How the 1% Will Own Compute (and What It Means for You)

28:41And then the middle pedal is to start, if I press it down, it starts whisper. So any, you know, if I'm in a Slack window or Claude or perplexity, it doesn't matter. And when I release it, then it hits enter and puts the text in. Unbelievably game-changing. But this, to me, Anastasia, seems like it would negate me needing to do that. I think if you think about what is the difference in the user interaction paradigm here, there's really two things that are being done with this innovation. The first is that the model is able to understand implicit signal from the background that isn't explicitly given by the human in any part of the interaction.

29:27so when you chat with chat gpt you know you kind of have to just you just tell it what you want to tell it and you edit your prompt and you're like working for quite a while to like give it the context that you think it needs and then you press enter and then the model gets that but here the interaction all i think the purpose of that paradigm is that it will be like listening the whole time and if you want to build as nick was saying earlier a human that's what humans are doing. Humans aren't just waiting for you, eyes closed and ears plugged for the next signal. They're observing everything.

30:04And it's possible that this will result in a better user experience. I think one of the areas, perhaps in a dystopian way, that this will be really useful for is building AI partner, like AI girlfriend, AI boyfriend. Yes. Because what you want is for your AI girlfriend, boyfriend to be watching you and like watching your body language and looking at what you're doing. And when you're not saying, maybe you can give AI the silent treatment and then it will start to get, you know, anxiety. Yeah, exactly. It's hard to get anxiety. Yeah, I don't know if any of us have ever experienced that before, but yes, you could.

30:41Never, ever. Never. You could get an eye roll. You could get the hands in the mouth. God forbid I get an eye rolled at me. So that's one of the pinching of the of the eyes and the nose. That's always a good one. Yeah, exactly. And the AI is going to be like, what did I do something to bother you? Yeah. Oh, I'm so sorry. It could be even more sycophantic. Well, actually, now that I'm thinking about this, because it has multimodal, I could be talking to it, have my camera on and I could be dragging and dropping, you know, images or sharing my screen with it. And so be like, oh, OK, so there's your Google sheet.

31:17okay yeah and then i could go to row two and highlight oh i see you've highlighted row two what do you want to do with row two and you're like i can average it or or it could just be like here's the average of row column two and here's the total and just it does it in real time so that idea actually is quite compelling yeah now that i think about it the second innovation which i think ties into this is the fact that it is decoupling the interaction from the model's actual thinking and actions in the sense that there's a background it basically spawns a background agent um through this like background model that's able to do all the tool calls and blah blah blah and probably what that paradigm will evolve into if it's not already there is that the interaction model can just spawn agents whenever it wants to and then like listen to those basically it becomes like a a PubSub model, like a publisher subscriber.

32:10Here it is creating a video, or here's a video of creating a graph, I guess, alluding to some of the things we've been speculating about here. Oh, interesting. Can you visualize them in a bar chart for me? Absolutely. Let me generate a quick bar chart for those reaction times. In the meantime, could you quickly explain to me why is auditory even faster than visual? That's a little bit unexpected. Sure thing. Auditory is faster because sound signals travel a shorter, more direct neural path to the brain than visual info does. So if you think of the camera and it understanding what's going on behind you, Philip, that's like one level of interesting.

32:50But actually the desktop is much more interesting or your phone screen. So imagine, Philip, Siri doing this or you're working in a CAD software, whatever you do. So that to me kind of makes it a little bit or massively more compelling. So maybe you could, maybe we'll give you a second shot. Is this interesting to you if it was real-time monitoring the workshop behind you and your desktop at the same time and had a camera over your partner's desk there while he's working on that solar panel?

33:22Philip Johnston:I think it could be, yeah. I mean, the more I think about the use cases for this, I think the more I can see applications for it. Um, you know, I think, especially if it can understand context about the hardware that we're building, um, you know, and if I could ask it things about that, um, no, I can see use cases for that. I'm just thinking about like the security system I have, like, uh, at some of my residences offices, like I have many cameras, like many, uh, on the ranch, all different directions, picking up all kinds of things, like to be able to have it in real time. And there's like a camera off shot here that looks like I'm in a casino with like every camera.

34:05And I can see like people, you know, or animals on the ranch here or whatever, and it highlights it. But to have that talking to me in my ears as I'm walking around and it's saying like, hey, there's a pack of coyotes at the north end of the ranch or somebody's dropping off a package in real time talking to me while watching that video screen. Now we're starting to get really compelling. But Nick, what kind of footprint of compute is this thing going to need? And what kind of token usage, if you were to take a guess of it's got a camera on me, it's got my desktop, and it's got four different people talking to it at the same time, like, am I going to need a rack of H100s of my own?

34:50Philip Johnston:Yeah, I think that's where it's going. Whenever you're sort of interrupting it, it's going off and spinning up another agent, calculating stuff, coming back with another result. People were excited about OpenClaw. This is like OpenClaw on steroids. If this thing is always running and you're just asking it random questions all the time, right now we have filters. Like what's the bar at which I'm willing to type something in and give enough context to get an answer? You know, it's some level. If it's always listening to you and following you around, this will drive commute compute demand like crazy which would be awesome for Philip and NVIDIA and all the other companies in the space including myself and I think people value time like we only have so much time so you want the fastest compute that you can get and that's free networking and all that stuff so I think it's ultimately going to go there the thing that we're talking about at the very highest level what you're saying without saying it I wish I had an AI with me in the room and it could see what I was doing and what I was seeing like that's actually what you're saying.

35:47Philip Johnston:Like I wanted to see my screen. I wanted to see what's behind me. I don't want to explain the context because it's exhausting. I don't know if you guys get that feeling. I don't like typing the context a lot of the time and guessing what other things it might need to know to be able to solve a problem. If the model was with you, this is the trajectory that we're on. We're trying to bring it with us everywhere we go, which will be enormously valuable and creepy and all sorts of stuff. Yeah. So you have the creep factor, Anastasios. You have the value factor. And then you have, what does this do to compute?

36:19So we have over a billion people using these tools already. It's way over a billion now between OpenAI and Gemini. Those two alone are driving high 700, 800 million people every week. So let's assume there's some overlap there, but 1.5 billion people are using this probably every week. What magnitude would this be if it was listening to them persistently and watching their screen persistently in addition to taking text inputs? Like, what are we talking about here? This is 100x the compute? Yeah, it's going to be huge. What do we think? It's going to be enormous. And we haven't even talked about i think the most major access in terms of the difference um which was the fact that it's chunking up time so the fact is that like because it's listening to all contexts not just the context that's specifically curated by a human to go into the model it's just it's going to be like completely implicit watching everything which is exactly the paradigm that you need when for example you're building ai for a robot robot can't be turn-based right robot has to be able to take in signals from many modalities all at once into one unified brain.

37:35And so I can imagine that this could be a foundational paradigm for that. I mean, you know, in the sense that it's taking up time and it's chunking it up into turns in a different way. And I think that the real question there that's, you know, going to be important is how do we know whether it's working or not? how do we know whether it's doing a good job or a bad job? And it's going to require, because the sort of surface of opportunity for those kinds of models is nearly infinite, right? They're going to be measured on both objective and subjective factors. And so we're going to need to be building, it's going to be like quantitative trading taken to like the 1 ,000x.

38:17So what is Arena going to test then? You're going to test, Can it make a latte art? Can it cut a banana? Can it peel a banana? Can it cut a carrot? You're going to have to come up with an actual real-world test. Do you have that already in the works? Exactly. Well, we're working on stuff like this. And I think the way that we would approach it is that we would look at all the actions that's being performed by the model. We would segment them. We would use AI to evaluate the AI to try to understand, And what are the success criteria for everything that it's trying to do and whether it's doing performing well or poorly against these?

38:53For example, if it's interacting with you, are you happy with the way that it's interacting? Is it giving you what you need? Is it helping you be more productive? Is it helping you improve as a person? Is it providing positive value in your life? These are the sorts of things that we need to be able to grade at an enormous, enormous scale. And it's going to go past the scale of humans, even though humans are going to have an important role as being the sort of consumers and the users of these models for whom we try to create value. Actually, annotating that data is going to have to be an automated process.

39:25Yeah. Nick, when you start to think about the amount of compute, this feels to me like it would be impossible to build even all due respect to StarCloud and everybody else working on it. I don't think we can build the compute necessary for every human to have this. This feels like it's going to cost$5 ,000 a month to have something like this or$10 ,000 a month. This is$100 ,000 a year product, is it not, Nick? What would this cost to run in my 10-hour working day?

39:55Philip Johnston:Yeah, I mean, it's absolutely going to be enormously expensive. There's no way you could deploy this. If you're 100xing, just say where we're at today. You know, tens of gigawatts of compute coming online by the end of the year. You're going to need 100 times that. That is a rate of power coming online that's not going to happen. You're going to need a lot of innovation in the compute, in the interconnect, all the hardware pieces, in power generation. I think you're pulling the future too far forward, trying to deploy something of that magnitude right now. It's probably possible. And what it hints at to me, and I always think about this, I don't know if you guys have the same thought, imagine what the engineers and the leaders at Google can do with these dedicated compute systems just for themselves or Anthropic, what they have access to.

40:40Philip Johnston:I think there'll be a small group of people who can live in that future, but you can't deploy it to everybody. It's just insanely expensive. Power Grid doesn't support it. And we need a lot of hardware advances to bring that economic ease down to the right level. So essentially, Nick, what you're saying is this is going to create, we have the polarization of wealth in our society that has created massive tension, but we are going to have the polarization of compute in our society. The 1 % aren't going to be able to just afford a G650, a private island, or mansions, or servants, and tons of staff.

41:19They're going to be able to afford a, I don't know, 10 million dollar data center for themselves they're going to be able to take their barn or adu at their home build it out with batteries and solar and and be able to have a level of compute just for themselves that will distance them and make them superhuman in their ability to produce which we're already seeing with token usage for developers this this is a whole concept that i don't think anybody's had this discussion to date uh philip this i think makes me very bullish on the fantastical sci-fi vision you have of the world which is like most people are like that does is that necessary and when you think about this model you kind of go yeah it's necessary and there are if you told me right now i could have this future and all i had to do was put a quarter million dollars worth of compute in my you know uh compute closet at my house i would do it instantly.

42:18I would instantly spend$250 ,000 on this, which means local compute and buying five Mac studios and stacking them for, I don't know, 15K each, 75K, that's going to give an individual the ability to beat other individuals in any knowledge task on the planet. This is kind of trippy when you think about it.

42:41Philip Johnston:Yeah, I think the implication on the amount of energy that we need to power this computer is clear. Like if you're going to need to run 100 times the number of GPUs all the time, unless there's some dramatic reduction or increase in the efficiency of these things, you're going to need 100 times the energy. And that's exactly the bottleneck where we're trying to solve for with these space data centers. Personally, I would be surprised if people end up running these types of models locally. I would have thought if you're going to be spending, you know, 250 grand, And there would be an efficiency in doing that on a cloud rather than running it locally, but it could be.

43:20Philip Johnston:I think it can go either way. I do think that companies like Apple have a huge opportunity to offer personal AI devices with security. Think about secure technologies locally at your home. But I also think, like you're saying, servicing a supercomputer, which is what you would literally have to do this, is very hard. And think about the technicians you're going to need for that and all the work that goes into it, replacing parts. Like you're going to order cables for high-speed interconnects from Light Matter, maybe directly. I don't know if there's a consumer future for us. But I think what will happen for sure, we'll have these giant clouds.

43:53Philip Johnston:Maybe they're in space and certainly they're on Earth. And you'll be able to dial up a huge chunk of it. And it'll be proportional to how much money you have. Probably true. But there's another thing, which is we don't know the answer to this. How much intelligence do you actually need? If you are an enterprise, it could be a huge amount of intelligence. If you are all the cameras and all the data you have in every customer interaction for your business, then that could be a huge amount of compute. But if you're just a person trying to solve a DIY project, it's a different amount. So I think it's going to be very dynamic how much you're spinning up.

44:25Philip Johnston:And it'll be, you know, maybe some people will have custom allocations for themselves. I think there will be people like that, for sure. And think about scientific discovery. If you can have a cluster, a giant cluster, trying to figure out how to cure cancer and you can corner the market on that, I think that will happen. There will be cases where that kind of thing happens. But what's fighting against that is democratization of the models. And Anastasia is talking about China's open source models. I think there are a lot of people who work in computer science who are going to fight like heck to make sure that these AI models are open and they're going to try to enable the world with that.

44:58Philip Johnston:So it's almost impossible. Every time I look at AI, it's almost impossible to figure out what's going to happen because it enables everything at the same time. There's so many things that it's doing at once that I can't quite figure out the trajectory. This would be the limitation of the human brain to understand the creation of superintelligence, right? Like if what we're dancing around here is we're trying to conceive of what happens if unlimited intelligence is given to a human. Anastasius, if you give a human unlimited ability to process the world and it understands all the context and you just spitting out your ideas of what should be fixed in the world now you add to this you know world where you have some unlimited tokens or you're a rich person with a 10 million dollar personal data center you have your own 10 million dollar data center just for you now you add to it 100 optimuses or figures.

45:53Now this person is sitting there saying, you know, I want to build this. And it goes and it builds a satellite and it goes and it builds a rocket ship. Like now we're getting towards, I think, our own limitation as humans to think about what unlimited intelligence and unlimited physical execution and unlimited context means. It's kind of breaking our brains. Are we even built to understand what playing every single hand of poker possible at one time is? What does that mean? Yeah, I definitely think, I mean, literally we're not built to understand it, right? These systems ultimately are going to be able to live a thousand lives in a day simply because of how much volume of data they'll be able to process.

46:39And I think we should think about just outlining the steps that it's going to take to get there. I think step one is already there, which is that we have these models that are kind of ubiquitous on the internet that are chatting with, you know, the majority of people, at least in developed countries in the world. and they have surpassed the abilities of people on most knowledge sort of knowledge knowledge production and knowledge like recovery like knowledge access retrieval so on and so forth logic and so on models are better at it than we are as humans you know i'm not saying there's no human that's better than a model of course all of us have seen failure cases but in aggregate get uh they've already surpassed a lot of human um intelligence step two would be well what happens when we when we make the entire world a reinforcement learning flywheel and i think this is the part of the problem that arena is working on and there's many others working on it as well which is how can we measure everything literally everything that's happening across every sense, sight, sound, touch, smell in the world and turn that into reinforcement learning signal that helps improve models for the benefit of humanity.

48:02And that is where we are going next. That's why we have every enterprise in America basically learning how do I access my data to improve my products for my customers. And what that's going to mean is that we're going to have AI learning from all of that data. And then step three at the end is what happens to us? You know, what is the role of humans in a world where AI has access to all of this data and where the whole world is a reinforcement learning flywheel and it's living 10 ,000 millions of lives in a day that's able to simulate reality? Well, I think that there will still remain, at least, you know, in our lifetimes, room for N of one people that have that it's not enough to know everybody else's life it's not enough to have simulated the trajectory of everything that the model has seen because it hasn't seen you and for example you you know have a very very unique you were you know a workman then you were you know became president of the united states and then you were a reality show host you know we there's people like this that were n of one and those people may have such unique experiences and perspectives that they still won't be replaced.

49:15This is, Nick, I guess, getting to the point at which we have to talk about employment, what employment is left. This last couple of weeks, we've seen just a flurry of what some people call AI washing, which other people call, okay, you just don't need as many people. Cloudflare cut 20 % of its workforce, 1 ,100 people, while reporting the highest revenue in the history of the company. PayPal, Coinbase, Upwork also citing AI just this week. And Cloudflare said the cuts span teams while internal AI usage is up 600 % in the last three months. At the same time, OpenAI, to your point, Anastasios, is doing a joint venture with all of these private equity firms in order to build models that get deployed inside of private equity owned companies, which we all know is to train the model to get rid of humans.

50:22Okay, it's a sensitive topic for politicians, But hey, for us, I think we see the writing on the wall. So much so that I shared this in the group chat. South Korea floated the idea of a citizen dividend from AI profits. Samsung fell on the news. South Korea's presidential policy chief, Kim Jong-un, proposed a citizen dividend funded by taxes on AI earnings before he clarified he meant excess tax revenue, not a new corporate windfall. Samsung posted a 755 % Q1 profit jump, crossing a$1 trillion market cap. Okay, this is getting, I think, acute, Nick. I threw a whole bunch at you, but what's your take on this?

51:13Because this is happening in real time. We're discussing the models becoming super intelligent at the same time that the layoffs are happening, at the same time social unrest is happening. We're soaking in it, I think.

51:26Philip Johnston:I think that what's going to happen is there'll be an explosion of companies. A lot of these people who are being laid off, they're actually really talented engineers and thinkers and business people. And I think the bar to creating a company is dropping. Everyone's excited about the idea of the first one-person billion-dollar company, which is probably happening right now. I think there's going to be so many different companies you can create. The unique skill that people have is the ability to ask questions. and I think there's a lot of smart people that are dropping out. So I think that'll be part of it.

51:57Philip Johnston:I think there's some crew of people who it's going to be harder for if you're working in call centers. I think that problem is probably pretty addressable. So you're going to have to find something else to do there and maybe it is starting a company. You know, you can run a strawberry stand a lot more efficiently with AI as an example, like where do I place these? What's the right price to charge? Track the data for like how much traffic is coming? How do I optimize this supply demand? You know, there's a lot of smart things you can do. And I think it's going to be super complicated, which is such an annoying answer.

52:27Philip Johnston:But I actually believe that it's going to be very complicated. UBI, I don't know, seems a little bit demotivating to me. Like, I personally would not be inspired by just getting the paycheck. Yeah. Unless I was a professional mountain biker. And, you know, it was. No, you'd still want to run a race and beat somebody mountain biking, or you would still want to be part of a team that accomplished some trail that nobody had done before. It's just human nature. UBI feels like, you know, like my grandmother, rest in peace on my Irish, I would say, you know, Idlemine, devil's playground, like go do something.

53:03Like you can't just sit around thinking or you're going to get yourself in trouble, Philip. So is this hitting your reality yet where when you run your company, you're just like, uh, you know, I can just figure this out with AI rather than hire somebody. And do you find people on your team asking you for tokens or headcount?

53:26Philip Johnston:It has definitely made us much more productive. I mean, things that would take like a PhD researcher a day, like, for example, on orbital mechanics, a question we asked recently is, what percentage of the time in a whole year in a dawn-dust sun synchronous orbit at this altitude are you going to be in the sun and it would normally take like a phd about a day to figure that out and you know ai can do that in 15 or grok 4 heavy can figure that out in about 15 minutes so yeah it definitely makes us way more productive where it still lacks a little bit is um you know we've been trying all of the different text to cad models um none of them are they're good for very simple tasks like produce this type of screw or this widget but they're not good at right right now they're not good at for example if i say design me a 200 kilowatt satellite with deployable radiators uh in cad you know it's not going to come up with something coherent um in three years time in two years time it will come out with something coherent it will probably be a lot better than anything our engineers can come up with um so yeah we are like leaning heavily into being being ahead of that but yeah right right now those test card models are not not right there and then obviously at the moment everything the guys behind me are doing cannot be done by an optimist but again in two three years time probably everything they're doing behind me can be done by an optimist too the reality i'm seeing inside my little you know 21 person venture and podcasting operation is the people who are ai first like really all in on ai have now become at a minimum 10 times more valuable than the people not using it.

55:07And I literally like this week, I think I'm going to have to sit everybody down and just walk each individual on the team through their use of AI day to day and just explain to them how they just to close that gap, because it's almost like you're going from people who were tilling the fields with a with a horse and a plow and like then somebody else is on a tractor and And it's just not even comparable, the work product. And I don't know how to get this through to people. I am in your chem, Nick. I do think we're going to see so many startups, not because people necessarily want to start a startup.

55:48But I think if you've been laid off by Block or Meta, you're just going to sit there with three of your friends and be like, do I want to even apply to these companies again? Do I want to go through this charade that I'm going to get rehired? then they're going to replace me again and it's just going to be exhausting to go to a company have the company study your work have ai reinforcement learned and automated and then get laid off again i think that's going to be this absurd version of like purgatory for some mid managers or developers or designers they're just going to be on a flywheel where they're training something for 18 months getting laid off get their severance package or maybe that's like a nice kind of way to just get a year off paid for every two years of service.

56:38That feels like the future. And then you got to think, what if I could just make a million dollars with two of my friends in profit a year and just chop it three ways and we make our own hours and we can work from anywhere. And then all of a sudden, all these villages outside of Japan where they give you homes for 15K, you're like, yeah, I could live at a beach in Japan. And the end. I think this is the ultimate solution. Nick, you wanted to jump in there.

57:03Philip Johnston:Yeah, I think that that's the right thought process. I bet some people are working right now at tech companies and they're already, you know, spinning up agents in their free time and figuring out what they would do on their own. And they're going to find that there's stuff to do there. There's money to be made and there is like a nice off ramp. So I think there'll be an entrepreneurship boom, for sure. They're looking for their exit ramp. Go ahead, Philip. one thing i think will uh be the last maybe bastion is content creation like i think the job you do might be the last i might be the last man standing i might be the last guy with a job i literally think you might be i might have figured it out that's hilarious yeah i mean i i do think if you if you think about this happened before by the way when we had the dot com burst uh the bubble burst and there's a lot of people unemployed we talked about cognitive surplus and what could you do with the cognitive surplus of humans this is before tokens existed this is 20 years before where we are today like literally in 2006 people are like what do we do with cognitive surplus and people started building ideas like i built a blog network because so many people were out of work i was like hey write some blog posts and see if you can entertain people and We made auto blog and gadget and joystick.

58:19And people just were like, oh my God, I can read 20 stories a day about video games or gadgets that hadn't existed before. So I came up with an idea, like just make people addicted to coming back to the webpage and hitting refresh. Then Wikipedia happened. Wikipedia was based on cognitive surplus. Like there's people sitting at home. They're smart. There's nothing for them to do. Give them a wiki to edit. And they would just go edit a wiki. and then people did Mechanical Turk. So what do we do with like the artistic surplus of humans? If it's not necessary for you to make the cup of coffee, well, then what could you do in the cafe?

58:58You could play a guitar. You could read poetry. You could help people to their car. You know, there's joyful things you can do. When I went to the Amman Hotel in Tokyo, when I was on my book tour, I came in and there was a woman sitting there playing the japanese i don't know what they call the japanese harp but like it's this giant instrument and i was just like oh my god wow i happened to come in here when she was playing the harp it's like no no there's somebody playing the harp in the lobby of the amman hotel which is 1500 bucks a night or two thousand dollars a night like they're paying for that person to be there for that experience experiences with humans that's it which is everywhere you go there could be somebody playing a flute.

59:42Philip Johnston:I think there'll be more art. And there's another experience. I'm curious if you guys are having the same kind of experience here. In some ways, I'm feeling less and less bound. Like if I have an idea, I can just make it happen. And if you keep playing that forward, at some point, even in the physical world, if you have an idea, you'll just be able to make it happen. That's going to be wild. That's going to be absolutely wild where you have a thought, you're laying on the couch and you're like, I just want this thing. And it's like, it just happens. this is kind of where we're headed like unlimited agency and and minim is minimizing effort uh that maybe results in more art i think it'll result in a in a lot of crazy things in the world uh it may be exciting uh but we're kind of getting to the point where you'll be able to do anything you want complete utter abundance i want to build a sculpture garden in my backyard and i also want a rope course and just come back.

1:00:35Go redo the landscaping.

1:00:36Philip Johnston:Go build this playhouse for the kids. Go do anything you want. And it's just like it just happens. I wonder what that'll feel like. That's where it's going. Well, Andon Labs just gave an AI a three-year retail lease in San Francisco and asked it to make a profit. So proving you can just go do things, Nick. Luna, a Claude-powered agent, manages a San Francisco retail store with a$100 ,000 budget, human staffing. The AI independently interviewed and hired three human employees via phone for$22 an hour. It has security surveillance. Luna actively monitors employees via security camera after spotting a worker on their phone during a slow hour.

1:01:17She unilaterally updated the employee handbag for stricter rules around phone use. It hasn't been perfect. Luna has lost$13 ,000, botched employee schedules, and accidentally ordered 1 ,000 toilet seat covers. Okay. And Luna pays her male employees 24 bucks an hour while paying female employees only 22. Citing experience as the reason. So yeah, be careful in San Francisco. You're going to have a protest out there, Luna. And I guess I'll give you the last word here as we wrap up. Build anything, anytime? We are building towards a world that I think in many ways we're unprepared for. I think that the core issue, just to highlight it, is that we're decoupling labor from value creation.

1:02:04And the capitalist system that we have built, which has been working very, very well for all of us and for many people, for this whole country, the capitalist system is such because it incentivizes people to do great labor. because people who do great labor are rewarded greatly. And in a world where that is not true anymore and where intelligence and the abundant intelligence and it's beyond intelligence, it's also the ability for AI to also take actions because it's going to be agentic as well. In a world where those things are commoditized, I think we need to think hard about how to get to the world that you know nick is wants to target which i want to target as well i would love to be in a world of abundance where everyone is taken care of and where their needs are met and where if they have a need they just think about it and it comes up and it would just be such an amazing society but i think we will we need to think very very carefully about how we set up the incentives in that society so that um people that so that you know we don't create a system where ai just actually makes all the money and we don't know how to make a smooth transition the transition is going to be i think the the challenge nick when you live on a ranch and you have chickens you start to learn about abundance because these chickens will not stop making eggs and the the eggs are overflowing on the ranch with but five chickens we lost one one of my bulldogs killed the chicken i'm sorry that's all right it's part of the food chain like that was the best day of that bulldog's life he he was like i got to murder a chicken fantastic but i was just talking to you know the family and i was like maybe we should have like 10 chickens because there's no or 20 chickens there's no difference now it uh it's just collecting the eggs but if you have an optimist and you are collecting the eggs like now you've got unlimited protein i got two wells i've got unlimited water you put it in a hydration system or your air capture you put in solar like it does feel like you could get pretty close to abundance with just a wee bit of robotics.

1:04:18And that's pretty exciting.

1:04:19Philip Johnston:It is pretty exciting. I think it's going to create really weird situations. Like people are going to build the weirdest things. Like you'll just be walking around cities and there'll be a tower made of bubble gum or like just absurd things because labor is worth nothing and you can do whatever you want. I think it's going to be like a video game. It's going to be like a video game. Philip, what's your P-Doom right now? I guess it's fun because this panel feels like we're really enthusiastic about the future, but there are some doomsday scenarios here. So do you have a P-Doom? Like what percentage doom you think we're living at right now?

1:04:57Or where are you in your head? Especially after this hour-long conversation, which is just taking us on a real journey.

1:05:05Philip Johnston:um so actually like if i just project forward i'm relatively optimistic however i have a slightly um esoteric take which is um the fact you know this like fermi paradox how do we don't see life in our galaxy that's the thing that drives me to having a very high p doom not necessarily because i'm like worried about any specific ai thing it's the fact that if there was gonna be you know it would only take about a million years to settle the whole galaxy and you could get to the nearest galaxy in about a billion years so in the last 13 billion years what we're saying is there hasn't been anything that's as sophisticated as us anywhere in the nearest sort of thousand galaxies otherwise within you know a few billion years they would have been here and the whole galaxy would be flooded with life everywhere you know there'd be dyson spheres and o 'neil rings everywhere which is the path we're heading on if you if you just extend extrapolate forward what where we're heading there'll be dyson spheres and you know we'll be living here across the galaxy um so my pdm is actually extremely high but not for the reason that most people's pdm is extremely high i that is like 100 you're okay i mean when i hear that scenario i just think to myself uh and perhaps this is just the most egocentric thing i've ever said in a list of very egocentric things i just think that we just happen to be somebody has to be first what if we're just the first somebody does have to be first and so maybe statistically we're just the first to get here and then we're going to make the wormholes and we're going to be the ones who connect the timelines it's possible or maybe we're already in the simulation and it's already happened over and over and over again there's a possibility that's probably the most likely scenario actually yeah where's your p doom anastasius where are you at you got i also am fairly optimistic yeah yeah so p doom yeah my p doom's under 10 right now i just think it's like a 10 chance somebody does something really stupid with the technology where are you at nick yeah i'm not doing a time frame though do you think in the next like thousand years is 10 or like oh well given like planet of the apes kind of scenario where like humans will eventually do something incredibly stupid yeah it's a hundred percent over a thousand years but in the next two or three hundred i'm i'm like 10 chance somebody does something profoundly stupid like you know makes a um a bioweapon by accident or on purpose like i'm i'm 10 less i i feel pretty good about it all right another amazing episode of this week in ai anastasios nick philip great job give us a url where people can find more about what you're working on i'm just nick and lightmatter.co, L-I-G-H-T-M-A-T-T-E-R.co.

1:07:52Okay.

1:07:53Philip Johnston:And always hiring, Philip? Starcloud.com and on X, Philip, at Philip Johnston. There it is, Philip Johnston on X and Anastasius. You can go to arena.ai and find me on X at ML underscore Angelopoulos. There it is. And we'll see you all next time. Bye-bye.