Meta’s AI Comeback Moment, Claude Mythos | Diet TBPN

Diet TBPN delivers the best of today’s TBPN episode in 30 minutes. TBPN is a live tech talk show hosted by John Coogan and Jordi Hays, streaming weekdays 11–2 PT on X and YouTube, with each episode posted to podcast platforms right after. Described by The New York Times as “Silicon Valley’s newest obsession,” the show has recently featured Mark Zuckerberg, Sam Altman, Mark Cuban, and Satya Nadella. Follow TBPN: https://TBPN.com https://x.com/tbpn https://open.spotify.com/show/2L6WMqY3GUPCGBD0dX6p00?si=674252d53acf4231 https://podcasts.apple.com/us/podcast/technology-brothers/id1772360235 https://www.youtube.com/@TBPNLive

Speaker names marked ? are inferred from speaking time and the show’s known hosts — they are not voice-verified.

• 0:00John Coogan?

  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. It's 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 putting out models at an accelerating pace. 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.

• 0:45Jordi Hays?

  Predicted that Meta would eventually bail?

• 0:47John Coogan?

  Yeah, the future of foundation models is closed source. He said, "Given Meta is the primary deep-pocketed, large, open-source model builder, open-source AI has become synonymous with Meta AI." 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 complements. He likes building cool products and cheap, performant 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.

• 1:29John Coogan?

  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. That all makes sense, and Llama 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 billion 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 Lutig wrote. 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..." Are on their own for model improvements thereafter. That begs the question if Meta is

• 2:10John Coogan?

  only pursuing open source insofar as it benefits themselves, what is the tipping point at which Meta stops open sourcing their AI 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 billion in CapEx is easy to open source. No one will ask questions. But when you reach $10 billion 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

• 2:52John Coogan?

  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, and image generation where Meta doesn't want to rely on a third-party provider like they had to rely on Apple. 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 is working on two new models. One was this text-based LLM codenamed Avocado, and then a separate model that was for image and video.

• 3:25Jordi Hays?

  Mango.

• 3:26John Coogan?

  Mango. Yeah. And so, have they clarified if this is Avocado? This feels like what Avocado should be, this Muse Spark. Is that what it's called?

• 3:35Jordi Hays?

  Yeah, Muse. I assume it is. I don't know what else.

• 3:38John Coogan?

  So, 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, it feels like it's not a coincidence that this news is dropping on the heels of Anthropic's 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 around with.

• 4:02Jordi Hays?

  They have a breakout Muse Spark, thinking against Opus 4.6 Max, Gemini 3.1 Pro High, GBD 5.4 X High, and then Grok 4.2. The way that they position it, it looks somewhat of a chart crime, but if you look... Uh, when you basically look at the top and you see that Muse Spark is gets an eight eighty six point four.

• 4:23John Coogan?

  Yeah.

• 4:24Jordi Hays?

  And it's in blue.

• 4:25John Coogan?

  Yep.

• 4:25Jordi Hays?

  And then you look over and it's and it's outperforming all the other models on that benchmark.

• 4:30John Coogan?

  Okay.

• 4:30Jordi Hays?

  You just sort of assume that like the highlighted blue means that it's.

• 4:34John Coogan?

  Oh, yeah, but it's not frontier at MMLU.

• 4:37Jordi Hays?

  Because there's a bunch of them as you get further and further down. So like Arc AGI two, Muse Spark dramatically underperforms.

• 4:44John Coogan?

  Oh, interesting.

• 4:45Jordi Hays?

  The other leading models.

• 4:47John Coogan?

  Yeah.

• 4:47Jordi Hays?

  And there's, there's a number of others where it is, there's plenty where it's where it's overperforming.

• 4:53John Coogan?

  Yeah.

• 4:53Jordi Hays?

  There's plenty where it's underperforming. I have, I of course, we started asking it jokes right away. So I'll pull up the joke. I said, tell me a joke.

• 5:02John Coogan?

  Okay.

• 5:03Jordi Hays?

  It said, gotcha. Here's one for you. Why don't skeletons fight each other? They don't have the guts.

• 5:09John Coogan?

  Okay.

• 5:10Jordi Hays?

  But then it doesn't even let me react. It just says, want a different vibe? I've got dad jokes, nerdy ones, or Malibu appropriate surf puns too.

• 5:18John Coogan?

  Hmm.

• 5:19Jordi Hays?

  And so I'm like, wait, why would you think I want Malibu appropriate surf pun?

• 5:23John Coogan?

  If you look in your previous chats.

• 5:25Jordi Hays?

  I have no previous.

• 5:26John Coogan?

  No previous chats. Because Meta AI crosses up Instagram. So when you search on Instagram, sometimes that prompts Lama or previous.

• 5:34Jordi Hays?

  Yeah. So I'm trying to get to the bottom of it.

• 5:36John Coogan?

  Yeah.

• 5:36Jordi Hays?

  Right? Like this feels like an oddly specific.

• 5:39John Coogan?

  Yeah.

• 5:39Jordi Hays?

  Uh, type of joke to ask me. And so I said, why would you think I want Malibu appropriate surf puns? Ha ha, fair call. Toss that in without you asking for it.

• 5:47John Coogan?

  Hmm.

• 5:48Jordi Hays?

  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. Uh, I just said, I don't believe it was random. And it says, you got me.

• 5:59John Coogan?

  You got me?

• 6:00Jordi Hays?

  That wasn't my smoothest moment. But then it denies it again.

• 6:03John Coogan?

  Weird.

• 6:03Jordi Hays?

  It says, it's just like, what kind of, what kind of joke do you actually want? No hidden motives here.

• 6:08John Coogan?

  Yeah.

• 6:08Jordi Hays?

  It said, you gave a hyper specific example based on my life, so I have to assume you were looking. At my other account for inspiration.

• 6:15John Coogan?

  Instagram.

• 6:16Jordi Hays?

  I get why, I get why that felt weird. I'm sorry it came off that way and then it denies it again.

• 6:21John Coogan?

  Hmm.

• 6:21Jordi Hays?

  Said, you're clearly lying.

• 6:23John Coogan?

  I mean, you have talked about being in Malibu on the internet for a full year. It's possible it got baked in the pre-training or something. I don't know. But yeah, I mean, what is personal superintelligence if it doesn't even know your name? Like that, that feels like they haven't dialed in the harness or whatever the tuning is to actually.

• 6:40Jordi Hays?

  Yeah, and of course Meta is going to be hyper aware. We don't want a PR cycle.

• 6:44John Coogan?

  Yeah, yeah, yeah.

• 6:45Jordi Hays?

  They trained on your data, right?

• 6:47John Coogan?

  Everyone's been, oh, that ad was a little bit too close to home.

• 6:50Jordi Hays?

  And you remember every, every once in a while, one of those like screenshot that's been screenshot like a thousand times, like goes viral and it's like, I do not give Mark Zuckerberg.

• 6:59John Coogan?

  Oh, yeah. Yeah, yeah, yeah. Like that works.

• 7:02Jordi Hays?

  Yeah.

• 7:03John Coogan?

  It's hilarious. This is, is this a rebuttal to the bench hacking allegations that happened last, last week? So, or last year. 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. Alexander Wang's hiring followed the disappointing release of Meta's previous model called Lama 4. 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.

• 7:45John Coogan?

  And so when I look at a model card like this where you could call it a chart crime where, you know, it's highlighted in blue and it feels like it's the best, but it's actually, you know, doing better on some. It does well on health bench hard. It underperforms on Arc AGI 2, as you mentioned. 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?

• 8:08Speaker 02

  There are rumors about them, like there was like extra bonuses if they, if they got number one on LM Arena.

• 8:13John Coogan?

  Sure.

• 8:13Speaker 02

  That was like something like the rumor.

• 8:15John Coogan?

  Yeah.

• 8:15Speaker 02

  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 89 and 91%.

• 8:26John Coogan?

  Yeah.

• 8:27Speaker 02

  And they're just like not very meaningful. Like you see.

• 8:29John Coogan?

  And you won't like actually feel that in the product necessarily.

• 8:31Speaker 02

  Yeah, you you kind of need to talk to these things for a long time before you can actually get the vibe.

• 8:35John Coogan?

  Yeah.

• 8:35Speaker 02

  But I I do think um uh this news is very interesting in the context of the, you know, Claude economic stuff.

• 8:41John Coogan?

  Dashboard, yeah.

• 8:42Speaker 02

  Uh because like, what, okay, what does it mean if if um the entire company has been like maxing their their Claude tokens?

• 8:48John Coogan?

  Yeah.

• 8:49Speaker 02

  Uh over the past month. It means that they weren't using this model.

• 8:51John Coogan?

  Yeah, to me, it means they they need to commoditize their complements, right? They need to bring down that cost potentially and the and if they're, I mean, we I we we sort of dug into, are they spending a billion dollars a month? It seems like absolutely not, but uh 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.

• 9:20Speaker 02

  Yeah, I think there's basically like two ways to like square those two things happening, like either one, this model's like not that good because the engineers aren't using it, or uh you know, your theory that they're just distilling cloth. So one of those is.

• 9:32John Coogan?

  That is not my theory. That is that is the schizo theory.

• 9:35Jordi Hays?

  The the news this morning, uh Meta Platforms and the information Meta Platforms has taken down internal employee-built leaderboard, tracking how many tokens staffers were using.

• 9:43John Coogan?

  Yeah.

• 9:43Jordi Hays?

  Uh showed total usage over a recent 30-day period, amount of over 60 trillion tokens. The dashboard now displays a message that is offline. It says, we've really enjoyed building this app on Nest for 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 sh- shutter it for now.

• 10:02John Coogan?

  It seemed like a fun side project. Uh 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. Uh employee projects come and go frequently, conspicuous timing though. But yeah, you you you don't want to have, you want to measure the output, the impact, not necessarily the input. Um and how much is uh is going on there. Lisan Al-Gaib says, uh Meta might actually be back with Muse Spark, still behind OpenAI and Tropic 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 uh GPT-5. 4 and Claude Opus 4.6. Muse Spark is the first new release since Lama 4 in April 2025 and also Meta's first release that's not Openweight.

• 10:47John Coogan?

  So a huge jump up in performance across a variety of benchmarks. So all good stuff there.

• 10:54Jordi Hays?

  The market is thrilled that Meta has released a a close to frontier level model, right? This is 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 what will be accomplished. And still unclear, like, are they going to go after CodeGen at all? Are they just going to try to compete on the consumer LLM side? Very, very.

• 11:28John Coogan?

  And can you economically go after CodeGen 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? 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.

• 11:48Jordi Hays?

  Yeah, the question is, will they try to send Meta Meta vibes?

• 11:53John Coogan?

  Again, with the new model.

• 11:54Jordi Hays?

  All the way up to the to the top of the App Store charts.

• 11:56John Coogan?

  Meta's new family of AI models can reach the same performance as Kimi K2 with only 30% of compute and only 10% of the compute to reach Lama 4 Maverick. So a much more efficient efficient computing frontier here. Meta Spark is an early data point on our trajectory and we have larger models in development. So the mythical 10 trillion parameter model, that that is the 10T is what everyone's working on right now, 10 trillion?

• 12:23Jordi Hays?

  Uh, yeah, probably in that in that range.

• 12:26John Coogan?

  Yeah, it's all rumored at this.

• 12:27Jordi Hays?

  Yeah, rumored GPT-4 was something like a trillion, right? You remember those memes where it's like a small circle and then the big circle?

• 12:33John Coogan?

  And then a huge circle.

• 12:34Jordi Hays?

  GPT-4, GPT-5.

• 12:35John Coogan?

  Yeah, Martin Casado 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 Blackwells. Then there will be Vera Rubens. Pre-training isn't saturated. Narrative violation. RL works. And there's so much computing coming online soon. Buckle your chin straps. It's gonna be wild. The scaling loss.

• 13:03Jordi Hays?

  And you know Brad Gersner had to come in with the 100 of MG.

• 13:06John Coogan?

  Yep, for sure. Yeah, there's a crazy bull case for Nvidia in the information, arguing it should be worth, what, 22 trillion dollars? That is a wild move. There's a lot going on. The scaling laws holding is the most important part of this.

• 13:21Jordi Hays?

  Yeah, articles from the information finance. Nvidia worth 22 trillion? This old school financial model says yes.

• 13:28John Coogan?

  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, world gardens or test environments? I don't know, the simulation.

• 13:48Jordi Hays?

  Sandbox.

• 13:49John Coogan?

  The sandbox, yeah. Breaking out of the 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, you know, they leak that out before big companies have time to go and address all the bugs, there could be serious, you know, serious ramifications for cybersecurity. And so, key partners include Apple, Google, Microsoft, Amazon, Nvidia, JP Morgan Chase, Broadcom, the Linux Foundation, Cisco, CrowdStrike, and Palo Alto Networks. They're all listed on the cybersecurity focus page for Project Glasswing.

• 14:30Jordi Hays?

  Chris Backy was having a little bit of fun because he noticed 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.

• 14:44John Coogan?

  So, yeah, it is interesting. I mean, people have predicted that AI models would be particularly good 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. It's sort of perfectly in the sweet spot for coding agents and reinforcement learning, combing through piles of code, tirelessly trying different exploits to find bugs, having a clear verifiable reward. Did you crash the system or not? Did you break into the system or not? 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

• 15:28John Coogan?

  Basically, no time delay. There's no lag. 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 in the cancer example, you know, you're going to need to be testing the drugs in vitro in mice, in monkeys, in 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

• 16:09John Coogan?

  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. Ben Thompson has a good piece on on the whole decision to to release the model or not and stage it out and and the go to market there. But even even if 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

• 16:54John Coogan?

  way out and has pretty moderate impact on the world. This was the story of GPT-2, the story of of ChatGPT, the question of, is this the model that's dangerous to put in the hands of people?

• 17:06Jordi Hays?

  Yeah, headline, a headline from February twenty two, two thousand and nineteen by Aaron Mack. OpenAI says its text generating algorithm GPT-2 is too dangerous.

• 17:17John Coogan?

  So there is, there is a, I think Ben Thompson called it like the the boy who cried wolf syndrome, the Mythos wolf. He says, there's a lot of skepticism about Anthropic's announcement. This tweet was representative from Bucocapitalbloke. Anthropic's Anthropic's marketing strategy is so funny, like, ah, the government is treading on me. 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 not make Mythos widely available beyond a lack of compute. 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,

• 18:01John Coogan?

  there's much more ability to scale, roll out, demand, set pricing. These companies might be able to pay more. The model is very expensive, but if you're justifying that against bug bounties for zero day exploits in your most critical system, when you look at like JP Morgan 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 if the rollout is paced 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.

• 18:40John Coogan?

  So I do think the systems, all of these 10 trillion 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. It's only been a few months since the last flurry of competing models from OpenAI, Anthropic and Google. And the next cycle is already off to an aggressive start. We had Meta. And then the other news is that Elon Musk announced that he is getting ready to do another larger model with XAI.

• 19:13Jordi Hays?

  He's got a few.

• 19:14John Coogan?

  He's doing seven models in training. Wow, that is a lot. Imagine V2, two variants of 1 trillion, two variants of 1.5 trillion, a 6 trillion model and a 10 trillion model. He says there's some catching up to do, but he says he will never give up, never. So he is continuing to grind and train more models.

• 19:36Jordi Hays?

  Mike from 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."

• 19:47John Coogan?

  Yeah.

• 19:47Jordi Hays?

  He says, "You should release it to a handful of trusted partners so that we can harden ourselves."

• 19:52John Coogan?

  George Hot 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. Trained AI models are the fastest depreciating asset in history. GPT-4 cost $100 million to train two years ago and is now worth less. Qwen 3.5 27B, 1 million. Sending the FOMO back. Clock is ticking, boys. It needs something like an NBL 72 to run at decent speed and even absurd API pricing doesn't cover it. There's more to be made on investor hype than API access. I just wish for honesty instead of a whole fake spiel about safety. Who remembers when GPT-2 1.5B was too dangerous? And so lots of back and forth. Dean Ball has some more thoughts on

• 20:36John Coogan?

  Mythos. It's a longer post that will let you go and read it. 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. We 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

• 21:20John Coogan?

  if the, even if the supply chain thing doesn't go through and then Anthropic can vend technology through Project Glasswing, through CrowdStrike, through Oracle and other partners to Cisco so that at least the systems are secure because everyone wants that. So he says, "A lot of people, including people in positions of authority, told us recently that models of Mythos's 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, but 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. 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

• 22:02John Coogan?

  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, we could enter a market dynamic where the best models are only available to the highest bidder. 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 and the frontier labs as in essence kingmakers. The governance regime I have described above in four is not designed to stop that dynamic.

• 22:41Jordi Hays?

  Scoop from Steven Nelson, CIA used a secret tool called ghost murmur to find airmen in Iran.

• 22:48John Coogan?

  Yeah.

• 22:49Jordi Hays?

  Ghost murmur pairs long range quantum magnet magneto magnetometry sensors with AI to find human heartbeats. I was wondering this while they were over the weekend, there was, you know, a search going on. How does somebody like, you know, an airman that's down send a signal that can be picked up by one group, but not?

• 23:11John Coogan?

  This is very odd. So there are some, there are some community notes on this saying that quantum magnetometry, I'm probably, I imagine that's how you pronounce it, detects heart magnetic fields. And I believe this technology works in labs, but only up to a few meters, not 40 miles as claims has claimed fields decay with one over R cubed, making long range detection implausible. So unclear if this is what worked, but there has to be some sort of device that you could carry on your person, like in your shoe, like an air tag that can talk to a satellite almost. 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,

• 23:56John Coogan?

  I mean, there's sat phones that are the size of large cell phones. That was available in the 80s and 90s. 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 to the place where it could be carried on your body, but it's probably classified. So I would be surprised if, 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 exceed the known public state of the art."

• 24:41John Coogan?

  The note is relevant, so it's very, very interesting. Anyway, thank you so much for tuning in today. 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 11 a.m. Pacific sharp. Goodbye.

• 25:05Jordi Hays?

  We love you.