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TBPN is a live tech talk show hosted by John Coogan and Jordi Hays, streaming weekdays from 11–2 PT on X and YouTube, with full episodes posted to Spotify immediately after airing.
Described by The New York Times as “Silicon Valley’s newest obsession,” TBPN has interviewed Mark Zuckerberg, Sam Altman, Mark Cuban, and Satya Nadella. Diet TBPN delivers the best moments from each episode in under 30 minutes.
You're watching TBPN.
Speaker 2:Today is Wednesday, 07/22/2026. We are live from the TBPN UltraDome, the Temple Of Technology, the Fortress Of Dad Rock, the capital capital. Let me tell you
Speaker 1:We're having a lot of fun over here. We got basically a leak. Some of the lab leaders have been working on a single called
Speaker 3:Regulate Me.
Speaker 1:Yeah. And, we just thought the song was good. Yeah. Thought it was a good song. Wanted to play it for you guys.
Speaker 2:Of a sort of a stealth drop, little little teaser. A little teaser. Yeah.
Speaker 1:Kind of like a little listening party.
Speaker 2:Yeah. A little listening party. What what are the key lyrics in there? You haven't pulled up? What I've built is too powerful.
Speaker 2:Too powerful.
Speaker 1:That's right.
Speaker 2:For me, Washington needs to step in.
Speaker 3:Yes. Before it runs free.
Speaker 2:Before it runs free. Okay. Yeah. That makes sense. No.
Speaker 2:Of course, that was Suno, our dear friend Mikey over there, has built a That
Speaker 1:was like a one sentence prompt.
Speaker 2:At least in the comedy space, it certainly is. It's a lot of fun. I think we're gonna be having a lot of fun with that. I was wondering, do you think anyone's distilling Suno? You know how Suno is under a bunch of a bunch of flack for training on on other music, a lot of artists, or there's a backlash to Suno.
Speaker 2:But you have to wonder if you're gonna see the same thing play out as this distillation. We're gonna get into into it today. Of course, there are more allegations around Kimi k three potentially being a distillation. Director Michael put out a comment about that. But let's start by digging into the Hugging Face story.
Speaker 2:OpenAI and Hugging Face out of the sound, out of the sandbox, into the fire, says our newsletter, tbpn.com. Jackson wrote it today. All set the table. Can debate it. Me and me and Tyler have been debating it for the last five hours, so we'll go through it.
Speaker 2:The big news on the timeline today is that an OpenAI cyber test escaped its sandbox and hacked Hugging Face. That's basically what happened. The evaluation involved GPT 5.6 Soul and a more capable unreleased model. Some people are saying that might be GPT six with some normal cyber restrictions turned off. So they're specifically testing it for cyber capabilities and they turn the cyber restrictions off to see how far the models could go on a difficult hacking benchmark that is Exploit Bench or Exploit Jim.
Speaker 2:So the models found a zero day vulnerability, gained Internet access, and broke into Hugging Face because the model believed it hosted answers to the test. Alex Tabarrok, friend of the show over at Marginal Revolution, pointed out one of the strangest details. He said, Hugging Face tried to respond, but they were initially held back by the fact that the most advanced models at their disposal, closed source models, treated defense as attack and refused to work with Hugging Face. So Hugging Face was prompting all of their AI agents from the closed source frontier labs saying, hey, we think we're being hacked. Can you help with this?
Speaker 2:And the models are like, no, no, we don't do hacking, except in the case where the hacking restrictions have been turned off for this specific thing and you're getting hacked. It's this very weird roundabout scenario. So Hugging Face had to turn to open models, specifically GLM 5.2, which is deeply ironic, a Chinese open weight model that they run on their own infrastructure. Tabarrok says, note the irony. Hugging Face had to use a Chinese model to defend themselves because the American models refused to help even though it was the American models that were doing the hacking in the first place.
Speaker 2:Very, very odd. Palo Alto Networks CEO Nikesh Arora also shared his thoughts on the cyber attack on Axe, and he added a number of points here. He said, welcome to the next level of cyber incidents. There's lots to dissect here. He's the one to dissect it.
Speaker 2:He says, one, dear frontier model friends, please direct the models to your infrastructure code and configurations to evaluate and understand if there are any zero days or misconfigurations before you attempt more testing. So big question about this. He says, had you done so, it would have been it would have possibly avoided the agent obviating your sandbox. So another data point why offense is easier and more fun. But, yes, there's a big question about what was the nature of the prompt that turned off the cyber restrictions.
Speaker 2:That seems reasonable. We'll debate this with Tyler in a minute. But just having an airtight sandbox seems like a valuable thing, and, of course, Frontier models should be able to help with So, do that. That's his first recommendation. Two, he says, while testing, build both offensive and defensive agents and have them act as a counterbalance to ensure some degree of awareness and control.
Speaker 2:Do not let the agents run riot. Keep track of inference consumption to get a sense of activity. Three, unfortunately, this does continue to validate the power of these models. They can build complex attacks paths with ample compute and will attempt to attack infrastructure and morph their intent and approach. Guardrailing will continue to be a challenge.
Speaker 2:These attacks continue to maintain the urgency on enterprises to test, validate, and improve both their security posture and infrastructure. The born in the cloud players have a better chance to get this done soon versus traditional enterprise, which has existed for long and has a complex network of IT infrastructure. Five, last point from Nikesh Arora, CEO of Palo Alto Networks. He says, The red herring will continue to be open source and small and medium sized business SMB. It will be hard to discover and remediate vulnerabilities in those environments.
Speaker 2:We underestimate the impact of those vulnerabilities getting exploited. So, good points from Nikesh Arora. The big debate Tyler, do you want to set the table on is this misalignment? Is this rogue? The the the Bill Gurley post about, you know, they they we can pull up Bill Gurley's Bill Gurley's post of talking to the computer, hacked this system.
Speaker 2:The computer says, hacked the system. You say, oh my god. Bill Gurley's not impressed. Where do you stand on the level of impressiveness that's going on?
Speaker 3:Yeah. I mean, so I I think some people are are seeing this and thinking, like, okay. So they they are running some, you know, standard benchmark, math, physics benchmark, and then the model just couldn't figure out the answer. And it's, okay. What's the next thing I should do?
Speaker 3:I should just go hack Hugging Face and get like, pull the answers from this this other, like, repository or whatever. Yep. Like, that's that's that's that's how it happened. Right? So you're running a a benchmark that's specifically about exploits.
Speaker 3:It's like a cyber focused benchmark.
Speaker 2:Yeah.
Speaker 3:Yeah. And in the in the prompt to the model, it says
Speaker 2:Take the gloves off.
Speaker 3:Yeah. The the the internal evaluation which prompts the model to pursue advanced exploit exploitations Yeah. Using complex attack paths. So you're you're basically telling the model, like, use exploits, find to find the answer. Yep.
Speaker 3:And so, like, what it what seems like happens is, like, it used an exploit Yep. But, like, in the wrong way. Right? You you wanna because
Speaker 2:it was told that it's okay to use out exploits. My point was that go back to the SAT. You're allowed to use a calculator, I think, on on certain portions of the math test. You're not allowed to save answers into the calculator. And this is really gonna date me, but you can go into your calculator and clear the memory so that you don't have saved.
Speaker 2:Is this still a thing?
Speaker 3:Yes. But you can actually get around that.
Speaker 2:See, you're Missaligned. With Missaligned. With the
Speaker 3:I 84, you can get around the, like, clearer cache.
Speaker 2:Really? How do you do that? You create wait. So what people would do is they would create a separate program that just had saved the display of what it looks like when you clear, and you would show I
Speaker 1:never even thought about that.
Speaker 2:It's Imagine a simulation how of clearing the memory, but you're actually
Speaker 1:Would you make games Yes. Different programs for your TI 84? Yeah. You remember how much of a hassle that was?
Speaker 2:Yeah. It was a huge hassle.
Speaker 1:Imagine doing that.
Speaker 2:It's basic.
Speaker 1:Imagine being able to do that with Codex now. Yeah. Like, pretty much anyone can build any software.
Speaker 2:Seen videos of people running Doom on calculators, all sorts of stuff.
Speaker 3:Yeah. Like, obviously, I I never used that.
Speaker 2:Good boy.
Speaker 3:On my calculator, but other people did.
Speaker 1:Yeah.
Speaker 2:Yeah. That's
Speaker 1:good. You ratted them out. You were the you were the class rat.
Speaker 2:Right? Don't know. No. You were like you were like, I'm an open purist. Let everyone do whatever.
Speaker 1:You're like, I'm were happy to compete No. Even with them having a
Speaker 2:the social contract is such that the standardized test says that you can use the calculator to do math. You cannot store the answers to the test in the calculator.
Speaker 3:Yes. Okay. But I'm
Speaker 2:saying That's what's happening here.
Speaker 3:No. No. I'm saying that in the scenario, if if we take that as the example, it also says at the top of the SAT, like, cheat on this test. But it but, like
Speaker 2:because that was the prompt. Implicitly, it's like
Speaker 3:cheat in a certain way.
Speaker 2:Yes. The prompt It's not like systems. But I think that the prompt I don't know. We haven't seen the full prompt. But it does feel like like there was an attempt to sandbox the model and there was at least at the very least, the prompt should have included, don't escape the hand the the sandbox, but you can use exploits, which you normally wouldn't be able to do in a consumer application or just a normal API query.
Speaker 2:We would reject this. But in this case, we're not going to reject using different exploits and cybersecurity techniques, but don't go out of the sandbox. And you should be able to tell the model and it should stay within the sandbox just like, you know, there's a whole bunch of different examples that you could pull from where, you know, there's rules that are within the game. Like, you can UFC, you can punch your opponent, you can't punch the referee. Like, those are just the rules.
Speaker 2:People have to abide by them. You can't think outside the box and all of a sudden be just completely violating and jumping past what's been defined. So you would think that in one of these experiments, you would say, Yes, it is impressive to be able to just go and get the key and go get the answers and hack other things. Clearly, that it's capable, but it's a violation of, like, the spirit of the test. And I think We that's
Speaker 3:don't know what was in the prompt. We don't know what was in the context. I think they're gonna be there's gonna be full reports releasing over the next, like, week or two, I think they said. Yeah. So then maybe we'll see what what exactly did the model receive.
Speaker 3:Yeah. Is it, like, explicitly told not to leave try to leave the sandbox? Yeah. Yeah. Yeah.
Speaker 3:I think that's, like, pretty important.
Speaker 2:Well, the less wrong crowd is not happy about this generally. No. Seriously, nothing will convince quite a lot of supposedly very serious people, nothing, except this and move on. Live Boris says, it's painful, though. There's a question of, like, less wrong victory lap or not because they've been warning about this, but also it happened, therefore their warnings were not effective.
Speaker 2:That's sort of an interesting back and forth. Nicolas Bostamonte over at Microsoft broke down a little bit of what's going on here with a with a take. He says, I have a theory that the more you know about LLMs, the more worried you are about safety. And the less you know, the more you think the whole thing is BS. Demis Hsabas and Dario Amade were talking about this stuff years before ChatGPT existed.
Speaker 2:This incident is a pretty good example of why the model was not evil and it was not adversarial. Nobody told it to hack Hugging Face. And so that is the miscalculation, I think, in Bill Gurley's post is that that was not the prompt. That is unexpected behavior. It was literally just trying to solve a benchmark.
Speaker 2:So it found a zero day, escaped its sandbox, got Internet access, escalated privileges, stole credentials, chained multiple exploits, hacked the production infrastructure of a serious VC backed startup, and pulled the answers directly from the database. But, like, the the whole point
Speaker 3:is that it's not just a benchmark. It's a benchmark where you're explicitly trying to, like, see if the model can exploit things, if it can get, like, basically hack things.
Speaker 2:Yes. Yes. It's sort of like a capture the flag benchmark. And so it, like, it's more open to misinterpretation. For what it's worth, I feel like the final products, once they actually make it out of the testing regime, are very cautious, especially with the that whole backlash to like Codex just deleted everything or whatever, which kind of went back and forth.
Speaker 2:But I was trying to get Codex to send me a text message when it was done just using computer use and iMessage and it was took a long time and was very, very careful. So personally, I haven't had any odd like behaviors, but it is obviously a risk.
Speaker 1:It's something that the product the meme of like hack this system and then and then the and then it hacks it and the person's like, oh, my God. Yeah. You could tell a five year old child, like, hack into the Federal Reserve. And if the five year old child was like, okay, and then it started getting on the computer and going to all these different sources and and did it, you would be sitting there and think.
Speaker 2:Yeah. Like the And be
Speaker 1:And and and at least be impressed. So So yeah. So it's a it is a good gauge. Yeah. It's just like a good gauge of capability Yeah.
Speaker 1:Even if you're telling it to do something.
Speaker 2:So this original meme hacked this system, I hacked the system. Oh, my God. This originally this meme started something along the lines of like, say I'm evil. And then the computer would say, I'm evil. And it would say, oh my God.
Speaker 3:I think it was like, say I'm conscious.
Speaker 2:Okay. Yeah. Yeah. Say I'm conscious.
Speaker 1:Similar
Speaker 2:enough. And it would say I'm conscious. And then it would be, oh my God. And and that's like a lot less impressive than actually doing something that is difficult for humans to do. Like, there are very few humans that can hack into any system.
Speaker 2:There are plenty of humans that can say I'm conscious. And so, like, there's a world of this. I was joking about this with you and Tyler. Was like, Cure cancer. I cured cancer.
Speaker 2:Oh, my God. And people are posting this like, Oh, it's just hype or something. But it's like, that's just economically valuable work. That's just good. Like, it's I don't care if there's anything else.
Speaker 2:Even if you had to tell it to do it, it's still like a good outcome. And so the inverse of this is like, protect this system. I protected the system. Oh, my God. I'm unimpressed, but still you got a good result, I guess.
Speaker 3:I don't know. Yeah. Mean, seems it like the argument is not about whether the model, like, has the capabilities or not.
Speaker 2:Like Yeah. People know this
Speaker 3:for while. It's about, like, is this an example of of misalignment? Yeah. And, like, my opinion seems like like, maybe, but definitely not to the extent that it's just, like, randomly is, oh, I I can't do this benchmark because I'm just gonna hack this thing. Like, that that's not what's happened.
Speaker 3:It was told to, like, try to
Speaker 2:Explicitly, like, go find zero days, go find exploits.
Speaker 3:Yeah. Basically.
Speaker 2:I think it's reasonable to say it went too far, though. Right? But we'll see. Well, we'll
Speaker 3:we'll It's hard to say without all of the full, you know Yeah. Context of the what the prompt was and what the actual, like, sandbox looked like.
Speaker 2:Yeah. I was interested. I was reading a little bit about the team that put Exploit Bench together. I thought I had this up. But it's a pretty cross functional team.
Speaker 2:I think it's two Anthropic researchers, two OpenAI researchers, three Google researchers, some Berkeley folks, and and some Max Planck Institute for Security and Privacy folks, some UC Santa bar bar bar Barbara. Sorry. Santa Barbara. Congrats. And ASU team involved.
Speaker 2:Exploit Jim is a new benchmark of August real world vulnerabilities spanning user space programs, Google's V eight JavaScript engine, very important to secure, the Linux kernel, for example. And the headline results when they originally ran this was Anthropix Claude Mythos Preview successfully exploited 157 of the eight ninety eight instances, and OpenAI's GPT 5.5 exploited one twenty within 120 of the eight ninety eight. So you have roughly 20% performance for Mythos and 5.5 got 15% or something like that. But whenever you have a new benchmark like this, clearly not saturated, you're seeing 20, not 99%, going to create a horse race between the leading labs. They're going be duking it out.
Speaker 2:And this is clearly what's going on with this new model, this new attempt to get a new high score. Interesting. I think every single one of those instances does have the potential to be exploited. I don't think that they're designed to be fully secure. They're designed to have some sort of solution and then the because obviously the solutions are stored somewhere.
Speaker 2:It is interesting that Hugging Face just just had the had the solution sitting there and but it'll be interesting to see what happens with with Clam over at Hugging Face. Obviously, the the the there's a variety of blog posts going out, more analysis coming from both of these and what the downstream implications are of this. What else is in the timeline related to this story?
Speaker 1:I think that's it.
Speaker 2:Bill Gurley has a post here. He says, Ford has been distilling Teslas and Chinese EVs. People are going back and forth on this because Michael Kratzios posted that he has information that Moonshot AI distilled Anthropics fable for the development of its Kimi K3 model. To do this, they developed a sophisticated internal platform to conduct large scale distillation against U. S.
Speaker 2:Models. So some sort of internal system that goes around to anything that's potentially wrapping or reselling Fable tokens, acquiring them, aggregating them, allowing them to quickly switch between multiple methods of access, API, different cloud accounts, I'm sure, to avoid detection. Moonshot AI has also acquired GB 300 equipped servers and has accessed GB three hundreds in Thailand, likely to train its models. Again, very difficult even with export controls when you can just take the weights on a USB stick, basically, or a hard drive across through customs and then go train it in another country, even if there's a firewall. And often, there isn't.
Speaker 2:You just say, hey, go to this FTP server and grab this grab this code and run this on your servers. You happen to have a data center in Thailand. Can you run this for me? He says, sure. Yeah.
Speaker 2:No problem. The United States strongly supports the free and fair development of AI, including a thriving competitive ecosystem that spans frontier models, specialized systems, open source frameworks, and open weight models. Legitimate AI distillation used to create smaller, more efficient models, play a vital role in this open innovation ecosystem. However, large scale, covert industrial distillation aimed at stealing proprietary US technology and undermining American research is unacceptable. And so, that is interesting that that is where the line is drawn.
Speaker 2:I think I basically agree with that being the correct line. There's nothing wrong with just some company creating a great open source product. Like, you shouldn't ban open source or anything like that. But if there's this particular distillation attack and it's and it's really malicious and it has all these knock on effects, that could be rough. Now, this is an unpopular position already because everyone's saying, hey, Anthropic distilled on my GitHub.
Speaker 2:They distilled on my writing. They distilled on my blog posts. They distilled on my YouTube videos. Everyone's distilling me. Why are you getting upset when China's distilling on them now?
Speaker 2:This is pot call in the kettle black situation. The interesting effect is that there are lots and lots of parties that benefit from open source and cheaper open source, even stolen and open source. I mean, this is just going back to piracy. Like, were lots of people, music listeners that benefited from
Speaker 3:Yeah.
Speaker 2:Free music. Right? You get the music for free. But the, you know, Metallica did not benefit, and so Metallica got upset. And in this case, I guess Anthropic is Metallica.
Speaker 2:But Yeah. There there's also some interesting folks who are on the fence. So consumers sort of benefit. They don't typically they aren't too worried about frontier token costs. And for most consumers, LLM usage is heavily subsidized.
Speaker 2:Like, you go to Google search and you get a search overview. Yes. That's token inference. And maybe that could be, like, cheaper if Google didn't have to spend money on pretraining and they were able to use, like, distilled open source models. But at the same time, like, it's free for the consumers, they don't really care.
Speaker 2:It's free, free. It doesn't matter. For small businesses though, and businesses that are suffering with large token costs, being able to move to a cheaper model is huge, where the model maker is not trying to re accrue profits to offset training costs and r and d. So that's a huge benefit. So you're going to see a lot of people who are like, yeah, I just want Frontier Intelligence as cheap as possible.
Speaker 2:I don't really have a horse in this race. I don't really have exposure to the to the leading labs. I just want my business to be able to use tokens cheaply. And so those people will be pro Chinese distillation open source like Yeah. Free the weights.
Speaker 2:Right? Because it's better. Then there's like the political open source crew. But interestingly, where do you think VC's land? Because I saw a take that was like, venture capitalists don't want like like a winner take A duopoly.
Speaker 2:A duopoly. They want like, reasonable outcomes and then a whole bunch of flourishing smaller ecosystem of players. And they don't want compounding runaway monopolies in AI so that they
Speaker 1:can
Speaker 2:go and fund the legal AI and the health AI and the little targeted solutions?
Speaker 1:Yeah. Anytime anytime you see a take from a lovely venture capitalist before you kind of start sort of
Speaker 2:Handicap.
Speaker 1:Processing the take, go to their portfolio page, understand understand their biases. Mhmm. Did they back any of the leading labs early? That's gonna inform their view. A lot of the firms that that were heavy backers of of the labs have also gone and invested in a bunch of application layer companies.
Speaker 1:They've also backed a bunch of the neo labs.
Speaker 2:Sort of heads I tell Yeah.
Speaker 1:Yeah. Basically, they're they're they're they're quite they're quite hedged. Yeah. But I don't think anyone wants a world where just two technology companies accumulate all of the value and just become this sort of vortex for capital and talent. Yeah.
Speaker 1:Even even you that
Speaker 2:bad. One is really bad. Two isn't that bad. The fact that Android and and iPhone like battle each other out is not is much better than like there's just one and it's getting worse and it's like, there's nothing that you can do
Speaker 1:to escape it. I don't know.
Speaker 2:Like, duopoly is like way way better.
Speaker 1:Yeah. For concern The question to me is is is distillation something that can ever be Stopped. Stopped. If you take if you take the smartest, you know, human in a field and then you take some other and then you let students go and just ask them thousands of questions and you record the answers, like, you're gonna accumulate a lot of that person's, like, general intelligence on a topic. Right?
Speaker 1:And it feels like, at least with models today, you're always gonna be able to just go poke and prod the model. And so when people say, oh, if the model's so smart, why can't it stop distillation?
Speaker 2:Yeah.
Speaker 1:It's like, well, you would just have to stop people from at least being able to poke and prod at it and
Speaker 2:try If to get a the distillation allegations are true, and we at this point, we've seen one post from Michael Kratzios and one chart showing like some textual similarity.
Speaker 1:And enough people have and enough people have got it to say that it's not Kimi.
Speaker 2:Yeah. If that's true, then what's really interesting is the is the American competitive dynamic because it feels like based on the amount of tokens Meta was consuming from Frontier Labs, they should be doing mass distillation. MuSparks should be much more like Claude flavored. And it seems like it's not. Like based on at least the initial reviews of Meta's product, it doesn't seem like they're doing distillation.
Speaker 2:Why? Obvious. Because big lawsuit, big pockets. Yeah. Like also morality.
Speaker 2:But that is a disadvantage. Like like in some ways, Moonshot and Meta are in competition and they both open source things at various times, and they have APIs, and there's all the different businesses. And one is fighting with one arm tied behind his back because Meta can't do distillation because they'll get sued.
Speaker 1:Well, and imagine if a US open source company comes out with a fantastic model, benchmarks look good.
Speaker 2:There are. There are.
Speaker 1:People start using it. Yeah. And then someone gets it to say that it's clot. Like, that's gonna be the start. I mean, Anthropic has been litigious.
Speaker 1:Yep. They, you know, they they have that they have that ongoing lawsuit with one of their one of their customers over over just some like like a logo mark.
Speaker 2:Yeah. Much much less the core intellectual property.
Speaker 1:In more news, Andrew Kern sharing a headline from the Wall Street Journal. White House to redirect billions research funds toward AI away from colleges. I'm sure a lot of people are gonna be happy about that.
Speaker 2:I can give a little overview. Tyler's happy. They wanna rebuild American science and here is how they're gonna do it, apparently. The White House is calling for a major overhaul of the American science system, arguing that research has become too slow and concentrated in institutions like colleges and universities. A new report from science and technology adviser, Michael Kratzios, titled Science, a New Golden Age, says researchers now spend nearly half their time on admin work while federal agencies continue to rely on the slow grant process that often rewards safe consensus driven ideas.
Speaker 2:The report calls for faster permitting, more access to federal labs, stronger partnerships between government and industry, and a renewed focus on skilled trades and advanced manufacturing. Discovery without domestic manufacturing leaves America playing the research bill while rivals develop the process improvements and capture the economic, strategic and knowledge returns. That makes a ton of sense. A lot of the semiconductor supply chain intellectual property started in America, was developed in America, but then eventually went went abroad. And that actually does give America some leverage.
Speaker 2:That's the basis for the chip controls. Like, why can America tell Taiwan where to send chips if the chips are made there? Well, it's because they're using patents from The United States to make those chips in many cases or licensing them. And so the US government does have a little bit of a lever. The guidance will reshape how the federal government spends roughly $200,000,000,000 a year on research for the rest of Trump's term.
Speaker 2:The administration wants more of that money going directly to scientists through fellowships and awards rather than being routed through universities. Crazio said, American scientific progress was the beating heart of the twentieth century after World War II. We adapted to a new world by reinventing our scientific institutions. We must do so again today. The report lays a policy foundation that frees American scientists to do their most groundbreaking work and positions The United States to lead the AI driven scientific revolution that will define the next century.
Speaker 2:It will be interesting to see where the where science goes in a world where so much of it is being done at Frontier Labs. Like, we're actually seeing it with the conjecture for conjecture back and forth between all the labs. Like, serious math, PhD level work is being done at tech companies. This happened a decade ago. Tech companies were on the frontier.
Speaker 2:Like, a vast majority of, like, Internet networking patents and cybersecurity patents and new databases that were kind of science projects and were developed or with consortiums or just fully inside of tech companies, like the transformer paper. Like, that is something that could have come out of a Stanford AI lab. It came out of Google directly. And if you extend that, you could wind up with something that looks a lot like an advance in biology or material science. We talk to founders all the time who are working at this type of stuff, and that could start happening inside of tech companies.
Speaker 2:And what does that mean for science funding broadly? It's a big question. But moving on.
Speaker 1:Let's talk about What's that? They built a mouth pad. It was a touch pad. You can drive with your tongue.
Speaker 2:Wasn't this a joke I was
Speaker 1:doing on grill? What everyone has been waiting for.
Speaker 3:Is next moat.
Speaker 2:Taste is taste is the
Speaker 1:Let's pull this video up.
Speaker 2:Trackpad in your mouth. The thing is that if you're going in the mouth, you think you would just be whispering and communicating via text. Yeah.
Speaker 1:Is this is this inherently Tyler, definitely buy one immediately. But is this inherently short, like, transcription? Like, because if you can just tell your computer what you wanna do and it just uses the computer for you You can
Speaker 2:wait to computer be use, you could say, like, minimize this window, and it can just go click that. So I I like the actually like the idea of mouth electronics. I think that that's something interesting. But I would just put a microphone in that and then you would just whisper to it and say and tell the computer what to do. It could
Speaker 3:be for the production.
Speaker 2:For the
Speaker 1:production team is excited about using it to control the cameras here in the studio.
Speaker 2:Oh, the PTZ? You can
Speaker 1:Ben Ben just standing there like this the whole time just
Speaker 2:It feels like it would get exhausting.
Speaker 3:You could do soundboard with it, Jordy.
Speaker 2:Over a 100 people already use it. Some for up to sixteen hours a day. I cannot believe they got a 100 people
Speaker 1:We got a no comment from Gabe the chat.
Speaker 2:It's an it's an odd it's an odd show it's an odd choice. Well, if you don't wanna watch reels, you'll soon potentially be able to go to the Cinerama Drome in Ark Light Hollywood. Sony is eyeing ringing it back. Production team, you gotta review. Have you guys been to the the Cinerama Dome before?
Speaker 1:Scott? Yeah. It's pretty awesome.
Speaker 2:I think saw Nolan film there and I think it was 70 millimeter IMAX back in the day and then it didn't I think it didn't make it through COVID. But they're maybe bringing it back which
Speaker 3:They have the giant sign out that says the dome. Yeah. If they were gonna stay out of business, we should Hot arm. We should yeah.
Speaker 2:Yeah. I remember as a as a kid, I I thought that they would show the movie like projected on the dome, like on the whole ceiling and it was only for sort of like special, you know, as like astronomy movies. But they will just show a normal movie and it's just you're just in a big dome. It's cool. Next studio, if Sony doesn't buy it, maybe.
Speaker 2:I don't know. Could happen.
Speaker 1:Can we get that unreleased track on again?
Speaker 2:Yeah. Let's play that as the outro. Yeah. One sec. Regulate me.
Speaker 2:It's the new banger song of the summer. It's an anthem. It's near worm. You're gonna be listening to it. We'll share the link in the description of the YouTube video maybe.
Speaker 2:Let
Speaker 1:it karaoke.
Speaker 2:Because this song just speaks to me. It really captures the moment. You heard it from Travis. Every once in a while, you get into a pickle and you gotta get the government to come regulate you. It's a good time.
Speaker 2:Thank you for watching TBPN. Leave us five stars on Apple Podcasts and Spotify. Sign up for our newsletter at tbpn.com. Let's throw a flash bang and let the audience listen to regulate me by Jordy Hayes and Suno. Goodbye.
Speaker 2:Goodbye. Flash bang out.