Jassy's Shareholder Letter, The Next AI Capability, 𝕏 Timeline Reactions | Saagar Enjeti, Joe Weisenthal, Kesava Kirupa Dinakaran, Brian Manning, Cobi Blumenfeld-Gantz, Changpeng Zhao, Tal Hoffman

You're watching TVPN.

Today is Thursday, April 9th, 2026. We are live from the TVPN UltraDome, the temple of technology, the fortress of finance, the capital of capital. We have a great show for you.

I was getting a little worried Monday. There was not a lot of fundraisers going on.

Sure.

I was looking at the schedule and I was thinking, is it over? And today I'm happy to report that we're back. Andrew Dai is coming on from Allurion, raised a $55 million seed round. We got Kaseva coming on with a $38 million Series B. We got a $170 million Series C later, and then a $100 million Series E. And then a nice little Mango seed from the Enclave team to cap it off. But really fun show today. We got Sagar and Jetty from Breaking Points, our friend over there, coming on. We got Joe Weisenthal.

Yeah.

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 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, a good take on that. Anyway, there is a ton of AI news. Andy Jassy released the 2025 shareholders letter. 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. Anthropic's 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. And there's this debate going on over how and when these models will roll out. I think this is gonna 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. 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 of Mythos, although people are disappointed because they wanna 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, you know, brute force reinforcement learning against. But you could imagine if a model develops capabilities maybe 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 sure, 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 scientists from, you know, high schoolers all the way to professionals. 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, I wanted to be a sportscaster. 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. 6 months later, A college classmate convinced me to interview at the consumer products company where he worked, and I spent 3 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 3 days after my last final exam in May 1997. Not exactly a straight line. He says, "AWS followed lots of squiggly lines too." And of course, Andy Jassy is by and large the creator of AWS. That was his major project during his tenure. Founder. 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, but it could also be used for little things like manual translation tasks. People weren't really using it for customer support tickets, but—

Data labeling.

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. 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 succeed. We didn't initially plan a database service and when we built one, our first attempt failed to get traction." We 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. 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, what is going on here? I am—

Out of order?

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 wrong page. Give me a second.

Right here.

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, and as it accelerated, so too did our capital expenditures, CapEx, with a dilutive impact on free cash flow. He's starting to make the case that there's this trade-off between free cash flow and CapEx. This will come back when he talks about his plans for taking advantage of the AI boom. He says, at our 2014, more than 12 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. Why are we doing this? It was confusing. and it was very different from being an online bookstore and then eventually the Everything Store. But 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 band I like from New Zealand called the Beths. Have you ever heard of the Beths? No. 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 a linear straight line.

The best top songs are generally considered to be "Future Me Hates Me" and "Expert in a Dying Field." Interesting.

And "Little Death." Yeah, I'm gonna listen to the Beths on the drive home today.

Any Beths, Bethsheads in the chat?

So 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 into 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. 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. So he talks about how broad Amazon is these days— retail, logistics, AWS, ads, Kindle, Alexa, pharmacy. There are too many new efforts in flight to mention them all. He talks about the long push to bring robotics automation, acquiring Kiva in 2012. He also talks about all of the benefits that Amazon has brought to rural customers, but who are often deprioritized by logistics. This is a 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's been able to solve it through a network of that delivers over 1 billion packages each year, customers living in over 13,000 zip codes spanning 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, 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'll best drive the desired trajectory. He says, "Two is greater than zero." When I was a kid, I used to go to New York Rangers games with my dad. I loved hockey, and it was a high-quality time together. I looked up to my dad, still do, and hung on his every word. One game, My dad noticed that one of the Rangers' defensemen, 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 very weird that his name is Dallas, I guess. Is that the confusing? So yes, it's fairly obvious that 2 is greater than 0, 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, more just investments in the core Amazon business. 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. Reasonable people can disagree, but if you believe you found one of these disproportionate shifts, you want to invest as aggressively as you can. 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, 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 of 2022, it reached 100 million users in 2 months, 4 times faster than TikTok and 15 times faster than Instagram. ChatGPT, our already has over 900 million weekly active users. Both OpenAI and Anthropic have run revenue run rates reportedly approaching $30 billion. 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. 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 gonna 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. The difference is that electricity took 40 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. 3 years after AWS launched commercially, it had a $58 million run rate, 3 years in. And Amazon was already a big business at that time. So, you know, he's talking about, talking about the twists and turns of launching AWS. It's a lot of products.

Seems so quaint.

It's very quaint to be 3 years in, have the backing of a massive company, and still 3 years in, only hit $58 million in run rate. He compares it to 3 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 $15 billion in Q1 of 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 Trainium. Their custom silicon, agent building, secure environments, et cetera. 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 end of 2027. And AWS is monetizing that capacity as fast as it's installed. In Q4 2025, AWS reported reported 24% year-over-year growth and a $142 billion revenue run rate. That's a lot of absolute growth, and yet we still have capacity strains that yield unserved demand. 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, the other projects. 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 Trainium 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. And so there's been a lot of reporting about our data centers delayed, we're gonna have to delay We're going to talk to Sagar and Jetty about some of the news and the political pushback to the data center buildout. He says that it typically takes between 6 and 24 months before we can start billing customers, depending on the component. However, these CapEx investments fund assets with many-year useful lives, 30-plus years for data centers, 5 to 6 years for chips, servers, and networking gear. The free cash flow cash flow and return on invested capital for these investments are cumulatively quite attractive a couple years after being in service. However, 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. He says, "We like the results, even though we've been through that cycle of high CapEx drawing down on free cash flow." He says, "We expect to feel similarly about this next wave with a much larger potential downstream revenue and free cash flow." He goes on to talk about—

Super strong.

I thought it was a very good letter.

Super strong.

Yes.

Different stuff. I think this is what people wanted out of Jassy, like, about a year ago, right?

Yeah.

He was getting— people were constantly chirping at Amazon leadership and wanting some kind of, basically, lay of the land like this to show that Amazon had a broad understanding and actually had real leadership and was committed, committed to, you know, being, being a real player.

Yeah. Well, in other Amazon news, Amazon Pharmacy to offer Eli Lilly and Company's new GLP-1 pill Foundeo via same-day delivery. Shiel Monod says this thing is going to fly. Amazon is up 3%. I don't know if it's on this news.

It's hard to say. Amazon's actually on It's almost up 5% today. And I would expect that to be because of the letter, but people tend to buy a lot of GLP-1 drugs too.

But it does seem like a good— I mean, we were talking about this with some of the fast ramp of that one company in direct-to-consumer GLP-1 and peptides, and there's so much skepticism 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 established as Amazon with all of the guardrails that they have in place feels like a very positive move for consumers.

Before we jump into the next story, Jassy did share letter to shareholders from 1997.

Yeah.

And there was— I'll read the first two paragraphs. To our shareholders, Amazon.com passed many milestones in 1997. By year end, we have served more than 1.5 million customers, yielding 838% revenue growth to $147.8 million 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. 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 so, hopes to create an enduring franchise, even in established and large markets. Well, they certainly did that. And the letter goes on. To talk about how it's all about the long term. So even back then, growing like absolute crazy, still wanting people to think about, think in decades. And so Jassy doing that now. And they have a good track record.

Yeah. Amazon's had decades of drawing down on free cash flow to invest in the future. And they've had long history of communicating that effectively to to the community and to the shareholders.

Well, the 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.

We miss the ads too.

Yeah, all we have now is. Well, we need it. We need some alerts because there's a debate on the timeline about OpenAI's new cybersecurity product. 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. 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? 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 extra commentary around this. The Axios story floating around about OpenAI limiting the release of their newest model, Spud, isn't true. 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.

Yeah, there's a very, there's a very strong argument to never release a model publicly that is specifically optimized for cyber Yeah. Because like you're just inviting a bunch of— like think about like the teenagers out there. I now get to be 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—

You would think having some cybersecurity capabilities in the model would just be better if you're vibe coding a product, it becomes secure out of the box.

Sure. I'm just saying, I'm just saying like— having this super powerful, like, cyber-focused product shouldn't be the kind of thing that anyone— like, you should probably have to KYC to see.

Yeah, sure, sure. Well, yeah, what do you think about this?

Yeah, I mean, also, I think, you know, when you zoom out on AI progress, it is like very smooth. 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 and you actually run enough times, you actually can find similar exploits, and it's just like kind of the efficiency of the new model versus the smaller open-source ones. So like, 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. Like, people have the capabilities right now. Maybe it's like a little bit harder.

You might get flagged. Sure, yeah.

But, and also like, yeah, I think, I mean, at some point, like, a 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 there's like big security vulnerabilities.

Yeah.

Even right now you can just ask, you know, Codex, whatever you're building something like, are there errors or are there, you know, security problems and it will solve them.

And this is the nature of 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 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 lot of precedent for this with bug bounties and timed disclosures. So oftentimes white hat hackers will go to companies and say, "We found a really bad vulnerability. We're giving you 90 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 fix it." react to this, and so it feels like you're sort of holding that company hostage a little bit. It can be a little bit tense, but I think if it's done carefully, it can be sort of a win-win.

But I think regardless, I think more KYC is probably the future, right? Even if you're just talking about risk of distillation and stuff like this. I think I've talked about this before where at some point you need more KYC. To ensure like people aren't just like, you know, training off the model or doing like nefarious things.

Yeah. Yeah.

Meek Mill pulled out a slide from Bill Ackman. The slide says a small percentage of songs are listened to. The overwhelming majority of music tracks receive zero or minimal engagement. AI is poised to exacerbate this reality. And so it shows that 0.2% of songs are culturally and commercially relevant. Commercially relevant is 10% of songs streamed 1,000 to 100,000 times. And then Meek is dropping that into what looks like Claude saying, you're not in that 88%, you already skipped the whole bottom of the pyramid. You're already in that top 0.2%. People know your name, they search for you specifically, they stream on purpose. That changes everything. You already have the hardest thing, attention. You don't need the algorithm to to find you. Your fans already look for you. So while AI is flooding the market with millions of trash songs, this is AI throwing AI at the guys. This is crazy. Your catalog just sits there collecting streams because people want Meek, not just a rap song. And Dimes Square Holding says, first in my bloodline to see a rapper with AI psychosis commenting on a deck from—

I think it's a reasonable—

It's a reasonable analysis.

It's a reasonable analysis.

I just think it's a little bit unfair for the AI to be dunking on the other AI.

Yeah.

It's kind of like a crabs' bucket.

There's a whole story about this in the journal the other day about 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 organize, who they should be calling. It sort of feels like a good use of AI in the sense that they're exercising their democratic rights properly through the correct channels. Like, it could be so much worse.

I don't know.

What do you think?

Yeah, well, hopefully like by using the model, like models enough to be like, oh wait, this is actually good.

Yeah.

Yeah. Or like, there are some parts that I like narrowly. But do we need this data center in my neighborhood? Maybe not.

And yeah, and they can also specifically on this, 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.

Oh, interesting.

Lil Baby. Yeah, Lil Baby, not Lil Baby. Okay. There was a post yesterday about someone who got paid to like set up OpenClaw for him. Yeah, you've seen this a bunch. Yeah, it's just funny. Like you don't see actors talking about—

Baby Keem.

Lil Baby was second after Baby Keem.

Yeah, that's right. That's right. I mean, Matthew McConaughey had some words about AI.

Oh yeah, when he was going to log in, he needs to log in.

Well, no, that was separate. Like, wasn't it like months? 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.

Yeah, but he's not talking about his specific.

Yeah, exactly. Exactly.

Yeah. I guess Ben Affleck had that company, right?

Yeah, yeah, yeah.

Ben Affleck already got the 9-figure exit. He's good.

Yeah, but you would imagine 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 economic impact, how many jobs will be created, what's the environmental impact, and being able to crunch through all those trade-offs so that the community gets to a net positive impact that the population can basically vote on and be happy about and say, "Yeah, we made this trade-off properly and we feel like we're getting the benefit." Because maybe it's generating a lot of 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 or is it going towards a project that people don't actually support? 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? It depends on what the city is building or doing with that revenue. Anyway, what is this post by Eigengender?

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 Dyson Sphere and then someone Someone's coping and just saying like, "Yeah, I mean, it's not that impressive." You're just watching the Dyson sphere be built around the sun thinking like, "Oh, 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 were seeking clients that claim to be harmed by social media while under the age of 18. And so there's been, these class action lawsuits have been a big, you see them on social media all the time. Usually it's some sort of data breach or some sort of random product that they're targeting you for. And I feel like many people just sort of scroll past them because 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? 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 than a dozen such ads that 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 and Messenger, plus Meta's Audience Network. One such ad read, anxiety, depression, withdrawal, self-harm. These aren't just teenage phases. They're symptoms linked to social media addiction in children. Platforms knew this and kept targeting kids anyway.

Yeah. So Meta has something in their terms of service that says we also can remove or restrict access to content, features, 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.

Huh.

Just basically like, we're not gonna let you use our product to take legal action against us.

Yeah, I wonder where the class action recruiting will go next.

You know, it'll go everywhere else.

Out of home?

Out of home.

Yeah.

Could go podcast, TV.

I mean, it's such a broad base that— yeah. Well, YouTube is another one.

It's relatively easy to reach Facebook and Instagram users.

Yeah, especially young people.

It's everyone.

It's everyone, yeah. So they just need to cast a wide net. But it'll be interesting to see how that develops.

Has anyone built an out-of-home advertising network for classrooms?

Classrooms?

What do you mean?

Like teachers?

I don't think people want to advertise to kids.

No. Kidding, kidding, kidding.

Anyway, the spreadsheet will become irrelevant, says Buco Capital Bloke. No, the spreadsheet is eternal. The spreadsheet paradigm is capitalism. The two are irrevocably intertwined. We were using spreadsheets 3,000 years ago to trade oxen. We will still be using them in 3,000 years. Long live the spreadsheet. And he shares a a stone tablet that appears to be a spreadsheet. This is in reaction to Signal's post that Microsoft 365 and Google Workspace have maybe 4 to 5 years of relevance left simply because the document spreadsheet paradigm itself will become mostly irrelevant. 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, Chat status updates is heading towards agent-mediated flows where humans set intent and AI handles execution. I don't know. I mean, it is like both can be true here because 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 only possible to build that so fast. Cloning Google Sheets used to be insane. We had some luck cloning Slack recently.

Yeah, our intern built a very, very convincing clone.

It's so crazy.

Slack in about an hour.

Yeah, I think it was on the— was it on the $200 plan?

Oh, wow.

That's incredible. So yeah, I think there's still the question of actually getting that to feature complete, maintaining it, really 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 not a firm believer in the near-term SaaSpocalypse broadly, but it does— I think the more likely scenario is that you will see software instantiated 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 requires sort of building a timeline or a chart. It can write Python, it can write HTML that will generate—

The other thing is just giving customers a lot more flexibility around the product and thinking that like, okay, if you're buying a piece of software, it'd be like buying like a home. You get the home and then you can make changes to it to fit your own needs over time. And so we'll see what ultimately changes, but you can imagine I can imagine a world where, you know, it stops being— I forget who was on the show, but they were talking about how— oh, it was Console.com. Talking about how instead of having, like, a request a feature button, you just let people build it themselves.

Yes. Well, there's been some back and forth on the timeline between Nate Silver and Nikita Beer over whether or not 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. 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— any changes in the algorithm with respect to how links are treated. As you can see, it's pretty clear that starting around the spring, summer of 2023, posts with links started to be penalized and eventually they were completely nuked until the spring, summer of 2025 when a reversal to that policy seems to have started. 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, 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 the, like, Google Docs, basically, and those would still rip somehow. And I don't know if that was, like, a specific link, but—

I think one thing has remained true the entire time, which is that if you are linking to content that is genuine, genuinely very interesting, it can still do numbers.

Yeah. And there is a little bit of maybe some feature of The New York Times where if you spent a year or two on X knowing that, okay, like there's sort of this adversarial relationship with links, you're gonna open it in the browser, you might actually just develop a different habit of, okay, I go and read the apps. Like I definitely developed the muscle memory to open the Wall Street Journal app regularly and scroll that newsfeed separately. And I don't really look for as much cross-pollination as, as I thought. Anyway, we have Sagar and Jordi from Breaking Points in the waiting room, so we'll bring him to the TV panel. Sagar, how are you doing?

I'm great, guys. Thanks for having me.

Thanks for coming on. Where should— let's start with the data center thing. Chassis. Oh yeah, yeah, the tie is—

I'm getting brutally time out.

Yeah, um, dude, uh, Jordi gets an exit and immediately starts dressing like a tech asshole. What's, what's going on here, man?

All right, to be clear, I've been, I've been having—

I, I have the limited edition Technology in Motion.

Okay, well, why has nobody sent me one?

How come?

Oh yeah, yeah, well, these are dropping, they're in the works.

We'll send you one.

You're going to be— you're going to get to wear TVPN all day long.

Yeah, that's great. So we were talking about Andy Jassy's 2025, 2026 shareholder letter, $200 billion of CapEx, tons of new data centers coming online. Every— this applies to every company.

You were hoping for a bigger number.

Yeah.

Oh yeah.

I mean, of course, as an American, I just want all of my farmland. I want all the trailer parks pushed out and I just want to 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 billion, $600 billion, something like that.

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 pointing to, the case studies that people are nervous about, energy impact specifically?

Well, I think especially, guys, you know, this is a pre-Iran war conversation. There's a post-Iran war conversation. I think that's 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. 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 Jashinsky actually talked to me about this, but a Wisconsin city has now been the first in the nation to actually pass an anti-data center referendum. 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, okay, on my show. He was a longtime viewer actually of the program. He was just like a normal, uh, activist type but hadn't really engaged with it. 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, I got to see a little bit more evidence for myself. Real quick, is your— go ahead—

is your mic— I, I don't know that we're— you're on the correct mic. We might be on the game, 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.

The chat thinks it's If a foreign adversary doesn't want to be on the mic right now.

Let's hear if it sounds any better now.

Is it a little better?

Oh yeah, I think that's great.

There we go.

Thank you. There we go. Amazing. Okay, so 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? How do you think this— where do you think this goes?

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 where I live, 40% of our power is actually consumed by data centers. And so you've seen organic pushback. It became a major issue in the gubernatorial campaign. Both the Republican and the Democratic candidates were against data centers. 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 going to 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 million for her land. She's like, I'm born on this land, I'm gonna die this land. So 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 going to be a major issue in '28.

'28. I think in '28 both candidates are going to have a data center platform. Maybe the Republican one, depending on who it is, is going to 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.

Is the sense in Virginia that Virginia would, would be better off if the state had never had a data center?

Well, it's complicated. Remember, you know, we're full of a military-industrial complex. But, uh, don't forget this: we had Amazon. Remember when they were going to leave New York and they were going to come here? They're actually going to come near where I live. 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. 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 going to be the military-industrial complex and all of these, like, ridiculous server farms that serve the CIA and the Pentagon. But I mean, in Oregon, I think it was 30% of power in the state of Oregon is being used by data centers. There's like 20% in a few, uh, different states. Virginia is definitely— we were the highest in the nation. But 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. And I've talked about this before, guys, do you know what it takes for a voter to actually care? You can barely get people to come out 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 able—

what is your—

what is your advice for, uh, the data center developers out there?

Because certain—

certainly, I, I like— you feel—

you feel—

let me—

you don't think that we should just not build any data centers?

It depends. You know, I don't know. I mean, I'm becoming more radical 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. Shout out to you, Sam. But I mean, look, I'm not giving any advice to the enemy. I think really what I would say to the tech community more generally, and John, you and I have talked about this, is just prove to me that this is going to make my life better. And stop talking about all these scary things because I'm starting to believe you. In fact, I do believe you. What is this new Claude news that their new model is so scary they have to pre-release it to the cybersecurity companies so that they can develop— so no, no, so that the new model can develop defenses against itself.

We're very much with you that the fear-based marketing like needs to stop because because it's not, it's not helping anyone. Like, part of the whole background.

But I don't know, guys. I mean, Jordi, 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 to go and be like, look, we're changing the world, we're going to destroy all these jobs. But like, I don't know. I mean, for, for, let's say like with Anthropic, I feel like—

so my point, my point was that it was very effective when there was no revenue in the industry, right? Yeah. 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 and they got a good answer. Like 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 know, writing any of these things that like now everybody's had the experience of. It clearly like was necessary necessary to kind of marshal enough capital for a bunch of upstarts to be able to compete with the biggest companies in the world on this, like 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 think we need to stop this as an industry because why would average American be excited about this if you're just trying to give them, you know, Terminator nightmares? But clearly the entire, you know, some people in the industry still feel like they need to, uh, because they think they really believe it. Yeah.

Yeah.

No, I think they believe it. That's, yeah, I'm with John. Like, I feel like Dario believes it and he just goes on every podcast in the world and says it like over and over again. And at a certain point, especially like with the new cloud 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 I mean, you know, you can only call yourself the new digital God so many times before. Look, again, I'm a Luddite. 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 want to 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. I would just be real careful about strolling around town and talking about how it's going to bring jobs in because, A, nobody believes you. All think that their bills are going to go higher. There needs to be— I think what this really needs, guys, is I don't think it can 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 going to have to supply the initial amount of energy that it's going to use. It 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 going to decide like this is cool for us. 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. I was about, I was going to 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. I don't really agree with some of the stuff he laid out, but yeah, Yeah, anyways.

Yeah, it was notable. So Demis had an interview with Harry Stebbings this week. It's just 30 minutes. You would probably appreciate it because Demis is one of the godfathers. And he even was kind of talking about potentially, you know, one solution to this is like sovereign wealth funds, like investing in the labs, getting a piece of it so that every sort of citizen benefits I thought that was notable because it was, you know, Google and, you know, the Gemini team is the most heavily funded lab in the entire world. And so we'll see how this stuff works out. In Virginia, Tyler on our team just dropped a truth nuke. He said in some localities in Virginia, 31% of total local tax revenue is from data centers. Is there, like, do you think that, like, I guess, like, part of what I'm trying to wrap my head around is, like, 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 local tax revenue would be a net positive, right? Maybe. And I believe that you're right, that individual areas should be able to decide, 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? But there are places in the United States where people have decided we're gonna drill for oil here and we're gonna, you know, be okay with those trade-offs. And so I think I generally, 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 needs to be, there needs to be some positive benefit for the local community. And so I think we agree there because—

You're not gonna be using the models.

Totally.

Because the data center could be halfway around the world, or—

and you still get, you still get access to all the AI tools that you want. It doesn't need to be in your backyard.

And so, and yeah, but I believe that to Tyler, yeah, uh, who's in the chat, uh, but I mean, 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 The promise is a lot of these things don't end up happening. Come on, guys, this is a tale as old as time. Every state in the country, remember when Amazon did that ridiculous pony show for every state to throw whatever it could to them and then they ended up, yeah, for HQ2. That's the project I'm talking about is that Virginia where I live also did that. 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.

That's what I'm saying.

Okay. And I also think the Fed's 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 reacted to market swings. One of the fears that I had really was that a lot of this, you 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, or 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, I believe. A couple of different tech infrastructure places were explicitly declared war on by the Iranians. So I do think that there's an element here where 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 40 years now— I mean, before data centers, it was Walmart, and before that it was something else. There's always going to be like a small guy versus big guy feeling, especially in rural parts of the country. And, you know, I'm from Texas, Jordi, with the oil industry. So I get exactly what you're talking I'm talking about, right? 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 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 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. 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, I want a say. And I don't think they're wrong to say that.

Yeah, I really don't know. For, for getting some sort of resolution on the federal level, is that like a new Bill or something, or like, obviously this is gonna happen 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 buildouts. Like, is there a world where the, like, a good data center exists in the sense that it supplies its own power with clean energy? It's not an eyesore, it's either buried or covered in trees or beautiful. 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?

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. I read it once, a report of a guy who just came from China, and he said nobody in China cares about power with data centers because they have a ton of power. He's like, we have energy, dude. He's like, bro, we don't care. He's like, yeah, you can build, you could build a data data center, we're good. Like we have cheap and abundant power. 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 on the power generation level, and this is why, you know, I'm a huge advocate of nuclear power plants or whatever, renewables, I don't even care at this point. Shale gas, let's put it all in together. But I actually think our grid and the delay of our grid 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. It doesn't need to be this way. Like really what we need is just a ton of power. If we have a ton of power, then we don't care about anything being built.

Yeah. So is codifying the ratepayer protection pledge into law a good move?

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, level and on the political level. Uh, I recommend you follow Ryan Groduski. He's done some more recent work, uh, on the data center question. 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, uh, position. He's, 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, 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 know, 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, that's about the whole picture of like technology and oligarchy and the economy. So you're fighting against a very, very big force right now in the country.

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.

Have you tried, just outta 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 few weeks?

I should try. That's a good idea.

I want the, like, you should, let's get you a backup. Schedule for a few weeks from now. And, uh, you will not use any, any AI at all until you're—

guys, it'd be so hard because even the chessboard behind me has built-in AI. It's everywhere. Yeah, it's got the built-in AI.

No, it's fine.

You can just—

no, just don't play chess, bro.

It's fine.

I can't do it. Just get a— just get an old-school board.

I've been one-shotted by the game. I've been completely one-shotted by the game.

Anyway, yeah, thank you so much for coming on. We'll talk to you soon.

Great to see you.

Great to see you.

Appreciate it.

Always helpful. We'll talk to you soon. Up next, we have Joe Weisenthal from Bloomberg and Odd Lots here to break down The New York Times analysis of the strongest Satoshi Nakamoto candidate. Joe, how are you doing?

Look, I'm good.

Look at that sweater.

Yeah.

What do you think?

You look fantastic. I love the green.

Incredible.

You think the green works?

Green here. Green is great.

And the colors coming out the top.

That's actually what I meant. I— when I said, what do you think? I was like, oh, actually, I'm wearing TVPN green.

Yeah, yeah, exactly.

So perfect.

Yes, glad you guys noticed the gesture.

Well, welcome back.

It's nice to see you guys.

Is, is the New York Times the most underrated company in the world?

Yeah, of course. It's the— it's the most— the— yeah, of course it's the most underrated tech company and the most underrated news.

Gaming.

The number of haters Yeah, the thing though is, to be fair, that's the hater comment, like, oh, it's just a gaming company. But look, like, it's an 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. And yeah, yeah, 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 the topic at hand. 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.

Did you have a candidate in mind before this piece dropped? Had you watched the HBO documentary that actually pointed to a different suspect?

Yeah, I've read a lot. I actually didn't watch the HBO documentary, in part, I guess, because it was just so heavily criticized, etc. They're like, maybe I don't need to watch it. I had often, often found the, um, the Nick Szabo— he's one of the candidates— I had always found that one to be fairly compelling.

Yeah, me too.

And, you know, on my first read of the New York Times piece yesterday, I thought about Adam Back, like I knew he had been in the mix.

Yep.

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 or an email. It didn't have that. It was sort of like— a lot of it was sort of linguistics, like, oh, he makes its and it's wrong, or hyphens wrong. I make those same mistakes too. I don't know, everyone, everyone makes those mistakes. So I wasn't totally convinced.

Yeah.

But then I read it a couple of more times over the last, you know, 24 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, that it is John Kerry. You have correctly, has correctly identified him.

Yeah. What have you worked with any journalists like John Kerry 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, really, he had the space. I have breathing room.

No, I love it. And like I said, But 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, a handful of journalists have like, I can be the one to crack this, which actually brings to my mind one of the more fascinating aspects of Bitcoin period, which is, it's amazing to think that like, OK, here is this thing, it's kind of like a digital gold and so forth. New kind of money. And whoever Satoshi is, he or her, group of people, whatever, maybe it is Adam Back, maybe it's not. But the OPSEC, I mean, can you even fathom being online for several years in a way that could not be traced back to you definitively? I wouldn't even know where to begin. 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 like this founder-creator myth, this sort of the divine birth by this entity that left almost no earthly trace is as much as a fascinating part of the story, almost as Bitcoin itself as a technical accomplishment.

Yeah, and also just the fact that then Satoshi, it wasn't an effort to remain anonymous in perpetuity. It was like, Then Satoshi went dark, and nothing's moved on the wallet. And it's just been this— that's obviously fueled the theory that potentially Satoshi passed away or something.

Yeah. So here's a question that I have. So one of the stronger arguments, or one of the pieces of evidence that the article in The New York Times points out, is that Adam Back is well known. He has a long history with the cypherpunks. He'd been interested privacy and digital money for a long time, going back to at least like the mid-'90s, et cetera. He had invented Hashcash, which was, you know, basically laid the foundation for proof of work, which of course is elemental to mining. 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. 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. 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. So, 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 going to have to talk pseudonymously or anonymously. That is not entirely obvious to me.

Yeah, yeah.

Uh, like, again, in retrospect, like, sure, like, in 2026 we could look back, yes, it makes a lot of sense that this person would have liked the pseudonym aspect. But when it's just a bunch of people, I don't know, part of a community trying to solve the problem of P2P payments who have been using their names. Why suddenly, like, when 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— BCash, HashCash, digital gold, etc. That's not totally obvious to me.

Well, the way that— I mean, the way you're talking about it is that I'm becoming more suspect that it was in fact you.

So this is a, yeah, wait, John, it sounds like you don't find this component.

No, I, yeah, I just, 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 motivations of that individual could be questioned and there's so much like, like risk tied to like a single person. It doesn't strike me as that crazy. I mean, clearly someone went anonymous, right?

Yeah, one exercise is like, is there a person that if it came out and we could determine that it was entirely factual that this one person, who's the kind of person that would make the Bitcoin sort of trade up in value, right? Because there's like, I can't really think of anyone. I can think of a lot of different groups that it would trade down dramatically. It comes out. Some government entity, you know, that goes down dramatically. And so there's not a lot of ROI for anyone on a personal level.

Well, one of the funny things about Adam specifically, if you go to his Twitter profile, it says, you know, lists his accomplishments, and it says he is the inventor of HashCash in parentheses, Bitcoin mining. And what's funny is many people over the years have actually accused Adam of overstating what his claim there. It's like, 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. It is a sort of a thing that precedes— it was one of the antecedents antecedents or the proceed— whatever— to Bitcoin mining, a similar technique, the whole proof-of-work concept. So there's been this claim that actually one of his issues is that he overstated his invention, a role in the creation of Bitcoin, which is very funny. Like, if it turns out it's him, that for a long time the accusation was that he overplayed his role. And then the other thing that's strange is that, like, since, you know, he's had— like, so, and 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 MicroStrategy-like entity that was just going to hold a lot of Bitcoin. And does that sound like something Satoshi Nakamoto would do? 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 stuff that feels a little bit scammy, feels a little bit cheesy, feels a little bit like Um, this guy is definitely broke.

There's no way, there's no way, there's no way he's got, you know, the tens of billions of dollars.

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 MicroStrategy company. Yeah, this does not seem very likely. But then the flip side is, man, if you were someone who like maybe some suspected being Satoshi, what would be the thing that would be the least Satoshi-like thing to do? And throw people like up, maybe it would be like create a Bitcoin treasury complex.

Or if you were Satoshi, but you lost the keys in some sort of silly mishap, then you would want to get back in the game because you're still a believer, but you don't have access. Anyway, last question.

Yeah, yeah, sure.

Yeah, last question on the Bitcoin thing. Did you ever go down the Paul Le Roux route? And were you ever a Paul Le Roux believer?

No, I was never a Paul Le Roux guy. Which one was that?

So he was a former criminal cartel boss, informant to the US 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, At one point, he didn't just own a 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.

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 is, I've always thought, like, that— 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.

Okay.

And it's about the prehistory of Bitcoin. So it's about this community of the cypherpunks in the '90s and '80s, and actually even going back to the 1970s.

Yeah.

Where people were talking about this fact that as the world was going to 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 on the internet. 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 3 decades or more before Bitcoin had been trying to solve this problem. And so like in the New York Times piece, it points out that Bach had been talking about all of these things that Satoshi had been talking about. And my first response is, yes, there were a lot of— of course they did, because this was this core group of people who for years understood that in the online context, if payments were ever going to be a thing, we would need a third party. And if there was a third party, they can block a transaction, they can reverse a transaction, they can penalize you for making a bad transaction, etc. 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 that they were all using roughly the same analogy. Technologies and so forth.

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 Paul LaRue. I think it's called The Mastermind. And I believe it was optioned into a movie. I'm not sure. I think Michael Mann was going to do it and that sounded really good, but the book is fantastic. Anyway, is—

This sounds really fun.

Has this been like a nice reprieve for you from covering the war? How have you been processing the constant gyrations in the oil market and the broader financial market? It feels like such a hard thing to cover, but obviously, you've been doing a great job with Odd Lots and beyond.

Thank you. The stakes are— it is a hard thing to cover. It's an awful thing to cover. It's a war, and wars are awful, and the stakes are so— there are so many ways that wars can get more— as catastrophic as they are, get even more and more catastrophic. So it's like, you know, it's a— 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. But the degree to the fallout, whether we're talking about fertilizer, whether we're talking about—

Real estate in Dubai, you guys had a great—

Real estate in Dubai, of course, which real estate in Dubai, which you guys probably know more people than myself, camping out to Dubai for the low taxes and stability, and then suddenly, you're like, oh, this could be—

Honestly, credit to Americans. Americans, like Dubai has just not been that popular.

I think it's different.

I think it's more of a British.

It's very much a European thing. When I was out there, I mean, it very much is like a melting pot. I've been there a couple of times and very limited number of Americans. And the Americans that are there for the most part, aside from on like scheduled fundraising trips, are not really in the same type of like business community that you and I are in.

Yeah, it does seem like more of like a British thing specifically in terms of like going there for the low taxes or the stability, etc. 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, then pain points that are being felt in Asia specifically and how they're already having to go into sort of like a 9 1970s 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 day.

I mean, the economic reverberation, I mean, it's clearly the biggest sort of global econ story since COVID Yeah, I was reading this article in The Economist this weekend in Buttonwood about how it feels like the market is not actually able to process what what a 20% decrease in oil rates is. 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 key stat that they were latching onto was that even if everything was world peace tomorrow, just bringing resources and infrastructure back online, just starting the flow and moving the ships again, 3 months, 6 months, and so you will see reverberations through the economy for months, if not years, even if we get a good outcome immediately, which is what we're all hoping for.

Yeah, some benign outcome. But this is the weird thing, and you're spot on, and this is the weird thing, which is that if you talk to the commodity guys, they're like, this is unbelievable. This is a scenario that we couldn't even really have contemplated. And then you look at the stock market. And oil is up a lot. It's not like oil markets are not registering. It's up a lot. But then you look at the stock market, and it's flat on the year, like as of the time I walked, or it's like down 0.3%. I mean, it's stunning, because you have to remember that 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 2 months of the year. Of the year, 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. Like, it's really hard. Like, you know, I try to— I'm sort of an EMH guy. And so I always think if I'm missing something, I just trust the market. It's very strange. It is very strange.

It is very strange. 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— there was political chaos. We were talking about the tariffs and whatnot. But it felt like broadly most industries were sort of seeing reasonable advances. Things were much less controversial. And we're in a much more tumultuous time.

I mean, it's hard to disagree with that. I mean, I think that there's basically— I think most people say there's basically there's really two parts of the economy that are growing, and one is anything related to AI and data centers, etc., obviously. And the other is like home healthcare jobs. And I don't think much has like changed on that front. And unfortunately, like, okay, like again, let's just go back to the world of February 26th 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. Now, there's a reason to think maybe it's down, maybe we have some softening, etc. But even with just essentially 2 cylinders out of— I don't know if the cylinders analogy is great, because I don't know how many cylinders, but 2 cylinders really firing, like, okay, ongoing need to provide people healthcare and then AI. Even with that, the economy was under a certain level of strain with price stress.

Yeah.

And so, then you add in, okay, now, all forms in terms of commodities are going to be more expensive. There's 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 healthcare? I have yet to see. I don't know. I'm certainly not feeling white-pilled. To the extent maybe the closest is like, look, I would say there's still evidence a little bit out there that, for example, we're not seeing the evisceration of tech and software jobs the way some people might have anticipated. And it continues to be like evidence like, oh, actually, like, that's 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. And so it's white-pilling in the sense maybe we don't have like the total evisceration the sort of the labor market. Yeah, like that part. We actually got a good jobs report last week on the Good Friday report.

So like I said, there are things and we trust all the jobs reports now. We could definitely lean on the revisions have been a little tumultuous for me.

There have been a lot of revisions. It's very tough to measure the economy, but I, I salute our brave statisticians at the Bureau of Labor Services.

And we did and we did talk to some other folks who were looking at like private market data, payroll data. And there were green shoots there as well. So I'm optimistic that that holds. Yeah, 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 polls very poorly. Poorly, so there's this difference there.

What does NPS stand for?

Net Promoter Score, or like approval rating. So like people might give ChatGPT directly like an 80% approval rating, and it has like a lot of good reviews in the App Store, for example. And if you just ask them about that or what they're building with Cloud Code, they'll say, oh, they'll tell you an amazing story of some custom software that they built for their business that they would've had to spend $1 million on consulting group to do it, and it maybe would have been really tricky to get it to math out. But then they'll just tell you like, oh yeah, we needed this dashboard and we just made it in a day or a couple of weeks.

So people love their specific things they built, but then it's like, but also, the abstract is terrible.

Yeah, they hate the abstract. Yeah.

No, I mean, look, I mean, I think this is actually seems to be a recurring phenomenon. People have even over the last several years, to some extent, said this about the economy generally. Like, I'm doing okay.

Yeah.

My financial situation is actually fine, but the economy is like really terrible. So it would be kind of interesting, like if maybe there was a pattern that we're seeing across domains where, you know, everything else out— I like AI, I like how it's doing, I like this thing I built, etc. It's all terrible. Maybe that's just sort of like a general disposition that people have towards a lot of things.

Yeah, it's the Kyla Scanlan vibe session concept.

And you're like, people, maybe they're happy in their media, maybe they're happy Or they're happy in their relationships, but they're like, oh, but dating for everyone else is a total wasteland.

Totally.

Jordi Hays, last question. Any prediction market predictions from your side? What do you think?

We had an episode— we have an episode out today with Tomas Petterfi, the founder of IBKR, which is also one of the most impressive trading entrepreneurs. They're getting prediction market— they're really getting into prediction markets. So I think my prediction is that it's not just going to 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 like a year ago.

Yeah. No, makes a ton of sense. Well, thank you so much for taking the time to come chat with us.

Great to see you, Jeff.

Take care.

Thank you. We'll talk to you soon.

Cheers.

Our next guest is Andrew Dai from Ellorian. He's the co-founder and CEO with a big raise coming in to the TVPN Ultra Dome. Let's bring in Andrew from the waiting room. Andrew, how are you doing?

Hi, good, thanks.

Thanks so much for taking time to join us. 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?

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, went to the University of Cambridge for computer science, and then I went to the University of Edinburgh for my PhD in AI.

And what did you work on when you were at Google?

At Google, I worked on a whole bunch of things. I worked on Google Now. I worked on Smart Reply and Smart Compose. But really, I had a paper about 12 years ago where we proposed language model pre-training and supervised fine-tuning. And that's the paper that all the GPT papers cite. And here we are today.

Wow. Turned out to be a big deal.

Yeah. Yeah. Did the—

Wait, wait.

Yeah, sorry.

I don't know if you're going to dig in deeper there, but at the time when you were writing that, how much conviction did you have around the paradigm? Did you expect—

And scaling laws in particular?

Yeah, I knew it was going to be something big. And I could tell because when I was giving my poster at NeurIPS that year, one of the inventors of of like LSTMs, which was the biggest model at that time, they said it just works. Like the method just works. And there I could tell, oh yeah, there's 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.

Yeah.

So did you go to NeurIPS this last year?

Yeah, yeah, I did.

How has it changed?

It's all LLMs now. A lot of language.

And VCs. A lot of VCs sneaking around too.

Yes, a lot of VCs.

That's right. Well then, yeah, take us through this company, the decision to launch this company, what you're thinking needs to be different about the current strategies employed by AI labs.

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. That's been very effective, right? We have new paradigms in cybersecurity right now. But the visual capabilities are kind of getting left behind. And there you have problems where the models are on visual problems at the level of like a preschooler, of like a 3-year-old.

Can you give me an example of that? Yeah. What does that look like? Like in practice?

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 balls 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.

Yeah, so I've seen sometimes the reasoning models will ingest an image and then wind up writing a bunch of Python code to basically count pixels and do things 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 writing all this math 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 is sort of underwhelming. But how are you thinking about the actual development and what you want to do differently? Are you focused more on a new architecture, new data sources, more scale? What's the shape of your strategy here?

Yeah, so we are basically a full-stack team. We have experience with pre-training and data multimodality. So 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. So we expect to be running the full gamut of changes. And this is really needed to really make a breakthrough in visual reasoning.

What does good training data look like today? Is it synthetic? Is it images, videos, 3D, virtual worlds? What's the shape of what's valuable?

As you can expect, it's a bit of everything.

All of it.

But yeah, 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 a weird place where it just outputs like M-dashes or just tries to repeat the same thing all the time. But yeah, data around the natural world, around the 3D world, that's invaluable.

What do you think the cybersecurity analogy is for visual reasoning? 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?

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 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. 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.

Make sure like everything is correct. And that's because there's not really any reasoning in our visual reasoning, our current models. And so we think there's a huge potential.

One of the hardest times we've ever laughed on this show was reacting to 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. Toilets and two baths, and it had one big— it didn't really understand the problem. So very exciting. Well, you raised some money. Tell us about it. How much did you raise? We want to hit the gong for you.

Yes, we raised $55 million.

Congratulations.

From who?

And that's from Spiker Ventures, Menlo Ventures, Ultimata, and NVIDIA and 49Pounds participating. And we have some great great angels there, including Jeff Dean.

He's been on an angel investing tear. 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. Well, thank you so much for taking the time to come chat.

Great to meet you, Andrew.

We'll talk to you soon. Have a good rest of your day.

Cheers.

Up next, we have Luminai and Cassava Dina Khorram in the waiting room. We'll bring him into the TVPN UltraDome. They have raised a $38 million $1 billion Series B to scale AI automation for health systems. How are you doing? Good to see you.

What's going on?

Doing, doing great.

Great to see you both.

Great to see you. I believe it's your first time on the show, even though we've met in the past. Please introduce yourself and the company.

Yeah, I'm Keshav, one of the co-founders and the CEO of Lumenai. Help large health systems drive automation in their operations and back office.

What is— so is this a diffusion story or is this —like a foundational AI research problem? Like, what is the secret to actually driving improved health care outcomes in these larger organizations?

Yeah, I think the models have kind of got to a place, probably in the last maybe 6 to 12 months, where some of the opportunities to actually drive automation end to end in a very reliable manner 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 many ways. And so you're kind of at this opportunity now to dramatically change how, how it's done in the first place.

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?

Yeah, I'll give you a very concrete example. So imagine, like, you know, 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, 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. Referral, right? And that referral basically gets sent from, you know, small clinician practices to massive hospitals that are based in, you know, even all the way from the Middle East. And they're all unfortunately, or at least at Illumini, sent via a fax machine. And these are sort of documents with handwritten notes where people are sent saying, hey, this is Keshav. He has some unique sort of left knee pain that requires, you know, specialized attention. Here are the details. And there is a huge sort of operations team on the Cleveland 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 facts—

I'm sorry to interrupt, but you guys— so just so I have it correct, you guys are making humanoid robots that can write handwritten handwritten notes to fax back through a physical fax machine to the original sender?

You know, I think 5 years ago that would have been an easier solution to solve in healthcare than try to get it implemented, but it's all enterprise software. So 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's sort of an example of many other problems that obviously exist within the the operations of a health system.

That makes sense. And so are you guys doing the kind of forward-deployed model where you basically say, hey, 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 approach so far?

Yeah, I mean, healthcare is extremely nuanced. You have to understand the specifics pretty deeply. And so without actually being on the ground, living in the offices of your customers, it's difficult to sort of scale solutions. And so, you know, about 20% of our team comes from Palantir. And so we've taken a very deep forward deployed approach to 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 do that.

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 healthcare 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.

I mean, there's definitely a massive amount of like barriers to entry and being able to actually drive or actually implement AI systems in these spaces. I mean, and for good reason, right? Like, this is like extremely, extremely sort of sensitive healthcare data that's flowing through these systems. And so there's the right amount of sort of guardrails put in place. 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 $1 trillion, just like wasted administrative operations work that, yeah, today can be done by software systems.

How are you thinking about on-prem these days? With the AI context, I mean, these models are so big, or the latest ones seem to run on NVL72s. 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 gonna be seeing like local inference happening for regulatory reasons or is it more about just interfacing with on-prem systems systems because they exist, and then this will be actually an accelerant to cloud adoption?

You know, we've offered on-prem to every single health system we work with. Really? But only, only, you know, 10 to 15% of them have actually taken us up on it. And, 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 data to basically leave your premises in the first place. And so we've chosen to go on-prem with, you know, even certain workflows with large health systems. But funnily enough, we thought it was going to be a massive need when in reality it's definitely a checkbox that they do to make sure that you can actually do it versus actually deploy some of this in full production. Interesting.

Last question for me. How dramatically is the quantity of data produced in healthcare 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 in tech audiences, but this one was specifically especially 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. It feels like we could be at some sort of data production inflection point. But what are you actually seeing in terms of the quantity of data that's being produced in the healthcare system?

Yeah, I mean, there are obviously a variety of folks who've done research on this. But I think healthcare has 8 times more data than the next largest enterprise industry on the, on the, uh, in the country. And over, over 90% of that data, um, is unstructured. So these are all like sort of, you know, uh, contracts and PDFs and handwritten notes and text that's like floating around the, the IT systems that exist. Um, so it's obviously a massive, uh, opportunity and problem at hand.

Yeah, well, uh, congratulations on the progress. Give us the details about the round.

Yeah, we raised a $38 million Series D. Fantastic. Led by the P15 team, which is the Sequoia India group, along with General Catalyst, as well as YC and a bunch of others. So grateful for all the support and interested in continuing to deploy pretty deeply.

When did you go through YC?

We actually started in summer '20. So yeah, so yeah, I've been, I've been sort of in the game grinding for the last—

I love it. 5 and a half plus years. Yeah. But I mean, what— you caught the perfect inflection point. I'm sure you'd done a ton of work to set up for the success and take advantage of the progress in AI broadly. So congratulations. What a fantastic story. Great.

Thank you so much.

Great to meet you. Have a great rest of your day. We'll talk to you soon. Goodbye. All right. Up next, we have Brian Manning from Zona Space coming in with a new Series C announcement, building a GPS alternative network.

Brian, what a setup.

Beautiful setup. I assume you're in your factory. Take us through an introduction on yourself, the company, and where you are. Thanks, guys.

Yeah, I know it's super exciting 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 $170 million Series C raise that we announced a couple of weeks ago. Thank you. So a lot of exciting things happening. So 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 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 really need to scale. But we started finding pretty quickly after that that there are 7 billion+ GPS devices around the world. Every single one of them is looking for better performance. And that's exactly what we're building a network here to provide.

Okay, so 258 satellites going into low Earth orbit. You're building them in that factory, I assume, but you probably have a deep supply chain and partnership. I imagine that they launch on other rockets. What is key about what you're building? Where are you partnering? Where are you doing R&D before the actual satellites get built and sent to space?

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 3 pieces that you have the ground segment, which is the mission operations kind of control segment. You've got the satellites and then you've got the user equipment. And then the user equipment 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, you know, everything from a dog collar to a phone to a tractor to a car to military devices and everything in between. 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'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. Got it.

So yeah, can you give me an example of a— 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? What is the benefit of this particular new constellation? For sure.

So there's 3 big areas that we've seen customers really need better capability, and it's— we try and make it simple to remember by precision, power, and protection. So there are some customers that are, you know, GPS in the automotive world, for example, can tell you a human driver kind of reliably what road they're on, where our system is designed to extremely reliably tell them 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 100 times stronger than GPS, which means it's strong enough to punch through jamming, it's punched through trees, even punch through a couple walls. So back to the dog collar. Yeah, right now everybody just accepts that like when you walk inside or when you go indoors or you go into your house, GPS just kind of disappears and location, you know, doesn't really show up anymore. With ours, our signal's strong enough so that you can see 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 today with existing GPS.

I heard this story years ago that I have no idea if it's true, that the current GPS constellation is higher resolution for military applications than for civilian applications, and the technology technology is not actually the problem. It's more that there are specific rules about the level of resolution that GPS data is like turned over to private companies. Is that true at all?

Sort of. So there's bits of that that are true and some, I think there are just some misunderstandings that are pretty common in the world. So the military does have a different GPS service than civilians do. 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. That's kind of what GPS is today, that everything is just wide open. 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.

Okay, so the software update handles, like it sort of enables the encryption as well, I assume?

Yeah, so effectively you can almost think of our service in a similar way to, you know, if 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, You don't know. The data doesn't work. Yeah, that makes sense.

That's what I was gonna ask. Okay. Business model.

But yeah. How big or small are current GPS devices? If you want to basically have an AirTag that you can throw in your shoe so you can know where you are 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?

Yeah, so the size of the device, I mean, we've got chipsets that we're working with that are, I think, like 3mm by 3mm. So it's something that's, you know, you could probably fit 10 of them on the end of your hand. Yeah. GPS is really one of the superpowers of GPS, and what we're building also is that it is a one-directional broadcast. So it's a receive-only signal that it doesn't do. Your GPS device, Like GPS doesn't know where you are. It only can tell you where you are. So there's no personal privacy concerns or anything like that. It just gives you the data to figure out where you are. And that 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. So it enables you to provide this into, you know, as you pointed out, things like the dog collar or the cow tracker. You know, we've even seen people with like peel and stick packaging labels that we're starting to work with that you can put on the side of a FedEx package to track it. Wow. So it is getting into smaller and smaller devices. And 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 logistics visibility and whatnot that really just doesn't exist today when GPS can't get into the place where the thing is at.

Tell us more about the factory. Yeah.

And, you know, hard— a lot of the sort of space companies that come on the show are obviously based down in Southern California. What have been the pros and cons of building in the Bay Area?

For sure. That's a very good question. That's something 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. There's a bunch of circuit boards. I mean, there's certainly solar panels and propulsion systems and other things around it. But the core, like the heart of it, and a lot of pieces that we've designed and built internally here have a lot more in common with a desktop computer than they do with, you know, a 747. And LA has a lot of great talent, a lot of big aerospace talent. But Silicon Valley is in many ways, you know, the heart of compute. Yeah. All these, you know, the chipsets and a lot of the talent, the people that we're looking for you know, it's a lot of electrical engineering, a lot of software engineering, a lot of mechanical engineering to put the pieces together, which is, you know, 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 2 navigation satellites in a year, where with what we're building here, 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.

What's the regulatory side of the picture? Do you have to get FCC clearance for your designs? Is there a— is there a wait wait-and-see period? Is that being accelerated at all by new tools and the ability to proofread documents with AI, anything like that?

It's, yeah, so very astute question from the space world that anything spectrum related. We started working 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 GPS broadcasts at about the power of a light bulb from an Earth and a half away from Earth in distance. 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 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 were able to show, look, there's our signal, there's GPS, it's 100% fine. And it's not only, you know, say fine, it's really necessary in the world today with so much 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 a wall or a roof or interference from somebody trying to jam the signal and prevent the capability from getting through.

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.

Thank you guys so much for having us. We'll be back on here soon.

Yeah, have a great rest of your day.

We'll talk to you soon. Awesome to meet you guys. Thanks all. Up next, we have Cody Blumenfeld-Gantz from Chapter raising a Series E to expand Medicare navigation. And launch financial products. Not with us. In the waiting room. We're waiting. We're waiting.

In the waiting room. Casey, nice that he got his M64. His M64. And he showed the packaging. It says, brought to you by the crack team at Mod Retro. At Mod Retro. Crack team.

The crack team. We have one over there. I saw some people playing Cruisin' USA, Cruisin' World maybe, something like that. This is gonna be fun.

What do you think they mean by crack team though? Crack team? If you look at this, if you look at the, the packaging, it doesn't say brought to you by the cracked team at ModRetro. It just says crack team. I don't know, maybe this is some new slang. They cracked it open.

Well, uh, we have our next guest in the waiting room. Let's bring in Cody Blumenfeld-Ganz from Chapter into the TVPN UltraDome. Cody, how are you doing?

Doing well, thanks for having me.

Thanks for hopping on. Uh, please introduce yourself and the company.

My name is 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. And I was just really appalled at how bad their experience was and wanted to make it much better.

So, 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— we're an aging country and everyone in retirement for the most part is dealing with this. What did you, what did you find? And then what gave you the confidence to start the company?

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. 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. Good.

Yeah. Yeah. 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 advisor? How do the users actually find the product?

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, I'm really proud of that because we're pretty sophisticated users of AI. 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, they'll find out about us through their financial advisor or their health system or hospital. 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.

And what does that tooling look like? Is it visualizing and analyzing numbers and sort of 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?

All of the above and a lot more. So I'll give you a couple of examples. Please. 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 most of them don't have APIs, as you can imagine. Yeah. So that's kind of 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. We have to know every prescription that that person takes in order to answer what sounds like a very simple question of what prescription will— what will a prescription cost on a given Medicare plan at a given pharmacy? That requires tens of billions of records. To know just that one question. And 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 to surface the right answer to the Medicare advisor. Yeah.

You guys just surpassed $100 million run rate. What seems pretty fast for, for a company in healthcare, which typically, you know, is this isn't like selling like some image gen model or something like that. What is best in class? Who are you guys going up against from a kind of $0 to $100 million run rate? I'm assuming you guys are one of the faster in history, but I'm curious.

I don't think of ourselves as a healthcare 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 Gleam. We went $1 to $100 mil in run rate revenue in I think about 2.5 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 healthcare.

So then what is the funnel to actually grow the business? What is the flow? You said you don't do consumer marketing. Is this, like you said, enterprises? Are you, do you have SDRs? Are you going outbound to companies? And financial advisory groups? What does that go-to-market motion actually look like?

We do have an enterprise partnership, enterprise growth team. Yeah, the team, the whole team is about 6 or 7 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 entire company.

No, no, no, just the enterprise growth team.

But all of, all of our sort of corporate headcount, product, engineering, growth, health, legal, et cetera, we're about 30 people.

Wow. That's still, that's remarkable. Well, congratulations. You just raised a round. Tell us about it.

Yeah, we raised about $100 million led by Al Gore's Generation Fund.

Nice. Massive. Oh, is he kidding?

Absolutely massive. Thank you so much for taking the time to come chat with us. Congratulations on all the progress. Thank you for everything that you do.

I'm sure you'll be back on probably multiple times. We'll talk to you at this rate. Have a good one. Goodbye.

Up next, we have CZ from Binance. He is the founder and former CEO. 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?

I'm good. Good. Thank you. Thank you.

Thank you so much for hopping on. Tell us about the book. What was the goal? Is this an attempt to set the record straight or just tell your story? What motivated you to write a book at this moment in time?

I think it's really just to tell my story. And then I was bored for— I had nothing to do for a couple years. So I started writing a book when I was in prison. Okay. And then I just finished when I got out. So I thought, you know, it might be an interesting story to share and let people know what my view is.

Yeah. What do you think people get wrong about your story?

Well, I think a lot of traditional media have many misconceptions about crypto, Binance, myself, et cetera. 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 me to share my perspective and have people understand crypto better.

What specifically do people get wrong about crypto or you or Binance?

Sure. I mean, from 2013, people think that Bitcoin is only used by drug lords or for illicit activities. The truth is actually, if you look at percentage-wise, illicit activities in crypto is actually much, much less than in traditional finance. And then by extension, a lot of the crypto players, a lot of crypto platforms get hit. And recently, there's more attacks about— just random attacks on me about how I do business, who I have connections with. So I'm a simple tech guy. So I just wrote the book the way I wanted to tell it. It's a pretty simple language, pretty straightforward book.

This is a simple guy. This is a simple guy.

I think I'm a relatively simple guy.

Yeah. How have you been processing the new regulation that's been proposed in the United States? What do you think needs to change in the crypto industry? Because I take your point about you know, the amount of illicit activity might be lower than in cash or the traditional financial system. But, you know, the goal, I think, for everyone would agree is to get that to zero. And so what do you like about the new regulation? What do you think is reasonable to ask for?

Well, I think right now, US is making really good progress on crypto regulation. The Genius Act was passed last July. But I think right now there's still quite a lot of debate based on my layman understanding, I'm not an expert, I'm not a lawyer, 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. So we will not, I think the current iteration of regulations will not get everything right on the first try, right? So there'll be some collaboration over time. So I think it's more important to make progress and move forward. Yeah.

How are you thinking about the broad trade-off between decentralization, anonymity, and then oversight and regulation? Like, it feels like we've been moving towards more 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 level of regulation in the crypto industry broadly?

So 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, you can track most of the transactions pretty accurately. So I think right now, there's a lack of preserving of privacy. But right now, the problem is many of the regulators and law enforcement people don't know how to use it yet. Yet. Some people do. I think some of the US law enforcement actually knows it quite well. In other countries, 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 we satisfy all the regulatory requirements, but we also need to protect individual privacy. For example, I'll give you a couple of examples. Please. For example, if your company pays everybody in crypto, And if you get one payment today on the blockchain, you can just trace to the address that paid you and see how many addresses that address paid in the last week. You can figure out everybody's salary. So that's a privacy issue. And if you stay at a hotel, you pay for the hotel, then people know where you— 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, right? So there's little problems like those that are not solved yet. So we need to, we need to strike a balance. It's hard to say exactly where the balance is, but I think over time we'll get there.

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 the intersection. But I'm curious if what your overall view is. And then if it's positive, some maybe specific examples of where you expect to see it manifest first.

Sure, absolutely. I think what both AI and blockchain are big, recent, new, big industries. I think there's really 3 big technologies in my adult lifetime, right? There's AI, there's blockchain, there's internet. Like it's on those levels. I think AI is, AI is going to use crypto for payments, for transactions. They're not going to use— they cannot KYC through a bank. They cannot do a selfie. They don't have a passport, et cetera. And also payments in every country is a little bit different, whereas crypto blockchain is the same across different countries. So when you integrate with the blockchain once, it works globally. And it also handles microtransactions, large transactions, et cetera. And 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 has a lot of benefit from AI. I think right now a lot of the applications are in blockchain quite difficult to build. I think with AI, we can probably build like safer, safer tools for people to do self-custody and safer tools for people to transact. So, and I think so today, the two industries, to be honest, have not really leveraged each other that significantly. But I think in the future they will.

How are you thinking about the risk of quantum computing to the cryptocurrency ecosystem broadly?

I think there's some risk, but I think overall though, any technology improvement is always going to be good. More computing power is good for crypto. So quantum may break the existing encryption mechanisms. Mechanisms. But with quantum computing, there's probably new— well, there will be new encryption algorithm. There are already quantum-proof 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. Also, more computing power with quantum, there's probably newer encryption mechanisms we have not even thought about that we can use quantum to encrypt, and decryption is always going to be much harder.

Sure. What about 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. 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?

I actually think AI is going to improve security for most projects, like Anthropic Cloud, right? So now they're— I think if you play like that, they could potentially discover many flaws, at least they claim, in many projects. But I think projects can also 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, to do illegal stuff. So I think right now with AI tools that's available, the developers can use those tools to find their own problems. But of course, if you don't do that, then the hackers computers may do that for you, which is a typical problem we have today anyway. So I think with AI, security is actually going to become better. I don't think it's going to become worse. So I'm pretty confident about that.

Do you know who Satoshi Nakamoto is?

No, unfortunately I don't. Even if I did, I would have said no, but I honestly don't.

Okay. Do you have— 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, wildcard theories, 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?

This is an interesting point. I should have put this in my book. Maybe the next edition. But I've come to peace with it. I think I'm curious, obviously. I mean, if there was one person I really want to meet in the world, that would probably be him. But I think there are negative consequences if we find out who he is, right? For example, if I couldn't lie on the oath, if people say, look, have you met Satoshi? If I say yes, then all hell's going to break loose. I think it's better if we don't know who he is. It's better if we did. Without knowing him, that we don't have a founder centralization. For example, if you look at Ethereum, Vitalik's there. So there's a founder centralization. What makes Bitcoin unique is that we don't know— well, the founder is no longer participating. He may not be around. He may not be participating. So that makes it more decentralized. I think that's a good thing. We should come to terms— I came to terms with it quite a while ago. So even though I'm curious, I'm not actively looking.

Yeah. Have you ever thought about doing an 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?

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. Most projects fail. Even with the founders heavily promoting, we know who they are, et cetera. For a new project, without knowing the founder, there's less trust in the community. Bitcoin was the first one. Somehow it got— it started very slowly. It took many, many years for it to get to where it is today. And for new projects to do that is very, very difficult. And there have been anonymous projects that are basically rug pulls. So there are also the other side of it. People lose trust with anonymous projects. So to do what Bitcoin did is very, very difficult. I would actually love to see more anonymous, fully decentralized projects. But what you mentioned is the OPSEC is also extremely hard. It's so hard today to not leave any trace, both digitally and physically. So the fact that nobody has really announced who Satoshi is means that his OPSEC is It's crazy. I think 99.9%, nobody else can do it really at this point.

Yeah. What do Americans miss about crypto adoption globally? Here, I mean, so many, at least younger generations, almost everyone has some exposure to digital assets or some experience buying, selling, maybe not using functionally for payments, but obviously, it's very different in other parts of the world with less centralized financial institutions. Yeah.

I think America, for the last few years before the Trump administration, was fairly anti-crypto. So many of the founders left, many of the projects left, and many of the liquidity left. The biggest crypto exchanges are not in America today. The biggest blockchains, the biggest stablecoins, they're not America-based. So I think America misses that liquidity quite a bit. America right now has very forward-looking regulations, and now people are 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. So the, the cost to American consumers today for accessing crypto is quite high. So that's a disadvantage that America has today. But America's large economy, a lot of entrepreneurs, a lot of VCs and good liquidity in traditional markets, I think. And I think America definitely has have the ability to catch up very quickly.

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. Is there any hope for de-escalation between the two countries?

I'm not an expert on the geopolitics of between different countries and also My layman understanding is both countries have leaders with pretty big personalities. So they're very hard to predict. I think President Xi in China is easier to predict than President Trump. President Trump is like a wild card, right? Which is in his advantage. You can't predict what he's going to do. But I do think both countries are large countries now with leaders who are smart and who are business-driven. They want the economy to grow. So if that's the goal, then there are certain— then I'm optimistic that, you know, there's certain outcome to be reached. 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're all hard negotiators. The negotiations at that level takes time. So, but I am fairly I'm fairly optimistic that, you know, both the two countries will work out something that's beneficial for both.

You've written the book. What's next for you? What do you think the next decade looks like?

I'm actually not too sure exactly. So I'm doing a few different things right now. I'm running investment fund. Well, I'm not really running it, but like I support it. I do some mentoring in the space for new entrepreneurs. I run a a free education platform, a 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, so and I also advise different governments on crypto policies. So between those 4 things that keep me pretty busy, the book was actually a huge distraction for me. I can imagine. It took a lot of time. It takes a lot of time to write a book. But I'm glad it's out there. And there's an audio version coming out soon. And then after that, I'll put that on pause, just let it be for a while, and then figure out what to do.

What was the strategy for the audiobook version? Did you narrate it yourself, hire a human narrator, use AI?

So one of my friends, Michael Santos, is going to narrate it. So we had this It's just sort of agreement verbally from a long time ago. And also Amazon doesn't allow AI-generated voices yet. I didn't know that. So you'll be a human read or audible. And then I've been playing with AI quite a bit myself. The AI cloning of voice is, I can't tell the difference from my own voice. And it's just better. It reads more smoothly. It's better than my own reading. In certain other platforms or in certain other countries, we may use an AI-generated voice that clones my voice to try to read it. I haven't finished that yet. There are still little quirks here and there. Sometimes AI makes very obvious mistakes. It pronounces Chinese names wrong, which I would not make that mistake. Sometimes you will say, when I write $400, you say 4-0-0. $0. So I would not make that mistake. But 99% of the time, he actually reads better than me. So we'll see. So I might do two different audio versions. We're still playing around with it.

Yeah. I wonder after Jassy's letter today if he's still going to be anti-AI voices. Yeah. Yeah. I did have one last question. I'm curious, how did you process the prediction market boom over the last two years? There had been, you know, 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 entire period.

Yeah, so I think today I do think prediction markets has a huge potential, and it's already pretty big. The top players are pretty big already, and there's like hundreds of thousands of upcoming platforms as well. And also, if you look at the regulatory landscape, the CFTC chairman, Michael Selig, he talks about prediction markets multiple times. Every time I watch him talk, he seems to mention prediction markets. So it seems like the regulators and the traditional markets are also moving in. So, and as you said, there have been many attempts attempts previously, but then timing is important. Some ideas, even though the idea is 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. The previous attempts struggled, and now it seems to be taking off. So I'm a big proponent for anything that's new and interesting. And I think prediction markets are very interesting. They're price discovery and truth discovery. They're kind of using price to discover truth, right? So which is actually a very— which is usually the reverse for what we do. We like information drives trading volumes. So that's a very interesting dynamic, I think. And 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 is a huge potential and it's hot. Yeah. And it works.

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, DAOs that had their moment in the sun and didn't quite reach escape velocity? Do you think anything will have a second wind in the near future?

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. There'll be something that's— even prediction markets today, they're different from the prediction markets 4 or 5 years ago. 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. So I do think that some of the things things that were there. I think DAOs will not disappear. I think DAOs haven't really took off, to be honest. The concept being there for years. It's like even in the 2010s, video streaming doesn't really work. Even today, this type of call, sometimes internet doesn't work. Sometimes the microphone doesn't work. So we get into those situations a lot. So a lot of things take a lot of time to mature. So I think the DAOs— NFTs, again, the next iteration may be slightly different. But you may still be called NFTs or NFT2. It may be a different name. But I think tokenizing art is probably going to come back at some point multiple times. I don't know when it will really hit big and stay. NFTs, I think honestly, we saw a rise and then a downward trend. So it's hard to say, but I think all of those Things eventually should be much bigger than they were today. Yeah.

Well, thank you so much for taking the time to come chat with us. Congratulations on the launch. I recommend everyone go check it out and hear CZ's side of the story. Thank you so much. Have a great day.

Thank you so much for having me. Thank you.

Talk to you soon. Goodbye. There's some lore on the timeline. Bluetooth is such a strange name for technology. Apparently it's named after a Scandinavian Scandinavian king who united Norway and Denmark, and the logo is a combination of two Norse runes. 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 about a seed round. How are you doing? What's going on?

Hey, thanks for having me.

How are you? We're good. Please introduce yourself and the company.

Yes, please. So I'm Tal, I'm the co-founder and I'm the CEO of Enclave. Essentially, we're an AI code security platform using LLMs to find critical vulnerabilities in codebases the way traditional scanners won't.

Yeah. 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?

Week? 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. Essentially, exploitability is the name of the game as I see it, right? Because the vulnerability that's not exploitable is not worth as much till right now unless something changes. 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, including ourselves.

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.

Yes. So I think especially with Miro 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 procure whether it's 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. Yeah.

How are you thinking about interfacing with 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?

Yeah, no, I 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 in use in them. So definitely want to partner with them. We are talking with them. Yeah. Again, I think they are doing a tremendous job, but I think ultimately most organizations do not currently have access to this technology. Yeah. And they need an independent system-level reviewer that's able to constantly deploy the state-of-the-art models.

Tell us about the round. You raised some money? Yes. Yeah, yeah, yeah.

So we have raised $6 million led by HTC. And then we have another bunch of exciting investors on board like Aaron Levy. There we go. Brother Aaron. Brother Aaron. Mark Benioff. Whoa. Yeah.

You got the dolphin in. The dolphin. The dolphin. You don't see him ripping personal checks.

Last question from my side. What have conversations been with customers like? Who do you need to get to? Who are the key stakeholders? How diffuse is the understanding of cybersecurity threats these days? And what are you educating customers about most frequently?

Yes, I think so. We are just out of beta just with this product. Is the product. I think for us, we're trying to cater to both the security practitioners at the end of the chain. We are seeing a lot of anger from them who have their own cloud code, their own cursor, their own shiny object. So we want to empower them. But I think most importantly, we want to empower developers to be able to deploy safely and quickly because it's becoming very concerning We can see because we have some new zero days that we'll be publishing soon following a responsible disclosure. And I think that like security is going to be very big as a whole, the new job. You see 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 zero days. So eventually, as more organizations get exposed to this powerful tech that is LLM-powered security research, the safer it becomes. And I think it's become very obvious. We don't have to do much education. It's like the opportunity is very obvious. The problem is very obvious. Yeah.

How are you thinking about the business model? Do you want to sit between Do you want to be monitoring the code that's written and the pull request and the code review phase? Do you wanna be actively monitoring systems in production, both? Yeah, definitely both.

But we are trying to be like to prevent those issues to begin with, whether it's through GitHub, through the pull request, through Cloud Code MCP, through Cursore. But also, yeah, definitely also prevent production. And I mentioned exploitability, so context is most important here. And looking at your— and I think this is something that Wiz has done a great job with— is looking at the cloud environment, the cloud environment at the runtime, see what's exploitable, what's not. Because you can have a 10.0 CVSS vulnerability that's completely irrelevant because it's not exposed to the internet. So yeah, we want to be both preventing but also finding live vulnerabilities. But right now we are focused on code.

Yeah, yeah, makes a lot of sense. Well, congratulations on the round. Thank you so much for coming on and breaking it down for us, and have a great rest of your day. We'll talk to you soon. See you soon. Goodbye. Cheers. Um, what else is in the timeline before we wrap up the show? Uh, Yahoo's G800 is at Augusta. If you got really good SEO between, uh, 1994 and 1999, then messed everything up after that, your executive team in 2026 will still have a G800 money, says Chris Backe. That is very funny. And Preston Holland is chiming in with some crying emojis. Secretary Kennedy, new podcast, 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. What do they want to do in their enormously valuable spare time? Fire up a mic and pod. Yeah. What does Jamie Dimon want to do after JPM? Start a media company. Pod again. RFK Jr. is in charge of all government health policy. What does he want to do with that power? Pod about it. Uh, in this, uh, Will highlighted Jeremy's post. Posting is the end state. It's the treasure that waited, 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. Celebrities, billionaires, industrialists, scholars all wind up up as the humble 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. And yes, truly very successful, but still enjoys a recorded conversation. In other news, the Acquired Podcast just released new website, acquired.fm.

Many people are calling it the most beautiful podcast website in history. 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, and it fits the brand perfectly. 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.

We gotta have him back on. That'd be great. Very soon. Yeah. But thank you for being with us today. We'll see you tomorrow. It's been an honor and a privilege to podcast with you today.

We'll see you tomorrow. Leave us 5 stars on Apple Podcast and Spotify. Sign up for our newsletter.