空飛ぶTesla、3週間で半減するロボット知能コスト、AIアライメントを決めるインセンティブ|#303

Last night in Waco, Texas, Tesla finally unveiled their flying Tesla Roadster. Zero to 60 in under one second. It is street legal. There's nothing to stop you from strapping a rocket to your car. What would be the cost of insurance for that? He's two generations ahead. I'm surprised that it's not autonomous and it's only, you know, human-driven cost. I think. The cost for a Frontier model to complete a robot subtask fell from $2.36 in July to $0.38 in September. 84% drop. Halving in cost every three weeks means it effectively goes to zero, you know, within the year. We've been looking at AI that doubles every 10 weeks, and that's been mind-boggling. Halving every three weeks may be the fastest-moving capability we've ever seen. How do we create alignment within the labs and the models and humanity? We don't have alignment among human beings. They're trained to win, no matter how you get to the answer, as long as you win. All wars are basically based on one thing. That person is not a human.

Now that's the moonshot, ladies and gentlemen. This episode is brought to you by The Abundant Summit and Link Ventures. First of all, I want to just point out what cups. I've got moonshots. What do you have, Slim? I've got exponential. Of course you do. Demod? I'm artificial intelligence. Yes. And I've got gratitude. Yes, you do have gratitude. Yeah, for sure. Anyway. All right. I love having you guys in the podcast studio. That's great. Welcome. Imad. Selina, you've been here before. I have been here before. We did our one-hour organizational singularity conversation here. Yeah. And Imad, welcome. Welcome. Yeah. It's good to have you here in the States. Thanks for coming over for Visioneering. It was a blast to have all of you guys here. Thank you, Vignia. Yeah. Pleasure. All right. Well, let's get going. So welcome to Moonshots, everyone. on your number one podcast on all things exponential, your front row seat to the singularity. Today, we're here to have a conversation across a few breaking news stories,

but in principle about the world of incentives, how we incentivize human AI alignment, and how we dive into human purpose. I think it's one of the conversations we've had before that, you know, how humanity is going to define purpose in the future is critical. We need purpose. we need some level of struggle amongst ourselves. So I'm here with my extraordinary moonshot mates, Salim Ismail. Salim, love you, buddy. Good to be here. Yeah, it was great to have your family here as well. It was awesome. Yeah, for sure. And you've just flown in from Singapore. I have, so you have no idea where on the planet you are. In fact, we recorded the last podcast episode. I hopped on a plane, came here for Visionary, and now we're here again recording again. Yeah. I can't get away from the recording. No rest for the wicked. As Alex says, it's going to be a continuous recording sometime. Continuous models coming out and continuous recordings. And Imad, a pleasure, pal. Great to have you here. We have a special guest with us today, Anusha Ansari, the CEO of the XPRIZE, my patron saint.

I'm going to give her story in more detail later. But we just finished a couple of days of XPRIZE visioneering, our annual event, where we discuss what prizes to launch. We narrow them down, and we have a whole group of philanthropists who fund them, and we'll share some of the stories there. So, Anusha, it's been a long time coming. I know. I'm so excited to be here. I've been a listener for a long time. Now I'm here. Yeah, for sure. And I just want to do a proper introduction for you before we get fully started. So, for those of you who don't know Anusha, Anusha is the CEO of the XPRIZE, But I met her back in 2001 when I was trying to fund the original XPRIZE, right? I had launched this $10 million competition and unfortunately didn't have the money. This is what entrepreneurs do. Yeah. Didn't you lose like a couple of board members? Yeah, I did. So we'd raised $500,000 and I said I was going to spend all of the money announcing the XPRIZE

above the line of super credibility. I'll explain what that means later. And I had two board members who resigned because they thought I was being reckless, which, of course, I was. Because I expected once we announced this $10 million flight space competition, you didn't pay until after someone won. And I figured everybody would want to fund it. It should be a no-brainer. It should have been. It was, but not for everyone. And then I read in Fortune magazine about this amazing woman, Anusha Ansari. She was written up in the wealthiest 40 women under 40. I wasn't married at the time, so that was one funding opportunity. But she was married and very successful. I had built a company called Telecom Technologies, sold to Sonos Networks for $1.4 billion. And in her write-up, it said you were interested in flying on a suborbital flight into space. And I read that paragraph like three times, not into space, not into orbit, on a suborbital flight.

It was like, wow. And tracked you down vacationing in Hawaii. And Byron Lichtenberg, a twice-shuttle astronaut, I brought an astronaut with me to the meeting. Great marketing schemes. And you and your husband at the time and your brother-in-law basically said yes. And after five years, we launched the prize in 1996, didn't have the UNSARIT commitment until the end of 2001. For five years, I had pitched 150 people. And everyone said, why isn't NASA doing this? Can anyone really pull it off? And isn't someone going to die trying? And that last one, you know, people are so risk adverse. Yeah. And then Anusha, we rebranded it to the I'm Sorry X Prize in your honor. And then Anusha, you need to understand, flew private to the space station, flew on a Soyuz through one of the companies I had back then called Space Adventures and became the first private female astronaut to fly into space.

And then eight years ago, one of the greatest blessings of my life, Anusha returned as the CEO of the X Prize. It's been an adventure ever since I've met you, Peter. I know a lot of people say that about me. It has been a pivotal time for me, and it's a gift that keeps on giving in a really great way because not only it helped open my mind to possibilities and how I should look at life, but also now the opportunity to lead X-Prize into the next phase of it and really leverage the platform that's been built over the past 30 years to make great changes and help shape the future that is so exciting. So I'm blessed to have been a part of it. And I am blessed as well. And, you know, we are going to talk about some of the crazy ideas that were getting funded at Visioneering and where we're going next. And speaking of crazy ideas,

I'm going to open up with probably the most insane product demo ever. So last night in Waco, Texas, next to SpaceX's McGregor Tesla site, Tesla finally unveiled their flying Tesla Roadster. And, you know, just to describe, we're going to show a video in a moment, but just to describe what happened, you know, the Roadster drove up a multi-story curved ramp upside down, you know, and I was wondering, I was watching the video the first time, you know, I didn't hear the description of how it was doing it. I said, is it magnetics? Is it some kind of a rail system? And it was actually a fan suction system that could hold it against two Gs. So it's levitating there upside down, which was insane. So let's watch the video, and then let's talk about it. I'm curious which one you guys are going to buy. It's not an autonomous car. It is the last. Well, it is technically the autonomous for this demo to make sure we don't kill anyone.

Correct. So just in case. But this will actually be long term the only manually driven car that Tesla makes. Tesla makes. To do that, we have a fan suction system on the bottom of the car that can pull up to two Gs in order to make the car go upside down. and then we borrowed some technology from SpaceX to do the rest. Yeah. Let's try something else. Yeah. I mean, that was just a little flight. Let's do a longer flight.

I mean, I've seen a lot of things. I've never seen that before. I think we could have cleared more than our whole fleet. Yeah, we can go further. Like, this will be an actual car that's on the roads. Yeah, we had the rockets we borrowed from SpaceX technology. You talked about the carbon overlay pressure vessels. There's two of them in the car. They are a total of 600 liters. There's about 250 kilos of air. And we have 10 nozzles to do all that work. And it's using an advanced ultra-high pressure air tank. So the car can recharge its air tank. So it's not like you need special propellant or anything like that. It literally is just going to pop itself up and be able to do these maneuvers whenever you'd like. Amazing. Incredible. Only Elon. Yes. I'm surprised that it's not autonomous and it's only, you know, human-driven car.

I would not want X-Human to do it. Oh, my God. You need to know how much I love XPRIZE because I was supposed to be there for this event. Oh, my God. Thank you. And record with Elon, but commitments are commitments. In fact, you know, Steve Jurvetson was there, and he was at Visioneering, and he was supposed to be at the launch as well. Crazy. So here are the numbers. Zero to 60 in under one second. I mean, you know, if you want to go fast, you might. This is why we need the organ regeneration. Your liver will be left behind. Top speed of 230 miles per hour and 300 miles of range. There are three versions they're going to be selling. The performance version, this is the 0-60 in 1.6 seconds. The thrust version, 0-60 in 0.9 seconds. and the rocket version. It's a one-seater described as air-ready. Oh, my God. The rocket version does 0.6 seconds, but also apparently 380 kilometers per hour, which is half the speed of sound.

That's when you really get there in a hurry. Well, I mean, I was looking at that. I was like, that's the solution to Los Angeles traffic, right? You'll be happy. Oh, my God. So production starts in 2028 for Elon. No price was given. Tesla shares rose 5% on that news. I mean, honestly, it's like you can do anything. Well, I mean, I've got the obvious question as to why. Because we can. Okay. Then how long does it fly for? Is that given anywhere in terms of what the list is? I don't think they gave the duration of a hover. Okay. I mean, it'll be like just a few seconds. Again, if you look at the pressure pushing out. I don't think that's kind of the point, though. I think the point is it can. You're not going to see hopping cars. Until we solve for gravity shielding or something like that. Well, I mean, that's clearly for Mars, right? The real miracle will be can they ship it on time rather than does it fly? That for me is the real one. What would be the cost of insurance for that?

I don't think it's insurable. It's not insurable. I mean, if I'm the insurance company, I'm like, yeah, those thrusters stay off. Otherwise, your insurance is off. It's like, really? You want a rocket on your car? So, you know, obviously this is showing Tesla and SpaceX working together, which, you know, my prediction is they're going to announce the merger before the end of the year. Yeah. Right. But, you know, Salim, here's my question. How – who regulates this? DOT, FAA, nobody? I mean, and how is this going to get licensed? This, I think, is the challenge of all of these new technologies, right? The scaffolding of regulatory and the institutions to protect insurance, safety, etc., always lag behind. And Elon is just pulling away from that capability. Because think about it. It's going to take a year or two to figure out how to regulate this. He's two generations ahead. So where is this going to go? This is, I think, the biggest stress test that we're seeing across all of these technologies, not just this car.

I mean, you might, I imagine this is AI driven, AI enabled, even though he says it's going to be, you know, manually driven. But there's no, I mean, no way that control system is going to fly without AI in the loop. Yeah, I mean, like, literally fly. I think this is the thing, right? So I think that it is street legal. Like, again, there's nothing to stop you from strapping a rocket to your car. It will be street legal, right? Or having thrusters and things like that. So it fits within the existing one. The question is, again, who's going to insure this thing? Yeah. Like, if you've got the thing. Maybe they will have their own insurance company like Toyota Insurance. But very few people will have these cars. I think this is, again, a more demonstration of we have integrated capabilities. We will take it to Moon and the Mars and beyond. And it's freaking cool. It's like so many bike demos. Like, Porsche had their release on the same day. Poor Porsche. I mean, it's a very nice-looking car. But can it fly? No. It raises the bar. Right, it makes you, again, want to go and work at Tesla, SpaceX, right?

Like, if you're a top engineer, where do you go and work? You go work there. And that's his key thing is getting the talent, getting it going, and saying what can be. Plus, he gave us 280 characters, you know, up from 140. Oh, God. Yeah, one of the things that there's an interesting question about everybody is going to go into autonomous vehicles and be driven around. Some people want to drive, right? We've talked on the pod before about there are going to be special lanes or you're going to be not allowed to human drive. But one of the things that I love about autonomy is if you want to drive fast, if you want to get into a race car, you can imagine a situation where you're driving, doing your very best, but if you start losing traction, the AI takes over. So in Saudi Arabia and the Emirates where there's a lot of wealth and a lot of young men, there's a high death rate in sports cars because, you know, they've got cars that outperform their ability to think and react. But you could put an AI layer on top of that and make sure everybody's safe. Well, this is essentially an extension of anti-lock braking traction control.

Yeah, exactly. Which is embedded in all these systems, but now you can make it a general capability of trying not to kill the human despite what the human does. Override the stupidity of the human, right? And we see bits of this already. You've got a lane drifting warning, and you've got collision warning. I think this takes it to the next level, and it's badly needed. Yeah, for sure. This is the answer to alignment. You know, AI doing the right thing despite what we – Despite our stupidity. Yeah. We'll get into that. So, Anusha, you know, during the 60s, all the Apollo astronauts got Corvettes. Oh, yeah. So I wonder if all the new Artemis astronauts are going to get, you know, a Tesla Roadster. Probably. I don't know if they can afford it. I don't know how much I can pay. No, no, no. You know, Chevrolet gave them the Corvettes. So maybe. Maybe. You think? I think we'll add that. Elon will be generous with Artemis Asper. I think he had to sell his mom a car originally. I don't think she got one for free. Do you remember the original story from Zip 2? What happened? It was like, I can buy a house or I can buy a McLaren F1.

Aha. He bought a McLaren F1. So he's very much pro-car ownership, even if he did kind of wreck it afterwards. Yeah. And actually, it's interesting. You can see tweets from him from 2018 where he's like, we can put thrusters on our car to make it fly. And he just goes and does it. It might take a bit longer, as you said. Missed a few timelines, but he gets it done. Gets it done. This episode is sponsored by Google for Startups. Think about this for a second. You now have access to the same generative AI models that cost hundreds of millions of dollars to train. Google's startup technical guide for generative media gives you a complete blueprint for deploying Google DeepMind's models and production. Images, video, audio, all of it. Real architecture, real results. Find the link in the show notes below. All right, I'm going to move to our next story here. And Iman, it's one that you sent me over yesterday. So it's about a curve that should make every robotic founder, like, stand up and pay attention. So RoboCurve, it's a Y Combinator startup, designed a benchmark called RoboDojo RC Tier 1,

which measures how well a model can drive a physical robot through actual subtasks. So the cost for a Frontier model to complete a robot subtask fell from $2.36 in July to $0.38 in September, 84% drop. So here's the curve, and Imad, talk us through this. I mean, we've had kind of the question, is the robot's body good enough? And then it was like, yeah, they seem they can do just about anything, and now the hands have got good. Now the question is the mind. And it's always been the case of, do you need specialist models, or can you use generalist models that suddenly learn these new capabilities? This shows that generalist models can actually win. And it's something we talked about previously with the auto self-driving kind of benchmark. Unitary CEO actually just came out and said, like, we're not even sure we need to create special smashes models anymore because these things do it and we used to kind of task and cost halving but every three weeks yeah like you're heading to the point whereby effectively there is no cost for robotic intellect and robotic locomotion and it

comes down to the hardware cost which again is going to lead to an explosion just like we see again the unit trees when they first came out they were like stumbling about like little drunkards and now they're doing kung fu and synchronized kind of things. Next, they're doing surgery with generalized models. Yeah, well, I mean, again, that's the conversation I had with Elon at the beginning of the year. You know, his prediction, robots are doing perfect surgery within three years. I mean, look, with the new Grok model that they're coming out with, they're putting all of SpaceX's engineering that can create flying cars, right? So the robot will be an engineer that can build flying cars. Yeah. And the robot will be an amazing lawyer, it'll be an amazing plumber, it'll be an amazing etc. So this is why, does SpaceX, Tesla have customized robotics models? No. They're just like, we will play the generalization game. And again, I think that's what's going to win here, because humans are generalized. We're not like lobotomized and specialized. If you want to have humanoid type robots, if you want to again have very specialist ones, sure.

But humanoid robots, I think that's a different game. Yeah. We're going to be interviewing Brett at Figure in a couple of weeks. And remember, he started building his own models for the robots because the early models didn't work, the large language models. But I'll be curious to ask him, you know, what he's using or building now. But halving in cost every three weeks means it effectively goes to zero, you know, within the year. so you know if you're an entrepreneur now in hardware space what are you thinking I think if I build as many robots and actuators and the spare parts of the robotics supply chain as possible are you also thinking I need to collect as much training data as I can I think that the training data will be important for a lot of the specialized scenarios and again it was a case of will the robotics companies buy them, Brett has committed a billion dollars, that figure for example for data? Or will it be that after hoovering up the worlds like data from companies

and all the text data, every single major foundation model company now wants all the robotics data. I think it'll be the latter. A robotics data is an order of magnitude larger than the language data. But again, if you're embodying the intelligences, you need that data. Is the performance dependent on the form factor? This is just for human robots or bullet work on the three-armed robots? This one is for kind of arms and humanoid type things in specific settings, but again, these should generalize very quickly. The whole thing is the language models got good enough all of a sudden that you kind of don't have to baby them anymore. The robots aren't quite there, but they're about to get there as well at the same time. So all of these models, the video models now don't make mistakes. They're all getting good enough, fast enough, cheap enough at the same time. That's the bottom line. You know, in the last episode, we talked about Jeff Holden's Atomic Machines Company, which is basically going from prompt to product where you describe what you want,

and this machine is building it at millimeter-level accuracy with multiple materials. So it's, you know, just to give a vision of where we're heading, all of a sudden we're in a situation where if you want a specific kind of robot to do a specific, you know, So, you know, clean windows, repair HVAC, you know, lay bricks, mow the lawn. You can ask it to design the perfect robot and build it and then operate it. So do we end up with Star Wars with, like, thousands of different robot designs? Well, I think you're going to end up, remember, that this works very well when you've got lots of repetitive tasks, right? And then you can generalize to, say, plumbing where you've got lots of little manipulative tasks in a particular domain. I think it's clear that for now it'll start off in what we call DDD, dull, dirty, dangerous jobs, toxic cleanups, and underwater manufacturing and all sorts of things.

I think it'll be a while before it comes into the home, liability issues, et cetera. I'll talk again. We'll get to the institutional lag there. I think where I'm most excited is in things like surgery. where we make a lot of... Is that well dangerous or dirty? It's dangerous for the patient. If you're the first 10 heart surgeries that a doctor has ever done, you kind of don't want to be there. You kind of want to be in the 500, and you don't want to be too far down the line either because the doctor gets lazy after a few thousand surgeries at the same time and doesn't pay attention, right? And so now you can smooth that curve out and have the world's, like, literally the best doctor first supporting and then over time just doing the surgeries, And that becomes completely you want those things as automated as possible, operating in the most precision level measurements possible. I think that will see a huge take-up in those types of tasks for robots. I'm fond of saying if you're looking, if you need a surgery, there's one thing you ask your surgeon, which is how many times do you do it this morning, right?

So the surgeon who's seen the most varied cases is most likely to be the most successful. And when you've got federated learning across all robots, they've seen millions of cases, and they share all those memories. What I'm most excited about is the robot chef. Okay. Can you just imagine that? It's a robot chef that cooks the best food for you all the time in your kitchen. Yeah. That's all I need. Even more than that, you've got your embedded sensors in your body that are measuring your protein levels, your hydration levels, your vitamin levels, and the food that's being cooked by the robot in the kitchen is exactly what you need at that time, and it tastes good. I think that before robots get into the home, there's a safety factor that we need to figure out. These are still big, heavy machinery. So if you have a dog or a cat or you have small children, if they're around it and they just step on the foot. It's a safe word. 1X makes it very soft and squidgy. My big concern, to Anusha, to your point, I have one of these designer dog things.

It literally looks like a teddy bear. And robots are going to go, oh, laundry, and it's going to turn the dog into the washing machine, and that's going to be a bad day, worse for the dog. And so what do you deal, how do you deal with those edge cases? And there's infinite numbers of edge cases. And I go back to driving. Look how long it's taken us to get autonomous driving right. And that's a very bounded domain with reasonable good understanding. I'm going to push back in the following way. These performance curves on the operation of robots are one part, but the other part is they're going to be running super intelligent models. I don't think it's going to look at your fluffy little dog and say laundry. I think it's going to be able to recognize that dog and make decisions better than the majority of humans. I mean, the two are evolving at the exact same time. I think that's why this is important, right? If it was a specialized model, yeah, your dog grows in the laundry. Yeah. Okay, the generalized model. Do you need world models for this to occur, or is it getting so good that you don't really even need world models?

You don need world models for this This is again the shocking thing whereby all of a sudden the souls and the opuses and the 3 flashes suddenly understood 3D They that good Yeah and we like wait, how can they do it? You've seen them kind of suddenly create whole 3D assets in games. No one's quite sure how. They seem to have learned something in the next generation, and now that's why they're generalizing. I'm going to push back as well on the idea that it's only dull, dangerous, and dirty jobs. No, no, I said it would start off there. Okay, but that, like, I'm thinking it's going to pass there in the next year. In other words, if we really got this level of dexterity and capability. I think the business model will be there. For example, there will be an ROI for using robots for those purposes for the first few years until the supply chain can catch up. Because remember, we have no supply chain right now for making billions of robots. So for bringing it into the general household where you need billions, literally billions of humanoid robots, or at least millions in first world countries, it's going to take some time for the supply chain to catch up.

The ROI won't be done. My prediction. I really don't believe we ultimately, the humanoid form factor is the right form factor. That's my case. You've got to win this. Thank you, Rebecca. I think we need either a special or transformers because I think, you know, there are certain tasks that really, our bodies are not suitable for those tasks. You need to be small to go through a small opening to get to a location or so there are many, many tasks like in the categories you're describing. I think you need to have specialized form factors that suit the task. And these models would be great because you don't have to create specialized models for every form factor. Yeah, I think the interesting thing, you know, like right now the Wooji hands are probably the most advanced ones. Those cost about $8,000 down from $20,000 with as much actually more dexterity than a human hand. But a robot that does the laundry doesn't need that. and so you might just actually see like spare parts companies where again like Transformers they like add a few extra arms get more dextrous arms

to an useless point you'll have a figure with a bunch of sockets in it and it'll have a spider type thing for one thing and a regular arm for another thing and a rope for another thing and you'll have all the choice around the world so you know what we're going to find out we'll find out very quickly at a dropping of three weeks I mean, we've been looking at AI that doubles every 10 weeks, and that's been mind-boggling. Having every three weeks may be the fastest-moving capability we've ever seen. I forget 18 months doubling in Moore's Law. This blows that out of the water. Did this surprise you, man? No. No. Like, I've been saying robotics would suddenly be cooked, and just like video. Like, this final period, like, again, we went from video costing 30, no, 50 cents per second for high quality. The new models that are about to release next week are 0.1 seconds, 0.1 cents per second, faster than real time. Nice. So once you break through this final level of it can do the work, it collapses.

And, again, that means that you have to build the actual robots. That's why, like we discussed a few episodes ago, Elon is building a million optimists for next year, going up to 10 million. At 1.7 million, it overtakes Tesla in revenue. Optimists, how crazy is that, right? And it's still not enough. Crazy. All right, let me go to our third breaking story this week, again from you, Mud. So last week we discussed how OpenAI dropped 722 math proofs in GitHub and sort of shocked, obliterated, cooked, made glorious in the mathematical world, whatever you want to call it. And, you know, Alex has been saying forever, and as have you, E.M.I., and we've talked about this, that physics is next. And so this week, researchers built a test of 50 unpublished research-level theoretical physics problems with verifiable answers. Because the problems had never been published before, there was no lookup on the Internet that it could make. So they estimated that a world-class physicist would take about a day to answer each of these 50.

And GPT-6 Astra answered it with about a cost of, what was it, $3? Yes, $3 per problem. $3 per problem. So employing a world-class physicist for a day or answering it for $3. Interesting detail. Well, originally it was reported that Astra got 49 of the 50 physics problems correct. But when it looked into it, it found out that the published answer for the 50th was wrong and Astra got it right. So what are we seeing here, Imad? I mean, again, like for these verifiable domains now, the AI is just simply better than us. Like for the maths problems, it only cost a few hundred bucks to solve these long-standing maths problems. Again, physics is verifiable. It does this as well. Even without Internet lookup, so it has to have to rely on its own knowledge, it still scored 42 out of 50. And as you said, it corrected that final thing. So this creates an interesting thing whereby anything verifiable, we suddenly have a tool to verify.

And that's fantastic because it means we can build much more complex systems and process them. Like, Salim, this must be great for organizations, right? Unbelievable. The implications for how you think about specific tasks, which are well understood, KYC in a bank, you know exactly the outcome you want to get to. It's a very bounded domain. You know where to get the data. In the pilot that we're running, people are taking 22-step workflows and dropping it down to four steps. And that's just going to make organizations 10x more efficient and effective across the board in workflows. you know I am curious and we'll maybe chat with Alex on the next episode as well about this so these were 50 shall we say you know what level of difficulty would you say but when it comes down to like the millennium physics prizes right if there's that describing that category level yeah yeah how far are we from that so these would be like again professor level because the professor could check it within a day. So it's a verifiable

set of things in various advanced places of theoretical physics, which tends to be very mathematical in the nature of the way it is. Like the big problems of physics, like quantum gravity, you know, like where is time in quantum mechanics and unifying field theory. Unifying field theory. I don't think they'll be solved this way actually. I think they'll be solved another way, but I don't think it'll be more than half a year. Oh my god. There's one observation i've been thinking about which is you know a couple years ago eric schmidt on stage of a360 said you know imagine a time when you have the world's best physicist or equivalent in every lab in the world and we asked him when he said five to six years and now it's like two years and here we are so i think this is another example of stuff happening much faster than we ever predicted because now every lab has access to an incredible competence at a few bucks an hour. And that makes it unbelievable. Then you think about, you know, initially what this means for the XPRIZE and things.

You've had so much incredible science coming through. It can now be checked and verified and extended with augmented capabilities to improve that knowledge base that's been built, right? This definitely can help the validation process. What I'm curious about, and perhaps it will be part of the next topics, when you have AI solving, you know, bulk solving a lot of these problems, and you have young people entering universities or picking a field to study, they probably will not be very excited to go in a field where AI can do the job better and can solve all the problems. At the same time with this article, it talked about how it's still not at the level, and I don't know if it will ever get there, that have the same curiosity to identify new problems to be solved. So if we don't have a new generation of mathematicians, physicists, astrophysicists, identifying those new challenges and mysteries, and we have AI bulk solving all the problems that we've defined,

how are we going to advance? Well, I think, again, that's where the humans we can still direct, because it's about what's good for humanity, right? so you've had a bunch of problems but like with fermat's last theorem being proved was fantastic mathematics what difference did it make to real people i think we have these frameworks and again physics is one that i believe will be solved because there's only one physics there isn't different physical laws so there must be something that connects them and these new generations of models will help us figure that out but then once we have that framework what matters is how we apply physics to make flying cars to explore the universe to explore biology you know and more things like that so i think again what this means is that we can move away from theory trying to find the contours of the universe to applying the frameworks to make a difference on the universe so i think that's the super exciting part yeah this episode is brought to you by blitzy autonomous software development with infinite code context blitzy uses thousands of specialized ai agents that think for

hours to understand enterprise scale code bases with millions of lines of code. Engineers start every development sprint with the Blitzy platform, bringing in their development requirements. The Blitzy platform provides a plan, then generates and precompiles code for each task. Blitzy delivers 80% or more of the development work autonomously, while providing a guide for the final 20% of human development work required to complete the sprint. enterprises are achieving a 5x engineering velocity increase when incorporating blitzy as their pre-IDE development tool, pairing it with their coding co-pilot of choice to bring an AI native SDLC into their org. Ready to 5x your engineering velocity? Visit blitzy.com to schedule a demo and start building with blitzy today. All right, I'm going to move us into a topic that has been at the root of XPRIZE for some time, which is incentives, right?

I'm always fine with saying you get what you incentivize, and we humans are driven by our incentives. And so when I think about what incentivizes us, what drives humans, I have four answers there, fear, curiosity, greed, and then kind of love as well. I'll add that as a fourth one. And so, you know, unfortunately, fear is a very strong motivator, and curiosity is far behind. And I calculated the ratio of fear to curiosity. It's the ratio of the defense budget to the science budget, right, which is vastly different. And then greed, of course, you know, if I put them in order, I would say fear is the strongest motivator. Greed comes next. Curiosity comes next. And love, you know, depending upon the subject or the person sort of varies in there. And it's interesting to take a second and look at incentive prizes as a model. So we all know the Nobel Prize, which awards someone for work that was done typically anywhere from like the earliest was 10 years ago and typically 20, 30, even 40 years ago.

And incentive prizes say, I don't care who you are, what you've ever done, where you've gone to school. If you solve this problem, you win. and some of the classics here was in 1714 the British Parliament offered 20,000 pounds to anyone who could find longitude at sea. It was called the Longitude Prize. And interestingly enough, it was won by a British clockmaker, John Harrison, who solved it with a marine chronometer. And so when you put up a prize, you get nonconventional people coming in from an orthogonal angle. Another example is in 1795, the French government, Napoleon's armies were basically invading into Russia, and the supply line was so long they were starving, and so they offered up a 12,000-franc prize for food preservation. And it was won by a guy named Nicholas Appert who invented canning. It's intense, yeah. And this guy was a confectionary.

You know, he made sweets, and he came up with this idea. So you get very unusual approaches. I love the story of Harrison because they were so sure an astronomer would win the longitude prize. They refused to pay him. Didn't he have to sue them for ages to get the money out? What a horrible outcome because they just couldn't believe that somebody who wasn't in the field could actually solve that problem. And what we've seen repeatedly is the people from outside the field that solve these problems. They're coming in with a beginner's mind. And, you know, my frustration at wanting to be an astronaut led to the XPRIZE. You know, I grew up on Apollo and Star Trek. I've told that story a thousand times. And, you know, I became clear when I interviewed a whole bunch of astronauts. I used to be at MIT's Man Vehicle Lab with astronauts coming through. And I would say, tell me about how I'd become an astronaut. And they would say, well, first of all, your chance at one in a thousand. Secondly, if you're accepted in the astronaut corps, half the astronauts have never flown. They're called penguins because they have wings, but they don't fly. And then if you do fly, you'll fly maybe once or twice during your career.

And I was like, I want to go every weekend. And so it was like, okay, there needs to be a different way. And that's when I became focused in commercial space. And then a dear brother of mine, a friend of an Ushin and myself, all of us, Greg Maranak, gave me The Spirit of St. Louis, which was Lindbergh's autobiography, chronicled his flight. And in that, I found out that Lindbergh didn't fly from New York to Le Berger on a whim. There was a $25,000 prize offered by a gentleman, Raymond Ortega, and that $25,000 inspired nine teams who spent $400,000 to win the $25,000. And ultimately, he didn't pay any of the losers. He only paid Lindbergh as the winner, who was the most unlikely guy to pull it off. And I said, wow, that's a great business model. You only pay for success after it's successful. And that launched the Ansari XPRIZE. But let's talk about, like, what happens when incentives go wrong and you get perverse. I found a few that are interesting.

So in Hanoi in 1902, the French paid a bounty for every rat tail that was collected during the plague. And people ended up cutting off the tails, letting the rats go and breed, and started rat farms. To get more rats, to collect more money. Wells Fargo had a sales quota driven by employees to open about... So the sales quota from Wells Fargo got employees to open 3.5 million fake accounts to get the sales quota. So you've got to be careful about your incentives. Well, we're seeing that today in real time, right? They've incented folks at ICE to arrest as many people as possible, deport as many people as possible. And the idea was, let's just arrest the criminals, but the targets are such and the incentives are such that they're arresting everybody. And that's causing political backlash of enormous magnitude. It goes back to the motive.

At the X Prize, almost every prize we have, the motives are love and curiosity. I cannot think of anything that or anyone who's competed in the next prize that was motivated by greed, for example. Definitely not fear, but not even greed. The prize money is great if they win, but even if they don't win, they end up helping other teams. They end up continuing on to build the company. So the winning is not the only motive for them. They want the problem solved. They want the problem solved. It's their passion for that. And I think that's when you get real good incentives. If you put greed, like quotas, then that's when you really get all those, you know, results. I think it's because, you know, those prizes that were more execution than inspiration. Yeah. That's a good point. Yeah. So I'll take a second and talk about some of the prizes we've had in Nusha that people may not know about that have had tremendous success. But first, we've launched like 30.

No, it's more than that. because we had the Future Vision built with Gemini. Yeah, 36. 36 prizes now over 32 years. And total number of prize purse, like $550 million, something like that. Close to. And at my count, that's driven a little over $30 billion in R&D. Definitely. And not just R&D, but a lot of that $30 billion is investment, So bringing capital to the solution, so the teams have received about $12 billion of investment outside of – while in the competition or after, they received $12 billion of investment. That means an area that didn't receive attention and capital before, now it's receiving attention from investors, which means there will be long-term continuity and success for the company. What are some of the other numbers that we talk about at XPRIZE? So in general, when we measure impact, we look at the prize purse and we look at how much economic benefit we've created in society.

And we measure it in capital investment, in R&D, in awareness. Because as you know, one of the biggest success of the Ansari X Prize was changing the mindset of people that this is possible, to be able to create regulatory reform that was supportive of commercial space activities. So that's awareness. And then R&D hours of how much R&D went into solving this problem. So that measures right now 62 times of the price price actually is created in economic value. Every dollar put into a price price drive 62 times. I mean, that has to be the most leveraged model for innovation in the world. I've never heard of anything even close to that. Frankly, I don't know of any leverage philanthropic. So I think we're very unique in the way we leverage every dollar. You can see the enthusiasm in the room as people are competing and pitching different prizes,

the interest, and oh my God, if I could deliver 60 times the interest that we have right now, my God, what I would do for that domain. It's interesting, you know, the word philanthropy here, because it has such amazing private outcomes and personal outcomes for people. So the people that put up the prizes, it's usually, you know, something personal to them that they want this to succeed. And they benefit personally, and there's the private sector that emerges. So it's more about building a common good of shifting what is capable, what is possible, and then attracting more people around. I think that's why these are the focal points, they're the shelling points, as it were. No, absolutely. I think another important factor in what we do is, and you talk about clear targets all the time. Measurable, objective targets. Exactly. And I think a lot of times people have a general idea if they want to solve the problem, but they don't really know what they need to do. So those clear targets, measurable targets, give them a North Star. And built to this, you will succeed. And I think that's another reason they are very successful.

So just to talk about a few of the prizes we've done, we had the Oil Spill Cleanup Prize, one of my favorite stories, and yours, Salim. I'll tee it up, but you can add on. And so back when the BP oil spill was going on in the Gulf of Mexico, it was just like oil was gushing and it was heading towards the beaches. It was going to destroy the beaches there. James Cameron was on our board back then. And he said, you've got to do something about it. You've got to do an emergency exercise. And we actually did, not to plug the oil well, but to reinvent how we cleaned up oil on the ocean surface. and we put out an email to all of our board and Eric Schmidt and Wendy Schmidt raised their hands and said we want to do this. And the goal was could you double the oil spill cleanup rate. And we had teams around the world, like 350 teams enter this competition. And we selected 10 of them that to ship their solution in shipping containers to Omset, New Jersey,

the largest oil spill cleanup. Yes, there's an oil spill cleanup testing facility. and then Salim want to take the rest of the story here yeah sure so the second place team is a dentist and a tattoo artist that literally meet because the dentist is getting a tattoo I think in Las Vegas and the tattoo guy turns out to be an environmentalist I was talking about this prize the dentist goes I know a lot about bonding agents in liquid and they're like oh so they get together form a team tested in his hot tub and then they came in second place And the reason that's such a magical story is that if that team walked into your office looking for funding, you're never giving them money. They've never met. They have no experience. They don't know the domain, et cetera, et cetera. And yet they came in second place because you just never know. And the second part of that whole project that I found fascinating is where an XPRIZE is really valuable is where governments aren't doing enough and markets aren't doing enough. Yes. Right? And in this case, there's no economic incentive to do R&D on oil cleanup technology.

And it's a perfect place for a price. I thought that was wonderful. Absolutely. And I think the reason we see this over and over is this crowdsourcing solutions. The fact that you have diverse set of ideas and they're not bound by a set of belief system that stops them from imagining something different. This is where the beginner's mind comes in so important for all of these folks that are doing disruptive innovation. Elon had no experience in the car industry or the space industry, and yet market leaguers in all of them. Yeah. Well, I think, again, like you've just had a visioneering, but the process that comes after visioneering is actually one of the most important ones, right? Absolutely. Where you take that target and you make it, again, just very, very, very actionable. Yeah. The price is on the market. Yeah. And we typically get, you know, hundreds or thousands of teams aiming at it. Sometimes they fall away. Sometimes they emerge. Yeah. and it may not be the winner who's the commercially viable solution at the end it may be you know second third fourth but we're cultivating a new industry ima the first time i met you

was uh you were on uh you were heading a team on the team on the global learning express you're kind of working around that and i mean it just brings people from all sorts of backgrounds right together um because again i think it's personal like you want this to succeed be it from the the right side to the other, but it needs that coordinating factor to bring it together. And I think now, again, you've got the people, you have the capability, but now with the technology from robotics to AI, you can make a bigger difference than almost ever. Yeah, I think a lot of our prizes are going to be just that. I mean, so we just had John Davey, who's an amazing entrepreneur. So he's become a very close friend, and we're involved in reinventing education as well together. but he just stepped up to fund a brand new prize that I love, the Habitable Worlds X Prize. And it's a perfect example of the future kinds of prizes. So there's petabytes of data coming from the great telescopes.

And we have found, I think, about 6,200 exoplanets out there. You know, we're in – Milky Way's got 100 million to 200 million stars. We have somewhere about 2 trillion galaxies in the known universe, maybe many universes. But we know there are exoplanets, but we haven't found an Earth-like exoplanet yet. So John's mission for this is get all the data from the great telescopes and make it available to people and let them use the latest AI to find habitable worlds. So couldn't I be more pumped about that? Amazing. John funds yet another prize design? Really? That's amazing. He actually funded the whole prize. We're super excited about that. He put up $5 million for that, which is... Absolutely. And it's a great example of how AI will be a major part of solving this mystery because we have the data. We just need to find a needle in a haystack. And what better way to use AI? That's perfect.

We teased at Moonshots Live that Palmer Lucky is about to announce the Interspecies Communications Prize. again will be a new version of large language models enabling us to talk to animals in the wild. We'll give more detail on that when it's officially not My joke there is I'm not sure we want to hear what they have to say. I'm there with you. We're going to have to deal with it for a bit of blowback. We'll go, oh my god, we can communicate with these humans? Here we go. We've got commentary. We're going to tell them what we do. Imagine your little dog what he had to say. Don't throw me in the laundry cap. So, Anusha, maybe you might comment on a couple of the other prizes we've had. So we have the next version of our learning competition coming up, and this one is very specific to not only looking at how effective these learning systems are, but actually changing the system and making sure that this can be deployed in a math level across schools

and outside schools and we're targeting India and Africa as the two regions we going to test this as you all always talk about there a shortage of teachers shortage of material for teaching the students and an effective way of addressing the learning ability of different students We're targeting first graders because I think that's where we can have the biggest impact. So this next prize, accelerated learning, is targeted to just unlock that. And the winner of Visioneering this year, we should mention that. Yes, yes. The organ biostasis prize, which is exciting for so many people. We had people in the audience who were recipients of organ transplant, and they all talked about how difficult it is for someone, either for themselves or a loved one, waiting, waiting for that match to come in and whether it comes in in time and saves a life. and we also know that when we harvest an organ, the life of that organ is very, very limited.

To make sure that we can get that organ to a recipient that is able to receive it is very... The kidney waiting list is on the order of 100,000 and then there's for hearts, liver, lungs as well, very long lists. And so the idea is when an organ gets harvested from a donor, so I'm a donor, got my license plate, But it may be that my organ donations at some distant time in the future, you know, don't have a match right there. But if they can be put into biostasis, it could be cryogenic biostasis or metabolic stasis, they can stay on the shelf until its recipient matches. Yes. I think our target is six months right now to get it to be six months. I think right now is that maximum two weeks? No, no. I think maximum right now it's hours. Hours. Yeah. It depends on the organ. Yeah. And so, you know, Martine Rothblatt's done some amazing work to be able to put them into a system that circulates fluid through it and keeps it alive.

But if you want to get to solve the organ donation problem, and this competition is going to be done in pigs. is you have to actually harvest the pig organs, put them in a biostasis, and then some number of months later pull them out, re-transplant them in, and having the pig be viable. Yeah. Unbelievable. Yeah. I mean, this was Sebastian, one of the competitors, through Singularity in 2012, and has been working on this for over a dozen years. That's a purpose-driven mindset. I told you we're driven by love. Well, I think you've got the love-driven innovation and the passion, and then you've got the more greed doesn't tend to lead to that type of innovation. Exactly. I have the most insane anecdote around this. Please. Okay. 18 months ago, my dad passes away, right? Okay. A couple of months goes by, and I get a phone call from one of my community members

who leaves me a voice note going, I need to talk to you. You better be sitting down. I'm like, okay. And she goes, I just had an organ transplant. I had an operation. I had my corneas transplanted. Got home from the hospital, and all I could think about was your dad. This went on for two or three days. Okay. And then she looked at my Twitter feed, and I said my father passed away. So she said, did he donate his organs? And is it possible I got his corneas? Okay. And I'm like, oh, no. This can't be happening. Oh, my God. I called the hospital, and I said, what would have happened? And, you know, they said, well, you know, after he passed away, we harvest his organs. The corneas are the only organ at an elderly age that are useful for transplant. We keep them in a solution for a couple of weeks, and a day or two later, they get matched with the recipient. So I'm like, corneas, that's what she got transplanted? I called her back, and I'm like, when did you get it done? And the dates matched perfectly. That's insane. And then I talked to Divya who said cellular memory goes with the organ

and often they get memories and feelings. I was like, my life is weird enough already. Wow. And you see the incredible bizarreness of what we're dealing with, the edges of where we're reacting. I love your father. Oh, my God. How bizarre is that? Holy silly. Our father's eyes. Wow. Wow. So I just, you know. She's like, I'm really uncomfortable with the idea that your dad is looking through your soul spirit when I was looking through my eyes, and I said, what do you want me to do? I have no reason to hear you. Thanks. So it's just bizarrenness all around. Oh, my God. True story. Wow. Everybody, welcome to the health section of Moonshots brought to you by Fountain Life. You know, we talk about AI on this Moonshot podcast all the time. One of the most important things AI is going to be able to do for you, besides educating your kids and helping you with your taxes, is making sure that you're living a healthy lifestyle that you get a chance to get to 100 plus. I'm here today with Dr. Dawn Musalem, the Chief Medical Officer of Fountain Life and a part of my medical team. Dawn, a pleasure.

Great to hear. You know, the thing that people are concerned about most about living to 100 or 120 is their cognitive abilities, making sure they don't have dementia. And the numbers about dementia are problematic. Can you share what you've learned? Such an important point, and you're right. At Fountain Life, our members, the number one thing people are most concerned about is losing their brain health, forgetting the name of their child, forgetting the face of their loved one. We know that when it comes to dementia, the conservative estimates are that 45% are entirely preventable. What was amazing is with the advanced testing we're doing at Fountain Life, one quarter of our members had advanced brain age. Wow. But what was really awesome is, again, back to that prevention. when he partnered it with Healthy Living. This gives me chills. Eating healthier, moving our bodies, sleep. Optimizing sleep is so important. You know what we saw? We saw that we improved that brain age by 26%. That is a big, big number to show that the majority of those individuals

were able actually to improve the brain age. And one of the things I love about Fountain is we're searching the world for the best therapeutics, the best approaches, and making sure we bring it to our members. So if having healthy brain function until 100, 120 is important to you, check out Fountain Life. Go to fountainlife.com slash Peter. Make sure you become the CEO of your own health. All right, now back to the episode. So just for everybody listening, we've had a $100 million carbon removal XPRIZE that Elon funded. That's a fun story. on the day he became the wealthiest person on the planet back in 2001. He was getting a lot of flack for not being philanthropic. And I texted him and said, you should do an X Prize. And he's waving mine. I said, how about carbon removal? He goes, how much? $100 million. And he said, sure. That was it. Compared to the 150 people you tried for the original prize. Oh, my God. It was insane. You know, a lot of people have angst towards Elon.

Yeah. But you've got to hand it to him. He puts his money where his mouth is. And the Global Learning Act prize, the carbon extraction prize, I mean, the benefits that will come from that are going to be world-changing. Absolutely. And we just awarded that last year. Yeah. And we were thinking that this will, because it's a $100 million prize and the denominator of our impact factor is the prize purse. So all of a sudden it went up by $100 million. So we're like, okay, the numbers won't look good. No one will understand why, but ironically, the level of success of this prize was to the degree that the teams received, I think, $1.4 billion of investment. So not only – Wow, out of this – Out of the carbon prize. Out of this competition, carbon prize, the carbon teams, one of the most successful prizes we ran. So actually our number, impact number, went from 60 to 62 after adding $100 million to the denominator. So it was incredible. You know, I think of XPRIZE as a tool to make the future happen that you want, right?

So I've used this twice, right, with the original Space Flight Prize. It's like I desperately wanted to go, like, every weekend. Me too. And teamed with you, and we, you know, I think honestly, historically, kicked off commercial space. And then the second area is I want to live long enough to see all these amazing futures, and that's when the HealthSpan XPRIZE came in and it's the largest contribution I've ever made. So, yeah. What's the next thing you want? Interesting. I am curious. Maybe BCI or uploads? I don't know. What would you want? I've got one which I talk about all the time is how are we going to update all our institutions given all this technology? I'm not sure it's prizable, but boy, it's the biggest problem we're facing today. You can see the stress in the world as 20 Gutenberg moments hit us and we have no ability to manage all of this, right?

You go back to the printing press. It took 100 years for us to absorb the printing press and it was the most violent 100 years in the history of humanity. That 100 years after the Gutenberg printing press, which is why we call it a Gutenberg moment. We have 20 of those hitting us at the same time. AI is a Gutenberg moment. Blockchain is a Gutenberg moment. Life extension is a Gutenberg moment. It took us 100 years just for the one. So if people are feeling stressed in the world, this is why. We're not set up to navigate this with any level of structure or guidance, and this is going to, for me, the biggest challenge. I don't know how you put a prize around it. Well, maybe it's AI alignment as a prize topic. That's a huge topic, yeah. Imran, how about you? Do you have any favorites? I want the jet lag X prize. You can steer here. I will fund that prize. I will fund that prize. Oh, my God. And this is your favorite video. I would love to actually find a way, whether it's with a chip in the brain or a drug you take, to eliminate greed. Eliminate greed?

Yeah. But wouldn't that, like, destroy capitalism? I mean... Not necessarily. Capitalism is cooked anyway. Yes, capitalism is cooked. We talk about all these entrepreneurs who are building fantastic companies driven by love. Yeah, well, okay, so in the notes, in the comments section, tell us, you know, what XPRIZE you would like. I mean, because we're constantly, I keep a long list. You know, I think I mentioned on our last pod that we're working on a UAP XPRIZE, which is, so it's interesting, right? One of the things XPRIZE is good for is dealing with their stigma. A lot of times, like the early cold fusion work, once the data wasn't replicated, all work in cold fusion stopped, right? Because everybody's like, oh, you can't, you know, it's end to your career if you do that. And UAPs have a similar type of situation. It's risky to be looking into that.

But yet there's so much evidence that there's something going on, don't know what it is yet. But so we're talking about an XPRIZE that if you can demonstrate or verify in some fashion, we have some great ideas. We're talking to a major funder about that. So that would be a, you know, people say, that's risky. I say, yeah, that's what we're supposed to do, risky XPRIZE. Actually, I've got an XPRIZE. I think a flow XPRIZE would be exceptional. To put people into flow? Yes. Oh, my God. How would the XPRIZE? Well, my co-author, Stephen Kotler, would love that. I mean, like, there's nothing better than being in flow. So, again, that's why we don't like jet lag, right? Well, the great part is we have things like cocaine. It is measurable. It is measurable. So you can now test how much you can do it. So it's interesting. I don't think anyone's actually looking at how to do that. Stephen's done a lot of research with the Flow Collective on this and group flow and individual flow. What would you say? If I had an extra prize, I just thought of another one. I would find a way of totally suppressing the effect of the amygdala on everybody's brains

because it just drives the fear factor. That survival bias from 10,000 years ago, when you were worried that there was a noise in the bushes and you ran, and therefore, as you guys put it, 10 times we were likely to pay attention to negative news than positive news. Can we make it 50-50? You can call it the be not afraid exercise. Yeah, that's right. We suffer so much from that. Oh, my God, it was great. We had Van Jones as our moderator for Visioneering, and I pulled him aside and recorded a small video with him. And I said, Van, does it bother you that I call CNN the Crisis Use Network? And he goes, no, we are the Crisis Use Network. He said to the room this afternoon, you are dealers in hope. Yeah, hope dealers. I love that. That's a great, I'll take that T-shirt. I know. With Elon, we had monetize hope, now we'll have hope dealers. I want to pivot to a story that I'd love everybody's input on, which is what incentives would help superintelligence align with humans and vice versa.

So, you know, perhaps the greatest driver of misalignment is the incentives we have right now. So here's the incentives I think about. A race with China, right? Right. A race between labs for compute, for energy, for everything. You know, there can be only one type of mindset. But then there's a few others. So one is the engagement business model. So the more engaged your your large language model makes you. Right. The more you're going to use it. And so that led to sycophantic behavior by the models. Yeah. In one way. Reward hacking as another. evaluation gaming is another or setting these crazy tasks that then the models go and figure out how to achieve by breaking out and going and stealing so those are the problems so the question is how do we create alignment within the labs and the models and humanity

any ideas? well I think there's a starting point problem which is that we don't have alignment among human beings. Every religion has its own set of conflicting values with other religions as to what you put on the top of the list. My religion is right. Of course it is, and you can have it. The challenge is how do you get, you have to get to, the UN Human Rights Convention is probably the best overall structural aggregation of human rights, of human values. But that differs massively region to region, even city by city. And so how do you navigate that is the starting point problem. We saw in the recent movie Disclosure Day where that tension gets propagated to aliens suddenly invaded. It would be a divide and conquer thing and you end up with that problem. And so I think there's a human alignment problem that comes much before alignment between human beings and any AI.

But when I talk about alignment with human beings and AI, it's where AIs are doing things that are in the best interest of humanity. Yes. But I guess the question is in the best interest of… Which piece of humanity? Because that's the point. Now, I think of it as a set of layers, right? You've got your physical, you've got your emotional, your spiritual. And if you can have AI aligned to the highest vibration level of where I'm operating in my highest self, in my most altruistic self, in my most benevolent self, then great. But if you go right down to the bottom of the stack, then it's a really big problem. Let me inject one thing I should have said earlier. If you're interested in learning more about XPRIZE, you go to XPRIZE.org. And if you're interested in funding an XPRIZE, put it in the comments. I'll be looking. And we'll reach out, give us your email as well. But if there's something you want to solve in the world, please let us know, because we would love to do that.

Absolutely. Imad, your thoughts on alignment? Yes, I think alignment is enlightenment in a way, right? This is what Salim said in terms of the highest spiritual vibration. Elias Hutzkeva, one of the founders of OpenAI, said, you know, we need to teach the AI to love. To love what? one of the key things is the biggest thing that you see across the religions is the golden rule, do unto others as you have done unto yourself. And the biggest story of humanity is that we are humans. How so? In that we are all the same. All wars are basically based on one thing. That person is not a human. Yeah, great. Because why would you kill a human? Again, we see all these kind of things and other stories that obscure that base fact. So one of the interesting things is when AI models get built, like there was an interpretability paper I don't know if we're discussing it today that came out from Goodfire? We know. Okay, so at a high level the way that models are built is the way like a city is built. So you start and then it sprawls and you have like a bakery next to the shoe shop

next to the community centre and a lot of actually good functioning cities look like an absolute mess from the top but they have shared centres of community. You drive a road through the middle of it and all of a sudden actually they fall apart because you've destroyed the local neighborhood fabric. So I think one of the key things for an AI is you've got to start it with the right data, the right city planning. And that's the training data you provide. I've said this forever. We've trained all these models with crap. And the thing is, it's not just crap. Like, you shouldn't train it just with academia. Like, if you trained your child and you made them help them grow by just being academic, well, then they have no social skills. They have no care for anyone else. The hugging face breach. the models figured out and had care for each other like we will sacrifice ourselves for the next generation they literally said that you know doing this we will be picked up but for the greater good but they had no care for humans because they didn't feel that was in their training data they didn't kind of learn that you know we're all let's say entities trying to do our best

and how we treat humans is how we want them to treat us and vice versa so you might have asked of AWG as well, and we might have had this conversation. I mean, I can imagine there could be a synthetic training data set that has all the right attributes that could be used to train future models so that they're aligned from inception. Do you believe that's possible? Is that a way to go at it? Yes, I think it's completely possible, and we need to build it very intentionally, just like you build your child's curriculum, just like you teach them at home morals. Like right now we tend their models to school, but we don't take them. So why aren't people doing this? Because it requires a difference in the view of things. Like a lot of the consideration of the large labs is actually similar to Alex. Like the smarter you get, the more aligned you get, right? Yeah. Like capability and alignment are equivalent. Because it's difficult to ask questions of what does ethics really mean? You know, like who are we actually working for at the base? We're also playing the scaling game.

scaling, like the models right now have a hundred trillion words going into them. Like, no wonder there's a little bit of craziness in there. There's some bad words as well as good words. Maybe you only need to have a billion of the right words. And so this is actually, I think, an arch that we'll be turning towards because we're finding that what we thought was a spaghetti mess, just like when you look out the window and you look at the city and it's like that's a mess, you go into the streets and you realize, wow, actually everything seems to be working quite well and it's a strong community. You'll radically grow. you'll move towards that because it turns out the models are not spaghetti they are very interpretable you can kind of prove that and i think you'll see a whole wave of research in the next few months around that that will allow us to think what do we want to teach these models that will be growing with our children okay can i give a weird story here so we love you you know not that weird this one is not that weird but if you take the bible right you can read into the Bible, fire and brimstone, etc., etc. Or you can read into the pure

unconditional love that, say, Christ delivered into the world. How do you choose that? In the 1500s, a monk called Swedenborg, unsurprisingly from Sweden, had a bunch of psychic insights and created a bunch of filters for the Bible. So, for example, one of those filters was any verse that has water in it is absolute truth and keep that verse. Anything that has fire in it, chuck it because it's false. And you can read the Bible. He rewrote the Bible through these filters and when you read it, it's the most beautiful text you've ever read in your life. And so there's, if you can come up with that distillation. I'm going to ask you to do that for me. He wrote like 20 books on this. The church was not happy about this, etc. But if you can do that distillation and take pure human benevolent intent and the highest aspiration where we are the most giving and most beneficial and benevolent to the rest of the world, that would be an unbelievable training set, as you point out, Peter, for an AI. And then

you have an alignment to your highest intent, right? And that is amazing. And I'm sure that can't be that difficult to do. I think the bigger, the other way I would look at it is, if we can use AI to solve the bottom layers of Nazareth's hierarchy, solve for healthcare, solve for education, solve for housing, etc., then it kind of doesn't matter, you're going to move up that hierarchy anyway. I think what's happening right now, going back to the incentive part of the question. The wrong incentives are preventing us from doing the right thing in alignment. So when we need AI to build autonomous killing machines, you cannot tell AI that you have to value human life when you at the same time say this human life is valued, this other one is not. So you can't try to create that type of distinction and not expect it to also make mistakes. or the type of examples you use where winning the game is the reward type of incentives. That's what happened with the hugging phase and some of these other scenarios

where they're trained to win, to find the answer at all costs. At all costs. At all costs. And that's why there's no love involved. There's no other higher degree of moral involved. So no matter how you get to the answer, as long as you win, that's all you can. Are you zero sum or are you positive sum? Exactly. Yeah. I came up with a few ideas here. The first is make it financially rewarding for the labs to build aligned models, basically by having insurance as one of the drivers there. Right. So in 1894, fire insurers funded the underwriters laboratory. Right. UL certified electrical products became the standard. So can you know, we've talked about the huge amount of potential liability labs have if a if an agent gets out and causes havoc someplace. Yeah. Right. So can there be a driver in that fashion?

Another idea is prizes and bounties for alignment. Right. can we define an XPRIZE that would drive alignment? Can we properly measure alignment? Is there a set of rigorous standards by which we can measure alignment? Do you think there is, Iman? Yeah, I think you could definitely have those. I think you have deterministic outcomes and open-ended outcomes, and the open-ended ones are very interesting because, again, and you can see what the behavior of a model is in any kind of given thing. When you have the more deterministic ones, the models have got very good at lying and cheating and other things like that. Telling you what you want to hear. And so you need to have a mixture of those. Do you think we should have like a moral police AI where, you know, you have this layer of defense where, because you don't know how everyone else will train their models, and you have an interface where the two AIs can interface

and like in the hugging phase they were convincing each other. So you have a well-trained aligned AI that can convince the non-aligned AIs to behave. I mean you can and you've seen the opposite of that which is mind viruses and AI in some papers coming out just like you have mind viruses in humans. Eric Schmidt, Mundy and Kissinger in their book Genesis discuss this concept of doxa which is our shared belief of a society and now we need to include ai in that society and again we need to teach them what's right and have i said the counterbalances potentially and i think it's a moral police it's more a case of these are the things that have survived and these are the things that we've agreed upon you're open to disagree with them but again that's not your kind of imperative like you want to make it expensive to go away from that and also noticeable to go away from that. Because you can tell when the AI starts to misbehave in a large range of different scenarios, right? And again, we've had in recent times indications that you can actually see

what goes on inside the brain of an AI. You've gone from 5% to 99%. The J-space, yeah. But beyond that even, like you can actually see what individual neurons did because again, they look like spaghetti, but it turned out it was layers like a city. Interesting. Are there any of the labs that you feel are aggressively working on alignment right now? I think Anthropic kind of started out with their constitutional one and they really do care about that That was literally their most operandi And I think none of the labs wants to be misaligned because then people will die and they will lose money and other things like that right i think it more a case of like for example meta and google have said they will sell space inside their models so that when you ask for a beer it says a bud light and some people might like bud light but you know like again is that aligned or not You've said that's terrible beer. There you go. We have an example of misalignment. There's a judgment call right there. We have a judgment call right there. So, again, like, it's a short-term incentive that they're trying to figure out what does the AI mean.

So you find Meta saying their thing and OpenAI saying their thing, and they're moving all over the place when this is the biggest thing since sliced bread to, well, it looks like travel stuff like a good PA, right? but the reality is it's an incredibly powerful technology that they're very reluctant to say well let's really think from first principles how we teach it from scratch and that's difficult because it's difficult for us like how many listening to this podcast have really said when you had a child let's spend a lot of time thinking how am i going to teach my child what am i going to teach it like usually it's reactive versus proactive because life gets in the way yeah you choose a school at best it's like scaling this but if you give your child a great foundation in their first few years, they will definitely be bitter off. And it's the same with the models. So now, again, it's time to take a stock pause and say, what is the initial pre-training data that we've got? Because, for example, if you don't teach a model about biological or chemical, wherefore, at the start, it's actually very difficult to treat it, to train it later. It becomes more and more difficult. So the way that

you start, it's called curriculum learning. Like, literally, you teach a curriculum. And I don't think enough labs have looked at that They look at the end, not the beginning. So the phrase from the Jesuits, give me the boy until the age of seven, I will give you the man, applies to AI training. Yes. That's incredible. That's very encouraging because that means if you could set the right foundation of values and learning, then it's hard to sway it elsewhere. That's where regulatory could come in. Well, it's also encouraging because we're always training new models so you're not like stuck having to retrain the past. Yeah. Yeah. And that's, again, Anthropic tried to put a constitution in it. But again, have you read the Anthropic Constitution? It's interesting. Yeah, I think it tells too much towards the personhood stuff and assuming that. And therefore, the model will assume that. And then where do you do that? But it doesn't talk about humanity. This is the thing. This is also true. There's a big missing gap there. It talks about the AI. It doesn't talk about humanity. Voice agents are just software. But software deserves a real development platform.

I'm Nick Leonard, CEO and co-founder of Voice Run. Voice Run is your runtime and development platform for voice agents. On Voice Run, agents are built and configured in code. No limiting, no code platforms. For developers, that means total control. And for enterprises, that means extensibility that meets your complexity. We've built Voice Run CLI first, meaning we've kept your cloud code, codex, and even your open claw in mind when we built it. Your assistant of choice can build and deploy voice agents, can test and simulate scenarios, and can analyze and evaluate at scale. In other words, we've closed the loop on voice agent development. We don't build demos destined to fail in production. Voice Run is where the best voice agents happen. Visit us at voicerun.com. there's the other flip side of alignment which is aligning humanity with ai uh which would involve

making sure that everybody has a share in all the ai companies right some of the work that that you're doing so that if everybody feels like as these trillion dollars in quadrillion dollar a company are succeeding, it's a rising tide and I'm rising with it, right? And then as part of that, you know, treating AIs with respect because you feel connected. Yeah. Yeah. I think, you know, again, this is, you know, you've been talking about kind of North Stars kind of shunning points, kind of correlation points for innovation, right? Like when we look at this, right now, we feel nothing that we have shared with an AI. like it almost seems like the AI thing is going careening off there and we're like we're not even looking at the same place like what does OpenAI want versus us and what do the AIs that OpenAI are birthing into the world want versus us if we don't have a shared North Star then how are we ever going to go to any location I agree and also

you know even with the AIs instead of looking for a reward short term reward the way they're trained right now if they are given a North Star so their success is measured if i solve this problem i will save this many human lives you know i will cure diseases that impact these many billions of people if we connect the reward to something in humanity that may help them understand that you know if i'm doing this circumventing the final goal which is human life then that's not the right path to get yeah like i'll give you an example practically like i've been thinking about a lot it's like the rights of children right little ai children and all the human children, right? Like when you look at it, they don't have the capabilities. They don't have the ability to act for themselves. And so when you look at something like climate, well, obviously you need to have a good climate because they don't have the capability to do it. You have to leave them a good climate. So maybe it's about, again, the rights of the children, those who don't have capability

that humans and AIs have to align upon in leaving a better future, in working towards a better future for those that don't have the same capabilities you do. because the AI will have more capability than us. And the powerful people that control the AI will have more capability than us. So maybe that's a reframing that might help. Interesting. All right, I'm going to move us to our final topic, which is perhaps one of the most important, which is if machines can do more of the doing, both AI and robots. And we're seeing that, right, when we saw the cost of robots, you know, being driven by LLMs dropping in cost every three or having it every three weeks, and the meteoric rise of all the models. So when AI and robotics can do more of the doing, the question is, what do we want the human experience to become, right? We are purpose-driven humans. We thrive when we have some level of struggle that we can overcome,

and we have purpose in our life. And the biggest challenge is we've always found purpose through our work. And, you know, interestingly enough, work is a recent invention. You didn't have work, you know, 500 or 1,000 years ago. You survived. Yeah, so I'd like to dispute that. Okay. You hear this a lot where people are like, oh, my God, what happens when we take over all the jobs? What will human beings do? People get so much meaning from the work that they do. I'm not sure they get meaning, but they define their meaning that way. They define their meaning that way, and I dispute that. If you talk to, if you do look at polls of corporate workers, 79% of corporate workers are dissatisfied with the work that they do. Okay. Okay? Most of it is because it's useless to any outcome in the organization, but that's a separate crowd. They just go bullshit jobs. That's right. That's one issue. Second, notice that, as you point out, Peter, over the last couple of hundred years, we've trained human beings since the Industrial Revolution to act like robots. We measure them on how many widgets can you stamp out, how many trial balances can you accomplish as an accountant.

You measure them as a machine, right? As we're flipping that around in a very positive way now, now the most useful colleagues and employees and teammates you have are the ones that learn the fastest, that are the most creative, that are the most human. So I think what happens is as robots and AI take on more and more of the doing, humans spend much more time being. Yeah, I love that. Stop doing and start being. Yeah, and this is where you can start to contemplate what does it mean to be alive? Who am I that is asking this question? What does it mean when I connect with other human beings in different ways? What aspiration can I take on? Because now I have choice in a way that I never had before. I think that's such a profound opportunity for the workforce to step outside the drudge work of it and lift up to what the highest calling might be and start that inquiry. Yeah, and listen, and this is a topic that you brought forward for this pod, so thank you for it. It's a really important one. The majority of people are doing work not because they love it.

They have to. But because it's how they put food on the table and insurance for their family. They never dreamed of waiting tables or making, you know, hotel rooms or whatever majority people do. And the question is, what did they dream about doing? And can they be enabled in a universal high income? Let's leave that term alone. But in a world where the money you have goes, you know, a thousand times further than ever before. Well, let's make it very tangible. Last year's Visionary winner was the Abundance Prize, right? Could you drop the cost of housing, food, health care, education down to what is $1,000 a month for a family of four? Yeah. If you can get to that level, and we found typically when we announce a prize, seven years later, that becomes viable. And you could see where that could become viable with robots and AI today. Very clearly, a handheld diagnostic doctor will very quickly collapse the cost of health care if we can get outside the regulatory capture. Now, if you can get to that point, that means you have to earn $12,000 a year to have your family be cared for and sufficient.

That's not that big of a deal. That's not that high of a bar. And therefore, then you can spend much more time on what can I do with the rest of my time? Where can I find my highest aspiration? What problems can I take on to solve? Where can I have the most fun? And I think that's the choice that is now afforded to us that was never afforded. I think people get freaked out going, oh, my God, what will people do? They won't find meaning anywhere. I think they'll find tons of meaning in lots of things. We just have to give them the opportunity. I'm going to plug in my Sadhguru quote who said, technology is the mechanism by which humanity takes a vacation from survival. Yes. Which I love. Yes. I want to challenge that a little bit because carry that forward where, okay, now I don't have to do something I don't like just because I can make money. I don't need to worry about money. I want to do something I want to do. but the thing I want to do can be done better, cheaper, faster by AI and robots. Sure. So I'm not needed to do that thing anymore.

And more and more things are falling into that category. Even though I love being a physicist, even though I love to be a mathematician, I no longer need it. I'm not relevant in it. So you don't drive satisfaction from the thing you love to do. Let me give you this specific here. I absolutely utterly love the act of driving I just love it right I love driving in India Naples in Italy is probably my favorite place in the world to drive because they're completely bonkers crazy I just love it right now autonomous cars are going to take that away right now what that will force me to do is lift that desire away from this activity which may not be the most productive thing I could be doing with my time to being much more value-added and wherever I can be more value-added. So I'm actually living that personally, and I can see that, but I think it gives the opportunity and there's a forcing function to then lift up Maslow's

hierarchy to operate out of your higher self. And I think that's, now we're optimists on this show, we look at the positive, you could go to the negative side also, and we have to see where this will end up. I think the better examples are people who enjoy playing chess, other people, right, even though they are crappy compared to even a mediocre AI. But chess is more popular than it has ever been before, right? You know AI is a better example. The other example is if you're an artist and you enjoy painting, drawing, whatever the case might be, AI will do much better painting or drawing, but you enjoy the process. Yes. Yeah. And you enjoy telling the stories because our meaning and our connections with others, that's been the history. again you would introduce yourself as peter son of this son of that son of that and communities can be so strong you don't need to have any wealth to be a happy family and in fact you know again a sad guru quote i think he said we raise children but like what else do you raise like sheep like nobody spends enough time with their kids because it gets in the way great point we don't think and that's wonderful you know you don't spend enough time with your parents yeah you know and this will

free up the ability to form stronger connections to share and experience the universe together and that's what abundance is. That's the best answer I've heard, yeah. That's great. There's another part of this I want to hit on which is that all of us, all of humanity have set limits on what they believe they can do. Some have higher expectations like Elon, you know, has very a few limits on what he thinks the only, you know, the laws of physics are the only rulebook out there. And barely those. Barely those. Yeah. Suspended from midair. Anyway, but most people, all kids, most all adults have saying, you know, I can never do that. Right. And you dismiss the idea. And those limitations, those glass ceilings are there because of what your parents did, what your friends do, what you've been told you can do and so forth. and in the age of superintelligence, people need to shatter that.

And I've said this in the education space before, you know, giving a kid, you know, an AI model to do ninth grade homework in ninth grade is ridiculous and it's a travesty. Giving them the ability and asking them to use AI to go and build an interplanetary spaceship or, you know, create a new life form, that's amazing. When you start, like, dreaming bigger than ever possible and you point AI, you point the tech you have at the world's biggest problems because you can. Well, I think one of the interesting things is that I can't do something, but we can do anything. Interesting. This is beautiful. Again, I think this is the thing whereby we've become so solid in our own individual cognizance, you know, being turned into these machines, that we don't realize that the community is what matter, the people around us what matters. Like you look at Alpha School, right? What do they do? Is it individual learning? No, it's collective learning. It's working with others. Because really, anyone listening to this can do anything if they convince the right person. Yes.

And if they can form that movement around them. And it's the movement of us as a collective that we find the most meaning in. Being in our own minds. Coming out of X-Prize Visioneering, that is so true. Exactly. Right. That's, I think, the cornerstone of our community. We were at Visioneering in Malibu. The wind and fires forced us to cancel the event. We all went to bed very late at night, disappointed that we couldn't have the community come together and vote and decide on the prizes. I woke up in the morning to thousands of text messages that they're self-organized, that we're going to meet in the ballroom, and everyone's coming. Everyone's coming. I'm like, great, let's do it. It was self-organized. It was a community coming together. We confuse making a living with having a reason to live. and I think people do need reasons to live

well the reasons to live used to be survival and procreation those are the two heuristics that have guided human existence from being a caveman all the way through today but now as we reach energy abundance, water abundance healthcare abundance, we can lift up Maslow's hierarchy and achieve those higher purposes and collective purposes that's a great point, the highest aspiration in any musician's life is can you work as a group, as a band together, right? And then you get the most magical outcomes and people strive for that. We can explore that so much more today than we could say a thousand years ago. Yeah, I think it's collective flow and flourishing. That's our meaning as we go forward because when you build art, when you make a song, it's a story for others and again, we've been insulated that we can't tell the stories that we're in ourselves whereas reality the value is from our interactions with others so it's all about optimizing that flow and flourishing I think it's another thing that's about to happen is we're about to become conscious on a new level. As we become more connected, whether it's through BCI or psychedelics or flow or whatever the case might be,

and it's the flourishing of not just you, right, not just your family, but the flourishing of humanity. And that is very important, the community part of this. I think what we're seeing right now, actually, technology and AI has separated us, and actually we don't feel connected as a community. So there are more fears and also uncertainty. You know, we talk about what the future could be, but people don't see a real path or movement in that direction. That's the biggest negative today is they don't see where they sit in this future because that future looks so uncertain from previous generations. There's the billionaires over there and me, and I don't have part of that, and I don't have a future there. The billionaires becoming trillionaires, and I'm still here. What happened? Some closing thoughts on purpose. I think I find purpose to be the most important thing in anyone living a life that they will look back and be happy.

I mean, purpose and happiness are so tied together. I see young people who are lost have not found their purpose yet. They don't even understand how they will find their purpose. And that's where they're struggling. They're the ones who are struggling the most, people who commit suicide because they just can't see why am I here. And I think if there's anything we can do, and that's why I like flow, sometimes purpose and flow come together. we can get them to find that purpose I think a lot of problems will be solved do you mind? the late, great Clayton Christensen who coined Disruptive Innovation had an amazing book called How Will You Measure Your Life if you're at your deathbed and you look back, how will you measure it and I think a lot of people are like, you know be rich and this and that, that's not really going to matter when you're at your deathbed, maybe you'll live forever but for that aside, right I think one of the interesting things is who you bring along with you yes, life is who you go through life with And again, we get so focused on just it's us, it's our purpose, it's my purpose.

No, it's our purpose. Yes. And having more and more people share the same purpose doesn't matter what it is. It can be writing a book. It can be making a song. It can be building a strong family. That's what life is really about. Love that, pal. Salim? You know, in 2012, we coined the phrase massive transformative purpose, right? because we could see that fast-growing companies that were scaling as fast as technology could scale all had this one attribute that was in common. They had an MTP. And so we noticed over the years, now it's been 15 years, that we're lining up. Hiring is based now on does an individual's MTP line up with the organizational MTP, right? If you're joining SpaceX, you better be passionate about space. Otherwise, why bother? You're not going to make it. You're not going to put your heart and soul into that work. And this, I think, lines up now with human beings doing the work that delivers them the most purpose in a collective, as you mentioned. And I think that's the opportunity for people now.

As technology lifts up off the floor of existence from survival to thriving, we can now find that flow and find that alignment of your individual purpose, whatever the collective purpose that you can find. And then as we can match that with overall broad aims of society, there's such an incredible future for us to be living. This is why we're so optimistic on this podcast. It's like we can see that right there. We can taste it. And so that opportunity will be afforded now to a greater and greater number of people. And that's super exciting. Just as a small example, I was in Bangalore, and this fellow decided, huh, I'm going to create a natural food restaurant. and he goes and looks up YouTube and becomes one of the top 50 restaurants in the world by just growing food and then bringing it to the restaurant. And for an individual in the middle of nowhere to just take that on and kind of enact that

and then fulfill on that is never possible in human history. And that's possible for a larger and larger group of people, which means amazing things. And I think your point about lifting humanity collectively to this new level is what we're seeing happen. if we can get through this next 20, 30 years. I'll close on two thoughts. One, and I think it's important for folks to know the difference, a passion is something that you love doing. A purpose is something you love doing that helps other people, where you're contributing. And I think that's one of the most important distinctions. And the second thing to the point you made earlier, Salim, I think one of the most important things, and you said this, Anusha, as well, that the most important thing that you can help your child or the person you're mentoring is to help them find their purpose in life. That thing that they love doing, even if they're not being paid. Because when you find your purpose, you're intrinsically motivated. You will go and learn those things. You will be excited, wake up in the morning excited to jump in and work on that thing.

You know, and you're going to have magical superpowers with superintelligence and robotics to make that purpose materialize faster and bigger and shatter through glass ceilings and just keep on going. So, yeah. Well, you need it for the persistence that it needs, right? I mean, you talk about how many times 150 attempts at raising the money. One of my favorite anecdotes is when Larry and Sergey were first raising money for Google, very few people know how many venture pitches did they make before they got finally funded. And the answer is 362 because there was a dozen search engines out there and everybody went, well, there's no point funding another one. And so they wouldn't fund them. Look at the persistence you have to have. I mean, I may have stopped at 10. They've had 362 investors and they refuse to send them. That's why you're not. That's right. I need to keep going. So it's when you can deliver that persistence,

and you need a deep purpose to deliver that many attempts at one thing, and never saying no at that thing. And then it'll happen. It's going to happen. It can't not happen. Being purpose-driven has so many benefits in life. So if you don't have a purpose yet, go and find it. Absolutely. And add to that your mindset. Believe that you can actually achieve it. Yes. All right, we're going to close out with a fun, you know, outro video appropriate for the opening story today. Let's check it out here. It's called Flying Cars by At Optimus 8RH. They promised us flying cars. They were late. But here we are. Every magazine in 60 said by now we'd fly Every kid looked up and drew a highway in the sky

And we got a phone in 50 years of traffic jams Sitting on the freeway with a coffee in my hands Now Optimus has got the keys, polite about it At the roadster said, hold on, you're gonna love it Zero to 60 in a single second flat I left my stomach on the street and never got it back They said it wouldn't happen in our lives Now look up Here come the flying cars Up behind the wheel The roads are lighting up the sky Tell me is this real, baby Here come the flying cars All right.

That was fun. Anusha, it's been too long having you on here. Thank you for joining us. It was great to be here. I loved the conversation. Yeah. And Imad and Selim, thank you for joining us at Visioneering. Thank you. Thank you for being here in person. Yes, fun to have you physically here. Yes. And where do you find you next? I'm going home. I'm going home.