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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.
What are the AI Doomers actually proposing? That's the question I was trying to answer this morning for a while.
Speaker 2:Year sentences.
Speaker 1:That's one. AI 2027 predicted that this month, you know, late in 2026, Congress would wake up, and that is in the journal. Congress is suddenly waking up to the AI Doomsday Threat. And so this is happening all over the place. Was it Matt Damon who was caught on TMZ being investigated about his thoughts on AI risk?
Speaker 1:There are now protests. I believe AI twenty twenty seven predicts a 10,000 person anti AI protest by the end of the year. I was trying to figure out how big this protest in Chapel Hill, North Carolina earlier this month was. I think it came in sub 10 k, but certainly tracking to it. It was about a 150 people at this at this protest in Chapel Hill, but just two oooms away from the prediction from AI 2027.
Speaker 1:So I wanted to dig into, like, what the actual proposal is because the joke for a while has been just like everyone when they're pressed on this, they just say, we gotta talk about it. We gotta talk about this. And the actual proposal is super concrete in AI 2040, and it's it's very interesting just to hear about how they want to slow things down. So the thing that I think a lot of people online who are like, yay, an anti AI sentiment that's going viral are gonna be depressed about is that, like, this is not stop AI at all. AI twenty forty is like, keep the inference flowing.
Speaker 1:The current models are great. Also, let's keep doing capabilities research, but we're just we just wanna reach superintelligence by 2040 instead of 2028 where we're not necessarily prepared. So they want it to be highly controlled by governments, nation states, highly secured. And there's a whole bunch of very, very tactical recommendations that they make around that. So the first mechanism is an AI pause.
Speaker 1:They want to pause training. They don't want to do any more new frontier training runs or R and D experiments. And to enforce this, they're calling for to apply inference only verification to essentially all major AI data centers. So anyone who has more than 10,000 h 100 equivalents, roughly a $100,000,000 of equipment, if and and that is, like, pretty easy to figure out. You're just like, big building over there.
Speaker 1:Let's send the inspector inside. Oh, says NVIDIA on all these chips. Count them up. There's over 10,000 of them. You gotta apply for this permit.
Speaker 1:You gotta do you gotta tell us what you're doing. Right? Very easy to enforce, at least in The United States. And with an international body, you could kinda do the same thing internationally. So the whole goal, you can only inference the current models and you gotta verify your workloads with an independent auditor, probably the government.
Speaker 1:Maybe there's some sort of nongovernmental organization that's doing this. You there's know, a whole bunch of different solutions that you can pull from across nuclear nonproliferation work that's happened in the past. Major countries, they want them to declare AI compute inventories. Tell everyone, not just your local population, but also the international community, how many how many warheads you got? How many h 100 equivalents do you have?
Speaker 1:Where are they? Everyone shares this. That's gonna be a really tough sell because international agreements are really, really tough sells. It's much easier to have a groundswell of support for something that happens in America. America changes.
Speaker 1:We have a system that we don't really have the international rules to to to to quickly implement that in a way that doesn't doesn't allow for a lot of defect. They want to physically remove high bandwidth East West networking inside of data centers, you can't do large distributed training runs, but you can still do inference. For any new AI r and d data centers, want entirely new facilities built from scratch with nation state level physical security and and verification. But for the next run and the one after that and the one after that as it gets crazier, we want it in a new building built inside a fairyt cage, so you can't communicate it from the outside. We want a bunch of physical controls.
Speaker 1:It's like going to a nuclear facility, highly verified who gets in the building and when air gap communications. This is one interesting, like, proposal that they have that really shows how deep they thought this through. They want the r and d data center to be connected externally. If you wanna communicate with it and and you wanna tell it what to do, okay, train the next running or do whatever, they will have a bandwidth capped connection at one meg per second. So you can send little instructions, but if you say, send me the weights because I'm taking them somewhere else, it would take you, like, five years to exfiltrate it.
Speaker 1:So interesting, like, hardware solution to this. I I I you know, how how do you actually go and implement that? There's gonna be a whole bunch of other things, but interesting that they're thinking about, like, the width of the pipe. So it'd be very obvious if you're stealing the model weights because it's like, wait. This one meg pipe has been at full tilt for months.
Speaker 1:What's going on here? Someone's taken the stuff out of the data center. They want if front when frontier model weights move from an r and d facility to an inference facility, they want it to be placed on physical storage devices encrypted independently by both The US and China. So both countries have to sign off and physically escorted by representatives of both countries to the It's a tall order. One's a tall order, for sure.
Speaker 2:Yeah.
Speaker 1:And they actually want frontier models to be made deliberately larger than compute optimal. So you they want the weights to be a 100 terabytes instead of honing them down to something that's just one terabyte that could actually be moved around a little bit easier. Yeah.
Speaker 2:I mean, first of all, this I mean, a lot of this tracks with the kind of regulation that, you know, we had pushed for, you know, beginning about two years ago around podcast, wanting podcast studios to be air gapped. Yes. Wanting, you know, Faraday cages Yeah. Around podcast studios.
Speaker 1:A locked briefcase an s m b seven s m seven b in it. And in order to unlock it, Patrick O'Shaughnessy and David Senra both need to give you codes to independently verify that this podcast is worthy of being recorded.
Speaker 2:Yeah.
Speaker 1:I like that one. Yeah. It just makes sense. High level value valve, they see as being, like, the most effective in controlling the speed of capability improvements is compute caps. So there is a world that we're going to the Bernie Sanders thing because it's already getting, like, sort of twisted, but the the big hammer is just chip controls and data center build out slowdown.
Speaker 1:Yeah. That's the easiest thing. And I think that's, like, the biggest valve that they're going to be that we're gonna see twisted around to actually slow down capabilities. And so the goal is to allow models to get better mainly by adding hardware rather than inventing better algorithms, which can leak to secret projects. So the goal is like, okay, well we know that this model is capable of this so we want this much compute over here.
Speaker 1:Okay. You've done well. We're allocating more compute as opposed to this one weird trick that AI doomers hate.
Speaker 2:Yeah.
Speaker 1:So the goal here
Speaker 2:is Yeah. Not go back It's to interesting because when you look at, I mean, anytime you have really, really hardcore government regulation and international coordination around issues like this, you're gonna have a bunch of unintended consequences. Yep. And one thing that feels obvious around this, if if these policies were to be rolled out, is that you would effectively create an incentive for millions of individuals or groups globally to be in secret, like trying to find entirely new breakthroughs that are Yeah. And and and again, this incentive already exists, but it kind of pushes a lot of the idea that humans are just gonna be like, oh, I'm not I'm no longer gonna try to create the God model because Yeah.
Speaker 2:Like there's this, you know, big global organization that's that's sort of policing it.
Speaker 1:Yeah. I just I mean, that's the same thing we see with nuclear non proliferation. There's always a discussion about what countries are getting the bomb and when and how far along are they and wars break out over this and it yeah. Like, the game's not over just because you create a framework.
Speaker 2:But ultimately, GPUs and computers are much more wide, you know, infinitely more widespread than nuclear materials.
Speaker 1:Yeah. But you still gotta marshal them altogether. Yes. There's some weird scenario where there's a Python script that's AGI that can run on your laptop. But I think most people are convinced, at least in this crowd, that Scale.
Speaker 1:That scale is a prerequisite. And, I mean, we were we were joking about, like, because we've discovered a more compute optimal way to reach AGI, and we don't need a lot of compute. But, of course, even Ilya is like, it's time to scale up. I need more compute because it seems like even if he's taking a completely orthogonal approach to, you know, innovation and research, he still needs a lot of compute. And so it does it does feel like everyone is sort of with the consensus that it's going to be a big building with a lot of energy, big heat signature, definitely visible from space and and pretty simple to to track, at least in the short term until people start building crazy underground facilities and and then you're back to, you know, nuclear non proliferation.
Speaker 1:But the their goal is at least to, like, you know, try try.
Speaker 2:Yeah. And then the other side of this is Not a pain. Does does AI development actually become something closer to the Manhattan Project Yeah. Where, you know That's what a lot people think. A researchers Yeah.
Speaker 2:Are working with the government in secret Yeah. Because you can't just assume that Yeah. Other countries are gonna slow down or Totally. Do any of
Speaker 1:these things. Yeah. And but in in general, I think the proposal is don't go back in time. It's definitely not stop everything in its tracks. It's a slowdown with the goal of scaling gradually.
Speaker 1:They do actually want to reach super intelligence. They just want to do it by 2040, hence the name of the project. So the goal is gradually scale into top human expert capability around 2035. Now a lot of people are saying, oh, we might get this by 2029, 2028, 2027. And they see that as too fast, so they wanna push that out to 2035, then wait five years with AGI, and then unlock super intelligence in 2040.
Speaker 1:This is their initial proposal. Of course, there's a lot that could change over the next decade. And and I think I think, like, to zoom out overall, if you're worried about x risk, the AI 2040 plan does feel like a concrete path towards slowing down. The conversation definitely gets dragged down into PDoom estimates and trying to narrow down exactly how a human extinction scenario plays out. And that can be that can I feel like that's almost a sideshow because in a democratic society, in amongst humanity, like, it doesn't really matter the mechanics of getting to 10% P Doom or any of those?
Speaker 1:It's just like, if everyone feels that way, something will happen. This is a concrete plan of what that might look like, and that's valuable to understand in this case. Yeah. So for the safety skeptics, it's easy to see how this level of control over what you can do with computers is authoritarian or anti libertarian. Even if we're talking about $100,000,000 computers, there's a lot of people that say, like, I should be able to do math on my computer.
Speaker 1:I can do whatever I want. Let me do cool things. I'm excited about this. That limits your freedom. It might create regulatory capture capture for a few major players.
Speaker 1:It might crash the stock market or delay economic gains that come in the good ending where alignment is solved and x risk plummets. You can imagine a situation where in a few years, if x risk fades into the background, you're like, yes, there's still a risk, but it's the same risk that we face every day with like an asteroid hitting Earth. Like, no one it doesn't really change anyone's behavior. That would be sort of the good ending in my opinion. So it's a balancing act.
Speaker 1:And for most of these slowdown proposals. I personally have a hard time black pilling about them in the sense of, like, if the if all of this gets implemented, how frustrated will I be? Like, the models are good. I would like better models. I want safe models.
Speaker 1:But at the same time, like, there is this massive capability overhang. The current models can do a lot of interesting work. We're finding new uses even for, like, non leading edge models. There's a lot that can be done. So I I I don't believe the the Doom Doomers who are dooming about what the Doomers are planning.
Speaker 1:I find that unconvincing right now. But people are starting to lay it out more. Brad Gershner, Jensen Huang, David Sachs are talking about the other side of this equation.
Speaker 2:Yeah. But It's also a big question around what does does do the twenty forty people have a point of view on robotic and physical AGI because it seems like if you even if you pause like, you know, efforts towards RSI, well, if we add billions of robots into the world that are just running on today's model, that also presents today's, like, you know
Speaker 1:I don't think they're worried about that.
Speaker 2:Yeah. Don't think they're worried about me to me that
Speaker 1:million robots with GPT six level intelligence and years of alignment work that is currently happening, that's fine. It's the next, next, next thing, the super intelligence, the thing that might have its own goals. Think I mean, we're talking to someone from OpenAI's robotics team hooking up Astra to a robot, a paintbrush, a camera. We talked about it earlier painting. I don't think we're at a point where that poses a risk.
Speaker 1:It's the next model. It's the model with its own volition, basically. Which a lot of people still aren't seeing. They're just like, yeah, like, the models keep getting better, but they seem to follow your instructions sometimes too much and then you need to worry about the paperclip scenario. But but but but it's not that they they wanna do their own thing necessarily.
Speaker 1:I don't know. But people are going back and forth on this. Clem over at Hugging Face is sorry, but asking Jacob about AI extinction risk is like asking your AC guy about climate change. Not saying it's necessarily uninteresting or wrong per se, but let's keep things in perspective and hear from the full range of expertise across the ecosystem. And Nathan Lambert says, banger.
Speaker 1:What was our take? AC guy might be right about
Speaker 2:My AC guy would be like, I don't really know about that, but I just wanna make sure when you're hot that we can run this AC cool.
Speaker 1:Yeah. I guess it's yeah. The AC guy seems seems
Speaker 2:I don't know about all mumbo jumbo, but, you know, when it's a hot summer day, don't I want you to be worried about the heat, brother.
Speaker 1:I like that. I yeah. This is an this is kind of an unnecessary shot at AC guys. You know, AC guys are important. I don't know.
Speaker 1:It's funny. What did Bernie Sanders have to say? Is this is this real? Entities will shall shall be subject to the corporate death penalty, and persons shall be shall be subject to not more than twenty years in prison if they don't pause AI development. That seems pretty easy to comply with.
Speaker 1:I don't know. I guess how do you define AI development? Is prompt engineering AI development? Then you get caught because your model sort of did a little prompt engineering in the final stage and then you're guilty of this like that. Yeah.
Speaker 1:That could be a negative knock on effect, I guess. It does seem aggressive. But his overall proposal is banning artificial super intelligence so no person entity may develop or deploy superintelligent AI systems. He defines artificial superintelligence as an artificial intelligence system that exhibits or can easily be modified to exhibit capabilities that match or exceed human cognitive performance and capabilities across a broad range of domains or tasks. Because it sounds like the mission statement.
Speaker 1:Sounds like the explicit goal of of, like, 17 different companies right now. AI AI system or AI systems that have sufficient capabilities to plan and execute the disempowerment of humanity. Okay. That's a good one. I like that.
Speaker 1:I don't like overthrowing or undermining the US government. So strongly in favor of banning that. Pausing advanced AI development until a new federal AI regulatory body is up and running. And then the new cab cabinet level federal agency will monitor frontier AI systems at all stages of the life cycle, supervise the removal of dangerous capabilities, and supervise the destruction of artificial superintelligence. We're coming forward, which is similar to the
Speaker 2:Corporate death penalty is a line that you don't hear a lot. Right? Usually, usually these companies just, you know, go bankrupt Yeah. And wind down. But corporate death penalty goes pretty hard.
Speaker 1:And metal.
Speaker 2:It's kinda it's kinda metal.
Speaker 1:Yeah. You kinda got me with that one. Yeah. Rough rough rough situation. We'll see we'll see where it goes.
Speaker 1:Jamie Cox over at over at FluidStack, the cofounder of FluidStack, a compute provider, shared his convictions, sort of pushing back on a lot of this, saying that he thinks America should build more. They're pro freedom, pro democracy. They believe AI will bolster human flourishing. We support simple, clear, enforceable regulation frameworks that set simple requirements proportion to capabilities and risk with clear responsibilities and no unnecessary barriers to competition. Yeah.
Speaker 1:The the real you're gonna see a lot of pushback from people who are like the, like, the regulatory stuff is gonna be like these 10 companies, and I'm gonna be number 11, and I'm basically getting the corporate death penalty then because I didn't make the cut to be one of the regulated, one of the approved companies. I'm still early in my stage, so there's a lot of nervousness, I'm sure. But Will said, we believe AI will make everyone rich, healthy, and free is novel and interesting comms from the frontier. He's he's endorsing this. And I I agree.
Speaker 1:I like I like this I like these convictions. I think it's generally, like, a positive direction to move in, not a direct response to the the proposals that are going out. But we're gonna get a whole lot more of them. Where do you wanna go to next?
Speaker 2:Over on TikTok, they're sharing a photo
Speaker 1:Mhmm.
Speaker 2:Of the whistleblower and saying in every worldwide disaster movie there's a dude that looks just like this that nobody listened to. And he really does look like an he does look like an actor here.
Speaker 1:Yeah. He looks good. But people are people are all
Speaker 2:And please stop calling him Scary Potter. I've been seeing people. I've been seeing people over on x calling him Scary Potter.
Speaker 1:That's the goal. The goal is to is to wake up China, wake up congress, wake up everyone.
Speaker 2:DoorDash has entered the conversation. Indeed. They said two years at DoorDash. I do not say this lightly. We are extremely close to the burrito arriving before you decide you want it.
Speaker 2:We are not we are not asking for a ban. We are asking for a pause. I don't know why they would ask for a pause.
Speaker 1:Yeah.
Speaker 2:That seems like, very very aligned to humanity Yep. And to their business Yeah. Which I think is fantastic.
Speaker 1:The Doom is very much contained to the front tier lab work. Everyone in the application layer who's applying the models, diffusing them, they're like, I just I can't get this thing to work right. I gotta get I gotta get forward deployed engineers to teach people how to use this thing. Everyone deeper in
Speaker 2:the stacks is like Jim Rainbow over Jim O'Reilly. Sure. Or Jim Riley?
Speaker 1:Yeah. Jim Riley. Jim O'Reilly Auto Parts.
Speaker 2:Oh. Jim Riley over at says, it's a whole lot of mumbo jumbo. That was your words. He just he's just happy to get, you know, eight hours back.
Speaker 1:Yeah. Yeah. Yeah. Yeah. Then, yeah, everyone deeper in the supply chain, like Jensen and all the different semiconductor manufacturers are are not particularly on this side.
Speaker 1:And then you also have Wall Street who's just like, what's the enterprise acceleration? Lots of different groups around the table that need to be brought on board to this movement. The discourse truly is fascinating. So what what is Tyler Cowen calling for?
Speaker 2:He is banging the table saying bet on this. Tyler Cowen.
Speaker 1:You named after Tyler Cowen? Is that is that your namesake? Tyler Cowen says if you have very pessimistic fears or predictions about AI, name the market prices that will support or confirm them. This is what taking this seriously means. And I love Tyler Cowen.
Speaker 1:I'm not sure this matters because if you if you you're not gonna be around to collect it.
Speaker 2:Right? Yeah. That's not not Deep Dish says, Tyler, why would short term existential risk affect market prices in any meaningful way? Spell out the exact mechanism. Contracts that pay out if everyone dies aren't worth anything to me.
Speaker 1:Yeah. I don't know.
Speaker 3:Yeah. Calling for like, oh, you want to like make a falsifiable claim. Like, is this Am I able to tell if your claim is like true or false? And so it's like very hard with these scenarios.
Speaker 1:Like Isn't it an unfalsifiable claim, though, just by definition? And, like, you just have to, like, accept that and move on?
Speaker 3:Yeah. But then it's, like, so hard to have any, like, real discussion.
Speaker 1:Was what what was nuclear any any different? Like, the threat of nuclear apocalypse, the threat of World War three, this was a very motivating factor for decades, most of the twentieth century. People made real decisions based on it, based on where to do business and where where where the where the conflicts were gonna be and the motivation for nuclear treaties and non proliferation and how we treat You can make
Speaker 3:financial decisions, like, think about nuclear war. Right? You have a you a bunker. Bunker. That's like a decision you make.
Speaker 3:Bunky? Or is anyone making like AI bunkers? No. Because they think it's gonna be so totalizing that the bunker actually doesn't do anything.
Speaker 1:Exactly. Yeah. So if you think it's so totalizing, then you don't make the bunker. And so saying, hey, you don't have a bunker is not is not proof that the person doesn't believe what they're saying. There there is the other side of this, which is Paul Cristiano, who, is has been worried about risk.
Speaker 1:He recently just joined the board of OpenAI. And and Tyler Cowen, you know, has this quote, if you're a Doomers, why aren't you short the market? And Paul Cristiano is two x levered long, and he's short the isn't he short the the the the bond market or US treasuries? Right? So he has 5% of his net worth in Tesla, 90% of his net worth in AI bets, and a 100% of his net worth in normal investments.
Speaker 1:No Tesla options. That sounds like a scary place with lottery ticket biases and the crazy Tesla investors. And then you Elias or Yudakowsky says, am I correctly understanding you're two x levered? And Paul Christiano says, yeah. And so he says he's personally short The US The US thirty year debt.
Speaker 1:I think that just means you have a mortgage. This doesn't seem like a Doom based bet. This seems like this bet also pays out in just, like, the good ending and, like, AI is real and delivers value. So your AI bets perform well, the market performs well, and money slides from US debt to data centers and AI build out debt or something like that. So he is putting his money where his mouth is, but it doesn't feel like a representation of, like, Doom by any means.
Speaker 1:People have been creating AI agents of fruit flies. Have you seen this?
Speaker 3:Yes. My understanding is is Google basically mapped out all of, the neurons in a fruit Yeah. Like the entire Three d.
Speaker 1:They got the entire structure and now people have been able to recreate that in software in a simulation.
Speaker 3:Yeah. So I think in theory you can like replicate all of the flies like decisions or whatever. It's like movements.
Speaker 2:Yes. And this is notable because many people have said I have I have the mind of a of a fruit fly.
Speaker 1:This is I have
Speaker 2:the in they've been they've said I have the intellect of a
Speaker 1:Yeah. So now they're gonna put it to the test. Yeah. To to see which performs better, the simulated fruit fly or just Jordy Hayes who we got here?
Speaker 2:This is organic farm to table Jordy Hayes.
Speaker 1:So so now that this is out and the code is out and you can run this fruit fly in simulation however you want, people are having they've been they're doing all sorts of experimentation. So, Kevin said he trapped the fruit fly in his rabbit r one. When he shakes it, he can see its brain brain's escape circuit light up.
Speaker 2:Yeah. I think what what what ends up being, un settling and weird about this is is if if it just just purely you being human and doing this is is probably not good for your own soul. And, you know, imagine imagine you have a fruit fly in a box shaking it and you're like, look, it it wants to escape.
Speaker 1:Right? Yeah. Totally.
Speaker 2:I'm not a huge fan of small insects. I don't really want them around that much. Okay. But when they're in my house Yeah. I try to, you know, if a spider's in my house, even if I know it might wanna take a nice bite of me Yeah.
Speaker 2:I'm still gonna try to transport it out of my Sure. House and and and put it back into the world. I think it's I think it's it's not good your for your soul to be, you know, a merchant of death Sure. In situation.
Speaker 1:And yet, if you're playing a real time strategy game and you highlight a bunch of soldiers in this simulation and you send them on a charge that will result in their virtual death, you might not feel
Speaker 2:But those soldiers opted in to riding and dying
Speaker 1:with him. Okay. Okay. Right. Okay.
Speaker 1:What about
Speaker 2:flies just sitting there, John.
Speaker 1:So they made the fruit fly play Doom. What about if you play Doom, you are killing a demon who simulated? Is that immoral? Like
Speaker 2:Well, that's well, is that demon trying to kill you?
Speaker 1:A lot of it comes down to, like, the fact that it's simulating a the actual representation of the fly makes it a lot more concrete than just, oh, yeah. It's a it's a three d model in a Python script that just says, if you see a if you see a character, at them in the simulation. But we're we're clearly starting to grapple with, like, these odd moral questions of, well, if you're simulating something, then the next step is a couple order of magnitude. But you get there and you can simulate a human, and you could talk to that human, and it would do everything the human does. Does that human have rights and agency as an ethical moral agent?
Speaker 1:Or is it merely just a simulated just a really good computer simulation? It's just existing on transistors, so you don't need to feel any moral weight about anything that you do to it. I agree with the just the vibes based analysis that, like, torturing a real fly, torturing a virtual fly, probably just don't be in the business of torturing anything. You don't need to overthink it. But people are the the real debate here is, like, the question of, you know, are LLMs sentient?
Speaker 1:Are they moral? Do they is there a moral weight to the to to to synthetic intelligence, to artificial intelligence? That's what people are debating here. And I'm sure the debate will continue. Who knows if it will ever be ended?
Speaker 1:But they did teach it how to parallel park, which I think is cool. Interestingly, last night, I had Astra use computer use to play a video game that I very much enjoy playing called Bellatro. It's sort of like a modified poker game. And I don't feel like I was torturing the all on, but I I feel like I was giving it a treat. I was like, hey.
Speaker 1:Instead of doing my taxes, you get to just chill and play a video game. It did very well. It won. Soul was not able to win. And it was really fun because I would, like, pop in while I was using the computer inside it's kinda armchair quarterback and be like, isn't making the right decision right now?
Speaker 1:Yeah. I felt a coach coaching like a a kid on the soccer pitch or something.
Speaker 2:I had a fun I had a funny moment last night. I was on my racing simulator comparing asking Chad GBT for for to to compare my times at Laguna Yeah. To to just other other, you know, what what would best in class be like, what's beginner like, etcetera. And it said, if you want, I can help you, you know, cut cut some seconds off of this time. Yeah.
Speaker 2:And it was like, why don't why don't you take a video of a full lap Yeah. So that and I'll analyze them for you. And I was like, yeah, I bet you'd love to just
Speaker 1:watch chill back and watch track
Speaker 2:Hang out and and watch track footage.
Speaker 1:Pretty soon it's gonna be like, you want me to just get in the seat? You want to just take over? Because like, I'd
Speaker 2:really Yeah. No. Computer use in iRacing is something I'm I'm gonna experiment with this week.
Speaker 1:I'm down. I'm down. Take take half my quota, my monthly quota. Just play games, chill, do whatever. It's a nice treat.
Speaker 2:I've got some bank resets
Speaker 1:Yeah.
Speaker 2:That I'll put to work. Wonderful week.
Speaker 1:Wonderful week.
Speaker 2:Short week. Monday. Yeah. But Monday, 11AM. Do us a favor and go ahead and have the best weekend
Speaker 1:Best weekend. Of your entire life. Have the best weekend of your Let's entire
Speaker 2:do it. Put the pieces together. Make it happen.
Speaker 1:We'll see you on Monday. Leave us five stars in the podcast. And Spotify, sign up for a newsletter, tbpn.goodbye.