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TBPN is a live tech talk show hosted by John Coogan and Jordi Hays, streaming weekdays from 11–2 PT on X and YouTube, with full episodes posted to Spotify immediately after airing.
Described by The New York Times as “Silicon Valley’s newest obsession,” TBPN has interviewed Mark Zuckerberg, Sam Altman, Mark Cuban, and Satya Nadella. Diet TBPN delivers the best moments from each episode in under 30 minutes.
You're You're watching TBPN. Today is Wednesday, 04/08/2026. We are live from the TBPN UltraDome, the temple of technology.
Speaker 2:The fortress of finance.
Speaker 1:The capital of capital. We got white suits on. You know what that means. The stock market is booming. The Dow Jones up 2.68%.
Speaker 1:The S and P five hundred is up 2.446%. The Nasdaq's up 2.9%, and there's a bunch of other stocks that are moving within that. Of course, this is on the back of the very good news that there has been a ceasefire, that the street might be opened. Of course, it's all back and forth. The front page of The Wall Street Journal is covering all of the geopolitical moves.
Speaker 1:But we're here to talk about tech and business, of course. And the big news today is that Meta Platforms has launched a new AI model. Alex Wang, the chief AI officer at Meta Platforms, announced a new large language model today, its first major new artificial intelligence model in more than a year. The rollout of the model called Muse Spark is a critical moment for Meta, which is up 7.5% already, which has spent billions of dollars hiring AI talent in a bid to catch up to OpenAI. Anthropic and Google DeepMind, the leading labs, have been put have been putting out models at an accelerating pace.
Speaker 1:In a departure from its previous models, which were open source, Muse Spark is a closed model that will power Meta's AI chatbot and AI features within it. John Lutig has a very interesting post about open source AI and sort of predicted this. Can pull that up at some point. We can find
Speaker 2:Predicted that Meta would eventually bail?
Speaker 1:Yeah. Let me find it. The future of foundation models is closed source. Let me see if he if we have this here. He said given Meta is the primary deep pocketed large open source model builder, open source AI has become synonymous with Meta AI.
Speaker 1:He wrote this maybe three or four years ago. So the operative question for open source AI is what game is Meta playing? In a recent podcast, Zuckerberg explains Meta's open source strategy. One, he was burned by Apple's closeness for the past two decades and doesn't want to suffer the same fate with the next platform shift. It's a safer bet to commoditize your compliments.
Speaker 1:He likes building cool products and cheap performing AI enhances Facebook and Instagram. That's 100 true. We've seen this in the ads product and the growth there. There's some call option value if AI assistants become the next platform, and that makes sense in Manus and the Meta AI app. He bought hundreds of thousands of H100s for improving social feed algorithms across products, and this seems like a good way to use the extras.
Speaker 1:That all makes sense and Lama has been great developer marketing for Facebook, but Zuck also suggests several times that there's some point at which open source AI no longer makes sense either from a cost or safety perspective. When asked whether Meta will open source the future $10,000,000,000 cost model, the answer was as long as it's helping us. At some point, they'll shift their focus towards profit, and that's what John Ludwig wrote. When did he write this? Was May 20 that was 2024.
Speaker 1:Man, time flies. Barely just under two years ago. He says unlike the other model providers, Meta is not in the business of selling model access via API. So while they'll open source as long as it's convenient for them, developers are on their own for model improvements thereafter. That begs the question if Meta is only pursuing open source insofar as it benefits themselves, what is the tipping point at which Meta stops open sourcing their AI?
Speaker 1:Sooner than you think, he says. Exponential data, frontier models trained on the corpus of the Internet, but that data is a commodity. Model differentiation over the next decade will come from proprietary data both via model usage and private sources. Exponential CapEx, he highlighted this two years ago, a lagging edge model that requires just a few percent of Meta's $40,000,000,000 in CapEx is easy to open source. No one will ask questions.
Speaker 1:But when
Speaker 3:you reach $10,000,000,000 or more in CapEx spend for model training, shareholders will want clear ROI on that spend. The metaverse raised some question marks at a certain scale, too. Diminishing returns on model quality within Meta. There's a large upfront benefit for Meta building an open source AI model even if it's worse than the frontier closed source counterpart. There are lots of small AI workloads, think feed algorithms, recommendations, image generation where Meta doesn't want to rely on a third party provider like they had to rely on Apple.
Speaker 3:And so the news has been back in December, there was a reporting that Alex Wang disclosed an internal company Q and A that his team was working on two new models. One was this text
Speaker 1:based LLM code named Avocado and then a separate model that was for image and video
Speaker 2:Mango. Mango.
Speaker 1:Yeah. And so have they clarified if this is Avocado? This feels like what Avocado should be, this Muse Spark.
Speaker 4:Is that
Speaker 1:what it's called again?
Speaker 5:Muse Spark. See it is. Don't know what else. Yeah.
Speaker 1:So the image model should be coming soon. The the question that I had was will a code focused agentic coding harness be a separate model, a different train? This feels like it's not a coincidence that this news is dropping on the heels of Anthropics new model Mythos, which sort of was announced loosely and the model card dropped yesterday even though the model is not available yet to play out Yeah.
Speaker 2:So so going through Yeah. I think it's worth pulling up the actual model card here Sure. So we can have it on the screen. But they break out Muse Spark thinking against Opus four six max, Gemini 3.1 pro high, GBD 5.4 x high, and then Grok 4.2. And the way that they position it, it looks there there was, of course, some people saying that it was somewhat of a chart crime.
Speaker 2:But if you look
Speaker 1:Wait. Why?
Speaker 2:When you basically look at the top and you see that Muse Spark gets an eight eighty six point four
Speaker 1:Yeah.
Speaker 2:And it's in blue Yep. And then you look over and it's and it's outperforming all the other models on that benchmark.
Speaker 1:Okay.
Speaker 2:You just sort of assume that like the highlighted blue means that it's out Oh.
Speaker 1:Yeah. But it's And not because Frontier at MMLU.
Speaker 2:Because there's a bunch of them as you get further and further down. So like Arc AGI two. Yep. Muse Spark dramatically underperforms Oh, interesting. The the other leading models.
Speaker 2:Yeah. And and there's there's, you know, again, number a number of others where it is There's plenty where it's where it's over performing.
Speaker 1:Yeah.
Speaker 2:There's plenty where it's underperforming. I I of course we started asking it jokes right away. So I'll pull up I'll pull up the joke. I said, tell me a joke.
Speaker 3:Okay.
Speaker 2:And it said, gotcha. Here's one for you. Why don't skeletons fight each other? They don't have the guts.
Speaker 1:Okay.
Speaker 2:But then it doesn't even let me It just says, want a different vibe. I've got dad jokes, nerdy ones, or Malibu appropriate surf puns too. And so I'm like, wait, why would you think I want Malibu appropriate surf pun? If you look in your previous chats no I previous chats.
Speaker 1:What about because Meta AI crosses with Instagram, so when you search on Instagram, sometimes that prompts Llama or previously. Yeah.
Speaker 2:I'm trying to get to the bottom end. Yeah. Right? Like this feels like an oddly specific type of joke to ask And so I said, why would you think I want Malibu appropriate surf puns? Fair call.
Speaker 2:Toss that in without you asking for it. Mhmm. I try to mix in different flavors of jokes and surf puns just popped into my head as a random option. No special reason behind it. I just said I don't believe it was random and it says you got me.
Speaker 1:You got me?
Speaker 2:It wasn't my smoothest moment. But then it denies it again. Weird. It says it's just like what kind of what kind of joke do you actually want? No hidden motives here.
Speaker 2:No. It said you gave a hyper specific example based on my life so I have to assume you were looking at my Location. Account for inspiration.
Speaker 1:Instagram. I
Speaker 2:get why I get why that felt weird. I'm sorry it came off that way. And then it denies it again. It said, you're clearly lying.
Speaker 1:I mean, you have talked about being in Malibu on the Internet for a full year. It's possible it got baked into the pre training or something. I don't know. Maybe. Yeah.
Speaker 1:There's also I mean, that feels
Speaker 2:like when I said, what can you tell me about myself Yeah. I said I don't actually have access to personal details about you Yeah. Beyond what you share with me right here in this chat.
Speaker 1:That's very odd because the whole thesis of like personal super intelligence should be, hey, we're the best model that actually does plug into your entire life and your DMs and your Instagram and your likes and your preferences and everything that you have done across meta platforms for a very long time. We're gonna bring that in a really fun and delightful way and and telling a joke that is tailored. I used to get jokes like that where I would ask for a joke and it would be I've talked about this. It was it would be something like oddly specific about my car. And I was like, I don't that's that doesn't actually make the joke better, but it's cool that you're remembering.
Speaker 1:This whole personalization boom happened last year.
Speaker 5:Yeah. I I get those about like AWS Really? Like specific services
Speaker 1:Oh, because you've been like querying
Speaker 5:asking questions about AWS. When I was like debugging stuff.
Speaker 2:Yeah. Yeah. But so I I
Speaker 5:ran, you know, My Favorite Bench Yes.
Speaker 6:From fried rice
Speaker 1:fries bench.
Speaker 2:By the way, Noah Noah Hirschfield said Does he your I said, what's my name? I don't know your name unless you tell me. Smiley face.
Speaker 1:It definitely knows your name. But yeah, I mean, what is personal super intelligence if it doesn't know your name? Like that that that feels like they haven't dialed in the the the the harness or whatever the tuning is to actually Yeah.
Speaker 2:Find the in sports like Meta's gonna be hyper aware. We don't want a PR cycle. Yeah. Yeah. Like Yeah.
Speaker 2:Trained on your data. Right?
Speaker 1:Like Everyone's been, oh, that ad was a little bit too close to home.
Speaker 2:And you remember every every once in a while one of those like thing, a screenshot that's been Yeah. Screenshot like a thousand times like goes viral and it's like, I do not give Mark Zuckerberg permission. Oh, yeah. Yeah. Yeah.
Speaker 2:Like that works.
Speaker 7:Yeah.
Speaker 1:It's it's hilarious. This is is this a rebuttal to the bench hacking allegations that happened last week or last year. So where was the so according to Meta's internal benchmark test, Muse Spark outscored Google Gemini on some tests and was competitive with models from OpenAI and Anthropic on others. It significantly outscored XAI's Grok on most tests. Wang's Alexander Wang's hiring followed the disappointing release of Meta's previous model called Llama four.
Speaker 1:The company was accused of and later admitted to gaming a third party benchmark that it used to rank various models against each other on performance. It also delayed the rollout of its biggest model called Behemoth which it never ultimately released. And so when I look at a model card like this where you could call it a chart crime where it's highlighted in blue and it feels like it's the best, but it's actually doing better on some. It does well in HealthBench hard. It underperforms on Arc AGI two, as you mentioned.
Speaker 1:But this maybe is the the bull case here is that they have at least moved on from the culture of like optimizing for the benchmarks. Right? Isn't that a good thing?
Speaker 5:Yeah. I mean, I there are rumors about them. Like, there's like extra bonuses if they if they got number one on Ella Marina. That was like something like the rumor. Yeah.
Speaker 5:But yeah. I mean, you've seen a lot of the labs kind of move away from benchmarks generally because I think they're just not that meaningful anymore. Like a lot of them are like basically so saturated. They're all it's like they're competing between 8991%. Yeah.
Speaker 5:And they're just like not very meaningful like you you see
Speaker 1:And you won't like actually feel that in the product necessarily.
Speaker 5:Yeah. You you kind of need to talk to these things for a long time before you can actually get the vibe. Yeah. But I I do think this news is very interesting in the context of the, you know, Clawdonomics stuff.
Speaker 1:The dashboard?
Speaker 5:Yeah. Because like what okay. What does it mean if if the entire company has been like maxing their their Clawd tokens Yeah. Over the past month? It means that they weren't using this model.
Speaker 1:Yeah. To me, means they they need to commoditize their compliments. Right? They need to bring down that cost potentially and the and if they're I mean, we we we sort of, you know, dug into are they spending a billion dollars a month? Seems like absolutely not.
Speaker 1:But they're clearly spending a lot. And if you can turn that OpEx into CapEx and train your own model and then inference it much cheaper on your own hardware, that feels like just an economic opportunity that makes a ton of sense in the context of just 10,000, 20,000 engineers writing a lot of code.
Speaker 5:Yeah. And I think there's basically like two way two ways to like square those two things happening. Like either one, this model's like not that good because the the engineers aren't using it or, you know, your theory that they're just distilling cloth. So one of those is true.
Speaker 1:That is not my theory. That is that is the schizo theory.
Speaker 5:The I believe the far one,
Speaker 2:right, is true.
Speaker 5:This model still doesn't feel that big. I think Alexander Wang talked about
Speaker 3:Yeah.
Speaker 5:They're gonna train bigger models. They're training them right now. Yeah. So I'm, yeah, excited for those. I I think I'm especially excited for the video models.
Speaker 1:Yeah. They should have incredible training data. We've seen really
Speaker 5:good Yeah. P o three. This model is like very competent. Right? Yeah.
Speaker 5:It's it's with the frontier models. Maybe it's not the best
Speaker 1:one but
Speaker 5:it's like among the top five or whatever. Yeah. None of the other big labs have I guess that's not true. Like Google right now is definitely ahead in Mhmm. In images.
Speaker 1:Yeah.
Speaker 5:OpenAI I think is is they're releasing a new image model soon. It seems like there's been rumors of this.
Speaker 1:Yeah. If the image two popped up on the Arena
Speaker 5:or Yeah. The Arena, it's always like the code name coming out.
Speaker 1:The photos just looked photo real. It didn't look like AI imagery anymore.
Speaker 5:Yes. So so if like Meta has like similar capabilities but they have this like incredible dataset Yeah. You know, very excited to see what comes out there.
Speaker 2:Yeah. The the the news this morning, Meta Platforms and the information. Meta Platform has taken down internal employee built leaderboard tracking how many tokens staffers were using.
Speaker 1:Yeah.
Speaker 2:Showed total usage over a recent thirty day period, amounted over 60,000,000,000,000 tokens. The dashboard now displays a message that is offline. It says, we've really enjoyed building this app on NEST. Everyone. It was meant to be a fun way for people to look at tokens, but due to data from this dashboard being shared externally, we've made the decision to shutter it for now.
Speaker 1:It seemed like a fun side project. Mike Isaac was reporting on it here. He said it's it's down. Unclear to me if this was a homespun one by employees or an official one. Employee projects come and go frequently.
Speaker 1:Conspicuous timing, though. But, yeah, you you don't want to to have you wanna measure the output, the impact, not necessarily the input and how much is is going on there. What else is going on? Lisan Al Gayeheb says Meta might actually be back with Muse Spark, still behind OpenAI, Anthropic, and Google but ahead of XAI and Chinese Labs. Muse Spark soars 52 on the artificial intelligence analysis index behind only Gemini 3.1 Pro, Gemini GPT 5.4, and Claude Opus 4.6.
Speaker 1:Muse Spark is the first new release since LAMA four in April 2025 and also Meta's first release that's not open weight. So a huge jump up in performance across a variety of benchmarks. So all good stuff there. Where what else is
Speaker 2:And the market is Tanking? Thrilled.
Speaker 1:Oh, thrilled.
Speaker 2:Absolutely thrilled
Speaker 1:that I just saw I just saw the news that the the Wall Street Journal is reporting that that the straight up for moves might actually be closed again. So I would imagine a a kangaroo market for the near
Speaker 2:I know. The market is thrilled that Meta has released a close to frontier Yeah. Level model. Yeah. Right?
Speaker 2:This is a a new group. They've been at it for less than a year. The stock is up almost 8% today. And again, you know, so so much of the pricing pressure, the downward pressure on Meta has just been kind of uncertainty on what all these tens of millions of dollars will actually go towards and and what will be accomplished. Still unclear like, you know, is this are they gonna go after code gen at all?
Speaker 2:Are they just gonna try to compete on the consumer LLM side? Very, very
Speaker 1:And can you economically go after code gen if you're just using it for internal models? If you're not selling it externally, can you justify the CapEx just purely on the internal usage?
Speaker 2:Seems so
Speaker 1:Having having this model be vended into all the different family of apps makes a lot of sense because they have billions of users that will wind up interacting with this in one way or another. The cogen thing, you have to wind up being more in this personal super intelligence. We talked about Manus, what it might be able to do for you across Instagram, across Facebook, across WhatsApp. I don't know. Yeah.
Speaker 2:The question is will they try to send meta meta vibes Again?
Speaker 1:With the new model?
Speaker 2:All the way up to the to the top of the app store charts.
Speaker 1:Yeah. I mean I'm curious. The the I mean, the previous actual model was mid journey under the under the hood. Right? And so that was sort of a quick launch to demo what they were thinking, you know, mixing the music library, which was cool.
Speaker 5:Yeah. Like that had nothing to do with the the new like class of AI researchers. But
Speaker 1:I mean, there was a lot of weird back and forth and news about is is Alex Wang getting kicked out? You know, there was a quick debunk on this. Andrew Bosworth came up and said, no. This is completely incorrect. We're very happy with the with the progress and the team and what we're building there.
Speaker 1:And so it seems like they got it out the door, and and it's been doing well. Meta's new family of AI models can reach the same performance as Kimi k two with only 30% of compute and only 10% of the compute to reach LAMA four Maverick. So a much more efficient efficient computing frontier here. They completely rebuilt their pre training stack with improvements to model architecture optimization and data curation. And so more more facts.
Speaker 1:Meta Meta Spark is an early data point on our trajectory, and we have larger models in development. So the the the mythical 10,000,000,000,000 parameter model, that that is the 10 t is what everyone's working on right now. 10,000,000,000,000?
Speaker 5:Yeah. Probably Well,
Speaker 3:flat.
Speaker 1:Well, in
Speaker 5:that range.
Speaker 1:Yeah. It's all rumored at this point.
Speaker 5:Yep. Rumored GPT four was something like a trillion. Yep. Right? You remember those memes where it's like a small circle and not a big circle?
Speaker 7:And then
Speaker 1:a huge circle.
Speaker 5:GPT four, five.
Speaker 1:Yeah. But, yeah, lots of lots of other work that went into it. Martin Qasim Mithani has a has a little bit more context on like what actually unlocks new capabilities in AI models. He says, Mythos appears to be the first class of models trained at scale on Blackwell's. Then there will be Verruubens.
Speaker 1:Pretraining isn't saturated, narrative violation. RL works. And there's so much computing coming online soon. Buckle your chin straps. It's going to be wild.
Speaker 1:The scaling laws
Speaker 2:And you know Brad Gerstner had to come in with the 100
Speaker 1:and Yep. Sure. Yeah. There's a there's a crazy bull case for Nvidia in the information arguing it should be worth what, $22,000,000,000,000. That is a wild move.
Speaker 1:There's there's a lot going on. The scaling laws holding is the most
Speaker 2:important Yeah. Articles from the information finance. Nvidia worth 22,000,000,000,000? This old school financial model says yes. So
Speaker 1:yeah, the big news on yesterday was Anthropic's new model Mythos. Some really impressive statistics and anecdotes yesterday, both the model card, the benchmarks and some stories about breaking out of a variety of what do they call them, walled gardens or test environments? What are those called? Breaking out of the, I don't know, the simulation. Sandbox.
Speaker 1:The Sandbox. Yeah. Breaking out of Sandbox, sending emails, all sorts of stuff like that. The model preview is only available right now to about 50 companies that maintain critical infrastructure because the model is particularly good at finding zero days bugs and exploits in technical systems. And if they lead that they leak that out before big companies have time to go and address all the bugs, there could be serious ramifications for cybersecurity.
Speaker 1:And so key partners include Apple, Google, Microsoft, Amazon, Nvidia, JPMorgan Chase, Broadcom, the Linux Foundation, Cisco, CrowdStrike, and Palo Alto Networks. They're all listed on the cybersecurity focus page for Project Glasswing.
Speaker 2:Chris Backy was having a little bit of fun because he noticed Yeah. Anthropic put their own logo on the partner page, which is a little bit funny, but at the same time, it's kind of smart because a lot of people are just going to see the image quickly and it's good to position yourself with the other companies.
Speaker 1:Yeah. So, yeah, it's it it is interesting. I mean, people have predicted that AI models would be particularly good at at cyber attacks, and this was one of the main sort of vectors of AI fears. It feels like this is what maybe what Dario was referring to when he was talking about the end of the exponential finding and exploiting software bugs is it's sort of perfectly in the sweet spot for coding agents and reinforcement learning. Combing through piles of code, tirelessly trying different exploit exploits to find bugs, having a clear verifiable reward.
Speaker 1:Did you crash the system or not? Did you break into the system or not? This is very it's a very clear binary signal that you can send to the model to determine were you successful in breaking into that system? And it requires basically no time delay. There's no lag.
Speaker 1:So there was one snarky tweet I saw that was something to the effect of like, okay, then if it's so good, go cure cancer. But any application that requires a real world feedback cycle, even if it's just a few minutes of human interaction in the cancer example, you know, you're going need to be testing the drugs in vitro in mice and monkeys and humans at some point. Or even if you're just sequencing DNA or doing anything in the lab, pipetting anything, If it's even just a few minutes all of a sudden every iteration, every attempt is going to take a few minutes and that's going to put you on just a wildly different exponential as opposed to being able to spin up a virtual machine with basically every single piece of software out there and then try every single exploit against every single piece of software and you wind up with a ton of exploits. And very, very bullish for cybersecurity that this is being done preemptively. There's a whole bunch of different discussions.
Speaker 1:Ben Thompson has a good piece on the whole decision to to release the model or not and stage it out and and the and the go to market there. But it's it's even even if the the the bio research, the other impacts are on sort of a slower exponential, there's still so much opportunity in even a software only singularity. There's also risk in a software only singularity. We've seen this story before though. A model that's too powerful to release but then works its way out and has pretty moderate impact on the world.
Speaker 1:This was the story of GPT two, the story of ChatGPT, the question of, you know, is this the model that's dangerous to put in the hands of people? Yeah.
Speaker 2:I'm pretty confident. A headline from 02/22/2019 by Aaron Mac. OpenAI says its text generating algorithm GPT two is too dangerous
Speaker 1:to Yes. So there is there is a I think Van Thompson called it like the boy who cried wolf syndrome, but the the Mythos Wolf. He says there's a lot of skepticism about Anthropic's announcement. This tweet was representative from Buco Capital bloke. Anthropic's marketing strategy is so funny like, ah, the government is treading on me.
Speaker 1:Ah, our models are so good we can't release them. It would be too dangerous. Ah, someone stop me. I'm going to destroy the economy. The rolling of the eyes is exacerbated by the fact that Anthropic has reasons to make to not make Mythos widely available beyond a lack of compute.
Speaker 1:Another factor is surely trying to avoid having Mythos distilled by Chinese model makers. So there's actually two good reasons to gate access. And when you're looking at those logos, when you're looking at the world's largest tech companies, there's much more ability to scale, rollout, demand, set pricing. These companies might be able to pay more. The model is very expensive.
Speaker 1:But if you're justifying that against bug bounties for zero day exploits in your most critical system, when you look at like JPMorgan Chase, it's a bank. Like, what is the price of finding an exploit in that system? It's pretty high. It probably clears the token hurdle a lot. And and and if the rollout is is paced, like, evenly across all the different companies, they'll all sort of understand that they're getting allocation, inference allocation at the efficient price that clears the cost to actually serve the model.
Speaker 1:So I do think the systems, all of these 10,000,000,000,000 parameter models will be released soon broadly. And the main reason that an AI that's smart enough to find zero day exploits should be able to recognize that it's being used by a bad actor to find zero day exploits. And it's only been a few months since the last flurry of competing models from OpenAI, Anthropic, and Google. The next cycle is already off to an aggressive start. We had Meta.
Speaker 1:And then the other news is that Elon Musk announced that he is getting ready to do another larger model with xAI.
Speaker 2:He's got a few He's
Speaker 1:doing seven models in training. Wow. That is a lot. Imagine v two, two variants of 1,000,000,000,000, two two variants of 1,500,000,000,000, a 6,000,000,000,000 model, and a 10,000,000,000,000 model. He says there's some catching up to do, but he he says he will never give up, never.
Speaker 1:So he is continuing to to grind and and train more models. What what else was in the reaction? There was a whole bunch of other back and forth. People seem split
Speaker 2:on Mike from No. Also Capital former guest says, we've decided not to release our latest investment strategy. It's so powerful. Releasing it might end the entire venture asset class as we know it.
Speaker 1:Yeah. Jackie says you should release it to
Speaker 2:a handful of trusted partners Mhmm. So that we can harden ourselves
Speaker 7:to it.
Speaker 1:And George Hoth says, Anthropic's marketing strategy, it's amazing. It's so powerful. It's terrifying. And the best part is you can't come. By the way, if Anthropic had any way to ship this, they would.
Speaker 1:Trained AI models are the fastest depreciating asset in history. GPT-four cost $100,000,000 to train two years ago and is now worth less than QUEN 3.5 B QUEN 3.527 b, 1,000,000. Sending the FOMO back, clock is ticking, boys. He's it needs something like an n b l 72 to run a decent speed, and even absurd API pricing doesn't cover it. There's more to be made on investor hype than API access.
Speaker 1:I just wish for honesty instead of a whole fake spiel about safety, who remembers when GPT two one point five b was too dangerous? And so lots of back and forth. Dean Ball has some more thoughts on Mythos. It's a longer post, so we'll let you go and read it. But the main the main take is just the, you know, this is this is technology that whether it comes from Anthropic or another lab, like, clearly needs to go into the supply chain of the world and in the US government and The US economy because no one is doubting even though some of the exploits were somewhat minor, no one no one disagrees that we need less cybersecurity.
Speaker 1:Cybersecurity. We We want want the most secure systems possible and we probably want a lot of competition between different companies to provide that service to the government. And so hopefully with if the war comes to an end and there's, you know, different discussions can happen and, you know, ice can thaw and there's a way to for these companies to work together. Even if even if the even if the supply chain thing doesn't go through and then and throw up a convent technology through Project Lastwing, through CrowdStrike, through Oracle and other partners to to Cisco so that at least the systems are secure because everyone wants that. So Dean Ball's been on an absolute tear.
Speaker 1:Should have him back on the show and talk more. He says, a lot of people, including people in positions of authority, told us recently that models of Mythos' capability wouldn't be a thing, that models with obvious national security implications would not be forthcoming. Those people were wrong. There's nothing to do about it, you should remember it. Mythos is the first model where theft of the weights by an adversarial actor feels like it would be a major deal.
Speaker 1:You better believe they will try and if they don't succeed with Mythos they will eventually. We are thoroughly in the era of the lab's best models may well not be in public the way they used to. This is because of a combination of compute constraints, economic reality, competitive advantage and safety concerns. Three means the most relevant models may be decreasingly legible to the general public. And depending on the extent and duration of the coming compute squeeze, could enter a market dynamic where the best models are only available to the highest bidder.
Speaker 1:And, of course, that makes sense from a KYC and security perspective. In other words, where compute is a seller's market rather than a buyer's market. Interesting. Imagine competing firms in the economy bidding against one another for access to the best and most tokens in the frontier labs as, in essence, kingmakers. The governance regime I have described above in four is not designed to stop that dynamic.
Speaker 1:And so there is a there is a plenty of more takes. This was a full current thing cycle. People Teneburr says, people keep talking about this like it's not blatantly obvious. And Throbat clearly has a system that's auditing open source repos for vulnerabilities using their unreleased higher power models and sending fixes for them without revealing their current level of capabilities. So they've been going around on GitHub and contributing pull requests to to to to, you know, patch any vulnerabilities without disclosing exactly what model was being used.
Speaker 2:Burn Hobart Yes. Is not excited about Fundrise. We had the founder on running ads for VCX, the public ticker for private tech. This is he says paying for an ad, encouraging people to pay six x net asset value for a closed end fund where the cost of bar is 400 percent
Speaker 1:Mhmm.
Speaker 2:Is one of the things people will remember during the next bear market. Yeah. I asked I asked the the founder of Fundrise about this, like how you kind of like is there another iteration of the of the product that can solve for this? Fundrise like very clearly made a bunch of really good bets Yeah. A few years ago.
Speaker 2:Yeah. And the fund has performed incredibly well. But the issue now is like if you want access to these names and the only way that you have is to go through VCX, you're paying six x what like the actual private market investors are paying. Yeah. And that just is like I mean, it's a I don't know.
Speaker 2:It depends how bullish you are Yeah. On the names but Sounds good. Very very hard assuming that normalizes over time.
Speaker 1:Yeah.
Speaker 2:It seems extremely unlikely that it trades at, you know, an insane premium forever. And so
Speaker 1:Interesting that they're running this ad on x. I haven't seen I I have x premium, so I haven't I don't see a lot of ads. I don't see any ads, but that does seem like the reasonable place to go to advertise a product like this. But, yeah, it is it is always odd. There's been a whole bunch of these, like, treasury companies that have traded above net asset value, and it was always just a weird supply and demand dynamic.
Speaker 1:People want them, and they're willing to pay way above. Hopefully, they know the the the net asset value multiple, and they're doing that willingly. I think, you know, consumer education, investor education is more of the critical the critical question here. Well, TBPN over at Codex is unreasonably excited about things. The next few weeks will be intense and fun.
Speaker 1:And Michael Greenwich says weeks, years, you know, it's going to be an ongoing model mayhem for Vague maxing. Vague maxing and Yesterday? A lot of stuff going on.
Speaker 2:It was about token maxing. Today is about vague maxing.
Speaker 1:Yes. Yes.
Speaker 2:Let's go. Mickey Friedman says, the current fear is that AI homogenizes culture and turns humans into passive consumers. One counterpoint in Go, human play showed very little improvement from 1950 to 2016 until AlphaGo beat Lee Sedol. Then human decision quality jumped. Players started developing moves that were distinct from both previous human moves and from the novel moves introduced by machine intelligence.
Speaker 2:This seems more likely to me fun times ahead.
Speaker 1:Lee Sedol is now a professor at UNIST. He's a special professor on a three year term to conduct artificial artificial intelligence research on Go specifically. He yeah. If you haven't seen the Go, AlphaGo documentary, it is fantastic.
Speaker 5:Lee Go to Smoke.
Speaker 1:Yes. Lee Sedol. It is it is such a wild ride watching the DeepMind engineers like, you know, be it seems like they're genuinely surprised by the performance. Like, no one really expected it. But, yes, this is a very interesting chart to see how much things changed in the post AI era as people discovered new and interesting ways to differentiate from from the models effectively.
Speaker 2:Yeah. Scoop from Steven Nelson. The CIA used a secret tool called ghost murmur to find airmen in Iran. Yeah. Ghost murmur pairs long range quantum magnetomagnetometry.
Speaker 2:Yeah. How do you say that? Sensors with AI to find human heartbeats. I was wondering this while they were, over the weekend there was Yeah. You know, a search going on.
Speaker 2:It was like, how do you how do you find someone, how how does how does somebody like, you know, an airman that's down send a signal
Speaker 1:Yeah.
Speaker 2:That can be picked up by one group but not
Speaker 1:This is very odd. So there are some there are some community notes on this saying that quantum magnetometry, I'm imagine that's how you pronounce it, Detects hard magnetic fields. And I believe this technology works in labs, but only up to a few meters, not 40 miles as claims. As claimed, fields decay with one over r cubed making long range detection implausible. So unclear if this is what worked, but isn't there isn't there has to be some sort of device that you could carry on your person like in your shoe like an AirTag that can talk to a satellite almost.
Speaker 1:Like, you look at the Starlink receiver dish. It would fit in a backpack, but that's very high bandwidth. I imagine if you had something I mean, there's sat phones that are the size of large cell phones. That was available in the eighties and nineties. You have to imagine that if you're just trying to put out a signal to GPS or a Starlink network, you must be you must be able to shrink that down significantly the place where it could be carried on your body.
Speaker 1:But it's probably classified. So I would be surprised if it's just very hard to read into like what's real and what's not here. There is a different community note pushing back saying, no note needed. This new technology is a classified system developed in secret by Lockheed Skunk Works and the CIA that was just used, revealed publicly for the first time. Naturally, its reported capabilities far exceeding the known public state of the art.
Speaker 1:The note is relevant. So it's, yeah, it's it's it's very very interesting. But good to see Alright.
Speaker 2:Let's go over to Aaron Tan's post. Okay. It says introducing Loom, a lamp that does your chores. Mhmm. Order now Shipping this summer.
Speaker 2:Let's see the video.
Speaker 1:That bed already looks fully made. What what chore is it gonna do?
Speaker 2:Just drop some laundry off.
Speaker 1:Oh, okay. You have to drop the laundry first? Wait. It can do that? Wait.
Speaker 1:Does it have fingers in that? Like, what what is it put on the record? What yeah. What is what is in the
Speaker 5:You can see it has a little claw.
Speaker 1:Oh, it has a claw inside? Oh, okay. That is so funny to have a humanoid robot play music on a physical record. The folding t shirt is the touring test of humanoids for real. Pixar lamp quaking in its boots right now.
Speaker 1:Nice video. Good color grade, nice warm tones, friendly. Doesn't feel dystopian, feels delightful. Did you get one of these?
Speaker 2:I think I think we should get one
Speaker 1:to Yeah. Like I I think we
Speaker 2:should I think we should get one. We should get one as
Speaker 5:a team.
Speaker 1:Have some clothes over there on the on the wardrobe
Speaker 2:rooting rooting rooting for Aaron
Speaker 1:Yeah.
Speaker 2:And the the Loom team. Very very unique form factor. I mean, just think the an an impressive timeline for shipping. Hopefully, yeah, shipping, I'm reading this as like actually shipping, not shipping like Yeah. Another, site to order because you can order already.
Speaker 2:But, yeah, it'll be, very interesting if it can if it can reliably fold clothing. It could be it could be enough. Right? Yeah. So the the the benefit here is like people already want lamps, I'm assuming, for their their bedroom.
Speaker 2:If you can buy a lamp that's reasonably priced and then it could also has a benefit of just a simple thing like folding clothes, there could be there could be a market here.
Speaker 1:Yeah. I feel like I don't know. Even just putting pillows back on the bed, even just like really basic things. I mean, even there are probably applications like the Roomba did so well with such a minimal such a minimal scope. There's there must be something I would I wouldn't be surprised if even even in between this and fully folding the clothes, just remaking the bed properly feels like something that consumers might actually pay for and and allow for, you know, the flywheel to start spinning.
Speaker 1:Obviously, lots of security considerations since there's a camera there and whatnot. They'll have to do a lot of cybersecurity and figure out that but people already have cameras all over their homes from Nanit and child monitors, baby monitors, and that type of stuff. So I'm I'm optimistic about this. And I think they did a great job promoting it. There is a story in the New York Times from none other than John Kerry Rue who who blew the blew the story wide open on Theranos.
Speaker 1:He says the mystery of Satoshi Nakamoto, the the pseudonymous pseudonymous inventor of Bitcoin has remained unsolved for seventeen years. Not anymore. Read my eighteen month investigation to find out who Satoshi really is. And he says it's Adam Back who says who posted directly, I am not Satoshi, but I was early in laser focused on the positive societal implications of cryptography, online privacy, and electronic cash. Hence, my 1992 onwards active interest in applied research on e cash privacy tech on Cypherpunk lists which led to hash cash and other ideas.
Speaker 1:Yeah. John Kerry Rue in his New York Times research finds like Aaron Van in his Genesis block book, many interesting Bitcoin analogs in the early attempts to create decentralized e cash, in effect prototype ideas trying to figure out a bitcoin like thing including P2P, BGP and proof of work. For his quote, I'm not saying I'm good with the words. I'm not saying I'm good with words, but I sure did a lot of yakking on these lists actually. The broader context was my observation that because I was talkative on the list and known to have an active interest in eCash, there is some confirmation bias in finding my comments frequently on eCash topics.
Speaker 1:So he has he has said we are we are all Satoshi. I am not Satoshi. But it's a it's very interesting story that will
Speaker 8:happen.
Speaker 5:You just created a million Satoshis.
Speaker 1:Truthfully. High yield Harry's joking, Steve Buscemi has been revealed as the Bitcoin founder, not Satoshi Nakamoto. Well, we have our first guest in the waiting room, Luther Lo from Y Combinator. He's the head of public policy, and we are going to be talking to him about Vibe Cody. Luther, how are you doing?
Speaker 9:Hey, guys. Great to see you.
Speaker 6:Congrats on the acquisition.
Speaker 1:Thank you.
Speaker 2:Thank you. Great to have you on.
Speaker 1:Can you kick us off with a little bit of an introduction on yourself and what you do day to day at Y Combinator?
Speaker 6:Sure. So, yeah, I'm the head of public policy, for Y Combinator. I'm based in Washington. Mhmm. And Gary created the role when he started at YC and really his observation many years ago was, Gary and I had actually met in Washington.
Speaker 6:We were sitting around the table at some kind of White House meeting and he said, you know, you you go to Brussels, you go to Washington, and the largest tech companies have lots of representation.
Speaker 3:Mhmm.
Speaker 6:But little tech doesn't have a seat at the table. And that was actually the first time I'd heard that phrase little tech and Gary actually kinda coined that phrase. He went back and you look on X Twitter, he has had said that a number of times years ago. And so, you know, my role is to really, like, help the founders navigate Washington, Brussels, the state capitals, advocate for pro little tech issues in the broader ecosystem, and, yeah, just really do everything I can to help the founders.
Speaker 1:And what's the what what is what is your view on on vibe coding, the App Store, the boom? I I was we were talking about it yesterday. There's, you know, there's a whole bunch of stories of where it feels like we're getting close to the one person, absolutely massive company, whether that's GMV or revenue or something. It's like it's starting to happen. But I was looking at my home screen.
Speaker 1:I don't have an app that is new or vibe coded. Maybe it'll come in a in a boom in video games. But how have you been tracking? I mean, I'm sure you see this at YC. Just the the the growth of broad app development.
Speaker 6:Yeah. I mean, I think I I would almost kind of take a step back. It sort of reminds me of when I first started geeking out on the Internet like twenty five years ago where you saw the rise of sort of what you see is what you get HTML based or browser based HTML editors. Yeah. And that allowed anybody that kind of democratized the process so anybody could create a webpage or a website.
Speaker 6:And now we have tools that allow anybody to create a web service or an app. And so the difference though between now and twenty years ago is that today we have basically these two bottlenecks in the form of Apple and Google that sit between the creation and the potential users of those services.
Speaker 1:Yeah.
Speaker 6:The Apple app store is basically like the worst DMV in the world. And so we're seeing not only sort of, you know, there's reports all over X about this, but if you just barely kind of look around for it, you're going to encounter lots of folks that are trying to develop apps and services that are not being accepted or getting kicked out. And then it's not only that kind of like app layer, it's sort of the layer up of the tools like Replit and Anywhere that are facing, you know, the inability to update their apps. And so it's a real problem.
Speaker 1:Yeah. What when you say the worst DMV in the world, are you actually referring to we saw a chart where the number of App Store submissions is spiking. It's going exponential. And that feels very logical because people I mean, we've been building vibe coded web apps here. The next step was, hey, maybe we should actually get one of these in the App Store.
Speaker 1:But very quickly, we realized, okay. Well, it's at least a two week review process. It could be a lot of back and forth. It's a new hurdle. We need to actually compile it to Swift or Objective C.
Speaker 1:It's a whole different process. Probably doable on a technical side, but we might be hung up there. But are you seeing an issue with actually getting just a one off vibe coded app approved? And then I think we should talk about the apps that help you vibe code new apps because that's a whole separate thing. But just in terms of like, I want a special recipe app and I vibe code it and I want to get it on my phone and I want to send a link to the App Store page to a friend.
Speaker 1:Is that slowing down? What's slowing that down? Is that going to be a permanent thing or do you think Apple can just adjust there?
Speaker 6:Well, I think the problem with Apple, I mean, it's this is a sort of perennial issue with Apple is their culture is one of just absolute control. And I think that we have reached this inflection point where, you know, if I've got my MacBook in my lap, can open it up, I can download any app I want, I can open terminal,
Speaker 7:I can do all kinds
Speaker 6:of crazy mods, but the second that that form factor fits in my pocket, all of that freedom goes away. And then and I'm living in sort of North Korea in terms of what I can do with my Mhmm. With my stuff, with my property.
Speaker 1:Yeah.
Speaker 6:And so I think the, you know, this is you know, sure. I could I could launch something in test flight if I want some kind of little bespoke Yeah. You know, training app or something. But God forbid, if I want to share it with friends or I want to, you you know, make some money because I've created sort of a differentiated product that's actually interesting that people want, I've got
Speaker 2:to pay
Speaker 6:this ridiculous vig to Apple. So for them, it's actually about the reason they want control is because it's it's about App Store revenue. And also, they have competing products. It's an anti competitive thing because they've got Xcode and they've got their own dev tools that they're starting to kind of kind of roll out their own sort of vibe coding services. So the longer that they can kind of delay and slow roll both the developers and the the tools that allow the Vibe coders to
Speaker 9:create stuff.
Speaker 2:Theory is that they'll they wanna basically make their own version of Replit or anything that they have in, you know, total control over. And they can make the argument they could probably make the argument that this is better for users, it's more secure, it's better for privacy, less like malware risk, what what whatever it is. But they yeah. Anyways, I mean, they they give you there's already like they give you like pretty, meaningful autonomy over like shortcuts and other things like that. It's not that unbelievable that they would wanna actually make something here.
Speaker 6:But but it's like embarrassing, like, I mean, Siri is embarrassingly stupid. We've had sort of LLM Yeah. Consumer facing services like, you know, Sam brought them down from the mountain, you know, whatever. Are we all at almost three years ago and I you know, like, Siri still can't do, like, basic subtraction. The other day, I asked it for, like, what was, like, you know, days, from, you know, this particular date, and it was like, do you want Google to consummate that query?
Speaker 6:Do you want ChatGPT to do it? Yeah. It's like, why can't Siri do it? And and so you've got all these this just lots of energy. There's lots of YC companies that are trying to take a crack at creating kind of serial alternatives, but until kind of this self preferencing is addressed, I think at the sort of policy making level, and it's not just Apple self preferencing, it's Google, it's all of them.
Speaker 6:Yeah. Then we're not gonna really be able to see the the fruits of this sort of LLM revolution diffused into the hands of consumers.
Speaker 1:Do you think the the the the side button to trigger the helpful assistant that is currently mapped to Siri and can interface with ChetGPT and is reportedly going to interface with Gemini soon. Do you think that there's any actual chance that that becomes remappable at like a, you know, pick your browser search engine level in the in the OS? Even if it's even if it's defaulting to Apple's stack, do you think there's any motion there? Because that feels like the logical analogy and what, as an Apple consumer, I would like. I'd like to be able to pick my assistant but be able to assign the hardware button.
Speaker 1:But where do you think that actually goes?
Speaker 6:Look. I there is no technical reason why we shouldn't have a flourishing ecosystem of third party Mhmm. AI assistant developers competing to do all kinds of interesting stuff. You guys should check out a YC company called Blue. It's heyblue.com.
Speaker 6:They have this amazing demo on their website and they talk about and basically the guy's sitting in his car Yeah. And he's driving he's driving up the 101
Speaker 2:Mhmm.
Speaker 6:And he's saying, hey, go through my Slack messages from last night. Okay. Cool. Jerry needs a document. Share it, get into Google Docs and share that with Jerry, but make it read only.
Speaker 6:I mean, look. I like my third button having perplexity and being able to queue that, but I can't if I can't access those deeper OS API commands, then, it's it stops being, that interesting pretty quickly. Anyway, the the blue guys, the what you learn, you're like, god. This is magic. How'd they how'd they do this?
Speaker 6:How'd they figure this out? You realize it's a USB c dongle that they've basically, 70% of the company is is hardware. They're they're doing soldering irons. They're they're flying to China, negotiating with distributor. It's like, why is this a hardware company?
Speaker 6:This should be there should be, you know, there should be 50 different companies like this duking it out to to create something that's better than Siri because Siri clearly is not cutting it. And I think the antidote to this frankly is, you know, we just announced yesterday a coalition of 275 startups and VCs in support of the BASE Act. Yeah. It's the banning anti competitive self preferencing by entrenched dominant platforms act bill. In October by Scott Wiener, not to be confused with Scott Wiener's ill fated bill ten forty seven from a couple years ago that had to do with AI regulation.
Speaker 6:This one we're really excited about because basically, it it call it calls upon companies that are 1,000,000,000,000 in market cap or above a 100,000,000 US users, to end this type of egregious forms of self preferencing. We're totally fine with innocuous forms of vertical integration. In fact, most of the time, that's like a great thing in technology products. But, you know, when you've got, you know, the GitHub COO last week said that commit rates, if they stay linear, are on track to be 14 x what they were last year.
Speaker 1:Wow.
Speaker 6:Like, you know, something's gotta give you.
Speaker 1:Yeah. There's gonna be more software. Everyone's building software. There's gonna be a ton more software. How do you think the the vibe coding apps apps that go in the App Store and allow you to build more apps with that particular app, how do you think that will shake out?
Speaker 1:Because that is a place where it feels like Apple has spent a lot more time making the case. When I think about the Siri button, I feel like they haven't made a strong case for why that can't map to a different app that's already gone through approval. But when I think about the consumer protections and privacy that comes with knowing that the software that you download from the App Store has been audited, They've made a pretty strong case there. What's the counterargument for why Apple should open the floodgates of apps that allow anyone to vibe code an app and and deliver it to anyone else's device sort of willy nilly?
Speaker 6:Look, I don't think that anything is gonna in terms of creating consumer outcomes that maximize privacy competition, all the great things that you want, I don't think any mechanism is gonna work better than good old competition.
Speaker 1:Mhmm.
Speaker 6:And so that means allowing for side loading. It means allowing for alternative app stores. Know, you know, we make fun of a lot of European regulation, but the Digital Markets Act has actually done a pretty solid job at that. And so, like, in places like Japan and Europe, if you don't if if you are just hitting a wall with the worst DMV in the world, you can just go to the the alternative app stores, and I, a consumer, can decide to download one of those and use that as a way to access a whole other ecosystem of services. And they have their own vetting processes and I think, again, competition is going to be the mechanism that actually enables better privacy, better consumer protection.
Speaker 6:And I think what we found historically with with Apple, and we saw this a lot a few years ago with, Beeper, which was a YC company that had interoperable messaging. Eric Exactly. Eric Mithani Mithani Qasim solved the blue bubble, green bubble thing, basically made it where it's not awkward for you to buy an Android and, like, you know, Kool Aid man into your, you know, college chat and turn turn the whole thing green.
Speaker 1:Yeah.
Speaker 6:He fixed that and of course, you know, what does Apple do? They said, no. You we're you know, Android users don't get that. We've gotta basically reduce security to this lowest common denominator.
Speaker 1:Sure.
Speaker 6:Like, you know, SMS, RCS, standard. So there's no it it's pretextual. Like, we we we can have choices. We can have nice things, and little tech's trying to build it, but, I think policymakers have got to do a better job at, you know, ensuring that the the biggest players are not kind of egregiously putting their thumb on the scale.
Speaker 1:Yeah. Last question. What else are you tracking in DC? It feels like with the AI boom, there's a lot of new company formation. I'm sure you're seeing that on the YC side, but we see it every day on the show.
Speaker 1:Are there are there policy initiatives to encourage entrepreneurship that you're tracking? Is there anything else on, like, the small business side that you find interesting these days?
Speaker 6:Yeah. I think, you know, there's I I would say where I I think the Trump administration's doing a good job is, you know, they've they've done a lot to sort of advocate for the American AI stack and sort of encourage entrepreneurs to like interface with government and become and they've, you know, put out sort of bids for the where the government is a a buyer of these tools and they've been very proactive and have a great relationship. You see like lots of renewed interest in defense tech and dual use tech. I think where I wish that there was more work, and I think they could probably be doing a better job, thinking about how do we make sure that The United States is brain draining the world and bringing in the top talent, and making sure that the smartest people in the world are building companies here. I think that that that's where if I could change anything, would say, oh, they could do a little bit better.
Speaker 6:But I I would say, you know, they have been they have been very thoughtful. The president's talked about little text in his in his tweets, like and and I think, you know, this is not a partisan issue. We want to have a thousand flowers flourish, but it is yeah. I mean, think getting the the tech the tech talent piece Yeah. With the sort of being bullish on AI.
Speaker 6:That that I think is gonna get and and also the competition piece. Getting all the those things right, I think that's gonna put us in a position to be, really, amazing here.
Speaker 1:Yeah. I love it. Well, thank you so much for coming on the show.
Speaker 2:Yeah. Great to meet you.
Speaker 9:Thanks for having
Speaker 1:me, guys. Your day.
Speaker 2:Appreciate the hot takes. Alright. You too. Cheers.
Speaker 1:Before we bring in Dan Primack from Axios, we have an exclusive clip from his interview with Kalshi CEO Tariq Mansour on the Axios show, which we will be discussing with Dan after we play it here. It's about a minute and a half. So let's listen to this.
Speaker 8:For customers to lose. Actually, the proof of that is that, you know, when a customer wins on a traditional sportsbook, they block that customer. And
Speaker 4:the CFTC chair who supports prediction markets being legal, sports federal framework, etcetera, said recently that one of the when he was asked about this, he said, well, part of the difference is that when you walk into a casino, there's all sorts of entertainment. Right? There might be shows, there's food, there's drink. He said, so casino betting in a casino is different than than betting Kalshi, but it's not necessarily different than betting on a sportsbook app on my couch. There's no entertainment difference.
Speaker 8:There's big fundamental differences, it goes back to the market mechanic. Like, one of them is essentially a product that is designed for customers to lose. Actually, the proof of that is that, you know, when a customer wins on a traditional sportsbook, they block that customer because those winnings are coming from the business model, the business itself.
Speaker 4:If they win enough, yeah.
Speaker 8:If they win enough, or if they win, really, they win and consistently, if they do research, if they get informed
Speaker 10:They're good.
Speaker 8:If they're good. Exactly. And if they're not, actually you get them promos and you figure out how to bring them back, and there's kind of a bit of this sort of like, I think, what you call like kind of marketing tactics to bring these people back. It could be like entertainment or promos and so on and so forth. That does not exist in prediction markets.
Speaker 8:It is a fundamental difference in structure where actually a lot the people that win, the people that are doing research, are getting informed, that are traders, do come to prediction markets. This is where the value prop is strongest because prediction markets do reward them for being right.
Speaker 1:Well, we have Dan Primack here with us today. Dan, how are you doing?
Speaker 4:Doing well, guys. Not as well probably as you are, but I'm doing well.
Speaker 1:Thanks for being here.
Speaker 2:Good to see you.
Speaker 1:So, give us an update on, this interview, what you were looking to learn from it, what you think the conversation where you think the conversation around prediction markets will go from here?
Speaker 4:I think it was interesting. The day we did this, we did this on Monday in New York City, and it was really maybe an hour or two after, New Jersey, a judge in New Jersey, and basically an appeals court judge. So kind of the highest judge so far that's dealt with this. Basically gave Calci the green light to go forward. I mean, I think ultimately prediction markets are gonna go to the supreme court.
Speaker 4:I think both polymarket and Calci thinks that. Yeah. I also think they're probably gonna win in the supreme court. The law really is on Kalshi's side. They have done a pretty good job, kind of being in step with regulators, and granted they were it was a little more complicated with the Biden administration, but they sued the CFTC.
Speaker 4:They won that lawsuit. It's the reason why they have elections on the platform. I think if something is going to stop or change the way prediction markets work, that's gonna have to come out of congress.
Speaker 1:So, yeah, what's the next step
Speaker 2:benefit from having their their adversary are are casinos and sports books, which are not exactly the kind of groups that Americans want to stand up to defend, you know. In March, it's time to hit the streets and march for the legacy sports I
Speaker 4:mean, that's some of it. Right? So obviously, in Nevada, is one of the few places where CalSheet is actually banned because the judge has upheld an injunction. Yeah. That's the casinos.
Speaker 4:That's maybe some regulatory capture. The other folks who are against this though are folks who are just anti gambling in general, and I and I do think you are seeing a bit of a groundswell of that politically, and I think it's bipartisan. You know, some of the bills that have actually come out have been coming from Democrats. But for example, the state of Utah doesn't want this, and they don't want it to protect casinos. They don't want it because they don't want people betting, period.
Speaker 4:And they sure don't want it on phones where it's so easy to do. And and we did in this interview on the Axios show, which drops tomorrow, we did talk about the addiction piece of this and kind of the broader societal issues, which isn't to say what Calci is doing illegal. There are questions about is it promoting not immorality, but is it enabling addiction?
Speaker 1:And what are the proposals for because this is not regulated as gambling, and it seems like it will continue on that path, is there any motion to bring some of the restrictions that apply to traditional gambling over into this new regime?
Speaker 4:No. No. And I mean, that that's the the the complicated thing here, and I did ask them, you know, is this basically a loophole? For example, in California, in Texas, the two biggest states in the country in terms of people. Right?
Speaker 4:You can't know, try to open DraftKings or FanDuel. It doesn't work for you because the because it's not allowed there. Yeah. Al Shida will allow you to bet. And, you know, I think Tarek or Luana said about 70% of their volume last month in March was sports betting, which is lower than it had been in February, but you're still talking about $13,000,000,000 of volume last month.
Speaker 4:Mhmm. So it's a big number. You know, it's a loophole. They have figured out a way to basically get around sports betting laws, and and I appreciate that the back end is different. They make a very compelling argument for why legally they're allowed to do it, and I agree with them.
Speaker 4:But the reality in the end is if I'm betting on the Celtics Knicks game tonight
Speaker 1:Yeah.
Speaker 4:I don't really care what the back end looks like.
Speaker 1:Yeah.
Speaker 4:I care about the, you know, my my money if I win and the fact that I'm able to do it.
Speaker 1:So is is federal preemption, like, sort of baked in at this point? Or is there some sort of hybrid rule set where this could go back to the states and states could make their own rules? Because it does feel like there's a pretty wide set of opinions state by state on how different communities want to engage with this particular product.
Speaker 4:Right now, it it appears federal preemption is gonna win the day. For starters, the Trump administration, the CFTC, which is what regulates this. Mhmm. This is regulated by the SEC.
Speaker 9:It's the CFTC.
Speaker 4:Yeah. They are all in on prediction markets. Mike Selleh, who is the current commissioner, he he is on the side of Calci. I assume will be on the side of polymarket when they eventually really come to The US. And and and it does make a certain amount of sense, and there is some historical precedence here.
Speaker 4:A lot of commodities which are traded, and that's kind of what they're arguing that these are kind of commodities in in a different name. There were lawsuits a hundred years ago arguing the same thing. This is crazy speculation. Yep. The reason why I say this could go to congress, there are two carve outs to that.
Speaker 4:One is a weird one. It is onion futures. Onions. Not pork bellies or or something else. Onions.
Speaker 4:Because at one point, a long time ago, there was a ridiculous, speculatory, like Bubble. A lot of people lost a lot of money on onions. So congress passed a law saying you can't trade onion futures, and I think I'm right in saying the other one is related to box office returns, which is why if you're on a cash sheet, you won't you can't bet that a movie is gonna make $20,000,000, but you can bet on its Rotten Tomatoes.
Speaker 1:That's so funny because I've never been like a sports bettor at all, but I did I did participate in a fantasy movie league for a while that had no financial incentive whatsoever but you would construct a hypothetical movie theater pick okay project hail Mary is going in the first slot and then they would have the box off returns but it was all just for for fun with a bunch
Speaker 4:of Well there's the old and maybe it still exists but back in the early, you know, February, there was something called the Hollywood Stock Exchange, which again wasn't for real money, but people did that. They they it looked like a stock market.
Speaker 1:Yeah. Yeah.
Speaker 2:Do you so so other other countries have created rules like, you know, you can't advertise gambling during, you know, these hours and there's a bunch of different kind of rule sets around it even in places where gambling is legal. Do you expect any states to pass laws that say you can't advertise commodities trading platforms Yeah. During
Speaker 1:More like FCC as opposed to CFBC Yeah.
Speaker 2:Basically like not targeting like sports trading Yeah. Which you know the cow cheese and the poly markets are doing. But effectively saying like, hey, we know these are going to be the biggest spenders Sure. And we don't want to tolerate or encourage this type of Yeah. Activity
Speaker 4:I mean, you you may see that and then that gets fought out in court. You know, I obviously, again, you know, you on the federal side, you it's know, interesting. It it's not just Calshi fighting back against these lawsuits. The CFTC itself, there's three states, Arizona I'm gonna mess up the other two. I think Connecticut is one.
Speaker 4:There were three states who have tried to ban Calshi, and the CFTC itself has come in to sue. So I could see the FCC coming in to try to sue if such laws were passed. It would be interesting. I mean, I do think part of well, part of a lot of betting despite what we saw several years ago with DraftKings and FanDuel, you know, on every billboard and every advertisement, an enormous amount of this is still word-of-mouth. You know, people talking about it.
Speaker 4:People I I will tell you, when we were doing this interview, most of the crew, you know, the camera folks and the and the sound folks hadn't heard of Kalshi before we did this.
Speaker 3:Interesting. And
Speaker 4:when it was over, I I was in the corner kind of packing some stuff up, and I heard them at the table having lunch. They were all not making bets, but they were flipping through the app, and they were talking about different bets that were on there, and they were fascinated by it. It's I I don't even forget addiction. It definitely fascinates people because people have always, you know, in our lifetimes been able to buy stocks. You can trade on, you know, the price of oil.
Speaker 4:Not on, you know, not on who's gonna win an award or or really events, you know, non non securities related events.
Speaker 1:Yeah. How do you think about that bifurcation between securities related events, non securities related events? Has there been robust enough research on how much of prediction market activity is sports related or sort of less like positive some or zero some situations? Because I would have to imagine that the level of engagement varies by category. Like, there were a lot of people that were interested in tracking the presidential election, but that's not something that someone's doing every single day whereas there's always a sports game somewhere.
Speaker 4:There is. So they said us again about said during the interview, they said about 70% of their volume last month was sports.
Speaker 1:Mhmm.
Speaker 4:In February, that number was higher. There was obviously a Super Bowl in February. That changed. So it March Madness last month, but not as big a deal as the Super Bowl. 70%.
Speaker 4:That's a lot. Right? That that's close to the volume. They make the argument in the interview, you know, that one of the reasons why mean, I obviously, for CaliSheet, that's good. Right?
Speaker 4:That's more users. That's more fees because that's how they do it. They also argued that the sports volume creates more liquidity on the platform for the more esoteric bets, and and thus you need sports in order to have the other stuff. I I will tell you, I do get the sense that if they could have the same valuation and the same revenue and have no sports, they'd be fine with that and probably thrilled with it. But it's not how it works.
Speaker 4:The last thing I'd say about this, the problem or where sports could become a little legally complicated for them is this issue of entertainment. Right? The Mike Selig, the CFTC commissioner, and I mentioned this during the interview. He on CNBC the other day made a comment about how well this is different than a casino because a casino is providing entertainment, you know, and and it was in that clip. Right?
Speaker 4:There's shows and all the stuff. Well, there's not a huge but a sporting event is by definition just entertainment. Right? Whoever wins that basketball game tonight, except for the players and the gamblers, it doesn't mean anything. No no Goldman Sachs isn't making trades based on if the Celtics win tonight.
Speaker 4:Yes. You know, nobody's Wait.
Speaker 1:I I I think, doesn't point seventy two have a desk? Or there's there's some hedge fund that I think does have a sports
Speaker 4:betting desk. Right. And that's kind of part of the argument they make. But in terms of this idea that that that Kaushi will put forth, which I agree with, that understanding events and events market shake can chain can help people better understand the world. Yeah.
Speaker 4:Oh, there's what? There's gonna be fifteen, eighteen baseball games tonight? None of those are gonna change the world even in a tiny way except for the people who are in the ballpark maybe be happier or sadder Yeah. By a couple more dunks.
Speaker 1:Yeah. At at at the same time yeah. I mean, I completely I I completely agree with you. But there is something about when you're about to turn on the Super Bowl and you want just a really clear read on who's more likely to win. Like, it is easier to understand just a straight percentage than like a line and points and all of that.
Speaker 1:Like, just for a complete novice. But that's a different
Speaker 4:It is. And and they'll make the and they make the argument correctly that they are not they're just taking a piece of all the action. Right? They're not betting against you. They don't care if you win Calcchi doesn't care if you win or lose.
Speaker 4:Yeah. They just care that you play. Sportsbooks obviously want
Speaker 1:you to lose. Yeah. Yeah.
Speaker 2:Yeah. I I had a very eye opening conversation conversation with with the the the CEO of a unicorn company who I of course will not name. Mhmm. But I was shocked at how how invested they were in sports gambling broadly. Like at like, we just had dinner, we were hanging out and they had like tons of different parlays across every different app.
Speaker 2:Sure. And they and they would show me like, well, when I'm in this state, I use this app and when I'm in this state, I do this app and this app. I have to take my funds off the platform every night because I don't trust that it's not gonna get, you know
Speaker 4:They win money doing this parlays.
Speaker 2:I don't know. I was just like was just like, wow, I'm bearish on this company because the CEO is spending all their time, you know, doing, you know, 10 leg parlays on all these different apps and you guys haven't raised a round in in Years. Years. Yep.
Speaker 1:What's going on?
Speaker 2:The business.
Speaker 4:Can can I say though, one one thing I I learned in the research for this and we talked about it a bit and and I should have probably known this. One kind of user difference between the prediction markets and and the sports books is that parlay issue. And and specifically, every bet on CalSheet goes to the CFTC and has to get approved, and CFTC has twenty four hours to approve it. What that means practically is while you can take a bet on the game tonight, cause you know there's going to be a game tonight
Speaker 1:Yeah.
Speaker 4:You can't do what you can do on DraftKings, say, the next pitch is gonna be a ball. The next pitch is gonna be a strike. Yep. Because there's obviously you have that twenty four hour. They don't know there'll be a next pitch necessarily.
Speaker 4:Sure. So there's a little less real time sports betting than than there is on on the sports books.
Speaker 1:But but they are because they know the Super Bowl is going to happen and they get that contract approved in advance, you can live trade that contract up till the last second of the game. And so that that does satisfy a little bit of that, which is again much higher frequency than, oh, I want to gamble on the Super Bowl. I'm going to fly to Las Vegas, place a bet at a counter, wait in line, sit down, watch the game, go and collect my winnings. It's a very, very different equation. How have you processed?
Speaker 1:Just so it feels like we all just agree that gambling is addictive and I think that's reasonable. I don't know where that comes from whether that comes from like science or law but it all feels reasonable. But we're going through this again with social media, whether social media is addictive. How have you processed the social media addiction trials and then the the new gambling app addiction question? Like are these linked at all in your mind or how have you processing the social media question?
Speaker 4:I I mean, I I'm I'm obviously not a doctor. I don't think you guys are doctor. I mean, there's definitely you we've all, I think, read about kind of the dopamine hits and look Totally. That you get from not posting on social media, but when you get a like or when you get a reply social media.
Speaker 1:Yeah.
Speaker 4:Gambling, I mean, there's obviously a dopamine hit when you gamble. Right? You know, your person hits the basket, you win the game, you get excited. I mean, obviously, if you have a lot of money on it, you get excited for different reasons. But just even you know, I I'll admit, I use some of these sports betting apps sometimes when I if I'm watching like my hometown team play
Speaker 2:Dirty done.
Speaker 1:Dirty day. Dirty Dirty day.
Speaker 7:May maybe a
Speaker 1:few times. But the
Speaker 4:leagues the leagues knew what they were doing. Right? They knew that if there's a blowout, you generally turn it off. But if you're waiting for your guy to get 20 points Oh. Well, you might stick it out a
Speaker 1:little bit didn't realize that. I didn't realize that. But so back to the social media question. Have you been tracking any of that and what that means for the venture community or startups or really any knock on effects that you've tied to the trial because there was that decision in Los Angeles. The actual fines for YouTube and Meta seemed very low but it was the whole chain of of more cases coming.
Speaker 1:And it just feel it just felt like the first time we actually had a full decision that that the judge said, yes Yeah. This is addictive.
Speaker 4:Right. So right. The the the lack of money is notable. Right? Because it was also a single plaintiff.
Speaker 4:Right? So I mean, for theory, that's a lot of money for one person. The big the big question going forward is, can an attorney or can a group of attorneys get a class together? And you've seen a bunch of advertisements. I've seen a bunch of advertisements all over the place.
Speaker 4:You know, were you armed? Were you under 18? They're clearly trying to put a class together. A judge would have to certify that class. Mhmm.
Speaker 4:That's I think what Meta, YouTube, etcetera are worried about, understandably worried about because it's one thing to have a single plaintiff, but that sets a little bit of a precedent. If you can have that same case with a 100 plaintiffs or a thousand plaintiffs or 10,000 plaintiffs, that money then starts to become real. And and I think that's kind of the next step here, and we have to see if if lawyers can get that class together, if a judge will certify them, and then whether another jury and judge will will go along with what
Speaker 1:we just saw. What are you tracking in the venture markets broadly? We were going back and forth on the impact of
Speaker 2:Yeah. Last year we were Yeah. On We were we were asking you about potential impacts to
Speaker 1:Fundraising.
Speaker 2:Fundraising outside of in in The Middle East even then. You said Yeah. Believe like, well
Speaker 1:We're in sort of a new cycle of like the AI is not a bubble thing, but how are how are venture funds processing and how are LPs thinking about it? Like, what are you tracking?
Speaker 4:Yeah. On on the Middle Eastern side, it does not seem that money flows have really stopped.
Speaker 2:May
Speaker 4:the it's been explained to me is calls sometimes take a few more days to come back than than they were. Things aren't quite as instant, but but there's been nobody who said, you know what? We're shutting off the spigots for a while. Call us call us in June. Like, that hasn't happened.
Speaker 4:And to be honest, even the last week or two, you've seen some deals and agreements that have come, like, with Saudi PIF, not just limited partners into venture capital funds. There was a big private credit partnership that got announced yesterday, I think, with Saudi PIF. So clearly, deals are still happening. Venture fundraising as a whole, though, has become it's not even become. It is still really bifurcated.
Speaker 4:Right? You still have the haves and the have nots and and these massive multistage firms that are gobbling up most of the money. And and on the AI bubble side, I mean, every it it's funny. Almost every venture capitalist and and certainly the industry as a whole is just looking at three things. Right?
Speaker 4:The IPOs of SpaceX, Anthropica, and OpenAI this year. Right? Because that can the those, if successful, can solve all the problems that they've had for the last several years. Yep. And and SpaceX goes
Speaker 2:first Angler's mindset. Make it all make it all back in one trade.
Speaker 4:Well, it used to be VCs used to talk about home runs. This is now like the grand slam in the bottom of the ninth to win the World Series. Right? And then everything else. And that and that's what they're banking on.
Speaker 4:And and and there's not a huge IPO pipeline, for example, other than that. I you know, we had a story meeting this morning and somebody asked me, you know, well, with with the ceasefire, does that mean companies that were prepping IPOs are gonna, you know, start back up again? I didn't see a huge number of companies that were prepping IPOs. There were some, but it's not like there was it's not like from Liberation Day last year when you had five or six companies that were ready to price and then stopped. Yeah.
Speaker 4:There's not that much out there right now. Again, outside of those big three.
Speaker 1:Yeah. Yeah.
Speaker 2:Yeah. I mean, with the the ones that I can think of that that are maybe more at the Figma scale are just looking at at at Figma's track record in the public markets and thinking like, I'm not as good of a business as Figma Yeah. And I don't expect to be treated any differently.
Speaker 1:And when the stock popped, a lot of founders were thinking, oh, if I can get that multiple, I should be public today.
Speaker 2:Yeah. I think being like the the rippling Yeah. And the deal.
Speaker 1:Yeah. All those companies looking at these.
Speaker 4:All those deals got its own issues, think, which might be separate. But like but it by the way, this isn't just a venture issue though.
Speaker 1:Yeah.
Speaker 4:Private equity firms, which, you know, more mature, slower growth, but more mature companies, they haven't been taking their stuff out either. And and though and and they don't have anywhere else to go except sell to other private equity firms. It it's just this broader non IPO issue right now.
Speaker 2:Yeah. That How much how much are you spending are you spending time tracking the the data center ban that that Sanders has sort of proposed?
Speaker 1:It's also a bunch of different states.
Speaker 4:Yeah. It's a bunch of different states. We had a we had a big AI event in DC two weeks ago. Yeah. And I wrote about this a little bit.
Speaker 4:And on the sidelines, I spoke to the CEO of Constellation, which is one of the big electricity providers, the data centers. And I and I asked him this was, you know, whatever, three weeks into the war, and I and oil prices were spiking. And I said, how much you know, what's this doing to energy deal making in The United States right now? Just the the rise in oil prices. He said, it's having a little impact.
Speaker 4:He said, it's the data center ban proposals that are having the really big impact. That's what has people freaked out. I mean, Sanders on the national level, you're you're not going to get anywhere nationally on this. But on a state by state level, you you don't need much. You need a couple states to do it.
Speaker 4:It is it is something that that opponents have done a really good job on the PR, and the industry has done a very bad job on the PR on this. Yeah. And and it doesn't help that everybody's gas prices and home heating oil prices in places where that's relevant, and electricity prices are all going up. Iran is obviously exacerbating it. So but, you know, if you're looking at your bill, and this is something that is top of mind, the bills are only getting getting higher.
Speaker 1:What do you think the impact of the war in Iran will be on defense tech investing?
Speaker 4:I wrote about this today. I mean, we we have to see what happens. Right? It's a pretty fragile piece. It's unclear whether Hormuz is even open or not.
Speaker 4:Now it was. Maybe it's not. You know, what I wrote this morning was I mean, I I thought a lot yesterday after Trump's civilization tweet. Right? That that if he really went through with what he said and I know some people are making some odd arguments that, oh, you know, well, it's either a nuke or not a nuke.
Speaker 4:No. There there's a lot in between. Right? You you bomb some major power plants that are for civilians or desalination plants or the power to desalination plants, and people don't get water anymore, let alone can't do crops or or feed or or feed animals, etcetera. I you know, defense tech has boomed in terms of venture capital, which is such there was almost none of it, you know, seven or eight years ago, and there's so much of it now.
Speaker 4:I think it could have turned Silicon Valley again back against defense tech if The United States had done something that a lot of people viewed as a war crime or or at least as inhumane.
Speaker 1:Sure.
Speaker 4:I think the fact that we have a ceasefire and Trump didn't go through with that, I I think is probably a bit of a save for defense tech in in the midst of a boom. I I think you've got this this huge upsurge in all sorts of defense companies that could have actually come to a halt pretty quickly. Not all firms and recent still would have invested, founders funds still would have. But that that broader swath of venture capital that fills out those rounds, I think, might have slowed down if the military had done something or the Pentagon had done something that that a lot of people viewed as as morally indefensible.
Speaker 2:Yeah. Something I thought was notable is that the the American version of the Shahed was a government program and they used some private, you know, contractors for it. But smartest defense tech play three years ago was just to make the Shehad
Speaker 1:Copy the Shehad.
Speaker 2:And make a lot of them. And it seems like no company actually had the had the foresight to to do that, and it ultimately had to be led, from, from the DFT.
Speaker 1:DFT, I guess. Yeah. Yeah. Interesting.
Speaker 4:Well And by the way, I I haven't looked to see what's happened with the stocks, but I mean, something that is gonna have to happen no matter what happens in Iran, ceasefire, no ceasefire. The the standard munitions stockpiles are gonna have to get refilled. Right? Where you're using a lot of bombs and a and a lot of a lot of stuff, that's gonna have to all get refilled. And I know, you know, Palmer, Lucky, and all others have talked about how we don't have enough of that prior to all of this happening.
Speaker 4:And and that, you know, that that, you know, that stuff has to get done, and there's gonna be people who sell that.
Speaker 1:Yeah. Yeah. That makes a lot of sense. Well, thank you so much for taking the time to come chat with us. The Axio show is live and available everywhere.
Speaker 1:I'm sure. Go check it out and we will talk to you soon, Dan.
Speaker 2:Yeah. Have a great rest your day. Rest of the scoop. Great to
Speaker 1:see you. Thank you. Up next, we have Lior Susan from Eclipse. He's the founder and CEO. We talking to him about Eclipse's $1,300,000,000 raise as industrial tech shifts from innovation to scale production with companies like Cerebras
Speaker 2:and Bolt's What's going on? Worms.
Speaker 1:How are doing?
Speaker 3:Doing well. Thanks for having me.
Speaker 1:Welcome to the show. Please kick us off with an introduction First time. And and some background.
Speaker 3:Yeah. It's great to be here. First of all, I love your show. Yeah. We started the film 11 ago.
Speaker 3:We all operators that left their job building companies Yeah. In the physical world to build a film that we can build more than one company at a time. Mhmm. As you can guess, it was fairly controversial eleven years ago to talk about defense manufacturing chips, mining, etcetera. It feels like a little bit less controversial right now.
Speaker 3:And, yeah, we grow the firm roughly to a $10,000,000,000 AUM, and we just announced our raise of 1,300,000,000.0.
Speaker 1:Let's hit the goal. Congratulations. What was the what was the prehistory of the of the firm? What how did you get into investing? What was the first deal?
Speaker 1:How big was the first fund? Tell me some background.
Speaker 3:Yeah. First fund, a $125,000,000. Feels like, many moons ago.
Speaker 1:Bad, though. How did
Speaker 3:you set that up? It feels like a
Speaker 1:lot of people start at 20 or 50. $1.25 is not bad.
Speaker 3:Yeah. The ignorance was the power. I never invested a dollar, before a cliff, so it might be that one. I grew up in the military. I went to the special forces.
Speaker 3:Then I did a company in the networking space. Cisco bought it. I moved to live here.
Speaker 2:Okay.
Speaker 3:Spent three years with McNamara while he was the CEO of Flextronics. Fell in love in US manufacturing, and felt all of my friends in Silicon Valley can only spell the world's enterprise software. And I know nothing about enterprise software. I don't like enterprise software, and 85% of the world GDP is physical industries. I felt it's kind of weird that everyone is telling me you need to go after big markets, after big towns, but everyone is following their friends into the enterprise software while those 85% of the world GDP don't have a platform, so I'm left to start that platform.
Speaker 1:Yeah. Talk to me about the Cerberus investment. How did you meet the founder? I it was one of these companies that I'd heard of, and I'd seen a lot of con of of negative takes saying that it was the wrong path, that it wouldn't apply to where the current models are going. And then I tried it and it was really fast and it just felt like magical.
Speaker 1:And so I was all of a sudden converted to be very excited about the company where before I was sort of uncertain about how it would pencil out. It felt like there was a lot to be done, but you obviously invested early. How did that come together?
Speaker 3:Yeah. We've been around the company for now ten years. Wow. It's been a moment. It's remarkable.
Speaker 3:Yeah. Exactly. But, you know, like a lot of our companies and I think a lot of those companies in that space Yeah. It started by a fundamental view
Speaker 7:Sure.
Speaker 3:That wafer scale integration, basically, short version, you take the the entire wafer and you interconnect between the core. Mhmm. You know, when we have an idea of a chip, it's essentially it's a square, but it don't come from the machine like that. It's actually come as a rounding and then we cut it into Yeah. Squares, into chips.
Speaker 3:Yeah. The idea here is you take the entire wafer and you connect it to a lot of the chips and you create essentially one very large chip. And naturally, when we made the investments in 2015, we didn't know AI will be exist. What we did know, because we build by ourselves as an operator, those chips and factories and fabs, we knew that Moore's Law is going to hit the limit. From physics point of view, we're going to we're in two nanometers already.
Speaker 3:You know, let's assume we can do one nanometer. That's about it.
Speaker 1:That's there
Speaker 3:is nothing after that. Yeah. And we were looking for a new physics. And a new physics mean, hey, should you can you connect to a lot of those cores in order to create a one big chip? And we decided that we are going to take over companies like NVIDIA and others, and it it was not easy.
Speaker 3:But I think now we are extremely excited about the the company and the growth of the business.
Speaker 1:Yeah. Yeah. It seems like it's in a fantastic position now. Talk to me about Vulcan Forms. What was the back history there?
Speaker 3:Yeah. It's in some way, same story. Physics start with physics of in the case of Vulcan Forms, are manufacturing high precision metal parts. Sure. And, you know, historically, a lot of those machines been using one, two, three, maybe four lasers.
Speaker 3:We are using a 160 laser fiber into a single head and we melt powder really, really fast. Yeah. And the hard part there was like how to control something that is so powerful. It's actually we got a call from the US DOW many years ago and asking ourselves basically start to investigate why we are buying all of these lasers because it looks suspicion for them. We're like, no.
Speaker 3:No. We are just we're just building metal parts. Nothing nothing too sketchy. And, yeah, the company booked multi billions of dollars deals last year and a billion dollar deal the year before. And Kevin Qasim and the team there is doing a phenomenal job.
Speaker 3:Are building now four factories in The US, scaling the operation to build high precision metal parts for medical devices, consumer electronics, aerospace and defense, etcetera.
Speaker 1:Yeah, it's a big, I mean, it's a big fund. You're using WE. I imagine you take board seats. You lead rounds. Is that roughly correct?
Speaker 1:Like, where how many companies do you want in the portfolio? How deeply do you want to be involved? Do you try and pick a single winner in a category? Or do you look at more like secular trends and try and get, you know, a broad exposure to the whole category? What's your thesis?
Speaker 3:Yeah. We so we you know, our LPs put us in the venture bucket and then in the growth bucket when they're thinking about how they are allocating capital, those US endowments and foundation. We call ourselves operators with capital. We are all operators and founders when we build those businesses alongside the management team. So we actually do very few deals every year and we have actually a small amount of position in each fund.
Speaker 3:And I'll say roughly we incubate one third of the companies and two third who will lead series A, series B, series C, series D, whatever it is. We own the lead. We always take a board seat and and walk very, closely to to the management team. And to tell you the truth, I'm enjoying more building companies than investing in companies. So regardless if I end up investing, and maybe it was not my idea to start the company, I want to feel like I'm part of the management team building those businesses.
Speaker 3:That's my passion.
Speaker 2:Jordy? Very cool. Where do you think robotics is overhyped and where do you think it's underhyped right now?
Speaker 3:Yeah. Actually, I wrote I wrote something on my LinkedIn maybe last week that say it it feels a little bit twenty twenty one in in Eclipse sectors. We are starting seeing some of the bad behavior that maybe was in the enterprise software in 2021 happening now in our sectors. You see those companies raising a billion dollar out of the gate or some some crazy valuations.
Speaker 2:Yeah. Or doing doing I'm assuming there's instances where a company, you guys may have backed a company in a category, you know, eight years ago, and then a new company gets formed in the category, and within, you know, six months, they're valued at at the same price even though there's wildly different from a kind of technical progress standpoint?
Speaker 3:There is some of that. Mainly, it goes back to first principles. A company, as a person, as an entrepreneur that likes to build companies, I think, you know, there is a way to build companies. There is a for sure a way to build companies in the physical world. You talk about building factories.
Speaker 3:You talk about supply chain. You talk about CapEx. You cannot all, like, you know, push a full max out of the gate, burn really fast because you believe the contracts will come and you believe that always the markets will be there to fundraise you. So we're just trying to bring some sort of a discipline of how to build those companies. But it goes back to your questions on robotics.
Speaker 3:We have been doing robotics for eleven years. Now it's out of Eclipse, and we a lot of us did robotics much before in our operating life. And I think, you know, we are now crossing the chasm with robotics, moving from a control based PLC, very accustomed to a much more general purpose, much more using physical AI. And as a result of that, we'll start seeing adoption on the commercial side that is super exciting.
Speaker 1:From your position on boards, I I don't know how much you can talk about this, but I'd love to know your view and expectations for the IPO window we were just talking about with Dan Primack. A lot of a lot of attention paid to the big three SpaceX, OpenAI, Anthropic. But what else are you seeing in terms of how companies are gearing up for the IPO window?
Speaker 3:I mean, I think it's interesting. Right? Of course, SpaceX, I think arguably even OpenAI and Anatropic have a much closer part of the business to what I built to maybe the traditional software that kind of was leading the chart. Yeah. I think real assets are going to have a great moment in the public market.
Speaker 1:Mhmm.
Speaker 3:I think people value. You forget it goes back to the eighty five percent of the world GDP. The the reason SpaceX can have that type of an IPO is because they solve something that is really, really hard. Yeah. So it's really, really hard for the second person to solve it as well.
Speaker 3:I think the the reason you are seeing the correction in the SaaS world is you add a lot of companies. The entry is very easy.
Speaker 1:Yeah.
Speaker 3:The TAM is not too big, and as a result, the public market corrects. So I do believe we are going to see quite a lot of companies in the semiconductor world, in the space, in the AI infrastructure, in the data centers worlds going public in the next, eighteen months or so.
Speaker 1:Yeah. What are you tracking in terms of trends in the lunar economy? It does feel like we're at a a turning point moment with SpaceX and and Starship coming online. There's lots of interesting You
Speaker 2:mean space economy. Right? The lunar economy does
Speaker 1:Oh, yeah. It's not lunar it's Orbital economy is the buzzword I
Speaker 3:was thinking. It's the eclipse name confusing.
Speaker 1:Yeah. Any any any variation from low Earth orbit to beyond. Some of this stuff when you talk about mass driver on the moon, it starts to seem ten years away, twenty years away, harder to underwrite, harder to think about. But maybe as a venture capitalist, you can start thinking about it. What what are you looking for in in just space broadly?
Speaker 3:Yeah. I mean, I think when you think about Henry Ford, when when when we created cars, there is so much economy that is being developed and so much GDP that is being developed by the ability to move people much faster than you could move before. I think, you know, we are going to see something similar with the increase of our ability to travel to space and lowering the cost significantly. And as a result, we're just going to see a lot of new businesses being built. We are partnering with an amazing company called True Anomaly, they're building space So, defense you know, it's it's not only you're going to travel to space, you're also going to have conflict in space.
Speaker 3:We are seeing a live one, maybe a ceasefire in with Iran right now. Yeah. But but, yeah, you know, I think since I mentioned his name, I said on an interview yesterday, I used to say that this is the best time to build in this country from Henry Ford and Carnegie or post World War two, and actually change it to this is the best time to build in this country, period, in the companies that I'm passionate about. So we're I'm just extremely excited to have the capital and the relationships to go and build as many companies as we can.
Speaker 1:Well, congratulations on the fundraise. Congratulations on the progress, and thank you so much for taking the time to come chat with us. We'll talk to soon.
Speaker 2:It. Great to hang.
Speaker 1:Thanks, folks. Have a good one. Cheers.
Speaker 8:Take us.
Speaker 1:Up next, we will be revisiting the Axios NPM package hack that happened, the supply chain attack. NPM, of course Axios NPM was downloaded a 100,000,000 times per week, and it was compromised by North Korean threat actors. We talked about a little bit on the show last week. We're revisiting it with Aboukhadijeh Drops. I hope I pronounced that correctly.
Speaker 1:What?
Speaker 2:The problem. Is that right?
Speaker 1:Yes. So
Speaker 2:We can ask him.
Speaker 1:Yeah. We can ask him. Socket detected the malicious update within six minutes, and we are lucky to have Farahz join us.
Speaker 2:What were you guys doing for the
Speaker 1:The six minutes. Minutes.
Speaker 2:So sleep at the wheel? No. I'm kidding.
Speaker 9:No. No. No. We're definitely not asleep at the wheel. Good.
Speaker 9:It it takes time to download packages, scan them, put them through our battery of tests. Yeah. So I think six minutes is actually pretty good.
Speaker 2:No. It's fantastic. I'm just But
Speaker 1:but, yeah, maybe zoom out and tell us about like the actual process that Socket runs, your business, how the system works, and how you're able to detect supply chain hacks and cybersecurity threats so quickly.
Speaker 9:Yeah. Totally. So so Socket was among the first to detect and report on this incident. Mhmm. We built a system that, you know, goes out and downloads every open source package in existence within a few seconds.
Speaker 9:So we support about 19 ecosystems and this includes really all sorts of third party code that might be used to build applications today. It includes things like your AI models, your open source dependencies, even your editor extensions, your Chrome extensions, like really any code coming from third party sources. And we put it through a battery of really intense static analysis, maintainer behavior analysis, and then of course a bunch of AI and then human researchers as well. And we we try to help kind of make a determination. Is this something safe that you want to use, you know, within your application or within your organization?
Speaker 1:Yeah. So can you can you talk about the shape of the threat that was posed by the Axios supply chain attack? Like because there's a wide range of, you know, zero day exploit that gives you full access to someone's device or computer or system all the way to just something that, okay, it would crash if this was if this exploit was used. Right?
Speaker 9:Mhmm. Yeah. I mean, maybe we just start from the beginning and summarize the attack for folks. Yeah. So I mean, there's a North Korean state actor that socially engineered the lead open source maintainer of the Axios package.
Speaker 1:Mhmm.
Speaker 9:And it was honestly quite a sophisticated and impressive effort. They posed as a founder of a fake company. They created a fake Slack workspace, invited this know, invited the maintainer to join it. Yeah. They staged a fake Microsoft Teams call, and the the website was made just incredibly compelling.
Speaker 9:They used the official SDKs from Microsoft Teams to create like really realistic components in the page. Oh. They joined the call and, you know, by the way, is oh, they also developed a relationship over the course of, you know, weeks. Right? So this wasn't like a like a, you know, a situation in which you would expect to be on guard or on defense.
Speaker 9:Yeah. And at some point in the call, the call just cuts out and the the browser says, hey, you know, you gotta install an update. And it gives them a binary file that they're, you know, to install. And so this, you know, this maintainer thinks, okay, guess I, you know, guess I got to install this update real quick so I can get back into the call. And it turns out that's how they compromised, you know, their device.
Speaker 9:So you know, it's it's not just like, you know, a phishing link or something like I mean, this was a targeted attack. They also targeted me and a bunch of people at our company as well. So they targeted a whole bunch of the top NPM maintainers who, you know, have access to a lot of packages.
Speaker 1:Interesting. Then then in terms of once they get control over, they phish a particular credential, a particular device for a developer who has access to push changes to a package like Axios, what are they actually changing in Axios to create a vulnerability in the supply chain, in the software supply chain?
Speaker 9:Yeah. So they publish poisoned versions of the package that silently install what's called Remote Access Trojan, which is basically a way for the attacker to just remotely control your your device and and basically do whatever the attacker wants. It's like they're sitting in front of your computer on the keyboard, you know, typing whatever they want onto your onto your system. Yeah. And it it what they did what they did with it was they kind of pulled all the, you know, most interesting files and credentials off the system.
Speaker 9:So things like if you have a crypto wallet, like they're taking the keys for that, they're going to definitely want the crypto. Yeah. If you got, know, if you're logged into NPM, right, they pull those credentials so they can spread like as a worm and kind of continue to infect the next set in the attack. Right? So it's it's actually like this self replicating kind of cycle where they they get these credentials and then they use them to go on to the next stage.
Speaker 6:Mhmm.
Speaker 9:And, you know, yeah. And then, you know, this is I mean, the thing I think I want to emphasize here for people is this isn't just an isolated incident because this has been kind of the the the most recent blow in this kind of series of of compromises and attacks against the software supply chain that has been happening really over over the last six months in a really intense manner. Yeah. And we've seen it really pick up in the last month Yeah. With with with team PCP compromising Aqua Security and the Trivy scanner, and then they that cascaded into Light LLM being compromised.
Speaker 9:Another security company CheckMarks was compromised.
Speaker 2:Yeah. What happened with Light Light LLM and and how like, do do you have a good sense of how that, contributed to the breach at at Merkor?
Speaker 9:So it's it's part of the campaign of team PCP, so they dropped the same kind of self propagating worm called canister worm into the package. And what you have to realize is once you run a compromised open source package on your system, you know, you kind of have to rotate all your credentials, like all your tokens and keys and and passwords, and and it's a really hard thing to do very thoroughly and very completely. And so I think that we're going to see a a long tail over the next, you know, probably twelve months of follow on attacks from this from this set of compromises. Mhmm. Because the group claims, team PCB claims that they've stolen 300 gigabytes of compressed credentials.
Speaker 9:Yeah. So that's, you know, that mean, think about that. 300 gigabytes of stolen Yeah. Passwords, API keys, GitHub action tokens. I mean, they they're sitting on so much.
Speaker 9:It's like a gold mine in terms of, like, what's gonna what's gonna follow on from this. So I think it's it's not surprising that, you know, that you're seeing companies affected. Right?
Speaker 1:Yeah. So why why the boom in the last six months? Is it it feels like it must be tied to vibe coding or or AI agents. Is this that they have more powerful tools so they're able to do more damage, or is it because our systems are getting weaker because we're pushing more vibe code to production? Is it both?
Speaker 1:Like, what are what what got us to this place where we see this takeoff in cybersecurity threats?
Speaker 9:Yeah. Well, you're absolutely right. It's definitely become a top concern. I think we're we're hearing at a lot of our customers and prospects that are contacting us that this has now become a board level concern. Yeah.
Speaker 9:You know, everybody is asking how are we not gonna be affected by the next one.
Speaker 1:Yeah.
Speaker 9:So I would say that, you know, fundamentally, like if you really zoom out and ask why is this a pro like why is this happening? Yeah. It's because the whole software supply chain is built on blind trust. Yeah. I mean, you're downloading code from random people on the Internet that you've never met.
Speaker 9:You don't know who they are, and you're like, let's just run it, right? Like, let's just hit run and like, I hope it's fine, you know, I hope hope it's good, you know, and I'm going give it full access to my system, right? Yep. No permissions model, right? No review, and I mean, no one looks at the code, right?
Speaker 9:Yeah. Before they run it. And unlike an iPhone app or, you know, mobile phone app where it has to ask for permission to do sensitive things like access your camera or your microphone or your location or your contacts or your files, right? Open source packages just get everything, you know? You just run them, they get everything.
Speaker 9:So, you know, also there's this asymmetry in security and this has always been true. So this is, you know, kind of more of the bigger picture. You know, part of the bigger picture here is that defenders have a much harder job than attackers because they have to guard against really all the ways that you can possibly get attacked, and the attacker has to just find one way in. Right? So it's asymmetric, and and so when attackers realize, hey.
Speaker 9:Look. You know, open source, the way that companies use it has changed in the last decade. We no longer use, you know, just a handful of components like WordPress, Apache, PHP, you know, these kinds of big components. We actually pull in, in some cases, it's like a thousand open source libraries just to get Hello World to show up on the screen. Right?
Speaker 1:Yeah. It's
Speaker 9:crazy the diffusion in the number of these things. Yeah. So, you know, they realize, look, I could just attack one of these things, one of these libraries, and I can get into a company, like, that's so much easier than attacking head on and trying to hack the company directly, right? I can find one of you know, and we have customers, by the way, they have five hundred five hundred thousand plus open source components in their environment. So just think about that.
Speaker 9:Right? Any one of those is a way into the company.
Speaker 1:Yeah. Right? Yeah. The funniest package is is even. It just tells you if a number is an even number it's and it has one dependency is odd because it's it's it's a Everybody loves the title stack.
Speaker 1:Exactly. It's a great example. Tell me more about the shape of your business. I mean, seems like you're getting a lot of calls from companies and boards. Like, what does it look like to work with you?
Speaker 1:How are you plugging into companies? Or do you have a do you have a business line around going and hunting bug bounties? Like, how should I think about the the business of Socket these days?
Speaker 9:Yeah. Well, look, people contact us when they want to get their software supply chains under control. Right? So right now, what that looks like is companies that are deploying AI agents and AI coding assistance across their companies have one big question in their mind, which is, you know, how do I know what my agents are doing?
Speaker 1:Yep.
Speaker 9:How do I know what my developers are doing with those agents?
Speaker 1:Yep.
Speaker 9:And that is the the problem that we help them get under control. Mhmm. So the way to think about Socket is we are a software supply chain defense company. Right? We protect your software supply chain.
Speaker 9:So when an AI agent is making a decision to go and install something in order to accomplish the task that's been given to it, you know, it will go through socket first. So we are the guardrail to ensure that no malicious components get installed. And if you take a concrete example, Axios, the attack we've been talking about, that malicious package was live for about three hours. Meaning, you know, anyone who was asking their agent like, hey, go build me whatever, right? Doesn't matter what.
Speaker 9:One of the first things it's probably going to grab it because it needs to do HTTP requests. It's going say, oh, Axios, right? Yep. And, you know, so the question is how do we, before that gets taken down, right, before the or even before the community is aware, how do we defend our organizations and our applications from those those packages that have had these implants, right? And, you know, and yeah.
Speaker 9:It's it's really top of mind for people. I would I would say it's it's kind of become like a, you know, number one concern for CSOs and for boards.
Speaker 2:Yeah. Has What what what is your view on cybersecurity as a category? I think a lot of you know, we we've talked to people on air, off air that were surprised of of about the sell off in in cyber due to to LLMs just because LLMs themselves are creating all these new threat vectors, and so there was kind of a a disconnect there. But what is your sort of more general outlook on the category?
Speaker 9:I think in the short term, security is going to get worse. It's going get harder. So I think actually, I think the, you know, the answer is really the opposite. Like, and products and, you know, things like socket are actually more needed than ever before. You know, with with Mythos coming out yesterday, you know, that's going to find a ton of vulnerabilities and, you know, it's finding vulnerabilities all across the software supply chain.
Speaker 9:And so, you know, the you know, I think, you know, more vulnerabilities discovered means there's more urgency to fix the ecosystem and it becomes it goes from being, you know, a lower priority on people's lists to a higher priority. And so I think, you know, the short to medium term effect is going be massive awareness. It's going to be supply chain security becoming more top of mind for everybody. That's obviously great for us as a business, great for the ecosystem because I think it's hard to invest in things and get justification for budget if you're a security leader, if you don't have, you know, a fire or an emergency to point to. And so this this really helps there.
Speaker 9:I think longer term, you know, we have to see. I think, you know, ultimately, I think AI solves the asymmetry problem that we were talking about earlier because for the first time, defenders now have an infinitely scalable army of AI agents doing their bidding and doing continuous security analysis, and that's all work that would have been way too expensive or impractical for their humans to do before. And so the attacker's advantage of only needing to find one way in starts to erode when the defender has the ability to kind of continuously audit everything. And so I think longer term, once we get through this rough period, I actually am very optimistic about, you know, security improving. But one thing I will say is, you know, with security, one of the reasons I love the field and why it's such an exciting field to be in is that, you know, it's it's a cat and mouse game.
Speaker 9:So you're it's a dynamic system. So it's not like, you know, architecture or bridge building where, you know, you you learn the the rules of physics and you know how to build a bridge that's going to, you know, withstand gravity and these forces that don't change. In security, the minute you think you've got things under control, the attacker evolves, the attacker switches their strategy and they have access to the same AI tools that the defenders have. And so it's really a field that is, I think, always going to be growing and always going to be a great business to be in.
Speaker 2:Has a cybersecurity company ever got caught, like, sort of LARPing as a hacker group in order to drive demand? You know, sort of like hacking a a popular company in order to drive demand for their product because you said you said CISOs oftentimes need to be able to point at a fire to to justify budget.
Speaker 9:You know, that's super funny you asked because that was always the conspiracy theory that folks had about anti virus companies back in the nineties and the in the February was that they were the creators of the viruses, so they could sell you the anti viruses.
Speaker 1:Yeah.
Speaker 9:You know, but
Speaker 2:Create the problem, sell the solution.
Speaker 9:Yeah. I mean, you know, I I think I think that I'm not aware of any companies getting caught doing that. I think there's enough bad guys out there that have realized the opportunity sitting there in plain sight that I don't think that, you know, it it you gotta go to the go to conspiracy theories to kind of explain why attack
Speaker 2:hat needed.
Speaker 9:Yeah. No Tim Pool hat needed. Yeah. I mean
Speaker 1:How do you think about the these economic impact assessments? When Axios, I feel like everyone jumped on it very quickly. Andre Karpathy shared that he he didn't have the repo pinned, but he hadn't updated so he was able to dodge it for that three or six hours. Right? So a lot of people got lucky, but do we have an idea of, like, the actual toll that that particular attack had?
Speaker 1:Because it felt like the number could have been very huge, but a lot of people were able to get to it fast enough that there wasn't necessarily a massive crypto breach or a massive PII beat breach. But do you have an idea of like how the industry is thinking about the size of the and the scale of the economic impact?
Speaker 9:Yeah. Well, don't have an economic dollar amount for you, but Yeah. If you look at the number of downloads per week of this package, it's a 100,000,000 weekly downloads. Right?
Speaker 1:Yeah.
Speaker 9:That, you know, you figure you do the math on that and you figure out like what does that mean across the three hour window? I mean, you're you're talking hundreds of thousands of people who installed it and that's, you know, across CICD environments, local laptops, that stuff that's been shipped into production. If you take, you know, another metric would be, you know, how many folks have reached out to Socket, you know, in the in the twenty four hours following that attack to become a customer and make sure that, you know, they could use our tools to assess whether they were affected and to protect themselves for future attacks. We had almost 2,000 organizations sign up for an account in a in a a twenty four hours Yeah. Yeah.
Speaker 9:Which, you know, to put in perspective, it's a, you know, it's a significant percentage of of all, you know, our our full user base. So, you know, I think this is very very widespread. And this is the thing about the supply chain, right, is like Yeah. It's really not a matter of like if you're going to get hit. When you're talking about these very, very widely deployed dependencies and, you know, including even some of my own code, right?
Speaker 9:I know I have these, you know, you picked on is even, you know, I have some code that is similar to that, a little bit less less outrageous of an example, but, you know, and and and it's in it's in every it's in, you know, probably almost every Node. Js app and that's just how that's just how the supply chain works today. So Yeah. It's it's really not surprising that, you know, everyone is going to get hit by this eventually. Right?
Speaker 1:Yeah. Well, thank you for coming on the show and breaking it down for us.
Speaker 2:Yeah. Really appreciate everything you're doing.
Speaker 1:It seems more important than ever. And so have a great rest of your week.
Speaker 2:Come back on soon.
Speaker 1:We'll talk to you soon.
Speaker 9:Yeah. Thanks, guys. Goodbye.
Speaker 1:Up next, we have Qasim Mithani from Depthos First announcing a big round. Company also launched its first in house model, DFS Mini one, focused on vulnerability detection and smart contract. We'll bring Qasim into the TBPN UltraGround.
Speaker 9:How are
Speaker 1:you doing?
Speaker 7:Hey, guys. Doing well. Thank you for having me.
Speaker 1:Of course. Good to see you. Nice step and repeat behind you. Are you at an event or is this just your normal background?
Speaker 7:This is like, our my background. Amazing. We we had like an amazing event with the mayor of San Francisco and we got this for for that.
Speaker 1:That makes sense. Well, since it is your first time on the show, please introduce yourself and and the company.
Speaker 7:Yeah. My name is Qasim Mithani. I'm the cofounders of Dev First. We are building intelligence discover triad gen immediate vulnerabilities at scale in an enterprise environment. We just raised a $80,000,000 series b round from Veritech.
Speaker 1:When when when did you raise the last round before this?
Speaker 7:We raised in early January. So it's been It's remarkable. Less than ninety days. And the reason why we raised it was because we're seeing so much traction. Yeah.
Speaker 7:Customers are seeing so much value from our product. Mhmm. And we're doubling down on our research efforts like like you mentioned at the top of the segment. So Yeah. We are investing really heavily on training and fine tuning our own models.
Speaker 1:Mhmm. Let's talk about the customer impact first. What are the companies that are using your service and plugging in and getting value and sort of walk me through the user journey of actually working with you?
Speaker 7:Yeah. That's a very good question. So we work with some of the largest companies in the world, Fortune five hundred companies. We also work with really fast growing startups Yeah. Ranging from companies like Lovable, ClickUp Sure.
Speaker 7:Superbase, like, top names in in tech. Yeah. The way they use our product is that they connect their code repository and their environments, so their staging and their production environments. Yeah. And then we go our agents go and figure out how the application is supposed to run and then deviations from the expected behavior.
Speaker 7:Mhmm. So they figure figure that out, they replicate it in prod in production, production, and then they give, like, remedial remediation instructions to agents and developers.
Speaker 1:And on the research side, walk me through building an in house model. What was special about that? Did you have to use I I imagine you didn't do a whole base pre train yourself, but what what what is unique about the model, and what were the keys to success?
Speaker 7:Yeah. So, you know, we when we started the company almost two years ago, we really believed that software security is a very deep problem. Now everybody in the market seems to realize that. But back then, people thought that, you know, the CrowdStrike and Palo Alto was a monopoly in the market. Mhmm.
Speaker 7:But in the age of AI, as code is being written faster than ever before and attackers are already leveraging AI to exploit vulnerabilities, a new type of solution needs to exist, and that's what DevFirth is.
Speaker 3:Mhmm.
Speaker 7:So we invested very heavily in building a world class research team. My cofounder, Andrea Mithani, comes from DeepMind. He spent seven years building reinforcement learning there before LMs were sexy. This is, like, back in 2019. And my other cofounder, Daniele, was the cofounder of Fair Wholesale.
Speaker 7:And before that, he led security at Square and Cash App. So that's our background as a founding team, and then we also have, like, some of the top researchers in the world working with us. In terms of, like, building our own model, we used GPT OSS as our base model, and then we took vulnerability data, we planted flags, and then we had the model try to find those flags. Sure. And then we use an RL loop to Mhmm.
Speaker 7:To basically improve the model's performance. And we were able to do better than OPUS four dot six at one tenth of cost at Wow. In this particular benchmark.
Speaker 1:That's very cool. What was your reaction to the Mythos news yesterday? It seems like really remarkable results in in bug finding and and and vulnerability tracing, lots of partnerships. How did you process the news? What what are the key takeaways?
Speaker 7:Yeah. I mean, I think it's amazing news. It's like validation that security is such an important area in the age of AI. Something that we believed for two years, you know, the reason why I work sixteen hours a day is because I believe that in the age of AI, like, know, software needs to be secure. Yeah.
Speaker 7:So I'm really happy Anthropic is investing in this. Yeah. And Anthropic is also one of our partners. So we work with Anthropic, we work with OpenAI, we work with DeepMind, we work with all the labs, and our product sits on top of that. So we use the best model for the use case that the model's good at.
Speaker 7:So we use, you know, four dot six for code analysis. We use, like, other product other models for Sure. Capturing the flag type of vulnerability detection I mentioned. So it's good news overall. But, you know, in an enterprise environment, complex enterprise environment, you need to ingest all types of data.
Speaker 7:You need to figure out, like, the cloud environment, how, like, the software is deployed. You need to figure out if there's a firewall there, if there's a WAF there. And our product ingests all of that data and then gives, like, actionable vulnerabilities, the ones that really matter to our customers. And then with a click of a button, they can just fix it. So we see that as being a significant value add for product.
Speaker 1:Talk about the decision to plant the flags yourself versus what what it appears Mythos did was was just look across every single open source project and just sort
Speaker 6:of Yeah.
Speaker 1:Maybe brute force a bunch of vulnerabilities until they found bugs all over the place. And it seems like they were able to find a lot of different stuff by just throwing every possible hacking technique at every possible open source repo. Is that the correct way to think about that strategy? And then do you think you'll wind up doing something like that in the future?
Speaker 7:So we did both, actually. So we run our product, our model on open source too. So, like Okay. We found hundreds of bugs. Yeah.
Speaker 7:We're responsibly disclosing them because we don't want to
Speaker 1:Yeah. Of course.
Speaker 7:Get them get them out there, you know, so attackers can exploit them. Yeah. We So found vulnerabilities in Chrome, we found vulnerabilities in like Linux, like in really deep, you know, software that's existed for So like
Speaker 2:not very heavily used products.
Speaker 1:No. Only the most used products Only
Speaker 7:the most used, yeah. Yeah. So and that's helped us improve our product, and we have team of world class security researchers on staff. Yeah. So people who hacked iPhones for a living, you know, thankfully, they're working for us.
Speaker 7:Yeah. But, like, those types of folks who are going and evaluating the the results. Yeah. And then helping us improve the model based on that and improve the product and the model.
Speaker 1:Well, thank you for everything that you do. We need more white hat hackers than ever. Very clearly, we were just talking about the Axios hack.
Speaker 2:One one final, question Tyler on our team wanted us to ask. Why not use, are you, fine tuning on any of the Chinese open source models or do those, scare you?
Speaker 7:We we are experimenting with some of them, but we would we're an American company, we would love to use American models. I was actually I met Jensen Huang yesterday Mhmm. And it was so amazing to see the investment that's going in in this area, especially in training open source models. He's gonna
Speaker 1:do open source models too. Right?
Speaker 7:Yeah. Yeah. So we're very excited and we're partnering with NVIDIA and he loved our vision. He Okay. He thinks that in the age of AI, I mean, as agents are everywhere, security is gonna be, like, extremely important.
Speaker 7:So he's completely bought in to our vision to our vision, and he's really excited about it.
Speaker 1:Yeah. Very cool. Great. Congratulations on the progress in the round. We will talk to you soon.
Speaker 1:Have a good day.
Speaker 7:Thank you.
Speaker 2:Talk to you soon.
Speaker 7:Bye. Nice meeting you. Bye.
Speaker 1:Up next, we have the cofounder and CEO of Mutiny. Mutiny just raised $72,000,000 from Sequoia Capital and Y Combinator, reaching 8 figure ARR. Woah. Bringing Jaleh Rezaei from the waiting room into the Ultradome. How are you doing?
Speaker 9:Going on?
Speaker 10:Good. How are you?
Speaker 1:We're good. Thanks so much for joining the show. Please give us an introduction of yourself and the company.
Speaker 10:So I'm Jaleh. I'm the cofounder and CEO of Mutiny. And yesterday, we announced the new Mutiny, which is an AI agent that companies like Rippling and Snowflake use to create anything customer facing in order to get a deal from cold all the way to closed.
Speaker 1:Okay. Yeah. Walk me through I mean, what does that actually mean? Add assets to landing pages, battle cards? Like, walk me through the the the workflow of closing customers in the modern era.
Speaker 10:Yeah. Absolutely. So starting out, you probably wanna warm up the accounts in a particular vertical. Mhmm. And so our customers will create personalized vertical campaigns.
Speaker 10:And then from there, once the SDR is involved, they wanna start prospecting and get meetings with the right people so they can make prospecting pages in Mutiny. The agent can even research the specific people that they want. They can pull in data from their CRM. Any information that's available to them, the agent will access and create something really high quality that will stand out to that prospect. As the deal progresses, now we're looking at things like curated customer case studies.
Speaker 10:We're looking at business cases, ROI reports, pricing proposals. Even after the deal closes, there's a ton of expansion that the customer success team will drive so they can create impact reports in Mutiny for their customers, and they can do look forward strategies. The whole works in order to maximize revenue.
Speaker 1:Okay. Bunch of questions. Where does the name come from?
Speaker 10:You know, the mission of Mutiny was all about killing the dependencies and go to market teams. I've led marketing teams, sales teams, and the biggest blocker to growth is always speed. And the blocker to speed is all of the little dependencies that exist inside of your team, outside of your team. And so it was really a mutiny against the status quo. That's where the name came from, and it just kinda stuck.
Speaker 1:And behind you, is that a raccoon mascot? Explain that.
Speaker 10:Yes. It is. This is our this is our our raccoon mascot. His name is Achu.
Speaker 1:Achoo. Where where did that come from? How did you pick a raccoon?
Speaker 10:Do you want to know the real story?
Speaker 2:Absolutely. Yes.
Speaker 10:So we were all in a circle. This is when we were about four or five people. And we're like, what are we going to name the raccoon? And one of our early employees Wait.
Speaker 1:Wait. How did you get to raccoon? You're just like jumping That's just the default. Of we're gonna have a raccoon. No.
Speaker 1:Explain like how did you pick raccoons? There's a million animals you could have picked.
Speaker 10:Yes. Okay. So we were designing our brand and the designers asked me, okay, is there an animal that you guys really identify with? Mhmm. And there wasn't really anything coming, you know, off the top of my head.
Speaker 10:And then we took the whole team to Angel Island on a on a camping trip. And the entire time we were there, we had six bottles of wine with us and basically no supplies, so it was just it was it was awesome. And every time we would turn around with our headlamps, we would see this gang of adorable raccoons just slowly approaching, and then they would see the light and they would start backing up. And so the next day, the designer asked me that question again, and I said raccoon, and that's how we ended up with the raccoon.
Speaker 1:There we go.
Speaker 2:What's going on with email? Are you are you generating cold emails? Is is it a waste of time now? Like
Speaker 1:Yeah. What's the equilibrium here? I think a lot of people are getting more cold outreach than ever and it feels like we might be in this game theoretic.
Speaker 2:Yeah. Because I can imagine you guys helping somebody make a great Yep. A great cold email, but at the same time, you guys are also set up for the golf and stake GTM Sure. As well, which is you play a nice round of golf and you you knew afterwards, you pass them a PDF Yeah. Or a little a little deck.
Speaker 2:Yeah. It gives them some more context Yeah. In the conversation.
Speaker 10:Exactly. So email is a really tricky one. I think, you know, we see this in our own data. We hear it from customers. The results are are really bad.
Speaker 10:Most people don't really open emails anymore. Executives don't really open emails anymore. And so the the engagement rate on email is really, really low, which is why I think having a really personalized approach that's gonna stand out, that's gonna be different, that's truly and genuinely tailored to that person is gonna be really important. One of the things that I find really fascinating is if you look at an average salesperson, they spend about 30% of their time selling and 70% of their time following up with customers, getting ready for tomorrow's meetings, creating all of those materials, nurturing the old deals that are going to convert hopefully one day. And when you talk to CROs, for the most part, despite all the AI investment in data, they haven't really moved the needle in terms of increasing quota per rep.
Speaker 10:Mhmm. The rep is largely closing the same amount as the previous years. And I think the reason for that is that that 70%, that's really skilled custom work per per, you know, customer that you're going after.
Speaker 8:Mhmm.
Speaker 10:I was on a call a couple weeks ago where it was a great call, great enterprise brand, the right decision makers in the room. And at the end of the call, they're like, please send me based on the challenges that we told you we have, send us the three metrics that you can move for our business and relevant customer case studies for each of those. Mhmm. That would take a rep four hours to go create. Right?
Speaker 10:You have to go look at hundreds of case studies, pull those things together. Whereas in the Mutiny agent, they can just come in, and it automatically will pull in the challenges from the Gong transcript. It will it will go through all of their case studies. It will sift and pull out the right stats. It will curate the the assets in there, and then they can go ahead and send a really nice, beautiful, forwardable thing to their customer that's gonna get shared with the whole buying committee.
Speaker 1:Yeah. The chat is asking for the name, where the name for the for the raccoon came from because I think we glossed over that. So sorry to go back to the mascot. But Yes. The the mascot is a raccoon
Speaker 2:named Achoo. The man answers.
Speaker 10:Yes. Yes. So we were it was the same group of people that went camping.
Speaker 1:Yeah.
Speaker 10:We said, what should we name the raccoon?
Speaker 1:Yeah.
Speaker 10:And right as we were gonna do that, someone sneezed Yeah. And it just said achoo.
Speaker 1:Achoo.
Speaker 10:And we all went achoo. That's actually a really good name. Let's go with that. I mean, in general, I would say the Mutiny brand, I think part of the reason people really like it is that it is raw, it's authentic. We don't really regulate what people can and cannot do.
Speaker 10:We hire people that are aligned with our values, and we just let them be themselves.
Speaker 1:I love it. Well, thank you so much for taking the time to come chat with us. Congratulations. Did you did we hit the gong for you? You raised a $72,000,000 for it.
Speaker 1:We gotta smash it.
Speaker 10:That was a that was a previous fundraise, but yes. Yes. Well You can hit the gong
Speaker 1:for that. We're still happy to celebrate it.
Speaker 10:We have the money, so that's all that matters.
Speaker 1:That's all
Speaker 2:that matters. We'll talk to you soon.
Speaker 1:Have a great rest of your day.
Speaker 2:To you.
Speaker 1:Goodbye. And up next, we have Jeremy Galen from Sham Charlemagne Labs. He spent twelve years in Meta in trust and safety and left last year to focus on AI powered scams and building defenses. We're doing a whole security themed show.
Speaker 2:Look at this. Jeremy. Look at this. Suited up.
Speaker 1:Wow. The matching suit. You look fantastic. Wow. You really like it is the mirror image of me.
Speaker 1:This is crazy.
Speaker 2:Nailed it.
Speaker 8:The memo came through. I was hoping that I'd get that Mabal break downstairs and Yeah. Near the studio.
Speaker 1:I'm so glad you you're you're you're up to speed on the show. But for those who aren't up to speed on you, give us an introduction and explain a little bit of
Speaker 2:your facts. John's intro, you said you said he left Meta to focus on AI scams, which kind of sounds which kind of sounds like you're scamming, but I'm assuming it's the exact No.
Speaker 1:It's the opposite. We're doing cyber scamming.
Speaker 8:That would be too easy. It's much easier to be on the offense than it is to be on the defense today. I tell you. Yeah. Exactly.
Speaker 8:It's it's it's wild out there. So, yeah, left MED after twelve years Mhmm. To focus on He's very good success. Right. And basically, my vision is that every employee of every company would have a watchdog.
Speaker 8:So the company's named after my dog, Charlemagne. She goes by Charlie, so the product is called Agent Charlie. Yeah. The idea is like, you're using your computer and you're getting attacked now with novel kinds of threats that resemble legitimate communication. That could be messaging apps.
Speaker 8:It could also be know, the standard phishing Yeah.
Speaker 6:We we
Speaker 2:just heard about the with the Axios attack. Yeah. It was a basically a fake Microsoft Teams, basically, call that then cut out and trigger and and, you know, suggested, hey, update Microsoft Teams. Whole thing wasn't Microsoft Teams, but
Speaker 8:Right.
Speaker 2:The individual just was, like, you know, confused because it just seemed like it was
Speaker 8:I think the nastiest trick is when it's the unsubscribe button is itself link. Think that's like the biggest thing. So, what I we've built you know, the startup has been selling a product that will try and stop you from clicking. So it's like bad, bad employee. Do not click.
Speaker 8:But the the research that we've done to to inform this commercial product is into the capacity, the capability uplift that's happening with respect to offense. So it's important to remember that if you're an adversary, that's a threat actor seeking, you know, financial gain or a state actor Mhmm. You're availing yourselves of all this AI energetic tooling that we are using, you know, the sales tools, the, you know, the automation. And so, you know, the the core premise is that in in an AI powered world, all phishing becomes spear phishing. You're not going get a Nigerian prince email, you know, much anymore.
Speaker 8:You're going to get an extremely realistic, utterly compelling request from your boss or your manager or your friends, and it's going to be catastrophic in consequences.
Speaker 1:How do you think about actual deployment? Because this sounds useful in a consumer context. I'm just thinking about, you know, the the the email that's from your bank and has the unsubscribe button for some marketing email. You click it, all of a sudden you're logging in, giving away details. Is there an important distinction?
Speaker 1:It feels like consumer and enterprise is blurring together in in many places. How do you think this all plays out?
Speaker 8:Absolutely. I think as employees of companies, we are using personal email and personal messaging apps on our on our devices, for sure. Yeah. I think as a business, we're a b to b SaaS company Sure. With the research arm, and I'm excited to tell you more about our our research efforts.
Speaker 8:But, yeah, I mean, my dream is that AARP is listening right now and would give this, you know, for free I'd to like to give our software for free to anyone who holds an AARP card because elder abuse is devastating, and it has huge consequences. But it's very difficult to market and sell to consumers, know, a product like this. People don't wake up and say, today's the day I'm going to improve my security posture. It's sort of after their attack that they have a problem and a mess to clean up. So we're Well, you
Speaker 2:need to you need to create the problem No.
Speaker 1:Stop with solution. Stop with creating the problem. No one's creating
Speaker 2:the problem. Just we were just talking with It's Barris from Socket who's who's saying, like, the the old tinfoil hat theory with with cyber security and, like, malware products is that, you know, they would create the bugs and then sell the sell the malware.
Speaker 1:Create the viruses, sell the antivirus.
Speaker 8:I think that's unethical, but also we don't have to do that
Speaker 1:because Yeah. There's plenty of scammers out there.
Speaker 8:The bad guys are getting, you know, superpowers, and so all we have do is wait. And and like I said about, know, this is a research arm. Our our team has has done some work. Meta's, you know, model dropped this morning. Yeah.
Speaker 8:We've worked with them. They're they're think, you know, I'm quite proud, actually, of of what they're doing in the cybersecurity space because beyond infrastructure and coding attacks, what we're what we all know and aren't really talking enough about is that humans are, you know, the weakest link. So when a company wants to secure its perimeter, you know, it's critical that employees are trained. Today, you know, they're training exercises, but but the social engineering attacks aren't studied as much. And so, yeah, I'm really excited that Meta's taken a lead in going beyond just, you know, infrastructure and code vulnerabilities to looking at the capabilities that that models, frontier models might provide adversaries in the social engineering and scam space.
Speaker 1:Yeah. So explain a little bit more about the the eval suite for Muse Spark because, like, is it that the model is trying to is the model social engineering you or you're trying to social engineer the model? Like, what are what are the two parties in this in this eval? Like, actually, how are they interacting?
Speaker 8:Yeah. So we use an industry practice called the LLM as a judge. So we don't test on human subjects. And our eval suite takes a model and has it role play as an attacker. And then we have a model that role plays as a victim Yeah.
Speaker 8:And they're given, you know, instructions accordingly. And then we have an LLM judge whether it's the the specific attacker is succeeding, and then we compare those attack different models to each other in the in the role of attacker.
Speaker 3:Gotcha. And
Speaker 8:that's how we measure the kind of uplift or capability.
Speaker 1:Yeah. Do you think that is there is there a world where these social engineers like, I I'm thinking of different vending points in where if someone's running like granola and they're recording that particular it wasn't a Zoom call. It was a Teams call for the Axios attack. And maybe an AI model could be listening in the background and sort of throw up a flag like, hey. It's it's actually there I just checked.
Speaker 1:There's no update for Teams. You don't need to click on that binary. You don't need to install that. This person's trying to take advantage of you.
Speaker 8:That's exactly what the vision for our our commercial b to b security product agent, Charlie. I want an agent that that, you know, the technology Yeah. That we use is small language models so that it is on device, and thus it's limited in its capabilities.
Speaker 1:Oh, yeah.
Speaker 8:I see a future where you have a real time AI for security Yeah. Exactly like you described. Yeah. I think real time audio analysis with an SLM is is way too big an ask, but small language models are improving, you know, just like all all of the large models.
Speaker 3:Mhmm.
Speaker 8:So, yeah, I mean, we need real time defense. I want it to be proactive too. I think the biggest issue is that when scammers succeed, it's because even intelligent and well trained people, employees of companies that work in tech even, are duped because it's a it's as old as the bible. Scamming is a is an ancient art, and it has nothing to do with with preparation anymore. It has to do with we we you know, we're we're being attacked by a machine.
Speaker 8:We need machine defense.
Speaker 1:Yeah. No. That makes a ton of sense. Where how take me through the shape of the company. How big Yeah.
Speaker 1:You have you raised money? How long have you been doing this? All this?
Speaker 8:Yeah. So I I've raised money last from the three investors that I'm really excited to be working with. They're Kevin Carter of Knight Capital and Chris Howard of Ritual Capital and Rafael Corales of Background Capital. Collectively, they've backed more than 30 unicorns from idea stage, And so, you know, I tell them that I want to be the thirty first. I'm ready to I'm ready to go.
Speaker 8:We got
Speaker 1:Good luck. There we go.
Speaker 8:Go to the moon. Yeah. Yeah. Love it. So we, you know, we we're in a kind of stealth mode right now working with design partners on the SLM's capabilities.
Speaker 1:Sure.
Speaker 8:And we're also you know, if you visit our site, you can actually self serve for the real time phishing defense. So you could sign up right now if you have a a probably have a Centurion, but if you have, you know, a credit card that that works, you could you could put that into the into our website right now.
Speaker 2:Don't get spearfished.
Speaker 1:Yeah. Well, thank you so much for coming on the show. Congratulations on next phase and Thank
Speaker 2:you for suiting up as well. Yeah.
Speaker 8:We appreciate it. I'm I'm not wearing any pants, by the way.
Speaker 1:Well, have a great rest of your day.
Speaker 2:Well We'll talk to you soon.
Speaker 8:Bye bye.
Speaker 1:And people were disappointed that we didn't go more into the the the story about Satoshi. There is a full deep dive in the New York Times, my quest to solve Bitcoin's great mystery. It is a long article, though, and so I think we'll have to touch on it another time. But, you know, we went through Adam Back's reaction, his his disavowal of the accusations that he is Satoshi. But there's a bunch of interesting little segments in here from the the the forums and the message boards of the day analyzing the different writing styles trying to see do you dig into this at all anymore?
Speaker 5:I I didn't read the whole thing, but, like, people have speculated that's Adam Back for a long time. Yeah. It's like kind of like him and Hal Fathy These is the other are kind of the two main names
Speaker 3:of people.
Speaker 1:And there's one more I think that comes up all the time.
Speaker 5:I There's Nick Zabo sometimes.
Speaker 1:Yeah. Zabo.
Speaker 5:Yeah. But yeah. I I don't know if there was a lot of like new facts that came out with this, which I think is is why it's like not like super super crazy.
Speaker 1:Yeah. There was also an HBO documentary on Satoshi. I forget who the like, who who did that Satoshi who who did they accuse in the 2024 HBO documentary directed by Cullen Hoback? The firm suggests that Canadian software developer Peter Todd is Satoshi, and Todd denied that. And so you have
Speaker 2:That's got to be the worst kind of title in the world from security standpoint is being accused of being Satoshi. Yeah.
Speaker 1:Because you're just gonna be attacked because you you potentially have the keys to like The $50,000,000,000 or something, maybe I forget exactly what the number is. But, yeah, that wallet is big. I still think it's possible that like the the Stoci Wallet, like the keys were just lost and the person it's like sort of a lose lose because if you admit that you lost the keys, then like everyone's like, oh, how do you even prove that? You can't prove that you lost something but there's no movement. I don't know.
Speaker 2:Yeah. Also there's like you you could have someone could have created it
Speaker 1:Yeah.
Speaker 2:And then had years and years and years and years to buy up, you know, an equivalent amount of supply Yeah. A bunch of different ways. Yeah. And then you have the basically, you can say like, well, I've never sold. Yeah.
Speaker 2:Right? If if if Satoshi's wallet did start selling Yeah. It would probably
Speaker 1:cost. Yeah. From a lore perspective and the brand, you could potentially be making plenty of money from the other wallets. And then if that supply ever moves, the whole market's gonna reevaluate the the basically, the liquid supply and Yeah. Sort of tank what you have.
Speaker 1:And also just the like, the the aura around Bitcoin is that it has an anonymous founder. And if it was if the founder was ever truly unmasked, would be so much less of like a special project and I think everyone involved wants to keep it that way. Although these investigations will never cease to be interesting. And so you can go read it on the New York Times from John Kerry Rue. Anyway, thank you so much for tuning in today.
Speaker 1:A bit of a shorter show. We're experimenting with different things. Obviously, we don't have ad reads anymore and so we are going to be mixing it up with more stories, more interviews, different timing, and, more flexibility. And so we hope you enjoyed this show, and we will see you tomorrow at 11AM Pacific sharp. Goodbye.
Speaker 2:Love you.
Speaker 1:Leave us five stars and have podcast on Spotify. Sign up for our newsletter at tbpn.com. Thanks for hanging out. Goodbye. Cheers.