics, space, industrialization, geopolitical and military conflict, and just as proficient golfers need to be skilled across driving, approach shots, chipping and putting, durable companies must be adept at managing different elements of inflections. I'll share some of our lessons below and why we're bullish on what's ahead for Amazon.
Speaker 2:So he talks about how broad Amazon is these days. Retail, logistics, AWS, ads, Kindle, Alexa, pharmacy. There are too many new efforts to in flight to mention them all. He talks about the long push to bring robotic automation, acquiring Kiva in 2012. He also talks about all of the benefits that Amazon has brought to rural customers, which who are often deprioritized by logistics.
Speaker 2:This is classic thing when you launch an e commerce site. Do you apply your flat rate shipping to Alaska? Because every time someone ships something to Alaska, it's going to charge you an arm and a leg. Amazon has been able to solve it through a network of that delivers over a billion packages each year, customers living in over 13,000 zip codes spanning 1,000,200 square mile 1,200,000 square miles. And he's also focusing on closing the digital divide in rural communities, so things like high speed Internet access, Internet LEO.
Speaker 2:He's been talking about Amazon LEO, the low Earth orbit satellite network. But he makes this point that Amazon must be willing to pursue parallel paths when it's unclear what will best drive the desired trajectory. He says two is greater than zero. When I was a kid I used to go to New York Ranger games, New York Rangers games with my dad. I loved hockey and it was a high quality time together.
Speaker 2:I looked up to my dad, still do, and hung on his every word. One game my dad noticed that one of the Rangers defenseman, Dallas Smith, had gone missing from the bench and stood up and exclaimed, where's Dallas? To which a nearby fan said, in Texas, moron. So yes, it's it's very weird that his name is Dallas, I guess. Is that the that's the confusion?
Speaker 2:So yes, it's fairly obvious that two is greater than zero. But too often companies focus on what looks most tidy instead of ensuring they have enough efforts in play to achieve an important outcome. Let's go back to fast delivery in our retail business. We know how much customers crave it and we see higher order completion rates when delivery promises are faster. So he talks about all the things that we know about Whole Foods and rolling out more stores, rolling out more just investments in the core Amazon business.
Speaker 2:But then he goes on to talk about artificial intelligence. And he says, If there's an obvious path to changing your trajectory, take it and run, but most new jumps aren't forward like that. There's invention and experimentation required and pursuing multiple paths gives you the best chance to find it. When you identify disproportionate inflections, bet big. Choosing which inflections are truly seminal versus just interesting requires judgment.
Speaker 2:Reasonable people can disagree, but if you believe you found one of these disproportionate shifts, you want to invest as aggressively as you possibly can. This will create investment spikes that will invite scrutiny, but the game changers don't typically accommodate smoother investment horizons. One of these seminal shifts, of course, he says is AI. And so he says, we've never seen a technology more quickly adopted than AI. When ChatGPT launched in November 2022, it reached a 100,000,000 users in two months, four times faster than TikTok and 15 times faster than Instagram.
Speaker 2:ChatGPT already has over 900,000,000 weekly active users. Both OpenAI and Anthropic have run revenue run rates reportedly approaching $30,000,000,000 These are breathtaking numbers for companies this soon after their commercial launches. And he has this great throwback to Thomas Edison and the dawn of electricity. A lot of people are looking for comparisons for what AI pattern matches to. And he goes back to the first commercial power station which launched in 1882.
Speaker 2:So at the time, most people understood the first commercial power station as a way a better way to light a room. That was going to be the main benefit of electricity. It was going to replace lamps and you were going to have electric lights. But what they couldn't see was that electricity would eventually reorganize every factory, home, and industry on Earth. And he says that AI may have a comparable impact.
Speaker 2:The difference is that electricity took forty years to get where it was going and AI appears to be moving 10 times faster. And he says that Amazon's smack dab in the middle of this land rush and companies are choosing AWS for AI. Three years after AWS launched commercially, it had a $58,000,000 run rate, three years in. And Amazon was already a big business at that time. So, you know, he's talking about the twists and turns of launching AWS.
Speaker 2:It's a you know, a lot of products
Speaker 1:Seems so quaint. It's
Speaker 2:very quaint to be three years in, have the backing of, you know, a a massive company, and and still three years in only hit 58,000,000 in run rate. He compares it to three years into the AI wave, which, of course, started in 2023, basically, and now we're in 2026. AWS's AI revenue run rate is over $15,000,000,000 in 2026, which is nearly 260 times bigger than AWS was at the same point, and it's ascending rapidly. And so he highlights a bunch of reasons why customers are choosing AWS for AI. Obviously, they have a product in sort of every single category now, model building, high performance inference, lower cost inference that runs on Tranium, their custom silicon, agent building, secure environments, etcetera.
Speaker 2:But he says that AWS could actually be growing faster, and they are, in fact, limited on capacity. So AWS added 3.9 gigawatts of new power capacity in 2025 and expects to double total power capacity by the 2027. And AWS is monetizing that capacity as fast as it's installed. In Q4 twenty twenty five, AWS reported 24% year over year growth and a $142,000,000,000 revenue run rate. That's a lot of absolute growth, and yet we still have capacity strengths that yield unserved demand.
Speaker 2:As an aside, two large AWS customers have already asked if they could buy all of the Graviton instance capacity in 2026, which is their widely adopted custom CPU chip. And he says, we can't agree to these requests given other customers' needs. You can't just say, okay, we're giving everything to one company. But it gives you an idea of the demand. And so he goes on to talk about the other projects.
Speaker 2:The chips business is on fire. They're talking he talks about in the CPU space virtually all of the workloads ran on Intel chips until they invented Graviton in 2028, has a 40% better price performance. And then, of course, they're working on Tranium and Nitro as well. And so he goes on to explore a little bit of how the AWS cash cycle works in a way that's faster than AWS, and it requires more short term CapEx. So AWS has to lay out the cash for land, power, buildings, chips, servers, and networking gear in advance of when we can monetize.
Speaker 2:And so there's been a lot of reporting about our data centers delayed. We're going to talk to Saagar Enjeti about some of the news and whether and the political pushback to the data center build out. But he says that it typically takes between six and twenty four months before we can start billing customers depending on the component. However, these CapEx investments fund assets with many year useful lives, thirty plus years for data centers, five to six years for chips, servers and networking gear. And the free cash flow and return on investment invested capital for these investments are cumulatively quite attractive a couple of years after being in service.
Speaker 2:However, in terms in times of very high growth like now where the CapEx growth meaningfully outpaces the revenue growth, the early years free cash flow is challenged until these initial tranches of capacity are being monetized and revenue growth outpaces CapEx growth. We've been through this cycle with the first big AWS wave where they invested a ton of money in CapEx building the servers before they were able to ramp revenue. And he says, We like the results even though we've been through that cycle of high CapEx drawing down on free cash flow. And he says, we expect to feel similarly about this next wave with a much larger potential downstream revenue and free cash flow. And so he goes on to talk about
Speaker 1:Super strong.
Speaker 2:But I thought it was a very Strong. Good
Speaker 1:Yes. Touches on a bunch of different stuff. I think this is what people wanted out of Jassy Yeah. Like about a year ago. Right?
Speaker 1:Yeah. He was getting, you know, people were were constantly kind of chirping at at Amazon leadership and and wanting some kind of like basically lay of the land like this to show Sure. That Amazon had a broad understanding and and actually had, you know, real leadership and and was committed Yeah. Committed to, you know, being being a real player.
Speaker 2:Yeah. Well, in other Amazon news, Amazon Pharmacy to offer Eli Lilly and Company's new GLP one pill foundeo via same day delivery. Shilm Monat says this thing is gonna fly. Amazon is up 3%. I don't know if it's on this new tab.
Speaker 2:Yeah.
Speaker 1:It's it's hard to say. Amazon's actually almost up 5% today. Yeah. And I would I would expect that to be because of the letter, but people tend to buy a lot of GLP one drugs too.
Speaker 2:But it does seem like a good I mean, we were we were talking about this with the some of the the the fast ramp of that one company in direct to consumer GLP-one and peptides. And there's so much skepticism about fly by night peptide operations, where are they being compounded, are they safe, do they contain even what you think they contain and giving consumers an option that's something as, you know, established as Amazon with all of the all of the guardrails that they have in place feels like a very positive move for consumers.
Speaker 1:Before we jump into the next story, Jassy did share a letter to shareholders from 1997. Yeah. And there's I'll read the first two paragraphs.
Speaker 2:Very good.
Speaker 1:To our shareholders, amazon.com passed many milestones in 1997. By year end, we have served more than one and a half million customers yielding 838% revenue growth to a 147,800,000.0 and extended our market leadership despite aggressive competitive entry. But this is day one for the Internet and if we execute well for amazon.com. Today, online commerce saves customers money and time. Time and money.
Speaker 1:Save both. Tomorrow through personalization, online commerce will accelerate the very process of discovery. Amazon uses the Internet to create real value for its customers and by doing doing so hopes to create an enduring franchise even in established and large markets. Well, they certainly did that. And and the letter goes on to to talk about how it's all about the long term.
Speaker 3:Mhmm.
Speaker 1:So even back then, growing like Mhmm. Absolute crazy, still, you know, wanting people to think about, thinking decades and and so Jassy doing that now. They have a good track record.
Speaker 2:Yeah. I mean, Amazon's had decades of drawing down on free cash flow to invest in the future. And the they've had long history of communicating that effectively to the community and to the shareholders.
Speaker 1:Level to which people miss the ads. This is never I don't think this has ever happened before Yeah. In the history Of content. Of podcasting. Yeah.
Speaker 1:We miss the ads too.
Speaker 2:Yeah. All we have now is Well, we need it. We need some alerts because there's a there's a debate on the timeline about OpenAI's new cybersecurity product. The there was a post that was deleted and then Axios issued an update. Basically, the question was OpenAI is launching a new model rumored to be called Spud, trained on Blackwell, sort of similar, you know, big model, lots of capabilities.
Speaker 2:And OpenAI has been working on cybersecurity products. Will they gate the rollout similarly? Are they running the same playbook? Will they take a different path? At what point will they make their models available?
Speaker 2:And people are going back and forth. And Andrew Curran is sort of clarifying here that the new model and the cybersecurity product are separate and only the cybersecurity specialized model will have a limited release, not the new model itself. So it looks like a general public release for Spud. Dan Shipper shared some extra commentary around this. The Axios story floating around about OpenAI limiting the release of their newest model Spud isn't true.
Speaker 2:He just spoke to OpenAI and it appears the story conflated two things. They do have a cyber product. They are testing with a trusted tester group, but this is not the same thing as Spud. The Axios story has now been updated.
Speaker 1:Yeah. There's a very there's a very strong argument to never release a model publicly that is specifically optimized for cyber. Yeah. Right? Because, like, you're just inviting a bunch like, think about, like, teenagers out there.
Speaker 1:I now get to be a a super powerful hacker even though you're just kind of like probably should just be vibe coding like a fun little app or something like that. Right? Yeah. And so
Speaker 2:You would think having some cyber security capabilities in the model would just be better if you're vibe coding a product. It becomes secure out
Speaker 3:of
Speaker 1:the I'm just saying I'm just saying like having this super powerful cyber focused product Yeah. Shouldn't be the kind of thing that anyone like you should probably have to KYC to
Speaker 2:Yeah. Sure.
Speaker 4:For sure.
Speaker 2:Well, yeah. What do you think
Speaker 3:about this?
Speaker 5:Yeah. I mean, also I I think, know, when when you zoom out on AI progress Yeah. It is like it is like very smooth.
Speaker 2:Yeah.
Speaker 5:Where like, you know, people were talking about this with Mythos yesterday where like, well, actually, if you run even like an open source model Mhmm. And you actually run enough times, you actually can find similar, you know, exploits. And it's just like kind of the efficiency of of the new model Yeah. Versus the the the smaller open source ones. Yeah.
Speaker 5:So like like I I I'm pretty sure right now I could take, you know, 5.4 and I could just run it a bunch of times and I could find a lot of exploits. Yeah. Like, people have the capabilities right now. Maybe it's like
Speaker 4:a little bit flagged.
Speaker 6:Sure. Yeah. Yeah.
Speaker 5:But and also yeah. Like I I I think I mean, at some point, like, lot of the coding agents, I think, you'll just see like in the, you know, in the system prompt or whatever of the coding agents, it'll be like, yeah, make sure you're checking to see if any if if there's like big security vulnerabilities. Yeah. Even right now, you can just ask, you know, codecs whatever, you're you're building something like, are there errors Or are are there, you know, security problems and it will solve them.
Speaker 2:And this is the nature of of every every advanced model is that in order to understand how to fight something, you'd have to know how to build it. And this is this is true. I mean, I'm sure that the folks at CrowdStrike or Palo Alto Networks, like, could definitely if they went black hat, it would be bad for everyone even in the pre AI era, and that remains true. And so having at least as much economic incentive as possible to put the resources and the tokens and the inference budgets towards like white hat hacking is good. There's also somebody in the chat is making the comment that there's a there's a there's a lot of precedent for this with with bug bounties and like time disclosures.
Speaker 2:So oftentimes white hat hackers will go to companies and say that we found a really bad vulnerability. We're giving you ninety days until we publish it. But it is in the public interest to know that this vulnerability exists broadly. So we have to release it but also we want to give you the time to react to this. And so it it feels like you're sort of holding that company hostage a little bit.
Speaker 2:It can be a little bit tense. But I think if it's done it's if it's done carefully, it can be sort of a win win.
Speaker 5:Yeah. But I I think regardless like
Speaker 2:Yeah.
Speaker 5:I think more KYC is probably the future. Right? Even if you're just talking about like risk of distillation stuff like this. Like I think I've talked about this before where like Yeah. Yeah.
Speaker 5:At some point, you need you need more KYC to ensure like people aren't just like, you know, training off the model or or doing like nefarious things.
Speaker 2:Yeah.
Speaker 1:Yeah. Meek Mill. What's going with Pulled out a slide from Bill Ackman. Slide says a small percentage of songs are listened to. The overwhelming majority of music tracks receive zero or minimal engagement.
Speaker 1:AI is poised to exacerbate this reality, and so it shows that point 2% of songs are culturally and commercially relevant. Oh, yeah. Commercially relevant is 10% of songs streamed a thousand to a 100,000 times.
Speaker 7:And
Speaker 1:then Meek is dropping that into what looks like Claude's saying, you're not in that 88%. You already skipped the whole bottom of the pyramid. You're already in that top point 2%. That's People know your name. They search for you specifically.
Speaker 1:They stream on purpose. That changes everything. You already have the hardest thing attention. You don't need the algorithm to find you. Your fans already look for you.
Speaker 1:So while AI is flooding the market with millions of trash songs, this is AI throwing This AI on the is crazy. Your catalog just sits there collecting streams because people want Meek, not just a rap song. And Dimes Square Holdings says, first in my bloodline to see a rapper with AI psychosis commenting on a deck
Speaker 2:I think
Speaker 3:it's a
Speaker 1:reasonable It's a reasonable analysis.
Speaker 2:Reasonable analysis. I just think
Speaker 1:it's a little bit unfair for the AI to be dunking on the other AI. Yeah. This is kind of like a crabs crabs
Speaker 2:bucket. There's a whole story about this in the journal the other day about a a a local group that's lobbying against data center development using AI tools, ChatGPT, like very heavily to understand the legal code, how they can how they can organize, who they should be calling. It sort of feels like a good use of AI in the sense that they're they're exercising their democratic rights properly through the correct channels. Like it could be so much worse. I don't know.
Speaker 2:What do you think?
Speaker 5:Yeah. Well, hopefully, like by using the model like models enough they'll be like, oh wait, this is actually good. Yeah.
Speaker 2:Or like or like there are some parts that I like narrowly but do we need this data center in my neighborhood? Maybe not. Yeah. And they can
Speaker 5:Also specifically on this, I I think it's interesting like among celebrities, it seems like rappers specifically are like really leaning in a lot more than other like types of celebrities. Little baby Yeah. Little baby, not little baby. Okay. There was a post yesterday about someone who who got paid to like set up Open Claw for him.
Speaker 5:Yeah. You've seen this a bunch. Yeah. It's just funny. Like, you don't see actors Baby talking about
Speaker 1:their little baby was second after baby Keem.
Speaker 2:Yeah. That's right. That's right. I mean, Matthew McConaughey said had some words about AI saying
Speaker 5:Oh, yeah. When he was gonna log in, he needs to log in.
Speaker 2:Well, no. That was separate. Like, wasn't it like months it it was like months months months and months later, he was like, this is coming. Like, you need to be prepared for this. You need to work alongside of it.
Speaker 5:Yeah. But he's not talking about his specific Yeah.
Speaker 2:Exactly. Exactly.
Speaker 5:Yeah. I I guess Ben Affleck had that company. Right?
Speaker 2:Yeah. Yeah. Yeah. But yeah. Yeah.
Speaker 1:Ben Affleck already got the the 9 figure exit. He he's good.
Speaker 2:Yeah. But you would you you you would imagine that that AI actually might be a useful tool for understanding the impact of building a data center in a particular community because everyone is debating the the economic impact, how many jobs will be created, what's the environmental impact, and being able to crunch through all the all those trade offs so that the community gets to a net, like a net positive impact that the population can basically vote on and be happy about and say, yeah, like we made this trade off properly and we feel like we're getting the benefit because maybe it's generating a lot tax revenue. Maybe the tax revenue is very durable. Maybe the tax revenue is going to the right place. Is it going to a tax refund because or is it going towards a project that people don't actually support?
Speaker 2:And so there's a whole other question of for the local community, is that tax revenue meaningful? Like what dollar value do they put on new tax revenues for the city? Depends on what the city is building or doing with that with that revenue. What what is this post by Eigengender?
Speaker 1:Actually that's not impressive. The concept of a Dyson sphere was already in the training data. This is like, you know, we build the dice, you know, and we build the Dyson sphere and then someone's someone's coping and just saying like, yeah, I mean it's not
Speaker 2:that impressive. You're watching the Dyson sphere be built around the sun thinking like, I'm not that important. Here's another like self referential thing. Like, you know, AI, should AI be used to fight data center construction? Today, Meta began removing ads from attorneys who are seeking clients that claim to be harmed by social media while under the age of 18.
Speaker 2:And so there's been the the these class action lawsuits have been a big a big you see them on social media all the time. Usually, it's some sort of data breach or some sort of, you know, random product that they're targeting you for. And I I feel like many people just sort of scroll past them because the the the default class action is like you wait a long time and then maybe you get a check for $5 in the mail. But Meta has begun removing advertisements from attorneys. What is their justification for this?
Speaker 2:Lawyers across the country are now seeking new plaintiffs in the hopes of bringing a class action lawsuit that could result in lucrative verdicts. It's unclear if any of them have been backed by private equity as the California lawsuit appears to have been. Axios has identified more
Speaker 8:than
Speaker 2:a dozen such ads were deactivated today some of which came from large national firms like Morgan and Morgan and Morgan. Almost all of them ran on Facebook and Instagram. Some appeared on threads in messenger plus Meta's audience network. One such ad read anxiety, depression, withdrawal, self harm. These aren't just teenage phases.
Speaker 2:They're symptoms linked to social media addiction in children. Platforms knew this and kept targeting kids anyway.
Speaker 1:Yeah. So Meta has something in their terms of service that says we also can remove or restrict to content, feature services or information if we determine that doing so is reasonably necessary to avoid or mitigate misuse of our services or adverse legal or regulatory impacts to Meta. Because basically like we're not gonna let you use our product to take legal action against us.
Speaker 2:Yeah. I wonder where where the the class action recruiting will go next. You know They'll go everywhere maybe? Out of home?
Speaker 1:Out of home. Yeah. Could go TV? Podcast.
Speaker 2:I mean, they it's such a broad case that yeah. Well, YouTube is
Speaker 1:easy to it's relatively easy to reach like Facebook and Instagram users.
Speaker 2:Yeah. Especially young Everyone. It's everyone. Yeah. So they they just need to cast a wide net.
Speaker 2:But it will be interesting to see how that how that develops.
Speaker 1:Has anyone built an out of home advertising network for classrooms? Classrooms? What do you mean? Like teachers?
Speaker 2:Don't think want to advertise to people.
Speaker 1:Kidding. Kidding. Kidding.
Speaker 2:Anyway, the spreadsheet will become irrelevant says Bucco capital bloke. No. The spreadsheet is eternal. The spreadsheet paradigm is capitalism. The two are irrevocably intertwined.
Speaker 2:We were using spreadsheets three thousand years ago to trade oxen. We will still be using them in three thousand years. Long live the spreadsheet. And he shares a stone tablet that appears to be a spreadsheet. This is in reaction to Signal's post that Microsoft three sixty five and Google Workspace have maybe four to five years of relevance left simply because the document spreadsheet paradigm itself will become mostly irrelevant.
Speaker 2:It already makes zero sense to draft review or analyze anything without a native AI environment around it. That gap only widens over time. Most communication including email, chat, status updates is heading towards agent mediated flows where humans set intent and AI handles execution. I don't know. I mean it it is like both can be true here because you you could be in a world where if you need a spreadsheet like the code is written on the fly and instantiated like we saw ramp launch ramp sheets very very quickly and it was a very full featured product that was clearly only possible to build that so fast.
Speaker 2:Like cloning Google Sheets is is used to be insane. We had some lot cloning Slack recently.
Speaker 1:Yeah. Our our intern built like a very very convincing clone It's so crazy. In about like an hour.
Speaker 2:Yeah. Like I actually I think it was on the was it on the $200 plan? Yeah. Oh, wow. Like that's that's incredible.
Speaker 2:So yeah. Like I I I think there's still the question of like, you know, actually getting that to feature complete, maintaining it, really you know, serving it, hosting it, all of that seems like a hassle compared to just signing up on a consumption basis or a seat based basis for a lot of SaaS. I'm still sort of, you know, not a firm believer in like this near term SaaS pocalypse broadly. But it it does it does I I think the more likely scenarios that you will see you will see software instantiated on like in real time. So if you're building something and it requires a spreadsheet to visualize and you're already seeing that with a lot of the chat apps when if you ask for a deep research report or something that that requires sort of building a timeline or a chart.
Speaker 2:It can write Python. It can write HTML that will
Speaker 1:Yeah. The other the other thing is just giving giving customers a lot more flexibility around the product and thinking that like, okay, if you're buying buying a piece of software, it'd be like buying like a home. Yeah. You get the home. Yeah.
Speaker 1:And then you can make changes to it Mhmm. To fit your own needs over time.
Speaker 3:Yeah.
Speaker 1:And so we'll see we'll see what ultimately changes. But you can imagine a world where, you know, it stops being I I forget who was on the show, but they were talking about how it was it was consoleconsole.com. Yeah. Talking about how instead of having like a request a feature button, you just let people build it themselves. Yes.
Speaker 2:Well, there's been some back and forth on the timeline between Nate Silver and Nikita Beer over whether or not links are truly deboosted on X. Philippe Lemoine said after the exchange between Nate Silver and Nikita Beer, I did a little test to check whether that was true. And to my surprise, what I found suggests that link deboosting was indeed reversed. What I did was randomly sample 15 tweets by The New York Times between 2019 and today. That feels like a small sample.
Speaker 2:It feels like you should look at maybe a larger swath there. But he computed the weekly average number of likes and retweets they got and plotted the results along with a trend line. The idea is that likes and retweets are probably a decent proxy for reach and The New York Times only posts tweets with external links. So by looking at this, we should be able to see how many changes in the al any changes in the algorithm with respect to how links are treated. As you can see, it's pretty clear that starting around the 2023, posts with links started to be penalized, and eventually they were completely nuked until the 2025 when a reversal to that policy seems to have started.
Speaker 2:To be honest, this isn't what I was expecting to find. So even if it's just a quick and dirty test, it's hardly definitive proof. It's good news and I thought I'd share the results. There is a question of like even so links links, yeah, there was clearly like a deboosting moment, although some really good stuff could break through. Like there were a few examples of people just posting links to links to the, like, Google Docs basically and those would still rip somehow.
Speaker 2:And I don't know if that was like a specific link but
Speaker 1:I think one thing has remained true the entire time
Speaker 2:Yeah.
Speaker 1:Which is that that if you are linking to content that is genuinely very interesting Yeah. It can still do numbers.
Speaker 2:Yeah. And and there is a little bit of maybe some some feature of the New York Times where if you spent a year or two on acts knowing that, okay, like there's sort of this adversary relationship with links, you're gonna open in the browser, you might actually just develop a different habit of, okay, I go and read the apps. Like, I definitely develop the muscle memory to open The Wall Street Journal app regularly and scroll that news feed separately. And I don't really look for as much cross pollination as I thought. Anyway, we have Saagar and Jetty from Breaking Points in the waiting room, so we'll bring him to the TBPN.
Speaker 2:Saagar, how are doing?
Speaker 3:I'm great, guys. Thanks for having me.
Speaker 2:Thanks for coming on.
Speaker 3:Yeah.
Speaker 2:Where should let's start with the data center thing. We were talking about Jassy. Oh yeah yeah. The tie is
Speaker 1:I'm getting brutally tie mop.
Speaker 3:Yeah. Dude, Jordy gets an exit and immediately starts dressing like a tech asshole. What's what's going on here, man?
Speaker 1:I've been having I I have the limited edition
Speaker 2:Technology in motion. Okay.
Speaker 3:Well, why has nobody sent me one?
Speaker 2:How come Yeah. Are drop
Speaker 3:and see.
Speaker 2:In the works. We'll send you one.
Speaker 1:Alright. You're gonna be you're gonna get to wear TBPN all day long.
Speaker 3:Yeah.
Speaker 1:So
Speaker 2:That's great. So we were talking about Andy Jassy's twenty twenty five twenty twenty six shareholder letter. $200,000,000,000 of CapEx. Tons of new data centers coming online. Every this applies to every company.
Speaker 1:You were hoping for a bigger number,
Speaker 2:wouldn't you? Yeah.
Speaker 3:Oh, yeah. I mean, of course. As as an American, I just want all of my farmland. I want all the trailer parks pushed out, and I just wanna make sure that there's beautiful data centers, that are just sitting on previously, like, taken care of and people with generations just get kicked out. So I wanted 400,000,000,000, 600,000,000,000, something like that.
Speaker 2:Yeah. I mean, maybe we can start with the shape of the pushback against data centers because it's fallen in a few buckets. But let's just start with, like, the big one, which is energy. What are the headline numbers and fears that people are are pointing to, the case studies that people are are nervous about the energy impact specifically?
Speaker 3:Well, I think especially, guys, you know, this there's a pre Iran war conversation. There's a post Iran war conversation. I think really important to say because, you know, who knows where the price of oil will eventually stabilize. But when you have high inflation at the gas pump and likely at least some moderate increase in electricity bills, we have we don't know exactly where things are going to stabilize. You're going to have a lot more cost consciousness whenever it comes to energy.
Speaker 3:Now, especially in the midst of a data center conversation, I know that the data center pro data center people are always telling us, don't worry, it doesn't actually impact your electricity bill all that much. Nonetheless, there is a feeling there. And, John, I just sent you that study or that story this morning, which is very interesting. My colleague, Emily Jassy's talked to me about this. But there was a Wisconsin city has now been the first in the nation to actually pass an anti data center referendum.
Speaker 3:And so the ballot measure is basically the last thing that the voters in that town felt that they had at their disposal to effectively ban the entire city from approving any of these new projects. You guys remember the guy who went viral in New Jersey who blocked the data center? I interviewed him on my show. He was a longtime viewer actually of the program. He was just like a normal activist type, but hadn't really engaged with it.
Speaker 3:And he went through the zoning and he was like, look, these developers are making all kinds of promises and he was concerned about water. And I know, you know, again, the pro people are are always telling me that that's not the case. Maybe. You know, I gotta see a little bit more evidence for myself. Oh, real real quick.
Speaker 3:City council Is
Speaker 1:your your mic I I don't know that we're you're on the correct mic. We might be on
Speaker 2:the gain might be a little high. I will I will give everyone some news about this Wisconsin city passes nation's first anti data center referendum. The vote suggests ballot measures could become a powerful new tool for grassroots activists.
Speaker 1:Chat thinks it's a foreign adversary doesn't want
Speaker 2:center projects. Let let let's hear if it sounds any better now.
Speaker 3:Is it a little better or
Speaker 2:taking the
Speaker 3:game down? I think
Speaker 2:that's great. There we go. You.
Speaker 1:There we go.
Speaker 2:Amazing. Yeah. Okay. So is so is this is this what is this local Wisconsin City referendum like, the new playbook that will spread all over America? Are there other jurisdictions that are already looking to copy and paste this?
Speaker 2:How do you think this where do think this
Speaker 3:goes from? I definitely do think it will serve as a model, especially as other remember, this is really a bottom up phenomenon. So it's really at the community level. And here in the state of Virginia Yeah. Where I live, 40% of our power is actually consumed by data centers.
Speaker 3:And so you've seen organic pushback. Yeah. It became a major issue in the gubernatorial campaign. Mhmm. Both the Republican and the Democratic candidates were against data centers.
Speaker 2:Yeah.
Speaker 3:And both a lot of the candidates are seeing all of the energy. I'm sure around this, I'm saying at the community level. I'm sure you guys also have seen all of these viral videos. I referenced the one more recently of this trailer park, which is being basically told they have to go out because they're gonna build a new one. There's the famous one recently, I think it was in Kentucky, of a woman being I think she was offered like $20,000,000 for her land.
Speaker 3:She's like, I'm born on this land. Yeah. I'm gonna die on this land. So I I really think that this is one of those bubbling political issues, which no major politician maybe Bernie Sanders, the only one that I've seen which has been willing to like jump on top of it. But I think it's a major issue in 2828.
Speaker 3:I think in '28, both candidates are going to have a data center platform. Maybe the Republican one, depending on who it is, is gonna try and square the circle around GDP, but I don't think that voters want to hear anything about it. That's just my personal opinion.
Speaker 1:Is is the sense in Virginia that Virginia would would be better off if the state had never had a data center?
Speaker 3:Well, it's complicated. Remember, you know, we're full of a military industrial complex. But don't forget this. We had Amazon. Remember when they were going to leave New York and they were going to come here?
Speaker 3:They're actually going to come near where I live. It it really didn't work. And there's a lot of local op eds. They're like, hey. We didn't get all the jobs that we were promised.
Speaker 3:Virginia threw all these tax credits. And so people do feel really taken advantage of, I think, especially by Amazon here in Northern Virginia. But, look, the backbone of our economy is always gonna be the military industrial complex and all of these, like, ridiculous server farms that serve the CIA and the Pentagon. But I mean, Oregon, I think it was 30% of power in the state of Oregon is being used by data centers. It's like 20% in a few different states.
Speaker 3:Virginia is definitely we were the highest in the nation. I can tell you at the organic level, Fredericksburg, more of the rural communities where there are the new projects that were being looked at. All of those city councils, people were lining up for hours to campaign against this. Same thing in New Jersey. People lined up for you know, in the middle of the night.
Speaker 3:And I talked about this before. Guys, do you know what it takes for a voter to actually care? Can barely get people to come out for election day for the president. Now for to come up for a local meeting against zoning, usually that's just really old people this time. People are bringing their children, they're sleeping in the room, they're waiting all night just to be
Speaker 1:What is your what is your advice for the data center developers out there? Because certain certainly, I I like, you you feel
Speaker 2:Well, here Let me let
Speaker 1:let You don't think that we should just not build any data centers?
Speaker 3:It depends. You know, I I don't know. I mean, I'm becoming more radical as as times go on, and so maybe we do just need a Butlerian jihad. I'm testing the limits of your editorial independence, by the way.
Speaker 1:Shout out
Speaker 3:to you, Sam. But, I mean, look. I I'm not giving any advice, to the enemy. I I think really what I would say, to the tech community more generally, and John, you and I have talked about this. This Yeah.
Speaker 3:Just prove to me that this is gonna make my life better. Okay. And stop talking about all these scary things because I'm starting to believe you. In fact, I do believe you. Yeah.
Speaker 3:What is this new Claude news that their new model is so scary?
Speaker 2:Pack everything.
Speaker 3:They have to pre release it to the cyber security companies so that they can develop so no. No. So that the new model can develop defenses against itself every day.
Speaker 1:Everybody's with you that the fear based marketing like needs to stop because it's not it's not helping anyone. Yeah. Part of the whole back
Speaker 3:I mean, Jordy, you have always made the case. And maybe you're right. Is that that's a great way to fundraise. Every time the company that bought you wants more money, they have
Speaker 4:to go and be like, look,
Speaker 3:we're changing the world. We're gonna destroy all these shops. I'm like, I don't know. I mean, for for let's say like with Anthropic. Feel like
Speaker 1:people my point my point was that it was very effective when there was no revenue in the industry. Right?
Speaker 3:Yeah.
Speaker 1:And and and it was kind of this kind of far out idea. Nobody had had like a magical experience with AI. They hadn't had like a question. Didn't have anyone to ask it to and then asked AI the question. They got a good answer.
Speaker 1:Like when when when the average American had not had a very cool experience with AI, they hadn't generated an image that was, you know, photo real or gotten help with their homework or help with, you writing. Any any of these things that like now everybody's had the experience of, I it clearly like was necessary to kind of marshal enough capital for bunch of upstarts to be able to compete with the biggest companies in the world on this, like the the Googles of the world. And I just think at this point, I made the case, like, you know, at the end of last year where it was like, we need to stop we need I I think we need to stop this as as an industry because why would why would average American be excited about this if you're just trying to give them, you know, Terminator nightmares? Yeah. But clearly, the entire you know, some people in the industry still feel like they need to
Speaker 2:because I think they really believe it.
Speaker 1:Yeah. Yeah. No. I
Speaker 3:think believe it. That's I'm with John. Like, I feel like Dario believes it. Yeah. And he just goes on every podcast in the world and says it like over and over again.
Speaker 3:At a certain point, especially like with the new Claude news, I'm like, dude, maybe I should just believe you. And, you know, people what is it? People are taking leaves of absences because they're afraid. And Yeah. I mean, you know, you can only call yourself the new digital god so many times before look, I get and I'm a Luddite.
Speaker 3:Yeah. I I don't know a ton about the technology. I listen to smart people like you guys and many others to try and figure out what's going on. But if anything, I just wanna be able to convey to the people who watch this show. You're not very popular right now, and especially in the midst of a global energy crunch.
Speaker 3:Yeah. I would just be real careful about strolling around town and talking about how it's gonna bring jobs in because a, nobody believes you. They all think that their bills are going to go higher. There needs to be I I think what this really needs, guys, is I don't think it could be solved at the federal level or sorry, at the company level. I think the government is going to have to step in and genuinely, like, codify, let's say, the executive order that Trump wanted to put in place where every data center project is gonna have to supply the initial the amount of energy that it's going to use.
Speaker 3:It'd have to prove it to the local city council, to the state, to the feds. Like, there needs to be genuine democratic buy in if we're all gonna decide, like, this is cool for us. Yeah. And I'm not sure that I'm not sure really that the tech companies are ready for that. Although, maybe Sam is you guys saw his new social contract.
Speaker 3:Yeah. I I was about I was gonna do a segment about it on my show, but I didn't have I didn't have a chance because of this entire Iran war thing. But I mean, look. I mean, clearly, he's he can foresee what the problem is. Yeah.
Speaker 3:I don't really agree with some of the stuff he laid out, but yeah. Anyways.
Speaker 1:Yeah. It was notable. So Demis had an interview with with Harry Stebbings
Speaker 3:Mhmm.
Speaker 1:This week. It's just thirty minutes. You you would probably appreciate it because Demis is, you know, one one of the the godfathers. And he even was kind of talking about potentially, you know, one solution to this is like sovereign wealth funds Mhmm. Like investing in the labs, getting a piece of it so that every sort of citizen benefits.
Speaker 1:I thought that was notable because it was, you know, Google and and you know, the Gemini team is most heavily funded lab in in the entire world. And so we'll we'll see how this stuff works out.
Speaker 2:On the data center.
Speaker 1:In in Virginia, Tyler Tyler on our team just dropped a a truth nuke. He said in some localities in Virginia, 31% of total local tax revenue is from data centers. Is there is there like, do you think that like like, I guess, like, part of what I'm trying to wrap my head around is, it seems like there are plenty of places in The United States where that, putting a data center somewhere that would generate a huge amount of of of local tax revenue would be a net positive. Right? That you're right that that individual areas should be able to decide.
Speaker 1:Is this an industry that we wanna support? Is this an industry that we want as a part of like Personally, do I want, you know, people, you know, drilling oil like, you know, 10 feet from my property line? Like, probably not. Right? Right.
Speaker 1:But there are places in The United States where people have decided we're gonna drill for oil here. And and we're gonna, you know, be okay with those trade offs. And so I think I I I generally you know, I I've said this before. I think there's a lot of reasons for somebody to like, citizens need to understand, okay, what is the benefit of putting this data center in our county, in our town? And it and it needs to be it needs to be there needs to be some positive benefit other that for for the local community.
Speaker 1:And so I think we agree there.
Speaker 2:Be using the models Totally. Because the data center could be halfway around the world or
Speaker 1:in you still get access to all the AI tools that you want. Doesn't need to be in your backyard. Yeah. And so Yeah. I I
Speaker 3:believe that To Tyler. Yeah. To who's in the chat. Please. I mean, I I do think though that that tax argument the problem is that largely, again, I'm speaking from a voter level, is they do not feel either that impact or that they often like with the Amazon, you know, example that I gave you is that we give these tax credits away, and then the promise is a lot of these things don't end up happening.
Speaker 3:Come on. Yeah. This is a tale as old as time. Yeah. Every state in the country remember when Amazon did that ridiculous pony show for every state to throw whatever it could to them?
Speaker 3:And they ended up yeah. For h q two. That's the project I'm talking about. Yeah. Is that Virginia, where I live, also did that.
Speaker 3:And then, of course, you know, local politicians feel very burned, and a lot of the voters do as well. But ultimately, Jordi, I don't think we're disagreeing, man. Like, local control is really what it's all about.
Speaker 1:That's what I'm saying.
Speaker 3:Okay. And and I also think the feds, though, I do think that, you know, considering the way that Trump and the AI industry are so like, they really do need each other just because of the way especially now after Iran. My God. Can you imagine? You know, like, look at how much he's he's reacted to market swings.
Speaker 3:One of the fears that I had really was that a lot of this know, you're talking about sovereign wealth funds. John, you and I know the amount of Gulf money sloshing around Silicon Valley. I'm like, guys, like, we're about to see force majeure just get declared. I mean, if you see even 10% go down from QIA, SIA,
Speaker 2:or Yeah.
Speaker 3:Any of these other investment funds, you're like, that's like an extinction level event for a lot of these or they might reallocate. They might start funding all these defense tech companies and not investing in data centers. And don't forget that an Amazon data center was struck by Iran in The UAE. That's right. I believe.
Speaker 3:Yeah. A couple of different tech infrastructure places were explicitly declared war on by the Iranians. So I I do think that there's an element here where what we're What we are watching play out, I think, politically, and even geopolitically, is that foreign adversaries can see clearly that this is a potential pain spot for The US economy. Here in The US, the administration is really aware of this. But there's also just this rising kind of populist tide against the data center movement and against, I think, really like abundance style assurances from politicians and from companies that after forty years now mean, before data centers, it was Walmart.
Speaker 3:And before that, it was something else. There's always gonna be like a small guy versus a big guy feeling, especially in rural parts of the country. And, you know, I'm from Texas, Geordie, with the oil industry. So I I get exactly what you're talking about. Right?
Speaker 3:Like, there's a symbiosis of we actually get rich off this stuff, so we're okay with drilling for oil. But, you know, there has been enough stories also even there where people go bust as a result, and then there's a lot of animosity towards the oil industry, especially pre shale revolution after things petered out. And, you know, I don't know. I've I've just seen this go politically in a lot of interesting directions enough to see that, a, something is happening. B, is that the tide is not only just turned, but I think coming very explicitly.
Speaker 3:And if what I would really advocate for is a genuine democratic process because that's what it's all about. Like, people just feel like this is out of their control. About AI Yeah. Especially. They're like, I want impact.
Speaker 3:I want a say. And I don't think they're wrong to say.
Speaker 2:I really don't. Flow for for getting some sort of resolution on the federal level, is that like a new bill or something? Or, like, after the midterms, but then Yeah. And it's gonna try and tie a bunch of these different questions in a bow around safety and cybersecurity and data center build outs. Like, is there is there a world where the like, a good data center exists in the sense that it supplies its own power with clean energy?
Speaker 2:It's not an eyesore. It's either buried or covered in trees or beautifully designed, and it doesn't have any environmental impacts. Like, is there is there a world where someone could get behind a data center at that level?
Speaker 3:Yeah. Absolutely. You know, and that's kind of the thing. Why are we just talking about data centers? I've talked about this before.
Speaker 3:I read once a report of a guy who just came from China.
Speaker 2:Yeah.
Speaker 3:And he said nobody in China cares about power with data centers because they serve
Speaker 2:a ton of power. I was like,
Speaker 3:we have energy, dude. He's like, bro, we don't care. He's like, yeah, you can build you can build a data center. We're good. Like, have cheap and abundant power.
Speaker 3:So if we have cheap abundant power all over the nation, no one will care either just about data centers, especially if we have, you know, cheap electricity, if there's just if there's no concern
Speaker 2:Yeah.
Speaker 3:On the power generation level, and this is why, you know, I'm a huge advocate of nuclear power plants or whatever, renewables. I I don't even care
Speaker 2:Yeah.
Speaker 3:At this point. Shale gas has put it all in together. But I actually think our grid and the delay of our grid and and really just the knowledge right now, we're not investing a lot more into it. It doesn't seem like things are propelling. That's what makes it a zero sum game.
Speaker 3:It doesn't need to be this way. Like, really, what we need is just a ton of power. We have a ton of power, then we don't care about anything being built.
Speaker 2:Yeah. So is is codifying the ratepayer protection pledge into law a good move?
Speaker 3:It would be a good move, but I don't think it's enough at this point. There's so much distrust, guys, like, at the local level and on the political level. I I recommend you follow Ryan Gerdusky. Okay. He's done some more recent work on the data center question.
Speaker 3:He's been talking about this. He's like, guys, this is just laying out there for any politician to pick up. And I'm talking about it from an anti data center position. He's much more of an expert on polling than I am. Go and check out his feed and some of the work that he's done, especially not just on feelings against AI, but data centers.
Speaker 3:Because he I think he crunched the numbers. I know it was within the last couple of weeks that he looked at the question, and he just said there's an overwhelming animus and that people are angry. So it's not just again, let's be very clear. It's about a feeling of lack of control over, you you're coming to take my job, you're increasing my electricity, you're changing my nation, And I have to have a say as a citizen. So that's not just no longer about electricity.
Speaker 3:That's about the whole picture
Speaker 2:Yep.
Speaker 3:Of like technology and oligarchy and the economy. So you're fighting against a very, very big force right now in the country.
Speaker 2:Yeah. No. It makes a ton of sense. Thank you for coming on and breaking it down. I'm sure we will be talking about this
Speaker 1:you have you tried have you tried just out of curiosity to just not use any AI? I mean, it's impossible to not use AI now because every company for the most part is using it. But have you tried to do your own personal like pause just for like a
Speaker 3:few I should try. You should try. Idea.
Speaker 1:I want the you should let's get you back on the schedule for a few weeks from now and Pause AI. Pause your own You will not use any AI at all until you're new
Speaker 3:to Guys, it'd be so hard because even the chessboard behind me has built in AI. What? It's everywhere. Yeah. It's got the built in It's got the chessboard.
Speaker 3:No.
Speaker 1:It's fine.
Speaker 2:You can just no.
Speaker 1:Just don't play chess, bro. Yeah.
Speaker 3:It's fine. No. I can't
Speaker 9:do it.
Speaker 4:I can't
Speaker 1:do get a just get an old school board. You're you're fine.
Speaker 3:I've been one shotted by the game. This is I've been completely one shotted by game. Anyway,
Speaker 2:yeah, that's Thank you probably so much for coming on. We'll talk to you soon, Saagar.
Speaker 7:Great to see you. Appreciate it.
Speaker 2:You're always helpful. We'll talk Up to you next, we have Joe Weisenthal from Bloomberg and Odd Lots here to to break down the New York Times analysis of the strongest Satoshi Nakamoto candidate. Joe, how are you doing?
Speaker 1:Look at this.
Speaker 4:I'm good.
Speaker 1:Look at that sweater.
Speaker 4:Yeah. What do you think?
Speaker 2:You look the green
Speaker 4:You think the green green
Speaker 2:hair. Green is great.
Speaker 1:Coming out the top.
Speaker 4:That's actually what I meant. I when I said, what do you think? I was like, oh, actually I'm wearing TBPN green for you guys. Exactly. So Yes.
Speaker 4:You guys noticed the gesture. Well, welcome back. Nice to see you guys.
Speaker 1:Congratulations. Is the New York Times the most underrated company in the Yeah.
Speaker 4:Of course. It's the it's the most Of course. It's the most underrated tech company and the most underrated news Gaming. The number of haters
Speaker 3:Yeah.
Speaker 4:That the and an under the thing though is to be fair, that's the hater comment. Like, it's just a gaming company. But look, like it's extraordinary juggernaut of both tech and news and so many people have some sort of criticism of it or whatever and find a reason to hate it
Speaker 2:and Yeah. Yeah.
Speaker 4:Everyone can find good reasons to complain about the media. But it keeps on winning in ways that I've certainly been very surprised about. So Yeah. I was really excited. I know a topic at hand.
Speaker 4:I This is one of my favorite Satoshiology is like one of my favorite topics. I was super excited to see that they took a stab at finding out who it is.
Speaker 2:Did you have a candidate in mind before this piece dropped? Had you watched the HBO documentary that actually pointed to a different suspect?
Speaker 4:Yeah. I've read a lot. I actually didn't watch the HBO documentary in in part, I guess, because it was just so heavily criticized Yep. Etcetera. They're like, maybe I don't need to watch it.
Speaker 4:I had often often found the the Nick Szabo. Yeah. He's one of the candidates. I had
Speaker 1:heard of him.
Speaker 4:I had always found that one to be fairly compelling.
Speaker 2:Yeah. Me too.
Speaker 4:And, you know, on my first read of the New York Times piece yesterday, I thought it was I about Adam Back, like, knew he had been in the mix.
Speaker 2:Yep.
Speaker 4:It struck me that most, you know, the piece didn't have a smoking gun. Right? And that's sort of what we're all waiting for. We want that smoking gun, whether it's some sort of digital signature Yep. Or an email.
Speaker 4:It didn't have that. It was sort of ling a lot of it was sort of linguistics, like, oh, he makes it's and it's wrong or hyphens wrong. I make those same mistakes too. I don't know. Everyone everyone makes those mistakes.
Speaker 4:So I wasn't totally convinced. Yeah. But then I read it a couple of more times over the last, you know, twenty four hours. I read it again right before I came on this because I wanted to be prepared to chat with you guys. And I am like I've been, like, upgrading my odds that
Speaker 2:That it is going bad.
Speaker 4:John Kerry, who has correctly has correctly identified him.
Speaker 2:Yeah. What what have you worked with any journalists like John Kerry Rue before? It feels like such a lost art, and it's so delightful when someone has a chance to it seems like this was reported for a year or more. Like, he really he had the space breathing room.
Speaker 4:No. I I love it. And I like I said, whether this is right or wrong, it's one of my favorite topics. And it is one of these things where, like, over the years, you know, a handful of journalists have like, I can be the one to crack this, which actually like brings to my mind one of the more fascinating aspects of Bitcoin period Yeah. Which is it's amazing to think that like, okay, here is this thing, it's kind of like a digital gold and so forth.
Speaker 4:It's a new kind of money. And whoever Satoshi is, he or her group of people, whatever, maybe it is add them back, maybe it's not. But the op sec I mean, can you even fathom being online for several years in a way that could not be traced back to you definitively. It's incredible. Know where to begin.
Speaker 4:Yeah. I wouldn't even know where to begin Yeah. How to, like, interact online in a way that, like, I could ensure my anonymity. And I think one of the fascinating things about Bitcoin is that it does have, this founder creator myth, this sort of this sort of the divine the divine birth by this entity that left no earth almost no earthly trace
Speaker 2:Yeah.
Speaker 4:Is is much as a fascinating part of the story almost as Bitcoin itself as a technical accomplishment.
Speaker 2:Yeah. And also just the fact that then Satoshi even like, it wasn't an effort to remain anonymous in perpetuity. Yeah. It was like then Satoshi went dark and and nothing's moved on the wallet and it's just been this like, you know, that that that's obviously fueled the theory that that potentially Satoshi passed away or something.
Speaker 4:So the question so here's a question that I have. So one of the stronger arguments Mhmm. Or one of the pieces of evidence that the article in the New York Times points out is that Adam Back, it's well known, he has a long history with the cypherpunks. He'd been interested in privacy and digital money for a long time going back to at least like the mid nineties, etcetera. He had invented hashcash which was, you know, which basically laid the foundation for proof of work, which of course is elemental to mining.
Speaker 4:So he was like right there. Now one of the arguments that the piece makes is Adam Back, like, disappeared, didn't have much of a digital trace of those first couple of years when Bitcoin was taking off. So maybe that was when he had slipped into Satoshi mode. Yep. On the other hand, there was no way that anyone in 2008 or 2009 or 2007 could have known really what a gigantic phenomenon Bitcoin was going to be.
Speaker 4:Mhmm. Why, you know, like, Adam Back clearly was very comfortable talking about many of his projects under his own name. He talked about Hashcash. All of these people had been talking about their work in applied cryptography for years under their own name. Yeah.
Speaker 4:So have not having been able to know how big of a deal Bitcoin was going to be, why would this particular project suddenly oh, he would like have the foresight to like, oh, I have to be pseudonymous for this particular project. I don't totally understand why someone who had like talked about digital money digital money for years under his real name would have had reason to think, okay, with this project, I'm gonna have to talk pseudonymously or anonymously. That is not entirely obvious to me.
Speaker 2:Yeah. Yeah.
Speaker 4:Like, again, in retrospect, like, sure. In 2026, we can look back. Yes. It makes a lot of sense that this person would have, like, the pseudonym aspect. But when it's just a bunch of people
Speaker 2:I don't know.
Speaker 1:Part of
Speaker 4:a community trying to solve the problem of p two p payments Yeah. Who have been using their names, Why suddenly, like, when this these pieces come together this way, would the creator feel impelled to be private in a way that they didn't feel impelled to be private with all the other b cash, hash cash, digital gold, etcetera. That's not totally obvious to me.
Speaker 1:Well, way that mean, the way you're talking about it is that Yeah. I'm becoming more suspect
Speaker 2:that it
Speaker 1:would impact you. No. Yeah.
Speaker 4:Well, so here so this is a yeah. Wait. John, what it sounds like you you don't find this component.
Speaker 2:No. I yeah. I I I just I I feel like after watching a number of projects sort of sputter where they did have a specific founder that could be just not even attacked but just like the the motivations of that individual could be questioned and and there's so much like risk tied to like a single person. It doesn't strike me as that I mean clearly someone went anonymous. Right?
Speaker 1:Yeah. One exercise is like, is there a person that if if if it came out and we could determine that it was entirely factual that this one person who who is the kind of person that that would make the Bitcoin sort of trade up in value? Right? No. Because there's like Yeah.
Speaker 1:I can't really think of anyone. I can think No. No. Lot of different groups that it would trade down Totally. Dramatically.
Speaker 1:Comes out Yeah. Totally. Oh, it's some government entity, you know. You know, that that that goes down dramatically.
Speaker 2:Yeah.
Speaker 1:And so there's not a there's not a lot of, like, ROI for anyone on a personal level. Yeah. They're
Speaker 10:if they're
Speaker 4:older funny things so one of the funny things about Adam specifically, so you go to, like, his Twitter profile, it says, you know, it lists his accomplishments and it says he is the inventor of hashcash hashcash in parentheses bitcoin mining. And it what's funny is many people over the years have actually accused Adam of overstating what his claim there is. So yes, there's clearly a lot of overlap between hashcash and the notion of proof of work that was elemental to how Bitcoin mining worked. But hashcash itself is not Bitcoin mining. Mhmm.
Speaker 4:It is a sort of a thing that proceed it was one of the antecedents or the proceed whatever to Bitcoin mining, a similar technique, the whole proof of work concept. Mhmm. So there's been this claim that actually one of his issues is that he overstated his invention Oh. On the creation of Bitcoin, which is very funny, like, if the if it turns out it's him that for a long time the accusation is that he over overplayed
Speaker 2:Yeah.
Speaker 4:His role. And then the other thing that's strange is that, like, since, you know, he's had like, so and this this is mentioned in the New York Times piece, he was one of the guys who last year or whatever, launched one of these Bitcoin treasury companies. Right? Like a micro strategy like entity that was just gonna hold a lot of Bitcoin. And does that sound like something Satoshi and Akamoto would do?
Speaker 4:In my opinion, not really. But then the flip side is, well, that's like the best OPSEC in the world. Do a bunch of
Speaker 3:stuff that
Speaker 4:feels a little bit scammy, feels a little bit cheesy, feels a little bit like opportunistic. Broke.
Speaker 1:There's no way there's no way there's no way he's got, you know, the tens of billions of dollars.
Speaker 4:Yeah. That's what I'm saying. So it's like on the first pass, I was like, no. Like, Satoshi is not gonna, like, launch a little, like, mini me micro strategy company. Yeah.
Speaker 4:This does not seem very likely. But then the flip side is, man, if you were someone who, like, maybe some suspect of being Satoshi Yeah. What would be the thing that would be the least Satoshi like thing to do? Yeah. And throw people like
Speaker 6:treasury.
Speaker 4:Maybe it would be, like, create a Bitcoin treasury company.
Speaker 6:Yeah. Or if
Speaker 2:you were Satoshi, but you lost the keys in some sort of silly mishap, then you would wanna get back in the game because you're still a believer, but you don't have access.
Speaker 4:Yeah. Anyway, last question. Yeah. Yeah.
Speaker 2:Sure. Yeah. Last question on the on the Bitcoin thing. Did you ever go down the Paul Larue route? And did you ever were you ever a Paul Larue believer?
Speaker 3:I was really convinced.
Speaker 4:Paul Larue guy. Which one was that?
Speaker 2:So he he was a former criminal cartel boss, informant to the USD drug enforcement agency. He created TrueCrypt and was really early in basically spamming, like, the classic email spam of, like, you know, mail enhancement. He would spam that out, scam everyone. He became so deeply entrenched that at one point, he didn't just own a, like, domain name and he would switch the URL. He owned a TLD or like a registrar so that no one could kick him off and he could create unlimited new websites.
Speaker 2:That's pretty funny. So he would just create a new website every day and so the Gmail filters would get confused because, well, we've never seen this one before. I love that. The thing
Speaker 4:is, I've always thought, like, that I I don't know if any of you ever read it, but there's an amazing book by an NYU professor, Finn Brunton, called I think it's called Digital Money.
Speaker 2:Okay.
Speaker 4:And it's about the prehistory of Bitcoin. So it's about this community of the cypherpunks in the nineties and eighties, and actually even going back to the nineteen seventies
Speaker 2:Yeah.
Speaker 4:Where people were talking about this fact that as the world was gonna go online, it would be very difficult for me to send you a payment without the need for like a third party database. The idea of like we need something that's cash like a bearer instrument
Speaker 2:Yeah.
Speaker 4:On the Internet. Yeah. And I think this is like a really important thing to know is that there have been there was a small group of people that basically for three decades or more before Bitcoin had been trying to solve this problem. And so like in the the New York Times piece, it points out that Bak had been talking about all of these things that Satoshi had been talking about. And my first response is, yes.
Speaker 2:Were a lot of people.
Speaker 4:Of course, they did because this was this core group of people Yep. Who for years understood that in the online context, if if payments were ever gonna be a thing, we would need a third party. And if there's a third party, they can block a transaction, they can reverse a transaction, can penalize you for making a bad transaction, etcetera. And so this was understood by some people from day one of the you know, pre Internet that this would become an issue. And so I'm not surprised Yeah.
Speaker 4:That they were all using roughly the same analogies and so forth.
Speaker 2:Yeah. The book is digital cash, the unknown history of anarchists, utopians, and technologists who created cryptocurrency. And I will recommend a book to you about Please. Paul Larue about Paul Larue. I think it's called the mastermind.
Speaker 2:And I believe it was optioned into a movie. I'm not sure. I think Michael Mann was gonna do it, and that would that sounded really good, but the book is fantastic. Anyway,
Speaker 4:is That was really fun.
Speaker 2:Has this been like a like a nice reprieve for you from covering the war? How have you been processing the the constant gyrations in the oil market and the broader financial market? It it feels like such a hard Yeah. Thing to cover, but, obviously, you've been doing a great job with Odd Lots and beyond.
Speaker 4:Thank you. The stakes are I mean, it is a hard thing to cover. It's an awful thing to cover. Right? It's a war and wars are awful and the stakes are so you know, there are so many ways that wars can get more as catastrophic as they are, get even more and more catastrophic.
Speaker 2:Yeah.
Speaker 4:So it's like, you know, it's a but it but it's also like an extraordinary story for the things that we like to cover which is like understanding the real flows of the economy and you know, prior to this war, I had not fully appreciated essentially, just like how I mean, I knew about for oil, I was aware that the Strait Of Hormuz was a very big deal.
Speaker 7:Yeah.
Speaker 4:But, like, the degree to the fallout, whether we're talking about fertilizer Yeah. Whether we're talking about Real estate
Speaker 1:in real estate in Dubai. You guys had a great
Speaker 4:Real estate in Dubai.
Speaker 2:Yeah. Was crazy.
Speaker 4:Which real estate in Dubai, which, you know, we probably you guys probably know more people than myself. It's a camping out to Dubai for the low taxes and stability, and then suddenly, you know, you're like, oh, this could be
Speaker 1:Honestly, credit credit to Americans, like, has just not been that popular.
Speaker 2:I think it's different. I think I think it's more of a European thing.
Speaker 1:It's very much, yeah, European thing. When when I was out there, I mean, it very much is like a melting pot. I've been there a couple times and very limited number of Americans and the American the Americans that are there for the most part aside from on, like, you know, scheduled, you know Yeah. Yeah. Fundraising trips are not really in the same type of, like They're not.
Speaker 1:Business community that that you and I are in.
Speaker 4:Yeah. It does seem like a more of, like, a British thing specifically in terms, like, oh, going there for the low taxes or the stability, etcetera. But, yeah, like, all of these things getting upended or this specific not just oil and gas that, yes, that goes out of the Strait Of Hormuz, obviously. But then, like, this specific acuity than pain points that are being felt in Asia specifically and how they're already having to go into sort of like a nineteen seventies rationing mode where you see these headlines about if you have you know, if your license plate ends with an odd number, then you can drive on this date. I mean, the economic reverberation I mean, it's clearly the biggest sort of global econ story since COVID.
Speaker 2:Yeah. I was reading this article in the in The Economist this weekend in Buttonwood about how it feels like the market is not actually able to process what a 20% decrease in in No. In oil rates And it feels like I don't know if that's just like hope that there will be a taco, that there will be a quick resolution. But the the the key stat that they were latching onto was that even if the everything was world peace tomorrow, just bringing resources and infrastructure back online, just starting the flow and moving the ships again takes, you know, three months, six months, and so you will see reverberations through the economy for for months, if not years, even if, you know, we get a good outcome immediately, which is what we're all
Speaker 10:hoping for.
Speaker 4:Yeah. Some sort of benign outcome. Yeah. But, like, the but the this is the weird thing to and you're you're spot on, and this is the weird thing, which is that if you talk to the commodity guys Yeah. They're like, this is unbelievable.
Speaker 4:This is like a scenario that we couldn't even really have contemplated. And then you look at the stock mark and, you know, oil is up a lot. It's not like oil oil markets are not registering. It's up a lot, but but then you look at the stock market and it's flat on the year. Like, as of the time I or it's like down point 3%.
Speaker 4:Yeah. I mean, it's stunning because you have to remember that even, like, the last thing we were all talking about prior to the war was like, oh, every legacy business model in the world is going to zero because AI is getting so good. So that was the first two months of the year. Yeah. And then the third month of the year is this war that massively shoots up the price of oil, kind of like takes the prospect of rate cuts off the table, and we're looking at a market that's flat on the year.
Speaker 4:Like, it's really like, you know, I try to I'm sort of an EMH guy, and so I was thinking if I'm missing something, just trust the market. Yep. It's very strange.
Speaker 3:It is.
Speaker 4:You know? Very strange.
Speaker 2:It is very strange. Have you have you found any particular corners of the economy that are serving as white pills these days? Because it feels like a year ago, things were sort of it was there was there was political chaos. We were talking about the tariffs and whatnot. But it felt like in broadly most industries were sort of seeing reasonable advances.
Speaker 2:Things were much less controversial Yeah. And we're in a much more tumultuous time.
Speaker 4:I mean, I it's hard to it's hard to disagree with that. I mean, I think that there's basically I think most people say there's basically two parts of the economy that are growing, and one is anything related to AI and data centers, etcetera, obviously. And the other is like
Speaker 8:Health care.
Speaker 4:Home health care jobs, and I don't think much has, changed on that front. And unfortunately, like, okay. Like, again, let's just go back to the world of February 26 before the strikes had begun. You know, we the issue was we were already still at that point well above target for the Fed's inflation.
Speaker 7:Now there's
Speaker 4:no reason to think maybe it's trending down, maybe we have some softening, etcetera. But even with just essentially two cylinders out of I don't know if the cylinders analogy is great because
Speaker 3:I don't
Speaker 4:know how many cylinders. But two cylinders really firing, like, okay, on some ongoing need to, like, provide people health care and then AI. Even with that, the economy was, like, under a certain level of, like, with price stress. Yeah.
Speaker 2:Yeah.
Speaker 4:And so then you add in, okay, now, like, all forms of commodities are gonna be more expensive. They're spending, of course. Wars are very costly from an expenditure perspective. And so where does that leave the rest of the economy that is not AI or health care? I have yet to see don't know.
Speaker 4:I'm certainly not feeling white pilled. To the extent maybe the the closest is like, look, I would say there there I there there's still evidence a little bit out there that, for example, that we're not seeing the evisceration of tech and software jobs the way some people might have anticipated. And Yeah. There continues to be, like, evidence, like, oh, actually, like, that sort of, like, the the economist optimism that maybe AI will create demand for software engineers because there are more things that can be softwareized. I actually think maybe that's looking okay, that thesis.
Speaker 2:Yeah.
Speaker 4:And so it's white pilling in the sense maybe we don't have, like, the totally evisceration of the sort of the labor market
Speaker 2:Yeah.
Speaker 4:Like that part. Totally. We actually got a good jobs report last week on the GoodFire report. So, like, I are things
Speaker 1:And we and we trust all the jobs reports now. We could definitely lean on.
Speaker 2:The revisions have been a little tumultuous for me.
Speaker 4:There have been a lot of revisions. It's very tough to measure the economy, but I I I salute our brave stat statisticians at the Bureau of Labor Services.
Speaker 2:And we did and we did talk to some other folks who were looking at, like, private market data, payroll data. Yeah. And and and there there were green shoots there as well. So I Yeah. Yeah.
Speaker 2:I'd be I'm optimistic that that holds. Yeah. I've heard I've heard the most optimistic take about just more companies building more new things. We've built a bunch of internal tools here. The actual, like, NPS score for most AI apps is actually very high even though AI as a concept pulls very poorly.
Speaker 2:So there's this there's this
Speaker 1:Oh, yeah.
Speaker 2:Difference there.
Speaker 4:What does NPS stand for?
Speaker 2:Net promoter score or, like, approvals approval rating. So, like, people might give ChatGPT directly, like, an 80% approval rating, and it has, like, a lot of it has a lot of good reviews in the App Store, for example. And if you just ask them about that or or what they're building with Clogged Code, they'll say, oh, it'll tell you an amazing story of some custom software that they built for their business that they would have had to spend a million dollars on a consulting group to do it, and it maybe would have been really tricky to get it to math out. Yeah. But then they'll just tell you, like, oh, yeah.
Speaker 2:We needed this dashboard, we just made it in a day or or or a couple weeks of the
Speaker 4:So people love their specific things they built, and but then it's like,
Speaker 2:but also abstract. Terrible. Yeah. They hit
Speaker 4:the abstract. Yeah. No. I mean, look. I mean, I think this is actually seems to be a recurring phenomenon.
Speaker 4:People have even, over the last several years, to some extent, said this about the economy generally.
Speaker 3:Oh, shit.
Speaker 4:I'm doing okay. Yeah. I my financial situation is actually fine. Yeah. But the economy is, like, really terrible.
Speaker 2:Yeah.
Speaker 3:So it
Speaker 4:would be kinda interesting, like, if maybe there was a pattern that we're seeing across domains where, you know, everything else sounds yeah. I like AI. I like how it's doing. I like this thing I built, etcetera. It's all terrible.
Speaker 4:Maybe that's just sort of, like, a general disposition that people have towards a lot
Speaker 2:of things. Yeah. It's the Kyla Scanlon vibe session concept.
Speaker 4:And maybe it's they're happy in their Media. Happy or they're happy in their relationships, but they're like, oh, but dating ever for everyone else is a total wasteland for everyone.
Speaker 1:Totally. Totally. Jordan, last actually
Speaker 4:kind of a thing these days.
Speaker 1:Yeah. Last question. Any prediction market predictions from your side? What do think, Sam?
Speaker 4:We had an episode out to we have an episode out today with Oh, cool. Tomas Pederffy, the founder of IBKR
Speaker 3:Oh, yeah.
Speaker 4:Which is also one of the most impressive impressive trading entrepreneur. They're getting prediction mark they're really getting into prediction markets. So I think my prediction is that it's not just gonna be like a two entity race for that much longer. I think, like, I think as it gets bigger, there's probably too much money to be left on the table for it to just be these two companies that most people have never heard of up until, a year ago.
Speaker 2:Yeah. No. Makes a ton of sense. Well, thank you so much for taking the time to
Speaker 10:come chat
Speaker 6:with us.
Speaker 4:To see
Speaker 1:you, Jeff.
Speaker 4:Take care.
Speaker 2:Thank you. We'll talk to you soon. Cheers. Our next guest is Andrew Dye from Elorian. He's the co founder and CEO with a big raise coming in to the TBPN of Trador.
Speaker 2:Let's bring in Andrew from the waiting room. Andrew, how are you doing?
Speaker 11:Hi. Good. Thanks.
Speaker 2:Thanks so much for taking time join I would love to hear a little bit about your background. Maybe we should start even before Google Brain and DeepMind. What was your academic track like going into tech?
Speaker 11:Yeah. So I grew up in The UK. I lived in Manchester and Sunderland and London all across following my dad's work. And then ended up in London, did my high school there. I went to the University of Cambridge for computer science, and then I went to the University of Edinburgh for my PhD in AI.
Speaker 2:And what did you work on when you were at Google?
Speaker 11:At Google, I worked on a whole bunch of things. I worked on Google Now. I worked on Smart Reply and Smart Compose. Oh, wow. But really, I had a paper about twelve years ago where we proposed language model pre training as well And as that's the paper that all the GPT papers cite and Wow.
Speaker 1:Here we are today. Turned out to be a big deal.
Speaker 2:Yeah. Yeah. Did did the Wait. Wait. Yeah.
Speaker 2:Sorry. I
Speaker 1:I don't know I don't know if you're gonna dig in deeper there but but at the time when you were writing that, how much conviction did you have around paradigm? Did you expect
Speaker 2:And scaling laws in particular.
Speaker 11:Yeah. I knew it was going to be something big. Yeah. And I could tell because when I was giving my poster at NeurIPS that year, one of the inventors of, like, LSTMs, which was the biggest Yeah. Model at that time, they said, it just works.
Speaker 11:Like, the method just works. Then I could tell, oh, yeah, there's something something happening here, but I never imagined it would get to this scale. And I never imagined I'd be doing it for more than a decade.
Speaker 2:Yeah. So Did
Speaker 1:you go to NeurIPS this last year?
Speaker 11:Yeah. Yeah, I did. Has it changed?
Speaker 1:How has it changed?
Speaker 11:It's all now. A lot of language. And VC's?
Speaker 1:Lot of VC's sneaking around Yes.
Speaker 11:Lot of VC's. That's right.
Speaker 2:Well then, yeah, take us through the the this company to decide to launch the decision to launch this company, what you're thinking needs to be different about the current strategies employed by AI Labs.
Speaker 11:Yeah. So our company is built around visual reasoning as a first class citizen, multimodal reasoning. So looking at all the labs, you see there's a lot of focus on text, on language. Yeah. That's been very effective.
Speaker 11:Right? We have new paradigms in cybersecurity right now. Yeah. But the visual capabilities are kind of getting left behind. Mhmm.
Speaker 11:And there you have problems where the models are on visual problems at the level of like a preschooler of like a three year old.
Speaker 2:You give me
Speaker 11:an Yeah. Example of
Speaker 2:What does that look like in practice?
Speaker 11:Yeah. So in practice, you can tell these models to generate a pool table and they will make a perfectly good looking pool table. Right? But if you ask them to count the number of bowls on the table or count the number of bottles in the bar, then they will just hallucinate. They'll be off sometimes by a large amount.
Speaker 2:Yeah. So I I've seen sometimes the reasoning models will ingest an image and then wind up writing a bunch of, like, Python code to basically, like, count pixels and do things, like, very much not the way I would imagine the way a normal human would process counting something. At one point, I was asking to estimate the height of a desk, and it was, you know, writing all this math to to to to sort of manually try and understand the size of things, which we meant it was a reasonable approach. It wound up just being a normal sized table, which was sort of underwhelming. But how are you thinking about the actual development, what you want to do differently?
Speaker 2:Are you focused more on a new architecture, new data sources, more scale? What's the shape of your strategy here?
Speaker 11:Yeah. So we are basically a full stack team. We have experience with pre training and data, So multi we are essentially building specialized models that includes new architectures for visual reasoning, very specialized sets of data with specialized data processing and new algorithms. Expect to be running the full gamut of changes, and this is really needed to really make a breakthrough in visual What
Speaker 2:does good training data look like today? Is it is it synthetic? Is it images, videos, three d, you know, virtual worlds? Like, what what's the shape of what's valuable?
Speaker 11:As you can expect, there's a bit of everything.
Speaker 2:All of everything.
Speaker 11:But, yeah. Definitely definitely natural data. So data that's not generated from a model is more valuable and more useful. Data from a model that's synthetic data has the risk of putting the model into, like, a weird place where it just outputs, like, em dashes or just, like, tries to repeat the same thing all the time. Yeah.
Speaker 11:But, yeah, data around the natural world, around the three d world, that's invaluable.
Speaker 2:What do you think the cybersecurity analogy is for visual reasoning? Like, cybersecurity is so equipped for text based models, coding agents. The entire cybersecurity threat can sort of be understood as a big string of text, more or less. Where do you think visual reasoning goes in terms of applications?
Speaker 11:Yeah. So for applications, one of the most promising ones that we're seeing is engineering. So right now, all these engineers, mechanical engineers, hardware engineers, and also architects, they're drawing all these diagrams in CAD software, which has been developed around, you know, the last few decades, but there hasn't really been AI breakthroughs there. People are still doing basically the same thing they've been doing for the past few decades. And so what we will do is we will produce models that really understand these drawings.
Speaker 11:Like, say, you have a real estate floor plan and you want to say, make this bedroom bigger or add an extension to my house. Right? Right now, that would take weeks and lots of manual time. And then you have to follow building codes. Yeah.
Speaker 11:Make sure, like, everything is correct. And that's because there's there's not really any reasoning in our visual reasoning in our current models. And so Yeah. We think there's a huge potential.
Speaker 2:One of the hardest one of the hardest times we've ever laughed on this show was was reacting to a a a floor plan that was generated by AI, and it looked so high fidelity. Every line was perfect. It didn't have any of the fuzziness that you've expected from earlier models. But when you dug in, it made no sense.
Speaker 1:Toilets and
Speaker 2:one toilets and two baths, and it had one big it it didn't really understand the problem. So very exciting. Well, you raised some money. Tell us about it. How much did you raise?
Speaker 2:We want to hit the gong for you.
Speaker 11:Yes. We raised $55,000,000. Congratulations.
Speaker 1:From who?
Speaker 11:That's from Striker Ventures, Menlo Ventures, Automata, and NVIDIA and £49 participating. And we have some great angels there, including Jeff Dean.
Speaker 2:Jeff Dean. He's been on a he's been on angel investing terror. It's really exciting to see. I mean, obviously, he's a legend, but he's clearly very optimistic about all these different approaches going forward. So very excited.
Speaker 2:Well, thank so much for taking the time to come chat Yeah.
Speaker 1:Great to meet you,
Speaker 2:Andrew. We'll talk to you soon.
Speaker 3:I'll talk
Speaker 1:to you soon.
Speaker 2:Have a good rest of your day. Cheers. Up next, we have Lum and I and Dinakaran in the waiting room. We'll bring him in to the TBPN Ultra Dome. They have raised a $38,000,000 series b to scale AI automation for health systems.
Speaker 2:How are you doing? Good to see going on?
Speaker 10:Doing doing great. Great to see
Speaker 2:you both. Great to see you. I believe it's your first time in the show even though we've met in past. Please introduce yourself and the company.
Speaker 10:Yeah. I'm Kesava, one of the cofounders and the CEO of of Lumi. Help large health systems drive automation in their operations and back office.
Speaker 2:What is so is this a diffusion story, or is this, like, a foundational AI research problem? Like, what what what is the secret to actually driving improved health care outcomes in in these larger organizations?
Speaker 10:Yeah. I think, you know, the the models have kind of got to a place probably in the last maybe six to twelve months where where some of the opportunities to actually drive automation end to end in a very reliable manner is is very possible. So it's 100% a diffusion story at the moment because the reality is like, you know, American healthcare still runs on faxes in And many so you're kind of at this opportunity now to dramatically change how it's done in the first place.
Speaker 1:So I would love an example of like a specific back office task. Is this like passing information to insurance providers, processing claims? Like what are some specifics?
Speaker 10:Yeah, I'll give you a very concrete example. So imagine like, one of the customers we work with is the Cleveland Clinic and they're obviously one of the most advanced sort of academic research organizations as well as hospitals in the world. And so there are patients who come from all over the world to Cleveland Clinic. And the way they actually get care is initially through something called a referral, right? And that referral basically gets sent from small clinician practices to massive hospitals that are based in even all the way from The Middle East.
Speaker 10:And they're all, unfortunately, or at least at the luminaire sent via a fax machine. And these are sort of documents with handwritten notes where people are sent, saying, hey. This is Kesava. He has, some, unique sort of, left knee pain, that requires, you know, a specialized attention. Here are the details.
Speaker 10:And there's a huge sort of operations team on the clinical clinic side where their job basically is to look at every single document, read every single sort of handwritten note. And by the way, these fax
Speaker 1:lines Sorry are sorry to interrupt, but you guys so so just so I have it correct, you guys are making humanoid robots that can write handwritten notes to fax back through a physical fax machine to the original sender.
Speaker 10:You know, I think five years ago, that would be easier solution to solve, in health care, than than try to get it implemented. But but, it's all all enterprise software.
Speaker 2:Okay. Okay. Okay.
Speaker 10:So it's it's just literally a virtual inbox agent that, you know, triages each referral that comes in, puts in the high risk patients first, and then processes the referral in an automated way. But that that's sort of an example of of many other problems that obviously exist within the the operations of our health system.
Speaker 1:That makes sense. And so are you guys doing the kind of forward deployed model where you basically say, hey. We we have a good understanding of current AI capabilities. If you let our team into your space, we'll figure out individual workflows to automate, or what's been the the the approach so far?
Speaker 10:Yeah. I mean, health care is extremely nuanced. You have to understand the specifics pretty pretty deeply. And so without actually being, on the ground living in the offices of your of your customers, it's difficult to sort of scale solutions. And so, you know, about 20% of our team comes from Palantir.
Speaker 10:And so we've taken a very deep, forward deployed approach, to every every customer we work with. And, you know, we work with some of the largest institutions in the country, and so sort of it lets us afford to actually be able to to do that.
Speaker 2:How much about deployment diffusion is gated by regulatory or approvals versus it's a less maybe, you know, obviously there's a lot of tech native people in these health care systems, but they might be a little bit less online, a little bit less aware of the progress. And so there's just an education element versus, you know, understanding the cost tradeoffs and actually implementing the processes.
Speaker 10:I mean, and there's definitely a a massive amount of, like, barriers to entry and being able to actually drive, or or actually implement, AI systems in these spaces. I mean, and and for good reason. Right? Like, this is, like, extremely extremely sort of sensitive health care data that's flowing through these systems. And so there's the right amount of sort of guardrails put in place.
Speaker 10:But once you're in, there's a dramatic amount of work that can be done by software and that can be done by AI in the first place. And it's sort of a, there's definitely areas we shouldn't touch like deep, deep clinical decision making and threads around that, that this is why we have doctors. But there's a huge amount, over a trillion dollars just like wasted administrative operations work that that, yeah, today can be done by software systems.
Speaker 2:How are you thinking about on prem these days? With the AI context, I mean, these models are so big. The latest ones seem to run on NVL 70 twos. That feels like a big lift in CapEx if you're gonna stuff that in a closet somewhere or in the local IT cabinet. Where do you see like, are we going be seeing, like, local inference happening for regulatory reasons?
Speaker 2:Or is it more about just interfacing with on prem systems because they exist and then this will be actually an accelerant to cloud adoption?
Speaker 10:You know, we've offered on prem to every single health system we work with.
Speaker 2:Really?
Speaker 10:But only only, you know, 10 to 15% of percent of them have actually taken us up on it.
Speaker 4:And Yeah.
Speaker 10:And so that's an interesting sort of one data point. But the primary reason to offer on prem in the first place is because because of the amount of data that you're sort of handling and you don't want those that that data to basically leave your leave your premises in the first place. And so we've chosen to go go on prem with with, you know, even certain workflows with with large health systems. But but funnily enough, we thought it was gonna be a massive need when in reality, it's it's definitely a checkbox that they do to make sure that you can actually do it versus versus actually deploy some of this in in in full production.
Speaker 2:Interesting. Last question for me. How how dramatically is is this the the the quantity of data produced in health care environments growing right now? We looked at this one company that was just an audio recorder that would transcribe everything that someone would say. We've seen a bunch of these targeted tech audiences, but this one was specifically for doctors to take notes and then have a running transcript of everything that they said as opposed to needing to scribble a bunch of notes.
Speaker 2:It feels like we could be at some sort of like data production inflection point. But what are you actually seeing in terms of the quantity of data that's being produced in the health care system?
Speaker 10:Yeah. I mean, there are there are sort of obviously a variety of folks who've done research on this, but I think the health health care has, like, eight times more data than the next largest enterprise industry on the on the in the country.
Speaker 2:And Yeah.
Speaker 10:Over over 90% of that data, is unstructured. So these are all, like, sort of, you know, contracts and PDFs and handwritten notes and text that's, like, floating around the the the IT systems that exist. So it's it's obviously a massive opportunity and and problem at hand.
Speaker 2:Yeah. Well, congratulations on the progress. Give us the details about the round.
Speaker 10:Yeah. We we raised a $38,000,000 series b. Fantastic. Led by the peak fifteen team, which is the Sequoia India group along with General Catalyst as well as YC and a bunch of others. So, yeah, grateful for all the support and and interested in continuing to deploy pretty deeply.
Speaker 2:When did you go through YC?
Speaker 10:We actually started in summer twenty. So yeah. So Sixth. Yeah. Yeah.
Speaker 10:I've been I've been sort of in the game grinding for the last
Speaker 2:I love it.
Speaker 10:Five and a half plus years.
Speaker 2:Yeah. But I mean, what? You you caught the perfect inflection point. I'm sure you've done a ton of work to set up for the success and take advantage of the progress in AI broadly. So Yeah.
Speaker 2:Congratulations. What what a fantastic story. Thank you so much. Great to meet
Speaker 9:you. Yeah.
Speaker 3:Have a
Speaker 2:great rest
Speaker 11:of your day.
Speaker 2:We'll talk to you soon. Goodbye. Alright. Yeah. Up next, we have Brian Manning from Zone of Space coming in with a new series c announcement, building a GPS alternative network.
Speaker 2:Brian.
Speaker 1:What a setup.
Speaker 2:Beautiful setup. I assume you're in your factory. Take us through an introduction on yourself, the company, and where you are.
Speaker 8:Thanks, guys. Yeah. I'm super excited to be here. It's been an exciting day. We're fresh off this morning, the announcements and launch of our new satellite factory here in San Francisco, which coming on the heels of our a hundred and seventy million dollar series c rays that we announced at the WTO.
Speaker 8:You. A lot of exciting things happening. So what what we're doing, what we're building here is we're basically building a new GPS. Yeah. And so we're building a network of these small satellites that are 20 times closer to earth than existing GPS Mhmm.
Speaker 8:To provide extremely high accuracy, extremely high reliability navigation capabilities. You know, I came from SpaceX. Our CTO came from Ford. Originally, the company was designed around providing autonomous vehicles the level of certainty and accuracy they need they really need to scale. Mhmm.
Speaker 8:But we started finding pretty quickly after that that there are 7,000,000,000 plus GPS devices around the world. Every single one of them is looking for better performance, and that's exactly what we're we're building a network here to provide.
Speaker 2:Okay. So 258 satellites going into low Earth orbit. You're building them in that factory, I assume, but you're probably have a, you know, deep supply chain and partnership. I imagine that they launch on other rockets. What what is what is key about what you're building?
Speaker 2:Where are you partnering? Where are you doing r and d before the actual satellites get built and sent to space?
Speaker 8:Yeah. For sure. That's a good question. So with satellite navigation, most people always focus on the satellites because satellites are cool, and that's always the fun thing to focus on. But a sat nav system is really three pieces that you have the ground segment which is the mission operations kind of control segment.
Speaker 8:Mhmm. You've got the satellites and then you've got the user equipment. And then the user equipment is is arguably the most important but it's also the most overlooked. So we are building the satellites, we're building the ground segment, and then we've partnered to integrate our capabilities into all the different user equipment that's out there. And so that's the chips that would go into, everything from a dog collar to a phone to a tractor to a car to military devices and everything in between.
Speaker 8:Yeah. We've designed our capability to be just a software update so that we can integrate in with these billions of devices that are going out there. And we we've been able to demonstrate that on over a dozen different receivers with the satellite that we launched last year that's up in the air now.
Speaker 2:Got it. So, yeah, can you give me an example of so a dog collar has a GPS chip in it. It's currently interfacing with satellites that are higher in orbit. And with a software update, you won't actually need to swap out the chip. You'll be able to get more accurate GPS data.
Speaker 2:What what is the benefit of this particular news new constellation?
Speaker 8:For sure. So there's three big areas that we've seen customers really need better capability. Mhmm. And it is we try and make it simple to remember by precision, power, and protection. Mhmm.
Speaker 8:So there are some customers that are you know, GPS in the automotive world for example can tell you a human driver kinda reliably what road they're on. Yeah. Where our system is designed to extremely reliably tell them not only what lane they're in, but if they're in the center of that lane or not. But we deliver that through a signal that's a 100 times stronger than GPS which means it's strong enough to punch through jamming. It's punched through trees, even punched through a couple walls.
Speaker 8:Smack to the dog collar. Yeah. Right now everybody just accepts that like when you walk inside or when you go indoors or when you go into your house, GPS just kinda disappears and location, you know, doesn't really show up anymore. Mhmm. With ours, our signal's strong enough so that, you know, you can see if if Fido's in the kitchen or in the backyard or at least knowing where they are at all, where you just can't do it today with an existing GPS.
Speaker 2:I heard this story years ago that I have no idea if it's true, that g the the current GPS constellation is higher resolution for military applications than for civilian applications, and the technology is not actually the problem. It's more that there are specific rules about the level of resolution that GPS data is is like turned over to private companies. Is that true at all?
Speaker 8:Sort of. So there there there's bits of that that are are true, some I think there are just some misunderstandings
Speaker 2:Okay.
Speaker 8:That are pretty common in the world. So the military does have a different GPS service than civilians do.
Speaker 2:Okay.
Speaker 8:The big difference between the civilian GPS and the military GPS though isn't the accuracy, it's actually more on the security aspects. And so there's more protections that exist on the military service to prevent, you know, bad actors from being able to fake the signal or being able to use the signal, and that's one of the big gaps in the civilian market today is that they don't have access to a service that gives the the level of protection that's needed. And so you can kind of think of it a GPS signal. Imagine taking your social security number and your date of birth, your mother's maiden name and everything, and putting it on a postcard and mailing it through the mail. Mhmm.
Speaker 8:That's kind of what GPS is today, that everything is just wide open. Yeah. Where what we're providing is a capability that's more similar to the military one where everything is secure, encrypted, protected, but making that available to civilians so that, you know, you can trust taking your hands off the wheel in the autonomous car and know that that signal's coming from us, that it has the protection. It's not coming from a bad actor.
Speaker 2:Okay. So the software update handles in like, it sort of enables the encryption as well, I assume?
Speaker 8:Yeah. So effectively, you can almost think of our service
Speaker 3:Yeah.
Speaker 8:In a similar way to, you know, GPS is like FM radio. It's the free service. We're more similar to like XM radio or satellite radio where we broadcast down and everyone can listen to it. But until you type in the subscription key Yep.
Speaker 2:You don't know.
Speaker 8:The data doesn't work.
Speaker 2:Yeah. That makes a ton
Speaker 1:of That's I was gonna ask. Okay. Business business model. But Yeah. Yep.
Speaker 2:How how big or small are current GPS devices if you want to basically have an AirTag that you can throw in your shoes so you can be so you can know where you are or or the dog collar. This feels like there's a we've been on a miniaturization path for a long time. Where are we now? Where are we going?
Speaker 8:Yeah. So the the size of the device, I mean, we've got chipsets that we're working with that are, I think, like three millimeters by three millimeters. So it's something that's probably 10 of them on the end of your of your hand. Yeah. It's GPS is really one of the superpowers of GPS and what we're building also is that it is a one directional broadcast.
Speaker 8:So it's a receive only signal that it doesn't your GPS device like GPS doesn't know where you are. It only can tell you where you are. Yeah. So there's no personal privacy concerns or anything It like just gives you the data to figure out where you are. Yep.
Speaker 8:That And enables it to also be used in these ultra low power devices because they just have to listen. They don't have to actually talk back. Yeah. So it enables you to provide this into, you know, as you pointed out, things like the the dog collar or the counter tracker. You know, we've even seen people with like peel and stick packaging labels that we're we're starting to work with that you can put on the side of FedEx package to track it.
Speaker 8:Wow. So it is getting into smaller and smaller devices and in in the world of AI, everything wants to know where it's at. Yeah. And the more accuracy you can provide with more availability and just enabling these things to know where they're at more of the time unlocks so many new insights and, you know, logistics visibility and whatnot that that really just doesn't exist today when GPS can't get into the place where the thing is at.
Speaker 2:Tell us more about the factory.
Speaker 1:Yeah. And and, you know, hard a lot of the the sort of space companies that come on the show are obvious are based out in Southern California. Yeah. What have been the what have been the pros and cons of building in the Bay Area?
Speaker 8:For sure. That's very good question. That's something we've we've had people ask before. If you open up our satellite and look inside of it, and we laid it out on a table, most people look at it and say, this looks like the guts of a desktop computer. Mhmm.
Speaker 8:There's bunch of circuit boards. I mean, there's certainly solar panels and propulsion systems and other things around it. But the the core, like the heart of it, and a lot of pieces that that we've designed and built internally here have a lot more in common with a desktop computer than they do with, you know, July. And LA has, you know, a lot of great talents, a lot of, you big aerospace talent. But Silicon Valley is in many ways, you know, the heart of compute.
Speaker 8:Yeah. All these, you know, the chipsets and a lot of the the talent, the people that we're looking for, It's a lot of electrical engineering, a lot of software engineering, a lot of mechanical engineering to put the pieces together, which is And the whole founding team came from Stanford, so we all kind of naturally landed here which had the right resources around us. The factory that we're stood up here is modeled more after, you know, a supercar assembly line than it is after a typical satellite assembly line. And so it's something that, you know, this satellite factory is built to start providing multiple satellites per week. Where to put that in context, The US currently produces maybe two navigation satellites in a year, where with what we're building here, you know, we can produce that many satellites in a week, which really just brings an entirely new capability to the world at a pace that's never been possible before.
Speaker 2:What's the regulatory side of the the the picture? Do you have to get FCC clearance for your designs? What is there a Yep. There a wait and see period? Is that being accelerated at all by new tools and the ability to proofread documents with AI, anything like that?
Speaker 8:It's yeah. So you you very astute question from the space world that anything spectrum related Yeah. We started working in the spectrum engineering years before we started working any of the satellite engineering. Sure. Because we knew that that would be the biggest challenge and one of the things that we've done that's very unique is with all the spectrum engineering we've done, we basically figured out how to provide a service that is in the GPS bands right next to the GPS signals without actually causing any sort of interference to those signals, which is incredibly difficult to do because in GPS broadcasts, at about the power of a light bulb from an earth and a half away from earth in distance.
Speaker 8:And so it was just such an incredibly weak signal that there's a lot of people that told us when we started the company like there's no way you'll ever figure out how to put a high power signal next to these GPS signals without causing interference. And a lot of people still didn't want to believe it until we launched the satellite last year and we're able to show, look, there's our signal, there's GPS, it's a 100% fine. And it's it's not only, you know, say fine, it's it's really necessary in the world today with so much, you know, electronic warfare and jamming and other things. You really need these high power signals to be able to fend off interference, whether that's interference from, you know, a wall or a roof or interference from somebody trying to jam the signal and prevent, the capability from getting through.
Speaker 2:Yeah. Yeah. That makes a lot of sense. Well, congratulations on the new factory. Thank you so much for coming on and breaking it down for us.
Speaker 8:Thank you so much for having us.
Speaker 1:Back on here. Soon.
Speaker 2:Yeah. Have a great rest your time. We'll talk to
Speaker 3:you soon.
Speaker 1:You too, guys.
Speaker 8:Cheers. Thanks a
Speaker 2:Up next, we have Cody Blumenfeld Gantz from Chapter raising a series e to expand Medicare navigation and launch financial products. Not with us. The waiting room. We're waiting. Waiting.
Speaker 1:The JC, nice guy got his m 64.
Speaker 2:His m 64.
Speaker 1:And showed the packaging. It says brought to you by the crack team at Mod Retro.
Speaker 2:At Mod Retro.
Speaker 1:Crack team.
Speaker 2:The crack team. I saw some people playing cruising cruising USA, cruising world maybe. Something like that. This is gonna be fun.
Speaker 1:What do you what do you think they mean by crack team though?
Speaker 2:Crack team?
Speaker 1:If you look at this, if you look at the the packaging, it doesn't say brought to you by the cracked team at mod retro. It just says crack team.
Speaker 2:I don't know.
Speaker 1:But maybe this is some new slang.
Speaker 2:They cracked it open. Well, we have our next guest in the waiting room. Let's bring in Cody Blumenfeld Gantz from Chapter into the TBPN Ultra Realm. Cody, how are you doing?
Speaker 6:Doing well. Thanks for having me.
Speaker 2:Thanks for Please hopping introduce yourself and the company.
Speaker 6:My name's Kobe. I run a company called Chapter. We are a Medicare navigation and retirement platform. I started the company a few years ago after seeing my parents struggle with the Medicare process. Pretty much every person in this country who's over 65 or retiring has to deal with Medicare.
Speaker 6:Yeah. And I was just really appalled at how bad their experience was and wanted to make it much better.
Speaker 1:Yeah. Early on, when you kind of discovered the problem, did you assume that that there was companies already solving it well? And, you know, when you when you talk about the scale of the market, it's like everyone over country and everyone in in retirement for the most part is dealing with this. What what did you what did you find and then what gave you the confidence to to start the company?
Speaker 6:I found really poor experiences all around. Most Medicare brokerages in this country are heavily incentivized to push plans that pay people that pay brokers more rather than focusing on what's best for the consumer. And there's really no good technology in the space at all. So you really have a combination of sort of mom and pop brokers. You can think of these as local real estate agents, and then you have these legacy call centers that are basically just like marketing orgs that are very bad at what they do and really nothing in between that really prioritizes the consumer's interest.
Speaker 6:So when my parents were going through it, they had to deal with faxes and phone calls and they got really bad guidance. My mom actually now has lifetime late enrollment penalties because she was told to sign up too late. Yes. The government imposes lifetime penalties on people if they sign up late for Medicare. Yeah.
Speaker 2:Talk to me about then how it seems like reaching the potential customer or user as early as possible is critical. What's the customer journey to actually get on chapter or work with an adviser? How do the users actually find the product?
Speaker 6:We take a really heavy AI driven approach, but we augment humans with the AI. Yeah. So we have one of the smallest teams probably of any tech company and especially any Medicare company for our scale. Yeah. And we're really proud of that because we're pretty sophisticated users of AI.
Speaker 6:Yeah. And so a consumer will find us through one of our partners. We do almost no direct to consumer work. It's all through enterprise partners. Yeah.
Speaker 6:They'll find out about us through their financial advisor or their health system or hospital. Got it. They will give us a call, fill out some information, and they'll be connected to one of our full time employees who's a licensed Medicare advisor. That Medicare advisor has a lot of tooling at their fingertips that we've built to make sure they can deliver really high quality guidance all the time for every single person.
Speaker 2:And what does that tooling look like? Is visualizing and analyzing numbers and sort of instantiating spreadsheets and dashboards and charts? Or is it actually going and filling out forms and dealing with, like, legacy government systems that can be abstracted into something that's just more usable?
Speaker 6:All of the above and a lot more. So I'll give you a couple of examples. One is every single insurance carrier has a different portal that one has to use to look up information and fill out forms. So we have to automate all of that and they don't and most of them don't have APIs, as you can imagine. Yeah.
Speaker 6:So that's kind of that's the automation of filling out forms and paperwork. For any given Medicare plan recommendation, we have to know every doctor that that person is in network with. Mhmm.
Speaker 3:We have
Speaker 6:to know every prescription that that person takes. In order to answer the what sounds like a very simple question of what prescription will will what will a prescription cost on a given Medicare plan at a given pharmacy Mhmm. That requires tens of billions of records to know. Just that one question. Tens of billions.
Speaker 6:That's one of many elements. So we do a lot of work to obviously, our Medicare advisors are not crunching those numbers every time they talk to someone. So a lot of that just surface the right answer to to the Medicare advisor.
Speaker 11:Yeah.
Speaker 1:You guys just surpassed $100,000,000 run rate. What seems pretty fast for a company in health care, which typically, this isn't like selling like some image gen model or something like What what is what is best in class? Who are you guys going up against from a kind of zero to a $100,000,000 run rate? I'm assuming you guys are one of the the faster in history, but I'm curious.
Speaker 6:I I don't think of ourselves as a health care company, really. I think of ourselves as a really good tech company, so we compare ourselves to the fastest growing companies where we grow as fast or faster than companies like Ramp, companies like Clean. We went 1 to 100 mil in run rate revenue in, I think, about two and a half years. So I really think about us as just like what do great tech companies do and we try to orient the team around that because the bar is just too low in health care.
Speaker 2:So then what is the Very what is the funnel to to actually grow the business? What is the is the flow? You said you don't do consumer marketing. Is this, like you said, enterprises? Are you do you have SDRs?
Speaker 2:Are you going outbound to companies and and financial advisory groups? What does that go to market motion actually look like?
Speaker 6:We do have an enterprise partnership, enterprise growth team. Yeah. The team the whole team is about six or seven people. Wow. So as I said, we're very small and we take a lot of pride in having a really high bar for The
Speaker 1:whole the entire companies?
Speaker 2:No. No. No. No. The growth team.
Speaker 2:The enterprise growth team is is
Speaker 6:But but all of all of our sort of corporate headcount, product, engineering, growth Yeah. Legal, etcetera, we're about 30 people.
Speaker 11:Wow.
Speaker 1:And so that's still remarkable.
Speaker 2:Well, congratulations. You just raised a round. Tell us about it.
Speaker 6:Yeah. We raised about a $100,000,000 led by Al Gore's generation fund. Nice.
Speaker 3:Massive.
Speaker 2:Thank you so much for taking the time to come chat with us. Congratulations on the progress. Thank you, Thank you for everything that you do. I'm sure
Speaker 1:you'll be back on probably multiple
Speaker 2:times here
Speaker 1:at this rate.
Speaker 2:A good one. Cheers. Bye. Up next, we have CZ from Binance. He is the founder and former CEO.
Speaker 2:He released his book, Freedom of Money, detailing Binance's rise, crypto's evolution, and his legal battle with US regulators. CZ, how are you?
Speaker 7:I'm good. Good. Thank you. Thank you
Speaker 2:for having me. So much for hopping on.
Speaker 1:Good day.
Speaker 2:Tell us about the book. What was the goal? Is this an attempt to set the record straight or just tell your story? What what what motivated you to write a book at this moment in time?
Speaker 7:I think it's really just to tell my story. Yeah. And then, I was bored for I had nothing to do for a couple years. Yeah. So I started writing a book when I was in prison.
Speaker 7:Okay. And then, I just finished when I got it when I got out. So, I thought, you know, it might be interesting story to share and stuff, you know, to let people know what my view is.
Speaker 2:Yeah. What do you what do you think people get wrong about your story?
Speaker 7:Well, I think a lot of traditional media have many misconceptions about crypto, Binance, myself, etcetera. So I think there's a lot of media that's not accurate about crypto. So I think this is a very good chance for for me to share my perspective and have people understand crypto better.
Speaker 2:What specifically do people get wrong about crypto or you or Binance?
Speaker 7:Sure. I mean, look, from 2013, right, people think that Bitcoin's only used by drug lords, or for illicit activities. The truth is actually, if you look if you look at percentage wise, illicit activities in crypto is actually much, much less than your traditional finance. And then, by extension, a lot of the crypto players, a lot of crypto platforms get hit. And recently, you know, there's more attacks about, you know, just just random attacks on me about how I do business, who who I who I have connections with.
Speaker 7:So I'm a simple tech guy, so I just wrote the book, you know, the the way I wanted to tell it. Mhmm. It's a pretty simple language, pretty straightforward book.
Speaker 1:This is simple guy. This is a simple guy.
Speaker 7:What I think I'm a relatively simple guy.
Speaker 2:Yeah. How how have you been processing the the new regulation that's been proposed in the in The United States? What do you think needs to change in the crypto industry? Because I take your point about the amount of illicit activity might be lower than in cash or the traditional financial system. But the goal, I think, for everyone that would agree is to get that to zero.
Speaker 2:And so what what do you like about the new regulation? What do you think is is reasonable to ask for?
Speaker 7:Well, I think right now, US is making really good progress on crypto regulation. The Genius Act was passed in last July. But I think right now, there's still quite a lot of debates based on my layman understanding. I'm not an expert. I'm not a lawyer.
Speaker 7:I'm not a not a regulatory guy. But, seems like, no, there's a lot of debates about, stablecoin interest rates. So, I think it's a big important issue, but from my perspective, any clarity is better than none.
Speaker 2:Mhmm.
Speaker 7:So and and, we will not we'll I think the current, iteration of regulations will not get get everything right on the first try. Right? So there'll be some collaboration over time. Mhmm. So I think it's more important to make progress and and move forward.
Speaker 2:Yeah. How how are you thinking about the broad trade off between, decentralization and anonymity and then, oversight reg and regulation? Like, it feels like we've been moving towards oversight, more regulation, more KYC. We've heard from some crypto leaders that that can lead to data breaches and other problems. But where do you sit on the level of regulation in the crypto industry broadly?
Speaker 7:I think right now the crypto industry, to be honest, is too transparent. It's actually extremely easy to track crypto funds. Like, the blockchain is a public ledger, and then if you couple that with a few centralized exchanges, KYC information Mhmm. You can track most of the transactions pretty accurately. So, I think, right now, there's a lack of preserving of, privacy.
Speaker 7:But right now, the problem is many of the regulators and law enforcement people don't know how to use it yet. Mhmm. Some people do. I think some of The US law enforcement actually knows it quite well. Mhmm.
Speaker 7:In other countries, they know they know it much less. So, hopefully, we'll get to a balance where I don't know where the optimum balance is, but there should be an optimal balance where, you know, we satisfy all the regulatory requirements, but we also need to protect individual privacy. Right? For example I'll give you a couple examples. Please.
Speaker 7:For example, like, if if this company if your company pays everybody in crypto Mhmm. And if you get one payment today on the blockchain, you can just trace to the address I paid you and see how many addresses that address paid in the last week. You can figure out everybody's salary. Yeah. Right?
Speaker 7:So that's a privacy issue. Yeah. And if you if you stay at a hotel, you pay for the hotel, then people know where know, if people know your address and the hotel address, people will know that you're going to stay at that hotel, which, for some people, may create security issues. There's little problems like those that are not solved yet. We need to strike a balance.
Speaker 7:It's hard to say exactly where the balance is, but I think over time we'll
Speaker 11:get there.
Speaker 1:How are you thinking about the interaction between AI and crypto? Generally, there's been a lot of excitement even from people in AI about crypto and intersection. But I'm curious what your overall view is and then if it's positive, some maybe specific examples of where you expect to see it manifest first.
Speaker 7:Sure. Absolutely. Yeah. I think what both AI and blockchain are big recent new big industries. I think there's really three big technologies in my in my adult lifetime.
Speaker 7:Right? There's AI, there's blockchain, there's Internet. It's on those levels. I think AI is AI is gonna use crypto for payments for transactions. They're not gonna use no.
Speaker 7:They cannot KYC through a bank. They cannot do, they cannot do a selfie. They don't have a passport, etcetera. And, also, payments in every country is a little bit different. Mhmm.
Speaker 7:Whereas crypto, blockchain is the same across different countries. So, one you integrate with the blockchain once, it works globally. And it also handles micro transactions, large transactions, etcetera. Also, crypto is going to increase the amount of transactions significantly, so the traditional payment rails may not be able to handle that. I think blockchain also have a lot of benefit from AI.
Speaker 7:I think right now, a lot of the applications are, in blockchain, quite difficult to build. I think with AI, we can probably build safer tools for people to do self custody and safer tools for people to transact. Today, the two industries, to be honest, have not really leveraged each other that significantly, but I think in the future, they will.
Speaker 2:How are you thinking about the risk of quantum computing to the cryptocurrency ecosystem broadly?
Speaker 7:I think there is some risk, but I think overall though, any technology improvement is always going to be good. More computing power is good for crypto. Mhmm. So quantum may break the existing encryption mechanisms, but with quantum computing, there's probably new well, there will be new encryption algorithm, but there are already quantum approved encryption algorithms that quantum computers do not have an advantage to crack. So we just need to upgrade the protocol to use those encryption mechanisms.
Speaker 7:Also, more computing power with quantum, there's probably newer encryption mechanisms we have not even thought about
Speaker 3:Mhmm.
Speaker 7:That we can use quantum to encrypt, and decryption is always going be much harder.
Speaker 2:Sure. What about non non quantum hacking? Throughout the crypto boom, there's been so many upstart projects. Many of them have been able to get to escape velocity, and they're still around today. A lot of them have had to go through hacks and adapt.
Speaker 2:And it feels like with the moment that we're in in terms of AI's effect on cybersecurity, we could potentially be looking at maybe a bifurcation between the projects that have the resources to actually harden themselves against new cybersecurity threats and those who are maybe smaller upstarts and don't, how do you think that effect plays out?
Speaker 7:I actually think AI is going to improve security for most projects. Like Anthropic Cloud. Yeah. Right? So now they're I think if you play like like that, you could potentially discover many flaws, at least they claim, in many projects.
Speaker 7:But I think projects can also use use their tool to fix their security problems. I think a big company like that, they already make a lot of money. They don't need to exploit smaller projects to hack and to do illegal stuff. So I think right right now with the AI tools that's available, the developers can use those tools to find their own problems. Yeah.
Speaker 7:But, of course, if you don't do that, then the hackers may do that for you, which is a typical problem we have today anyway. Yeah. I think with AI, security is actually going to become better. I don't think it's going to become worse. Sure.
Speaker 7:So so I'm pretty yeah. I'm pretty confident about that.
Speaker 2:Do you know who Satoshi Nakamoto is?
Speaker 7:No. Unfortunately, I don't. Even if I did, would have said no, but Yeah. I honestly don't.
Speaker 2:Okay. Do you have have you how have you processed that question of who is Satoshi? Have you wrestled with it? Have you done a bunch of research to try and figure it out? Have you had various suspects at various points in time, favorite pet theories, wild card theories?
Speaker 2:Or has it sort of been a quick ride to sort of process that and then let go of that desire because it's the unsolved mystery?
Speaker 7:This is an interesting point. I should have put this in my book. Maybe the maybe the next edition. Yeah. But I've come to peace with it.
Speaker 7:I think I'm curious, obviously. Yeah. I mean, if there was one person I really want to meet in the world, that that would probably be him. But I think there are negative consequences if if we find out who he is. Right?
Speaker 7:So for example, if I couldn't lie on the oath, if people say, look, have you met Tatoshi? If say yes, then, you know, that's gonna hell is gonna break loose.
Speaker 2:Sure.
Speaker 7:I I think it's better if we don't know who he is. Yeah. It's better if we did and without knowing him, that we don't have a founder centralization. Yeah. Right?
Speaker 7:For example, if you look at Ethereum, Metallic's there. Right? So there's a founder centralization. Yep. What makes Bitcoin unique is that we don't know who we well, the founder is no longer participating.
Speaker 7:He may not be around. He may not be participating, so that makes it more decentralized. I think that's a good thing that we should come to term I came to terms terms with it quite a while ago. So even though I'm curious, I'm not actively looking. Yeah.
Speaker 2:Have you ever thought about doing a anonymous project? Or do you have a reflection on why we haven't seen more projects effectively run, at least to my knowledge, the Satoshi playbook of maybe it requires some crazy opsec to go anonymous for a couple of years. But if it worked for Bitcoin, I would imagine that somebody would have thought I'm going to do the same thing for this new project with slightly different opinions about how the technology is built. I haven't seen it happen, but what's your take on the idea of a new attempt at a Satoshi like founder in the crypto industry?
Speaker 7:I actually really want to see that too. I think that's a really, really cool idea, to be honest, but I think it's also very hard to do. Mhmm. Most projects fail even with the founders heavily promoting it. We know who they are, etcetera.
Speaker 7:For a new project, without knowing the founder, there's less trust in the community. Bitcoin was the first one. Somehow, it got, you know, slow. It started very slowly. It took many, many years for it to get to where it is today.
Speaker 7:And for a new project to do that, it's very, very difficult. Yeah. And there have been anonymous projects that, you know, that are basically rug pulls. Right? So, they're also the other side of it, people Sure.
Speaker 7:People lose trust with anonymous project. So, to do what Bitcoin did is very, very difficult. I would I would actually love to see more anonymous, fully decentralized, you know, projects. But what you mentioned is the ops sec is also extremely hard. Yeah.
Speaker 7:It's so hard today to not leave any trace, both digitally and physically. Right? Yeah. So the fact that nobody has really announced who Tatoshi is means that his ops sec is crazy. Yeah.
Speaker 7:I think 99.9 well, nobody else can do it really at this point.
Speaker 1:What do Americans miss about crypto adoption globally? Here, I mean, so many at least at least younger generations, almost everyone has some exposure to digital assets or some experience buying, selling, maybe not maybe not using it functionally for payments. But obviously, it's very different, in other parts of the world with with, you know, less, centralized financial institutions.
Speaker 7:Yeah. I think America, for the last few years, before the Trump administration was, you know, fairly anti crypto, so many of the, founders left, many of the projects left, and many of the liquidity left. Right? There's, the biggest crypto exchanges are not in America, today. The biggest blockchains, the biggest stablecoin, they're not America based, So I think America misses that liquidity quite a bit.
Speaker 7:America right now has very forward looking regulations, and now people flocking back. I think the talent pool is coming back, but, some of the larger players are not backing America yet, so I would love to see that changing. I think right now, crypto if you buy crypto, Americans are probably paying the highest fees in the world, whereas if you buy anything else, America is usually paying the lowest price. The cost to American consumers today for accessing crypto is quite high, so that's a disadvantage that America has today. America has a large economy, a lot of entrepreneurs, lot of VCs, good liquidity in traditional markets.
Speaker 7:I think and I think America definitely has the ability to catch up very quickly.
Speaker 2:You were born in China. How are you thinking about geopolitical relations between The US and China? Tensions seem to have been rising for years. There's trade tensions. There's all sorts of geopolitical tensions.
Speaker 2:Is there any hope for de escalation between the two countries?
Speaker 7:I'm not an expert on the geopolitics between different countries. Also, my lamely understanding is both countries have leaders with pretty big personalities. Yeah. They're very hard to predict. Mhmm.
Speaker 7:I think the president Xi in China is easier to predict than president Trump. President Trump is like a wildcard. Right? It's like which is which which which is in which is in his advantage. Sure.
Speaker 7:You can't predict what's he what he's gonna do. And, but I do think both both countries are large countries now with leaders who are smart and who are business driven. They want the economy to grow. Mhmm. So if that's the goal, then there are certain then I'm optimistic that, you know, there's certain outcome to be reached.
Speaker 7:Between two countries, there's usually a fairly large zone of overlap that you can reach deals. Right now, it's just the personalities, and also both countries are quite proud, so they they're all hard negotiators. Yeah. The negotiations at that level takes time. Yeah.
Speaker 7:So, but I I am, I am fairly I'm fairly optimistic that, you know, both the two countries will work hard on something that's beneficial for both. Mhmm.
Speaker 2:You've written the book. What's next for you? What do you think the next decade looks like?
Speaker 7:I'm actually not too sure exactly. I'm doing a few different things right now. I'm running an investment fund. Well, I'm not really running it, but, like, I support it. Sure.
Speaker 7:I do some mentoring in the space for new entrepreneurs. I run a free education platform, Giggle Academy, that provides free education to 240,000 kids now. And we've only been at it for like a year and a half. And then I also yeah. And then I also advise different governments on crypto policies.
Speaker 7:Mhmm. So between those four things that keep that keep me pretty busy, the book was actually a huge distraction for me. Can imagine. It took a lot of time. It takes a lot of time to write a book.
Speaker 7:Yeah. But I'm glad to know it's it's out there, and there's an audio version coming out soon. And then after that, I'll put that, I'll put that on pause. Just let it be for a while and figure out what to do. Yeah.
Speaker 2:What was the strategy for the audiobook version? Did you narrate it yourself, hire a human narrator, use AI?
Speaker 7:So one of my friend, Michael Santos, is gonna narrate it.
Speaker 2:Okay.
Speaker 7:So he we had this sort of agreement verbally from a long time ago. And also, Amazon doesn't allow AI, generated voices Interesting. Yet.
Speaker 2:I didn't know that.
Speaker 7:So we we are human read or audiobook. Sure. And then, I've been playing with AI quite a bit myself. Yeah. The AI cloning of of voice is I can't tell the difference from my own voice.
Speaker 7:Yeah. It's and it's it's just better. It reads more smoothly. It's better than my own reading. So in certain, we on certain other platforms or in certain other countries, we may use an AI generated voice that clones my voice to to try to read it.
Speaker 7:I haven't finished that yet. There are still little quirks here and there. Some sometimes AI make very obvious mistakes. You know, you you pronounce Chinese names wrong, which I would not make that mistake. Yeah.
Speaker 7:You pronounce this. Sometimes you will say, like, when I write $400, you say $4.00 $0. Sure. So I would not make that mistake. But 99% of the time, you actually read better than me.
Speaker 7:So we'll see. So I might do two different audio versions. We're still playing around with it.
Speaker 3:Yeah.
Speaker 1:I wonder after Jassy's letter today if he's still going to be anti anti AI voices.
Speaker 2:Yeah. Yeah. He's
Speaker 1:I did have a one last question. I'm just curious. How how did you process the prediction market boom over the last two years? There had been long people had long had predictions that prediction markets would intersect with crypto and be really big, and yet there was attempts in the 2010s that didn't really reach critical mass. So I'm curious, you know, how you process that that that entire period.
Speaker 7:Yeah. So I think I today, I do think prediction markets has a huge potential and it's already pretty big. Like, the the top players are pretty big already and there's, like, hundreds or thousands of upcoming platforms as well. And, also, if you look at the regulatory landscape, the CFTC chairman, Michael Silek, he talks about prediction markets multiple times. I every time I watch him talk, he seems to mention prediction markets.
Speaker 7:So it seems like the regulators and the, traditional markets are also moving in. So, and as you said, there have been many attempts previously, but then timing is important. Some ideas, you know, even even though the ideas are very obvious, if you implement them too early, they don't get traction. You have to implement the right idea at the right time. I don't know what all the ingredients are for prediction markets, but somehow now seems to be the right time.
Speaker 7:The previous attempts have struggled, and now it seems to be taking off. I'm a big proponent for anything that's new and interesting, I think prediction markets are very interesting. They're enterprise discovery and truth discovery. They're kind of using price to discover truth, right? Which is actually a very which is usually the reverse for what we do.
Speaker 7:Sure. Information drives trading volumes. That's a very interesting dynamic. Also, the EZ Labs, the fund I'm involved with, we invest in multiple prediction markets, so we'll see which ones work. But I do think that it's a huge potential and it's it's hot.
Speaker 7:Yeah. And it works.
Speaker 2:Are you how are you thinking about any of the previous crypto booms or narratives or themes coming back? Things like NFTs or crypto gaming. Are you optimistic on any projects or DAOs that had their moment in the sun and didn't quite at least reach escape velocity, do you think anything will have a second wind in the near future?
Speaker 7:I do think so. I think many things will have a second wind, but the second wind will most likely be a little bit different. Yeah. Right? There'll be something that's know, even prediction markets today, they're different from the sort of prediction markets four or five years ago.
Speaker 7:Mhmm. So every iteration, there will be some tweak and it's usually that little tweak that makes it a little bit different and maybe the microenvironment. I do think that some of the things that were there, I think thousands will not disappear. I think thousands haven't really took off, to be honest. The concept has there for years.
Speaker 7:Yeah. It's like 19 even in the February, video streaming doesn't really work. Even today, this type of call sometimes the Internet doesn't work. Sometimes the microphone doesn't work. Yeah.
Speaker 7:Right? We get into those situations a lot. A lot of things take a lot of time to mature. I think the DAOs, the NFTs, again, I don't the next iteration may be slightly different, but you may still be called NFTs or NFT two. You may be a different name.
Speaker 7:But I think, tokenizing art is probably gonna come back at some point, multiple times. Yeah. I don't know when it will really hit big and stay. Yeah. NFTs, I think, honestly, we saw we saw, like, a we saw a we saw a rise and then and then and then a downward trend.
Speaker 7:Yeah. So it's hard to say, but I think all of those things eventually will should be much bigger than they were today.
Speaker 2:Yeah. Well, thank you so much for taking the time to come chat with us. Congratulations.
Speaker 1:Yeah. Congrats on the I
Speaker 2:recommend everyone go check it out and hear CZ's side of the story. Thank you so much. Have a great day.
Speaker 7:Thank you so much for having me.
Speaker 2:Thank you, We'll talk to you soon. Goodbye. There's some more on the timeline. Bluetooth is such a strange name for technology. Apparently, it's named after a Scandinavian king who united Norway and Denmark, and the logo is a combination of two Norse runes.
Speaker 2:I like Bluetooth. Anyway, let's bring in our next guest Tal Hoffman from Enclave. He's the founder and CEO. Here to tell us my seat around. How are you doing?
Speaker 1:What's going on?
Speaker 9:Hey. Thanks for having me. How are you?
Speaker 2:We're good. Please introduce yourself and the company.
Speaker 9:Yes, please. So I'm Dan.
Speaker 7:I'm the
Speaker 9:co founder and CEO of Enclave. Mhmm. Essentially, we're an AI code security platform using LLMs to build find critical vulnerabilities in code bases
Speaker 2:Yeah.
Speaker 9:The way traditional scanners want. Yeah. Yeah.
Speaker 2:So huge week. Take us through how you've been processing it. From your perspective, what is AI actually capable of doing? What is not there yet? How have you been processing all the news around AI and cybersecurity this week?
Speaker 9:Yeah. I think what Tropic has done is like tremendous for the industry. I think it's a tremendous leap forward for security. I think the really novel thing that they did besides finding the unknown unknowns, the vulnerabilities that have been there for decades Sure. Were able to exploit autonomously vulnerabilities.
Speaker 9:Essentially, exploitability is the name of the game, as I see it. Right? Mhmm. Because a vulnerability that's not exploitable is not worth as much till right now unless something changes. Mhmm.
Speaker 9:So I think it's a huge leap forward, and I think they have done very correct moving deploying it safely. Yeah. I think it's very exciting for anyone that's in code security Yeah. Including ourselves.
Speaker 2:And, yeah, how do you see yourself fitting in? Tell me about the shape of the business, the strategy, how you want to roll out your products.
Speaker 9:Yes. So I think especially with mirrors and the recent changes, I think that it's going to be asymmetrically deployed. And so I think that this creates an opportunity for other organizations that do not have access to the technology to be proactive about it and and for Q, whether it's for to us or competitors. I think it's a net positive for the industry, especially with new attack surfaces being exposed and created and with new teams from regular developers to go to market and everything in between, deploying more code. So I think it's a tremendous opportunity.
Speaker 9:Yeah.
Speaker 2:How are you thinking about interfacing with Project Glasswing? Do you want to fold into that and then be able to do things on top of the private models that are maybe deployed in this asymmetric way? Or do you want to use other models and sort of figure out a different way to differentiate and add value?
Speaker 9:Yeah, no, think we want to go and partner with Anthropic that has done great work and OpenAI and all those big labs. I think the Alpha is currently using them, so definitely want to partner with them. We are talking with them. Again, I think they are doing a tremendous job, but I think ultimately most organizations do not currently have access to this technology. Yeah.
Speaker 9:And they need an independent system level reviewer that's able to constantly, like, deploy the state of the art Tell
Speaker 1:us about the round. You raised some money.
Speaker 9:Yes. Yeah. Yeah. Yeah. So we have raised $6,000,000, led by $8.50.
Speaker 9:And then we have another bunch of exciting investors on board like Aaron Levy. Yeah. There we go.
Speaker 1:Brother Aaron.
Speaker 9:Brother Aaron. Mark Benioff. Yeah.
Speaker 1:Woah. Yeah. You got the dolphin
Speaker 2:in. The dolphin.
Speaker 1:You don't you don't see him him ripping ripping personal checks.
Speaker 2:Last question from my side. What what have conversations been with with customers like who who do you need to get to? Who are the key stakeholders? How how diffuse is the understanding of cybersecurity threats these days? And what are you educating customers about most frequently?
Speaker 9:Yes. I think so. Are just out of beta just to release the product. I think for us, we're trying to cater to both the security practitioners. Mhmm.
Speaker 9:At the end of the chain, like, we have we have seen very we're we're seeing a lot of anger from them. Mhmm. We have their own cloud code, their own PLSR, right, their own shiny object. So we wanna empower them. But I think most importantly, we wanna empower developers to be able to deploy safely and quickly because it's becoming very concerning.
Speaker 9:Yeah. We can see because we have some new zero days that we'll be publishing soon Sure. Following a responsible disclosure. And I think that, like, security is gonna be very big
Speaker 3:Yeah.
Speaker 9:As a whole, the new job. You see how how sexy security has become the last couple of weeks. So I would say, like, argue security personnel, but ultimately, this whole thing is very good for them. You can assume that bad state actors already utilize those those vials. Eventually, as more organizations get exposed to this plow powerful tech that is LLM powered security research, the safer it becomes.
Speaker 9:And I think it's become very obvious. We don't have to do much education. It's like the the opportunity is very obvious. The problem is very obvious. Mhmm.
Speaker 9:Yeah.
Speaker 2:How are you thinking about the business model? Do you want to sit between the code that's written and the pull request and the code review phase? Do you wanna be actively monitoring systems in production? Both?
Speaker 9:Yeah. Definitely both. But we are trying to be, like, to prevent those issues to begin with, whether it's through GitHub or the Pillar two request Sure. Through Cloud Code, MCP, through Kesava. Yeah.
Speaker 9:But also, yeah, definitely also prevent production. And I mentioned exploitability, so context is most important here as look and looking at your and I think this is something that Weis has done a great job with.
Speaker 3:Sure.
Speaker 9:He's looking at the cloud environment, the run at the cloud environment at the run time, see what's exploitable and what's not, because you can have a 10 CVSS vulnerability that's completely irrelevant
Speaker 3:Mhmm.
Speaker 9:Because it's not exposed to the Internet. Sure. So, yeah, we wanna be both preventing but also finding live vulnerabilities. But right now, are focused on code. Yeah.
Speaker 2:Yeah. Makes a lot of sense. Well, on the round. Thank you so much for coming on and breaking it down for us and having Yeah.
Speaker 1:Great to meet you.
Speaker 2:Rest of your day. We'll talk to you soon.
Speaker 7:See you soon. Goodbye.
Speaker 2:Cheers. What else is in the timeline before we wrap up the show? Yahoo's G 800 is at Augusta. If you got really good SEO between 1994 and 1999 then messed everything up after that, your executive team in 2026 will still have a g 800 money says Chris Backey. That is very funny.
Speaker 2:And Preston Holland is chiming in with some crying emojis.
Speaker 1:Secretary Kennedy.
Speaker 2:New podcast.
Speaker 1:The Secretary Kennedy podcast. Coming soon. Derek Thompson says the urge to pod cannot be denied. Tech VCs and David Rubenstein are richer than God. Do they want to do in their enormously valuable spare time?
Speaker 1:Fire up a mic and pod. Yeah. What does Jamie Dimon want to do after JPM? Start a media company, I. E.
Speaker 1:Pod again. RFK Jr. Is in charge of all government health policy. What does he want to do with that power? Pod about it.
Speaker 1:In this, Will highlighted Jeremy's post. Posting is the end state. It's the treasure that awaited Alexander at the end of his conquest. It's all that's left for man after gaining the world. It's all there is at the very end of it all.
Speaker 1:Celebrities, billionaires, industrialists, scholars all wind up as the humble poster.
Speaker 2:Poster. David Rubenstein's podcast is deeply underrated if you're not already listening to it. The David Rubenstein Show peer to peer conversations airs on Bloomberg Television. He's also done history with David Rubenstein on PBS. He is the chairman of Carlyle Group.
Speaker 2:And yes, truly very successful but still enjoys a recorded conversation. In other news, the Acquired podcast just released a new website, acquired.fm.
Speaker 1:Stunning. Many people are calling it the most beautiful podcast website in history.
Speaker 2:It's incredible. Really, really well done. Every time you mouse over something, you get a vinyl record that pops out. I'm very excited to see, the physical instantiation of this. It fits the brand perfectly.
Speaker 2:It's a great, so many iconic episodes, so many iconic interviews. So congratulations to the folks at Acquired. Every company has a story. Really, really well designed.
Speaker 1:We gotta have them back on
Speaker 2:It'd be great.
Speaker 1:Very soon. Yeah. But thank you for being with We'll us see you tomorrow. It's been an honor and a privilege Yeah. To podcast with you today.
Speaker 2:We'll see you tomorrow. Leave us five stars on Apple Podcast and Spotify. Sign up for news alerts.