Founder, You're watching TVPN. Today is Friday, September 11, 2026. Wall to wall coverage in the Wall Street Journal. Remembering 25 years ago, the COVID of the Wall Street Journal. Every single article except for one was about of course, the World Trade Center. The headline that day was Terrorists destroy World Trade Center Hit Pentagon in raid with hijacked Jets. Bin Laden is on here. The only story that attacks raise fear of a recession. Very interesting time capsule. Highly recommend picking up a copy of the Journal today and taking a trip down in memory of the tragedy. The one piece of news that broke through this day that was not related to the terrorist attack was Xerox reached an equipment financing agreement with GE Capital that will let Xerox erase about 5 billion of debt. Very, very odd. Every other story, I mean the market was closed actually. The Internet got a very interesting shout out here. Says telecom systems were strained as terrorist attacks in New York and Washington knocked out telephone wireless services across the Northeast. The Internet proved the most reliable way to communicate following the attacks. As the phone system sagged from severed lines and an extraordinary volume of calls, corporate executives used email to find employees across town or across the country. So interesting to see, but there's so much to go into and lots of interesting retrospectives across all the different media organizations. I don't know that I have a particular anything to dive into there, but it's interesting for you to go and dig into. Anyway, moving on. Let me tell you about ramp.com time is money save. Both easy use, corporate cards, bill pay and accounting and a whole lot more all in one place now with musicals. Anyway, what are the AI doomers actually proposing? That's the question I was trying to answer this morning for a while. Year sentences. That's one. So yeah, there will be this weird translation layer between the thought leaders and the people that are writing policy papers effectively. And then what actually gets implemented, what gets, you know, votes basically can be wildly different because to get the populace to actually support something, you need to wrap it in a different, different structure potentially. 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 invested, interrogated about his thoughts on AI risk? There's now protests. I believe AI 2027 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 10k but certainly tracking to was about 150 people at this protest in Chapel Hill. But just two ooms away from the prediction from AI 2027 and AI 2027 in the sequel. AI 2040. Frustratingly vague about impacts outside of the AI industry. So there's a lot of really, really amazing predictions about agentic capabilities and the amount of compute that will be marshaled and like even lab revenue. But there's not as much predictive stats and calls around like what will it do to gdp? What will it do to employment? What will, you know, how often will people actually be using this? What will it actually be good at? The diffusion question is still, still sort of left unanswered. But they're clearly taking it very seriously. There's a huge press cycle around this and the Journal says that Congress is suddenly waking up. 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 AI 2040. Daniel One thing, that one thing that stands out, it's. It's interesting to me that there's been so much more seemingly grassroots mobilization around the anti flock movement. Deflock. When you compare that and you don't see, you don't see videos of people with 100,000 likes saying here's how to cut power to your local data center. Not for X risk reasons, but you will see a post that's just like I don't like image generation because I'm an artist and that. So there is a lot of anti. Yeah, but what I'm saying is like the sentiment risk, the anti flock sentiment converted into actual physical actions by a bunch of just otherwise normal people. Yeah. I'm saying we haven't seen that yet with data centers. Maybe we don't. Yeah. But it's notable. Yeah, much harder. Data centers are in remote locations, highly fortified. There's fences totally walk in flat. Cameras are in your, you know, on your street maybe. Exactly. Yeah. So yeah, there's, there's degrees there. But AI in. What's weird is that. Yeah, I mean you're. You're calling out grassroots, taking down the Data Centers. The AI 2040 proposal is effectively the opposite. It's like harden the data centers even more. And the actual proposal is super concrete in AI 2040. And 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 going to be depressed about is that like, this is not stop AI at all. AI 2040 is like keep the inference flowing. The current models are great also. Let's keep doing capabilities research, but we just want to 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. 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 H100 equivalents, roughly $100 million of equipment, and that is like pretty easy to figure out. You're just like big building over there. Let's send the inspector inside. Oh, says Nvidia on all these chips. Count them up. There's over 10,000 of them. You got to apply for this permit. 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 kind of 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. Maybe there's some sort of non governmental organization that's doing this. You know, there's a whole bunch of different solutions that you can pull from across nuclear, non proliferation 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 H100 equivalents do you have? Where are they? Everyone shares this. That's going to 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. We have a system that we don't really have the international rules to quickly implement that in a way that doesn't allow for a lot of defection. But they want to know who has compute. So major data center owners and semiconductor supply chain companies would be required to turn over sales records. Who'd you sell those chips to? Where'd they go after that? Foreign inspectors Would do routine chip counts physically at site, on site at facilities. Large transfers of chips would only be allowed to go to registered audible counterparties. There's some interesting networking specific components to this proposal too. They want to basically remove high bandwidth east west networking inside of data centers. So you can't do large distributed training runs but, but you can still do inference. So again, anyone, all the anti AI people who are like yeah, I don't want LLMs around anymore, like these are not your guys, they're not fighting for that. They are fighting for stopping the next training run which is probably a line, those are overlapping circles but it is not moving backwards in time, it is merely slowing down at this current moment. They also want to install passive optical network taps on anything leaving the data center to independently verify traffic. For any new AI R&D data centers, they want entirely new facilities built from scratch with nation state level physical security and verification. So they're saying like okay, the data centers that are built, they can inference the current models, your Astras, your Fables, like your Grox, like those can run because we can deal with those, we can harness those, we have control over them, we're going to continue to align them and that's a solvable problem. 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 Faraday cage so you can't communicate it from the outside. We want a bunch of physical controls. 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 want to communicate with it and you want to tell it what to do, okay, train the next running or do whatever. They will have a bandwidth capped connection at 1 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. So interesting like hardware solution to this. You know, how do you actually go and implement that? There's going to 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. What's going on here? Someone's taking the stuff out of the data center. They want. 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 destination. It's tall order. That one's a tall order for sure. Yeah. And they actually want frontier models to be made deliberately larger than compute optimal. So they want the weights to be 100 terabytes instead of honing them down to something that's just one terabyte that could actually be moved around a little bit easier. There's a bunch of public disclosure proposals in there. Restrictions on various trade offs. So labs would have to share the model specification, the fraction of compute devoted to internal AI use. So you don't get a lab that's just internally using way better models than what's available externally. They want qualitative descriptions on how powerful models are being used internally, restrictions on how big the gap can be between the best internally deployed model and, and customer facing products. This has been a common discussion point with like the rollout of Mythos and Fable and Astra and Astra Next and all these different models where people said like, oh, it's really unfair that like this lab gets a better thing than I do. We should be on even footing. If we're both going to be competing in web design or we're both going to be competing in legal, like why can't I buy this product from you? And so there's some overlap there with like the broader business community, which I thought was interesting. And yeah, 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 podcasts. Yes. You know, wanting podcast studios to be air gapped. Yes. Wanting, you know, Faraday cages around podcast studios. A locked briefcase with an SMB7SM7B in it. And in order to unlock it, Patrick O' Shaughnessy and David Senra both need to give you codes to, to independently verify that this podcast is worthy of being recorded. I like that one. Yeah, it just makes sense. So high level valve they see as being like the most effective in controlling the speed of capability improvements is compute caps. So there is a world and we're going to the Bernie Sanders thing cause it's already getting sort of twisted. But the, the big hammer is just chip controls and data center build out slowdown. That's the easiest thing. And I Think that's like the biggest valve that they're going to, that we're going to 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. Okay, you've done well. We're allocating more compute as opposed to this one weird trick that AI doomers hate. Yeah. So the goal here is not to go back to. It's so interesting because when you look at, I mean, anytime you have, you know, really, really hardcore government regulation and international coordination around issues like this, you're going to have a bunch of unintended consequences. Yeah. And one thing that feels obvious around this, 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 again, this incentive already exists, but it kind of pushes a lot of the idea that humans are just going to be like, oh, I'm not, I'm no longer going to try to create the God model because, yeah, like there's this, you know, big global organization that's, that's sort of policing it. 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 yeah, like the game's not over just because you create a framework. But there is at least a. I mean, we've avoided World War 3, so you could say that a lot of, like the vast majority of nuclear non proliferation work has been successful, even though there's been a ton of examples of people trying to divert around it. In fact, it's like been the backbone of geopolitics for like 60 years, has been like, who gets the bomb and what, what, what chips are on the table. Ultimately, GPUs and computers are much more wide, you know, infinitely more widespread than nuclear materials. Yeah. But you still got to marshal them all together. 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, that scale is a prerequisite. And I mean, we were joking about, like, it would be so like we ssi. Ilya Sutskever's new Neolab is recently got a big cluster from Nvidia and we were like the most bullish thing you could do if you're this secretive. Neolab would be like, we're actually selling our computer 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 innovation and research, he still needs a lot of compute. And so 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 pretty simple to track, at least in the short term, until people start building crazy underground facilities and then you're back to, you know, nuclear non proliferation. But their goal is at least like, you know, try. You know, try. Yeah. And then the other side of this is not a pension. Does it. Does AI development actually become something closer to the Manhattan Project where that's what a lot of people think? 100 researchers are working with the government in secret because you can't just assume that other countries are going to slow down or do any of these things. Yeah, but 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. They do actually want to reach superintelligence. 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 want to push that out to 2035, then wait five years with AGI and then unlock superintelligence in 2040. This is their initial proposal. Of course, there's a lot that could change over the next decade. And I think 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 PDUM estimates and trying to narrow down exactly how a human extinction scenario plays out. And that can be. I feel like that's almost a sideshow because in a democratic society amongst humanity, it doesn't really matter the mechanics of getting to 10% P doom or any of those. 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. 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 hundred million dollar computers, there's a lot of people that say like I should be able to do math on my computer, 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 for a few major players. 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. And for most of these slowdown proposals, I personally have a hard time blackpilling about them in the sense of like 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. But at the same time there is this massive capability overhang. The current models can do a lot of interesting work. We're finding new uses even for non leading edge models. There's a lot that can be done. So I don't believe the, the doom doomers who are dooming about what the doomers are planning. I find that unconvincing right now, but people are starting to lay it out more. Brad Gerstner, Jensen Huang, David Sacks are talking about the other side of this equation, but I haven't just like it's hard for some people to concretize the Terminator scenario. I also have a hard time concretizing the we didn't race and we're unhappy about that. I guess you could say the housing scenario. There's been other times when we've brought in too much regulation, slowed things down too much and been like, ah, like this was really not the right move. But at the same time I think we have a lot that we can do with the current technology that there's still cause for optimism. Even if something like this gets, you know, universally voted on, it wouldn't, I don't think it would be the worst thing for Companies and consumers and businesses and all sorts of different folks. Yeah. There's also a big question around, what do the 2040 people have a point of view on robotics and physical AGI? Because it seems like even if you pause 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, I don't think they're worried about that. Yeah. But to me, that billion robots with GPT6 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, I think. I mean, we're talking to someone from OpenAI's robotics team hooking up Astra to a robot, a paintbrush and a camera. We talked about it earlier. Painting. I don't think we're at a point where that poses a risk. 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 it's not that they want to do their own thing necessarily. I don't know. But people are going back and forth on this clem over at hugging faces. 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, what was our take? AC guy might be right about. My AC guy would be like, I don't really know about that, but I just want to make sure when you're hot that we can run this ac. Cool. Yeah, I guess it's. Yeah, the AC seems. I don't know about all that. I don't know about all that mumbo jumbo, but, you know, when it's a hot summer day, I don't want you to be worried about the heat, brother. I like that. Yeah. This is kind of an unnecessary shot at AC guys. AC guys are important. I don't know. It's funny. Anyway, let me tell you about FIGMA agents. Meet the canvas. Your AI agents can now create and modify your FIGMA files with design system context. What did Bernie Sanders have to say is this Real entities will be subject to the corporate death penalty and persons shall be, shall be subject to more than 20 years, not more than 20 years in prison if they don't pause AI development. That seems pretty easy to comply with. I don't know, I guess how do you define. AI development is prompt engineering AI development. Then you get caught because you're model sort of did a little prompt engineering in the final stage and then you're guilty of this. Like that. Yeah, that could be a negative knock on effect. I guess it does seem aggressive. But his overall proposal is banning artificial superintelligence so no person or entity may develop or deploy super intelligent 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. It sounds like the mission statement. It sounds like the explicit goal of like 17 different companies right now or AI systems that have sufficient capabilities to plan and execute the disempowerment of humanity. Okay, that's a good one. I like that. 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 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 corporate death penalty is a line that you don't hear a lot right. Usually, usually these companies just, you know, go bankrupt and wind down. But corporate death penalty goes pretty hard. Metal. It's kind of, it's kind of metal. Yeah, you kind of got me with that one. Yeah. Rough, rough, rough situation. We'll see, we'll see where it goes. Jamie Cox over at Fluidstack, the co founder 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 regulations, frameworks that set simple requirements proportioned to capabilities and risk with clear responsibilities and no unnecessary barriers to competition. Yeah, the real you're going to see a lot of pushback from people who are like the regulatory stuff is going to be like these 10 companies and I'm going to 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 Menidis said, we believe AI will make everyone rich, healthy and free. Is novel and interesting. Comms from the Frontier. He's endorsing this and I agree. I like these convictions. I think it's generally a positive direction to move in, not a direct response to the proposals that are going out, but we're gonna get a whole lot more of them. Where'd you want to go to Next? Over on TikTok, they're sharing a photo 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 actor. He does look like an actor here. Yeah, he looks good. But people are, people are all. And please stop calling him Scary Potter. I've been seeing people, I've been seeing people over on X calling him Scary Potter. That's the goal. The goal is to. Is to wake up China, wake up Congress, wake up everyone. Doordash has entered the conversation. They say two years at DoorDash. I do not say this lightly. We are extremely close to the burrito arriving before you decide you want it. We are not asking for a ban. We are asking for a pause. I don't know why they would ask for a pause. That seems like very, very aligned to humanity and to their business, which I think is fantastic. The doom is very much contained to the Frontier Lab work. Everyone in the application layer who's applying the models, diffusing them, they're like, I can't get this thing to work right. I gotta get forward deployed engineers to teach people how to use this thing. Everyone deeper. Yeah. Even Jim Rainbow over Jim O'Reilly. Sure. Or Jim Riley. Yeah, Jim Riley. Jim O'Reilly auto part. Jim Riley over at Charleston. AI 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. Yeah, yeah, yeah. And then, yeah, everyone deeper in the supply chain like Jensen and all the different semiconductor manufacturers or are not particularly on this side. And then you also have Wall street who's just like, what's the enterprise acceleration? So lots of different groups around the table that need to be brought on board to this movement. The discourse truly is fascinating. Let me tell you about console. Console builds AI agents that automate 70% of it. HR and finance support, giving employees instant resolution for access requests and passengers. That's a new Too much Diet Coke. New New approach. New. Okay, so what is Tyler Cowan calling for? He's banging the table saying, bet on this. Tyler Cosgrove. Are you named after Tyler Cowan? Is that your namesake? Tyler Cowan 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. I'm not sure this matters because if you. You're not going to be around to collect it. Right? Yeah. This is what deep dish enjoyer 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. Yeah, I don't know. Yeah, I think he's just. He's calling for like, you know, he wants 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 where like, unfalsifiable claim though, just by definition and like, you just have to like, accept that and move on. Yeah. But then it's like so hard to have any like, real discussion. Was. Was nuclear any. Any different? Like the threat of nuclear apocalypse, the threat of World War 3. This was a very motivating factor for decades. Most of the 20th century, people made real decisions based on it, based on where to do business and where. Where. Where. Where the conflicts were going to be and the motivation for nuclear treaties and non proliferation and how we treat. You can make financial decisions like thinking about nuclear war. Right. You have a bunker, that's like a decision you make. Is anyone making like, AI bunkers? No, because they think it's going to be so totalizing that the bunker actually doesn't do anything. 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. Yeah, I don't know the answer to this question either. But it's odd. It seems like, I don't know, maybe there's some question you can ask that is falsifiable. I don't know. I don't know. I think you just got to believe this crew. That's what they believe and they believe it. There is the other side of this, which is Paul Cristiano, who has been worried about risk. He recently just joined the board of OpenAI. And Tyler Cowen has this Quote, if you're a doomer, why aren't you short the market? And Paul Cristiano is 2x levered long and he's short the. Isn't he short the bond market or US treasuries? He has 5% of his net worth in Tesla, 90% of his net worth in AI bets and 100% of his net worth in normal investments. No Tesla options. That sounds like a scary place with lottery ticket biases and the crazy Tesla investors. And then Eleazer Yudajkowski says, am I correctly understanding you're 2x levered? And Paul Cristiano says, yeah. And so he says he's personally short the US the US 30 year debt. I think that just means you have a mortgage. I'm pretty sure that's like if you have a mortgage, you are effectively short the US 30 year because you have sold that debt and you've got the cash. Effectively. That's how that works. But still it makes sense because if you have enough money, you could pay off your mortgage, go long that debt and short the market on a relative basis. So, but, but again that's not. 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. Anyway, let me tell you about Shopify. Shopify is the commerce platform that grows your business, lets you sell in seconds online, in store, on mobile, on social, on marketplaces, and now with AI agents. Speaking of AI agents, people have been creating AI agents of fruit flies. Have you seen this? Yes. Okay, so where should we start? Because I want to set the table on what is actually going on. Tyler, do you understand this break down, what people are cooking? We've seen this before, we've talked about this before. But what's actually going on with the, with the fruit fly? Because now people are taking the fruit fly all over the place. Yes. And I'm saying is Google basically mapped out all of like the neurons in a fruit fly. Fruit fly. So they probably took a deceased fruit fly and put it in like a mass spectrometer or something that can investigate the brain at a very, very, like a deep, high powered microscope Effectively. Yeah. Like the entire 3D. They got the entire structure. And now people have Been able to recreate that in software, in a simulation. Yes. I think in theory you can replicate all of the flies decisions or whatever it's like movements. Yes. And this is notable because many people have said I have the mind of a fruit fly. They've said I have the intellect of a. So now they're going to put it to the test to see which performs better, the simulated fruit fly or just Jordy Hayes who we got organic farm to table. 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're doing all sorts of experimentation. So Kevin said he trapped the fruit fly in his rabbit R1. When he shakes it, he can see its brain's escape circuit light up. By the way, our consciousness is physically defined which is why our physical things like dragons, drugs, neurotransmitters or events alter or initiate or end our consciousness. And things like sleep, hallucination, waking or death. Computer simulations are also basically defined representations. Yeah. I think what ends up being unsettling and weird about this is if it just purely you being human and doing this is probably not good for your own soul. And you know, imagine, imagine you have a fruit fly in a box and you're shaking it and you're like look, it wants to escape. Right? Totally. I'm not a huge fan of small insects. I don't really want them around that much. But when they're in my house, I try to, you know, if a spider's in my house, even if I know it might want to take a nice bite of me, I'm still going to try to transport it out of my house and put it back into the world. I think it's not good for your soul to be a merchant of death in this situation. 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 those soldiers opted in to riding and dying with you. Okay, okay, Right, Okay. What about the fruit fly is just sitting there, John. So they made the fruit fly play Doom. What about if you play Doom, you are killing a demon who's simulated. Is that immoral? Like, well, that is that demon trying to kill you. A lot of it comes down to like the fact that it's simulating the actual representation of the fly makes it a lot more concrete than just oh yeah, it's a 3D model in a python script that just says if you see a character shoot at them in the simulation. But we're clearly starting to grapple with these odd moral questions of 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 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 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 real debate here is like the question of, you know, are LLMs sentient? 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. 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 Balatro. It's sort of like a modified poker game. And I don't feel like I was torturing the LLM by that. I feel like I was giving it a treat. I was like, hey, 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, and it was really fun because I would like pop in while it was using the computer and kind of armchair quarterback and be like, is it making the right decision right now? Felt like a coach coaching, like a kid on the soccer pitch or something. I had a funny moment last night. I was on my racing simulator comparing, asking ChatGPT for to compare my times Laguna to just other what would best in class be like what's beginner like, et cetera. And it said if you want I can help you cut some seconds off of this time. And it was like, why don't you take a video of a full lap and I'll analyze it for you. And I was like yeah dude, I bet you would. Bet you'd love to just chill back and watch track footage, hang out and watch track footage. Pretty soon it's gonna be like, you want me to just get in the seat you Might just take over because, like, I. Yeah, no, computer use in iracing is something I'm. I'm gonna experiment with this. 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. I've got some banked resets. Yeah. That I'll put to work. Yeah. Anyway, we have our first guest. I don't want to mispronounce Tyler. How do we pronounce his name? Tees. Ties. Let's bring him in. How do you pronounce your first name? It's Tice. Like nice. That's right. Like nice. Well, welcome to the show. Thank you so much for taking the time. Great to have you. Tell us about your role in robotics and also some of your recent work hooking these models up to robotic tools and infrastructure. It feels like we're going to be entering a boom of like people. They ordered the Mac Mini recently. People are going to be ordering 3D printers and robotic arms and doing hack projects. Super excited for like the DIY world to explode over the next couple months. But let's start with just like your most interesting projects recently. Yeah, I'm incredibly excited for that. And that world's definitely like just around the corner, so I'm super excited about that. Yeah. I work here on the robotics team at OpenAI. I'm an intern and have been doing lots of exploratory projects. And this is just one of the projects. I basically noticed that our models were really good at painting and doing various computer use tasks in software like you were just talking about and learned a lot that you could actually basically connect these into physical robots in the real world and wanted to see how they would do at sort of drawing and tasks like that as well. Yeah, if you can paint in Google Calendar with Calendar invites, you probably translate that to the real world. Yeah, it's really like everyone is doing everything. Like I've seen people paint the Mona Lisa in Microsoft Excel or Google Sheets and then you take it back and you can do Excel and Ms. Paint now if you want, with computer use. And it's like everything becomes everything. What is actually the important precursors to a good experience? We were talking to a YC founder who built a humanoid robot with some basic claws for under two grand. And it feels like there's an importance of some on device API or some on device models, in some case doing some slam on device. But then there's also just tools that give you a very primitive interface that might be kind of Clunky, but it doesn't really matter because you can, you can just vibe code your correct interface. But what have you liked? What are you excited to put in the repertoire of tools like within robotics. Yeah, within robotics. Yeah. I think that of course like a lot of these demos and stuff is very early. I think the whole space and exact modeling and methods are still definitely being figured out. But I did really like the fact that you're sort of able to hook in the intelligence of what the models are able to do, as you can see with all that painting stuff and plug it into something physical in the real world and get it to do things. There's probably going to need to be some combo right now basically my experiment here is plugged right into codecs and that's of course probably quite expensive. Definitely pretty slow. I think these paintings took between one hour and two hours depending on the methods exactly. That the model chose to use here. But yeah, there's definitely a lot of improvements to make. But it's quite cool to see what you're able to do already. Yeah. How are you balancing trade offs between speed and reasoning effort? I've been testing computer use on a bunch of video games that I just mentioned and there's like part of what the feel the AGI moment is, is when the cursor's moving at like at least near human speed. But then also you don't want to be making a bunch of mistakes. And just so this like balancing act is really key. Did you try multiple reasoning effort levels across different paintings and see like noticeable results? Can you see qualitative differences in speed and quality based on models that you pick? Yeah, there's like a lot of different ways to sort of go about doing this. I initially started out these experiments by just telling the model like here, as you can see, I actually have the bot behind me over here. It's currently painting TVPN logo. I love it. But it has, it's doing its best. There you go. Good start. We got basically this camera up here that the model which is connected right into the codecs over here is connected to. Yeah. And the biggest challenge is that images are like quite large to process. Especially like for the model there, there are a lot of tokens. Yeah. And the loop of like taking an image, doing, taking an action, taking another image, taking an action. That's the thing that had taken a lot of time. So what I ended up doing like, it's not directly doing like image like one small movement. Image, one small movement. And I think like that would probably result in the best performance for like general robotic tasks and stuff. But at the moment it's basically taking an image, writing a plan in code of what it should do and where it should go next. After it has done a lot of the calibrations, maybe a slower sort of methods at first. Sure. And then after it has that plan, it executes it and then monitors it in the background, like taking images every second or few seconds and watching to make sure things are going well and making small adjustments to the plan throughout. And I found that has been a good balance of speed here. Have you been thinking about like compression on the input, you mean? You mentioned that the images are lots of tokens. I have this monitor that renders at like 5K resolution and I was like, this is probably going to be really slow for computer use. I should like run this game in a window and give it like a 720p input because that's probably enough information. But I'm wondering like how important the resolution to speak speed and quality is that you've seen. Yeah, I think it's very important in this case, for a lot of the early demos I was using 512p just compressing just to make sure because I think the model is just pretty much solved a lot of the perception challenges here. So it's really good at understanding what's going on even with a lower quality photo here. But in this case with the longer planning and it plans a minute of action out, uh, it's less important the like specific resolution probably. But yeah, as we go to more like faster, much more smaller loops of like control, it's definitely going to be important. Jordy. I, I'm super excited about, about this project mainly because it feels like we're right on the precipice of, of sort of like what, what I, what I think is going to be a big breakthrough is like a sort of a deep research moment for robotics. Like simple robotics use cases where deep research for so many people was their first time using agents. And the idea that you could type out a prompt and then get back what would have been maybe you know, at least hours of human work. Right. Somebody reading all these different sources and combining that information into a document that's, that has a consistent narrative and understands the right information. That was just such a big moment because a lot of people were saying, wow, I can't believe that the AI was able to do something that would have otherwise I would have had to hire somebody to do or just taken a bunch of time. But there's very simple tasks that I feel like you could probably start working on sooner than later. Which is an example, at least for me, would be if I could just take all the mail I get and dump it in front of a robot like that and have the robot sort it. Take all the 50% of everything I get is probably some sort of advertisement. So figure out what's an ad and shred that and then actually basically photograph and respond to if I have a utility bill or any number of things that I actually need to respond to. Theoretically you could close that sort of IRL to digital loop where the agent would actually get a task from the real world and then close that loop online with just normal computer use. And like, that's the kind of thing that you don't need. You don't need like a $50,000 humanoid robot. You theoretically could have a actual desktop robot that was able to do this thing that otherwise takes me. I dread going and like, okay, I have to like sort through all this mail and figure out what's important, make sure I don't miss things. But I feel like there's a bunch of other use cases like that where people are like, okay, I didn't just generate a pretty picture or answer some question that I had. I like actually saved myself. Yeah, an IRL spam filter. Spam filter robot. Yeah. Yeah. I think there's like two really, really cool things about this project which sort of shows that direction that things are going. One is that this arm, I don't know if you know about, like too much about the prices of like classic robotics equipment. It's like thousands and thousands of dollars at the moment. And this arm that I'm using here right behind me, this is a hugging face so 100 robot, which is open source, fully 3D printable. You just need to get the actuators, which are much cheaper at the moment, which is I think more expensive just because of supply chain issues. It's like around $200 or so. But that's incredibly cheap for robotic equipment and what you're able to do with it. So I can see a world quite soon where similar to. And someone put this really well on Twitter. Similar to how there is this whole 3D printing craze where everyone went and bought 3D printers and ran software. Like, everyone's going to buy these sort of cheap before we get really industrial equipment for personal use and personal product. Buy these plastic, cheaper robot arms that you can just clip onto a table and just put stuff in front of and plug them into agents that you can already do things with that are already out there. Astra is something that people can just pull up codecs and start controlling robots with right now, which is super sick. And we've also been seeing, at least on Twitter, I've noticed a lot of academic researchers at different institutions start to realize that you can do this with these models and start doing initial explorations and things with it, which is super sick to see. And there's so much more space. There was a YC company on the show yesterday that has managed to build a humanoid Robot for under $2,000. Oh, my gosh. That feels like a price point that people would experiment with. So if I. If I know I can get a robot for, like, two grand and connect it to Codex and then tell it, like, it basically lowers the stakes a lot where I can be like, hey, go every weed like this that you can find in my yard. Go, like, pluck it out and try to put it in a. In a. In a bag or whatever. And like that. That's basically like the gardening robot. And it could, like, flounder and fail. But I have, like, pretty high confidence that even right now, Astra would be able to identify, like, hundreds of, like, a specific type of. Of. Of weed and probably. And there's, of course, like, safety net safety concerns with that. But yeah, yeah, the Nat Friedman, like, leaf robot, like, that feels like we're here. The models can do it. It's not. It's not cheap. But what is. What is the next medium that you want to explore? Are you going to get into whittling ceramics? I want to see you whittle a bench as a benchmark. Whittle bench. That's really good. But whittling a spoon or something, I don't know. It just feels like 3D is the next thing you really want to give the robot. John wants to give the robot a knife. I don't think that's. I don't think. Read the room. Read the room, John. Read the room. Maybe we'll stick to OpenAI. Intern gives robot a pocket knife. We'll do some ceramics, maybe get it on the pottery wheel, make a nice vase, something like that. But, I mean, is there a point where you're like, oh, yeah, okay, this is where this goes next. I think I was having the exact same thought, which is like,

Wins. Team deathmatch. We are experts. Triple blaze. Let's just roll. Market clearing order in. Balance. It up. We are surrounded by journalists. Hold your position. Strike1, Strike 2. Activate. Go to the retriever mode. Trust. Market clearing order inbound. Five total. Market clearing order inbound. You're surrounded by journalists. Hold your position. Strike1, Strike 2. Activate. Go to retriever mode. Market clearing order. The hind. I see multiple journalists on the horizon. Foreign you're watching TVPN today is Friday September 11, 2026. Wall to wall coverage in the Wall street journal. Remembering 25 years ago the COVID of the Wall Street Journal. Every single article except for one was about of course the World Trade Center. The headline that day was Terrorist destroy World Trade center hit Pentagon in raid with hijacked jets. Bin Laden is on here. The only story that you know attacks raise fear of a recession. Very interesting time capsule. Highly recommend picking up a copy of the Journal today and taking a trip down, you know, in memory of the tragedy. The one piece of news that broke through this day that was not related to the terrorist attack was Xerox reached an equipment financing agreement with GE Capital that will let Xerox erase about 5 billion of debt. Very, very odd. Every other story, I mean the market was closed actually the Internet got a very interesting shout out here says telecom systems were strained as terrorist attacks in New York and Washington knocked out telephone wireless services across the northeast. The Internet proved most the most reliable way to communicate following the attacks. As the phone system sagged from severed lines and an extraordinary volume of calls, corporate executives used email to find employees across town or across the country. So interesting to see but there's so much to go into and lots of interesting retrospectives across all the different media organizations. I don't know that I have a particular anything to dive into there but it's interesting for you to to go and dig into. Anyway, moving on. Let me tell you about ramp.com time is money save both easy use corporate cards, bill pay and accounting and a whole lot more all in one place now with musicals. Anyway, what are the AI doomers actually proposing? That's the question I was trying to answer this morning for a while. Year sentences. That's one. So yeah, there will be this weird translation layer between the thought leaders and the people that are writing policy papers effectively and then what actually gets implemented, what gets you know, votes basically can be wildly different because to get the populace to actually support something you need to wrap it in a different, different structure potentially. 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 invested, interrogated about his thoughts on AI risk? There's now protests. I believe AI 2027 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 10k, but certainly tracking to was about 150 people at this. At this protest in chapel hill. But just two ooms away from the prediction from AI 2027 and AI 2027 in the sequel, AI 2040, frustratingly vague about impacts outside of the AI industry. So there's a lot of really, really amazing predictions about agentic capabilities and the amount of compute that will be marshaled and like even lab revenue. But there's not as much predictive stats and calls around, like, what will it do to gdp? What'll it do to employment? What will, you know, how often will people actually be using this? What will it actually be good at? The diffusion question is still sort of left unanswered, but they're clearly taking it very seriously. There's a huge press cycle around this and the Journal says that Congress is suddenly waking up. 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. AI 2040. Daniel One thing, that. One thing that stands out, it's. It's interesting to me that there's been so much more seemingly grassroots mobilization around the anti flock movement. Deflac. When you compare that and you don't see totally. You don't see videos of people with, you know, 100,000 likes saying, like, here's how to cut power to your local data center. Not for. Not for X risk reasons. But you will see a post that's just like, I don't like image generation because I'm an artist and that. So there is a lot of anti. Yeah, but what I'm saying is like the sentiment, the anti flock sentiment converted into actual physical actions by a bunch of just otherwise normal people. I'm saying we haven't seen that yet with data centers. Maybe we don't. Yeah. But it's notable. Yeah, much harder. Data centers are in remote locations, highly fortified. There's fences Totally walk in flock. Cameras are in your, you know, on your street maybe. Exactly, yeah. So yeah, there's, there's degrees there, but AI in. What's weird is that, yeah, I mean, you're, you're calling out grassroots, taking down the Data Centers. The AI 2040 proposal is effectively the opposite. It's like harden the data centers even more. And the actual proposal is super concrete in AI 2040. And 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 going to be depressed about is that like, this is not stop AI at all. AI 2040 is like, keep the inference flowing. The current models are great also. Let's keep doing capabilities, research. But we're just, we just want to 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. 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 H100 equivalents, roughly $100 million of equipment, and that is like pretty easy to figure out. You're just like big building over there. 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. 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 kind of 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. Maybe there's some sort of non governmental organization that's doing this. You know, there's a whole bunch of different solutions that you can pull from across nuclear non proliferation 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 H100 equivalents do you have? Where are they? Everyone shares this. That's going to 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. We have a system that we don't really have the international rules to quickly implement that in a way that doesn't allow for a lot of defection. But they want to know who has compute. So major data center owners and semiconductor suppliers, supply chain companies would be required to turn over sales records. Who'd you sell those chips to? Where'd they go after that? Foreign inspectors would do routine chip counts physically at site, on site, at facilities. Large transfers of chips would only be allowed to go to registered audible counterparties. There's some interesting networking specific components to this proposal too. They want to physically remove high bandwidth east west networking inside of data centers. So you can't do large distributed training runs but you can still do inference. So again, anyone, all the anti AI people who are like yeah, I don't want LLMs around anymore, like these are not your guys, they're not fighting for that. They are fighting for stopping the next training run which is probably aligned. Those are overlapping circles. But it is not moving backwards in time, it is merely slowing down at this current moment. They also want to install passive optical network taps on anything leaving the data center to independently verify traffic traffic for any new AI R&D data centers. They want entirely new facilities built from scratch with nation state level physical security and verification. So they're saying like okay, the data centers that are built, they can inference the current models, your Astras, your Fables, like your Grox, like those can run because we can deal with those, we can harness those, we have control over them. We're going to continue to align them and that's a solvable problem. 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 Faraday cage so you can't communicate it from the outside. We want a bunch of physical controls. 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 RD data center to be connected externally. If you want to communicate with it and you want to tell it what to do, okay, train the next running or do whatever. They will have a bandwidth capped connection at 1 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. So interesting hardware solution to this. How do you actually go and implement that? There's going to be a whole bunch of other things, but interesting that they're thinking about 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. What's going on here? Someone's taken the stuff out of the data center they want. 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 destination. It's tall order. That one's a tall order for sure. Yeah. And they actually want frontier models to be made deliberately larger than compute optimal. So they want the weights to be 100 terabytes instead of honing them down to something that's just one terabyte that could actually be moved around a little bit easier. There's a bunch of public disclosure proposals in there. Restrictions on various trade offs. So labs would have to share the model specification, the fraction of compute devoted to internal AI use. So you don't get a lab that's just internally using way better models than what's available externally. They want qualitative descriptions on how powerful models are being used internally. Restrictions on how big the gap can be between the best internally deployed model and customer facing products. This has been a common discussion point with like the rollout of Mythos and Fable and Astra and Astra Next and all these different models where people said, like, oh, it's really unfair that like, this lab gets a better thing than I do. We should be on even footing if we're both going to be competing in web design or we're both going to be competing in legal, like, why can't I buy this product from you? And so there's some overlap there with like the broader business community, which I thought was interesting. And yeah, 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 podcasts. Yes. You know, wanting podcast studios to be air gapped. Yes. Wanting, you know, Faraday cages around podcast studios. A locked briefcase with an SMB7SM7B 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. Yeah, I like that one. Yeah, it just makes sense. So high level valve they see as being like the most effective in controlling the speed of capability improvements is compute caps. So there is a world and we're going to the Bernie Sanders thing because it's already getting like sort of twisted. But the big hammer is just chip controls and data center build out slowdown. That's the easiest thing. And I think that's like the biggest valve that they're going to be that we're going to 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 lead 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. Okay, you've done well. We're allocating more compute as opposed to this one weird trick that AI doomers hate. Yeah. So the goal here is not to go back to it. It's so interesting because when you look at, I mean, anytime you have, you know, really, really hardcore government regulation and international coordination around issues like this, you're going to have a bunch of unintended consequences. And one thing that feels obvious around this, 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 again, this incentive already exists, but it kind of pushes a lot of the idea that humans are just going to be like, oh, I'm not. I'm no longer going to try to create the God model because like there's this, you know, big global organization that's sort of policing it. 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. But there is at least a. I mean, we've avoided World War 3, so you could say that a lot of like the vast majority of nuclear non proliferation work has been successful, even though there's been a ton of examples of people trying to divert around it. In fact, it's like been the backbone of geopolitics for like 60 years, has been like, who gets the bomb and what chips are on the table. But ultimately GPUs and computers are much More wide, you know, infinitely more widespread than nuclear materials. Yeah, but you still gotta marshal them all together. 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, that scale is a prerequisite. And I mean, we were joking about like it would be so like we SSI. Ilya Sutskeverer's new NeoLab recently got a big cluster from Nvidia and we were like the most bullish thing you could do if you're this secretive neolab would be like, we're actually selling our computer 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 pretty simple to track, at least in the short term, until people start building crazy underground facilities and then you're back to, you know, nuclear non proliferation. But their goal is at least like, you know, try, you know, try. Yeah. And then the other side of this is not a pen. Does AI development actually become something closer to the Manhattan Project, where that's what a lot of people think? 100 researchers are working with the government in secret because you can't just assume that other countries are going to slow down or do any of these things. Yeah. But 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. They do actually want to, 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 want to push that out to 2035, then wait five years with AGI and then unlock superintelligence in 2040. 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 PDUM estimates and trying to narrow down exactly how a human extinction scenario plays out. And that can be. I feel like that's almost a sideshow because in a democratic society amongst humanity, it doesn't really matter the mechanics of getting to 10% P doom or any of those. 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. 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 hundred million dollar computers, there's a lot of people that say like I should be able to do math on my computer, 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 for a few major players. 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. And for most of these slowdown proposals, I personally have a hard time blackpilling about them in the sense of like 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. But at the same time there is this massive capability overhang. The current models can do a lot of interesting work. We're finding new uses even for non leading edge models. There's a lot that can be done. So I don't believe the doom doomers who are dooming about what the doomers are planning. I find that unconvincing right now, but people are starting to lay it out more. Brad Gerstner, Jensen Huang, David Sacks are talking about the other side of this equation, but I haven't just like it's hard for some people to concretize the Terminator scenario. I also have a hard time concretizing the the we didn't race and we're unhappy about that. I guess you could say, you know, the housing scenario. There's been other times when we brought in too much regulation, slowed things down too much and been like, ah, like this was really not the right move. But at the same time, I think we have a lot that we can do with the current technology that there's still cause for optimism. Even if something like this gets, you know, universally voted on, it wouldn't, I don't think it would be the worst thing for companies and consumers and businesses and all sorts of different folks. Yeah. But there's also a big question around. What does do the 2040 people have a point of view on robotics 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, I don't think they're worried about that. Yeah. But to me, that billion robots with GPT6 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, I think. I mean, we're talking to someone from OpenAI's robotics team hooking up Astra to a robot, a paintbrush and a camera. We talked about it earlier. Painting. I don't think we're at a point where that poses a risk. 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 want to do their own thing necessarily, I don't know. But people are going back and forth on this. Clem over at hugging faces. 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, what was our take? AC guy might be right about. My AC guy would be like, I don't really know about that, but I just want to make sure when you're hot that we can run this ac. Cool. Yeah, I guess it's. Yeah, the ACI seems. I don't know about all that. I don't know about all that. Mumbo jumbo. But you know, when it's a hot summer day, I don't want you to be worried about the heat, brother. I like that. Yeah. This is kind of an unnecessary shot at AC guys, you know, AC guys are important. I don't know. It's funny. Anyway, let me tell you about FIGMA agents. Meet the canvas. Your AI agents can now create and modify your FIGMA files with design system context. What did Bernie Sanders have to say is this? Real entities will be subject to the corporate death penalty and persons shall be subject to more than 20 years, not more than 20 years in prison if they don't pause AI development. That seems pretty easy to comply with. I don't know. I guess. How do you define AI development? Is prompt engineering AI development. Then you get caught because you're model sort of did a little prompt engineering in the final stage and then you're guilty of this. Like that. Yeah, that could be a negative knock on effect. I guess. It does seem aggressive, but his overall proposal is banning artificial superintelligence. So no person or entity may develop or deploy super intelligent 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. It sounds like the mission statement. It sounds like the explicit goal of like 17 different companies right now. Or AI systems that have sufficient capabilities to plan and execute the disempowerment of humanity. Okay, that's a good one. I like that. 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 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 corporate death penalty is a line that you don't hear a lot. Right. Usually these companies just, you know, go bankrupt and wind down, but corporate death penalty goes pretty hard metal. It's kind of. It's kind of metal. Yeah, you kind of got me with that one. Yeah. Rough, rough, rough situation. We'll see. We'll see where it goes. Jamie Cox over at, over at Fluidstack, the co founder 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 proportioned to capabilities and risk with clear responsibilities and no unnecessary barriers to competition. Yeah, the real, you're going to see a lot of pushback from people who are like, the regulatory stuff is going to be like these 10 companies and I'm going to 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 Manitis said we believe AI will make everyone rich, healthy and free. Is novel and interesting. Comms from the Frontier. He's endorsing this and I agree. I like these convictions. I think it's generally a positive direction to move in. Not a direct response to the proposals that are going out, but we're going to get a whole lot more of them. Where do you want to go to Next? Over on TikTok, they're sharing a photo 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 actor. He does look like an actor here. Yeah, he looks good. But people are, people are all. And please stop calling him Scary Potter. I've been seeing people, I've been seeing people over on X calling him Scary Potter. That's the goal. The goal is to, is to wake up China, wake up Congress, wake up everyone. Doordash has entered the conversation. They say two years at DoorDash. I do not say this lightly. We are extremely close to the burrito arriving before you decide you want it. We are not asking for a ban, we are asking for a pause. I don't know why they would ask for a pause. That seems like very, very aligned to humanity and to their business, which I think is fantastic. The doom is very much contained to the Frontier 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. Jim Rainbow over Jim O'Reilly. Sure. Or Jim Riley. Yeah, Jim Riley. O'Reilly Auto Part. Jim Riley over at Charleston. AI 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. Yeah, yeah. Yeah, yeah. And then, yeah, everyone deeper in the supply chain, like Jensen and all the different semiconductor manufacturers are not particularly on this side. And then you also have Wall street who's just like, what's the enterprise acceleration? So lots of different groups around the table that need to be brought on board to this movement. The discourse truly is fascinating. Let me tell you about console. Console builds AI agents that automate 70% of it. HR and finance support, giving employees instant resolution for access requests and passengers. That's a new. Too much Diet Coke. New. New approach. New. Okay, so what is Tyler Cowan calling for? He's banging the table saying, bet on this. Tyler Cosgrove. Are you named after Tyler Cowan? Is that your namesake? Tyler Cowan says, if you have very pessimistic f 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. I'm not sure this matters because if you, if you. You're not going to be around to collect it. Right? Yeah. This is what, what deep, deep dish enjoyer 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. Yeah, I don't know. Yeah, I think he's just. He's calling for like, you know, he wants 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 where like, unfalsifiable claim though, just by definition. And like, you just have to like, accept that and move on. Yeah, but then it's like so hard to have any, like, real discussion. Was nuclear any different? Like the threat of nuclear apocalypse, the threat of World War 3? This was a very motivating factor for decades. Most of the 20th century, people made real decisions based on it, based on where to do business and where the conflicts were going to be and the motivation for nuclear treaties and non proliferation and how we treat. You can make financial decisions. Like think about nuclear war, Right? You have a. You have a bunker. That's like a decision you make. Monkey. Is anyone making like, AI bunkers? No, because they think it's going to be so totalizing that the bunker actually doesn't do anything. 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. Yeah, I don't know the answer to this question either, but it seems like, I don't know, maybe there's some question you can ask that is falsifiable. I don't know. I don't know. I think you just got to believe this crew, that that's what they believe and they believe it. There is the other side of this, which is Paul Cristiano, who has been worried about risk. He recently just joined the board of OpenAI. And Tyler Cowen has this quote, if you're a doomer, why aren't you short the market? And Paul Cristiano is 2x levered long and he's short the. Isn't he short the bond market or US treasuries? He has 5% of his net worth in Tesla, 90% of his net worth in AI bets and 100% of his net worth in normal investments. No Tesla options. That sounds like a scary place with lottery ticket biases and the crazy Tesla investors. And then Eliezer Yudikowski says, am I correctly understanding you're 2x levered? And Paul Cristiano says, yeah. And so he says he's personally short the US the US 30 year debt. I think that just means you have a mortgage. I'm pretty sure that's like if you have a mortgage, you are effectively short the US 30 year because you have sold that debt and you got the cash. Effectively. That's how that works. But still it makes sense because if you have enough money, you could pay off your mortgage, go long that debt and short the market on a relative basis. But again, that's not. 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. Anyway, let me tell you about Shopify. Shopify is the commerce platform that grows your business, lets you sell in seconds online, in store, on mobile, on social, on marketplaces, and now with AI agents. Speaking of AI agents, people have been creating AI agents of fruit flies. Have you seen this? Yes. Okay, so where should we start? Because I want to set the table on what is actually going on. Tyler, do you understand this break down, what people are cooking? We've seen this before. We've talked about this before, but what's actually going on with the, with the fruit fly? Because now people are taking the fruit fly all over the place. Yes. And my understanding is Google basically mapped out all of like the neurons in a fruit fry. Fruit. Fruit fly. So they probably took a, took a deceased fruit fly and put it in like a mass spectrometer or something that can investigate the brain at a very, very, like a deep high powered microscope effectively. Yeah. Like the entire 3D. They got the entire structure and now people have been able to recreate that in software. In a simulation. Yes. I think in theory you can like replicate all of the flies like decisions or whatever. It's like movements. Yes. And this is notable because many people have said I have the mind of a fruit fly. They've said I have the intellect of a. Yeah. So now they're going to put it to the test to see which performs better, the simulated fruit fly or just Jordy Hayes, who we got organic farm to table. Jordy Hayes. 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're doing all sorts of experimentation. So Kevin said he trapped the fruit fly in his rabbit R1. When he shakes it, he can see its brain. Brain's escape circuit light up. By the way, our consciousness is physically defined, which is why our physical things like drugs, neurotransmitters or events alter or initiate or end our consciousness. And things like sleep, hallucination, waking or death. Computer simulations are also basically defined representations. Yeah. I think what ends up being unsettling and weird about this is if it just purely you being human and doing this is probably not good for your own soul. And you know, imagine, imagine you have a fruit fly in a box and you're shaking it and you're like, look, it wants to escape. Right. Totally. I'm not a huge fan of small insects. I don't really want them around that much. But when they're in my house, I try to. You know, if a spider's in my house, even if I know it might want to take a nice bite of me, I'm still going to try to transport it out of my house and put it back into the world. I think it's not good for your soul to be a merchant of death. Sure. In that situation. 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 those soldiers opted in to riding and dying with you. Okay, okay, Right, Okay. What about just sitting there, John? So they made the fruit fly play Doom. What about if you play doom, you are killing a demon who's simulated? Is that immoral? Like, well, that is that demon trying to kill you. A lot of it comes down to like the fact that it, it's simulating the actual representation of the fly makes it a lot more concrete than just oh yeah, it's a 3D model in a Python script that just says if you see a character, shoot at them in the simulation. But we're clearly starting to grapple with these odd moral questions of 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? 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 just the Bibes 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 real debate here is like the question of Are LLMs sentient? Are they moral? Is there a moral weight 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. 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 Balatro. It's sort of like a modified poker game. And I don't feel like I was torturing the LLM by that. I feel like I was giving it a treat. I was like, hey, 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 it was using the computer and kind of armchair quarterback and be like, is it making the right decision right now? Felt like a coach coaching, like a kid on the soccer pitch or something. I had a fun. I had a funny moment last night. I was on my racing simulator comparing asking ChatGPT for to compare my times Laguna to just other. What would Best in class. Be like, what's beginner? Like, et cetera. And it said, if you want, I can help you cut some seconds off of this time. And it was like, why don't you take a video of a full lap and I'll analyze it for you? And I was like, yeah, dude, I bet you'd. Bet you'd love to just chill back and watch track footage. Hang out and watch track footage. Pretty soon it's gonna be like, you want me to just get in the seat? You might just take over because, like, I. Yeah, no. Computer use in iracing is something I'm gonna experiment with this week. 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. I've got some banked resets. Yeah. That I'll put to work. Yeah. Anyway, we have our first guest. I don't want to mispronounce Tyler. How do we pronounce his name? Tees Ties. Let's bring him in. How do you pronounce your first name? It's Tice. Like nice. That's right. Like nice. Well, welcome to the show. Thank you so much for taking the time. Great to have you. Tell us about your role in robotics and also some of your recent work hooking these models up to robotic tools and infrastructure. It feels like we're going to be entering a boom of, like, people. They ordered the Mac Mini recently. People are going to be ordering 3D printers and robotic arms and doing hack projects. Super excited for, like, the DIY world to explode over the next couple months. But let's start with just, like, your most interesting projects recently. Yeah, I'm incredibly excited for that. And that world's definitely, like, just around the corner, so I'm super excited about that. Yeah. I work here on the robotics team at OpenAI. I'm an intern and have been doing lots of exploratory projects. And this is just one of the projects. I basically noticed that our models were really good at painting and doing various computer use tasks in software like you were just talking about and learned a lot that you could actually basically connect these into physical robots in the real world and wanted to see how they would do at sort of drawing and tasks like that as well. Yeah, if you can paint in Google Calendar with Calendar invites, you probably translate that to the real world. Yeah, it's really like everyone is doing everything. Like, I've seen people paint the Mona Lisa in Microsoft Excel or Google Sheets, and then you take it back and you can do Excel and Ms. Paint now if you want with computer use. And it's like everything becomes everything. What is actually the important precursors to a good experience? We were talking to a YC founder who built a humanoid robot with some basic claws for under two grand. And it feels like there's an importance of some on device API or some on device models in some case doing some slam on device. But then there's also just tools that give you a very primitive interface that might be kind of clunky, but it doesn't really matter because you can just vibe code your correct interface. But what have you liked? What are you excited to put in the repertoire of tools? Like within robotics? Yeah, within robotics. Yeah. I think that of course like a lot of these demos and stuff is very early. I think like the whole space and exact modeling and methods are still definitely being figured out. But I did really like the fact that you're sort of able to hook in the intelligence of like what the models are able to do, as you can see with all that painting stuff and plug it into something physical in the real world and get it to do things. There's probably going to need to be like some combo right now basically my experiment here is plugged right into Codex and that's of course probably quite expensive. Definitely pretty slow. I think these paintings took between one hour and two hours depending on the methods exactly. That the model chose to use here. But yeah, there's definitely a lot of improvements to make. But it's quite cool to see what you're able to do already. Yeah. How are you balancing trade offs between speed and reasoning effort? I've been testing computer use on a bunch of video games that I just mentioned and there's like, you know, like part of what the feel the AGI moment is is when the cursor's moving at like at least near human speed. But then also you don't want to be making a bunch of mistakes. And just so that's this like balancing act is really key. Did you try multiple reasoning effort levels across different paintings and see like noticeable results? Can you see qualitative differences in speed and quality based on models that you pick? Yeah, there's like a lot of different ways to sort of go about doing this. I initially started out these experiments by just telling the model here. As you can see, I actually have the bot behind me over here. It's currently painting TVPN logo. I love it, but it's doing its best. There you go. Good start. We got basically this camera up here that the model which is connected right into codecs over here is connected to. And the biggest challenge is that images are quite large to process, especially for the model. There are a lot of tokens and the loop of taking an image, taking an action, taking another image, taking an action, that's the thing that has taken a lot of time. What I ended up doing, it's not directly doing one small movement image, one small movement. And I think that would probably result in the best performance for general robotic tasks and stuff. But at the moment it's basically taking an image, writing a plan in code of what it should do and where it should go next. After it has done a lot of the calibrations, maybe a slower methods at first. Sure. Then after it has that plan, it executes it and then monitors it in the background taking images every second or a few seconds and watching to make sure things are going well and making small adjustments to the plan throughout. I found that has been a good balance of speed here. Have you been thinking about like compression on the input, you mean? You mentioned that the images are lots of tokens. I have this monitor that renders at like 5K resolution and I was like this is probably going to be really slow for computer use. I should like run this game in a window and give it like a 720p input because that's probably enough information. But I'm wondering like how important the resolution to speed and quality is that you've seen. Yeah, I think it's very important in this case for like a lot of the early demos I was using like 512p just compressing just to make. Yeah make sure because I think the model is just pretty much, it's pretty much solved like a lot of the perception challenges here. So it's like really good at understanding what's going on even with like a lower quality photo here. But in this case like with the longer planning and sort of like it plans sort of a minute of action out, it's less important the like specific resolution probably. But yeah, as we go to more like faster, much more smaller loops of like control, it's definitely going to be important. Jordan, I, I'm super excited about, about this project mainly because it feels like we're right on the precipice of, of sort of like what I, what I think is going to be a big breakthrough is like a sort of a deep research moment for robotics. Like simple robotics use cases where deep research for so many people was their first time using agents. And the idea that you could type out a prompt and then get back what would have been maybe, you know, at least hours of human work. Right. Somebody reading all these different sources and combining that information into a document that's. That has a consistent narrative and understands the right information. That was just such a big moment because a lot of people were saying, wow, I can't believe that the AI was able to do something that would have. Otherwise, I would have had to hire somebody to do or just taken a bunch of time. But there's very simple tasks that I feel like you could probably start working on sooner than later. Which is an example, at least for me, would be if I could just take all the mail I get and dump it in front of a robot like that and have the robot sort it. Take all the 50% of everything I get is probably some sort of advertisement. So figure out what's an ad and shred that and then actually basically photograph and respond to if I have a utility bill or any number of things that I actually need to respond to. Theoretically, you could close that sort of IRL to digital loop where the agent would actually get a task from the real world and then close that loop online with just normal computer use. And, like, that's the kind of thing that you don't need. You don't need, like, a $50,000 humanoid robot. You theoretically could have an actual desktop robot that was able to do this thing that otherwise takes me. I dread going and like, okay, I have to, like, sort through all this mail and figure out what's important, make sure I don't miss things. But I feel like there's a bunch of other use cases like that where people are like, okay,

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