0:00First uh our first speaker is uh is Elon Musk. As the uh CEO of Tesla and SpaceX, Elon has shown that conquering challenges of physics and engineering uh can be easier than cutting through red tape. And I think his uh dedication to doing both however continues to inspire people people around the world. So thank you Elon for for joining us. We were just wrapping up our introductory uh session where we made clear that under this presidency um you know we believe that economic growth is one of the most
0:29important uh drivers for all of us and and we believe that technology is a big a piece a big piece of that. So you've been on the on the front lines of this for for quite a while and I think one of the the key questions I think for the group and something that we wanted to talk to you about was as you have um as you have driven innovation across multiple countries around the world. You know what in your opinion separates countries where innovators can successfully turn breakthroughs into deployed technologies from those where where progress actually stalls because I
0:58think there's a lot of lessons learned about what people governments should be doing and what maybe they they shouldn't be.
1:06Well, yeah. I I think a lot of people have talked about this and I think some of it frankly is is is pretty straightforward is that um you you have to have an environment that's relatively free of regulation, meaning that new things must be default legal as opposed to default illegal. Um so, uh in in the EU for example, we find that the the regulation level is extraordinarily high and things are generally default illegal. Um and this inhibits uh
1:35progress of new technologies. Um it it slows it down. It doesn't it doesn't ultimately stop it, but it slows it down uh quite considerably. Um then of course you need to have um a you need to have venture capitalists um and an environment that is supportive of new companies. You can think of new companies like little like they're like small saplings in a forest. So what what
2:03most countries tend to do is they tend to provide too much support to the large existing trees in the forest and not enough to the small saplings. But the large trees don't need the support. It's the small saplings that do the startups.
2:20And so the system should be generally biased towards supporting the small the small trees as opposed to the large ones. Um but that is rarely the case. Uh because the law the the the large companies have access to um usually they have access to the leadership of the countries and the small the small startups do not. So you so you really need to foster the the growth of of
2:48young companies and take active steps in that regard. Um and like I said make things default legal not default illegal.
2:57One question that um a lot of the countries here face is a question around adoption. I think there's a a general um recognition that adopting emerging technologies can be very beneficial to economic growth um no matter what sort of shape size of of any country is. Um you know how do you think about adoption? What country what should countries be doing to encourage adoption? Does it go back to the same sort of regatory structures or or how do you think about adoption as a as a key
3:28Yeah, I I I think you you want to have a lean forward try new technologies approach to new technologies otherwise as opposed to be somewhat stuck in the past. Um naturally new technologies need need to be need some encouragement and and uh I I think should be embraced. Um we are going to see and are seeing in fact significant productivity gains from artificial intelligence. Um and and
3:57we'll see very dramatic gains in productivity from robotics. Um you know things like the Tesla self-driving car is going to be a tremendous boon or is a tremendous tremendous boon already um to users. Um and and and I think humanoid robotics will be just an incredible change. I I think just to give you some sense of scale here, I think the um I I think AI will probably
4:27increase the global economy by 20 to 30%. That's my rough rough estimate. Um meaning on the order of 20 to30 trillion per year. um and and AI will be able to do anything digital, anything that does not require shaping of atoms by hand um probably by the end of next year.
4:49So, as as I'm sure people know, uh AI is already incredibly good at software. Um and it it's getting to the point where AI won't just be good at software, it'll be what I call Stockfish level good. So, Stockfish is a chess program that can beat the world's best chess players very easily. In fact, at this point, you could run Stockfish on your phone and beat Magnus Carson at chess. So, uh at
5:19some at some point next year is my prediction. Uh software will be so good, AI software will be so good that it will be Stockfish level good. Meaning that it is impossible for a human to compete um in writing software uh with AI. But like a AI will just crush all humans at software and I think it will it will be uh extremely good possibly stock level but but certainly extremely good at all forms of of engineering and
5:46anything digital uh literally in 12 12 to 18 months.
5:53I one of the so actually let me add just one one more thing to my apologies. um the the so 20 30% increase of total global economy. So this is quite a lot of prosperity we're talking about here um uh just just from digital AI but from robotics uh from um from humanoid basically think of it like a general purpose robot robot AI I think we'll see many multiples of the global economy meaning like you you can
6:22increase the economy by a factor of 10 or more These are mindboggling numbers.
6:29Yeah, I was just about to say that. I [clears throat] mean, one of the stats we gave to the group here was that um in the four years since sort of chat GBT was launched, I think we there's, you know, over a billion people around the world already using AI. There's been very quick uptake around around the country on around the world on that. I guess a question to you is I think a lot of people think about sort of the the next chapter being in this sort of applied or or sort of physical AI. Where where do you see sort of robotics trending? How quickly is it going to be implemented? I think I remember in the first Trump administration we were talking about sort of automated
6:59factories and now we're a year later 10 years later. So how how you know how quickly do you think these these changes are happening in the sort of physical AI world?
7:08Yeah. So so anything physical always takes longer than anything which is digital digital you know it's when you solve something digitally it's just software that you can easily copy across other other computers. Um when it's physical you've got to build up an entire massive supply chain. you've got to you've got to move a lot of lot of atoms. Um all and and supply chains are very much global at this point. So that's why it takes longer. Nonetheless, um, when you think of humanoid robotics,
7:35the way the the way to think about it, I I think the right framework is to consider that the usefulness of a humanoid robot, a general purpose robot, is going to be um roughly the uh digital the the AI software, how good is the AI software times how good is the uh AI chip in the robot times how good is the electromechanical dexterity, especially of the hands. Um now all three of those things are improving exponentially. Um and and the usefulness of the robot is
8:05those those three things multiplied by each other. Then when you make the robots the robots will um um the robots will start manufacturing the robots. So you get a recursive effect. So it it starts off very very slowly but then grows um at an explosive rate. Um so if you you say like 10 years from now I would say there are well over a billion humanoid robots.
8:34Um and the productivity per robot will be probably five times that of a human.
8:42Meaning meaning that the productivity in 10 years of humanoid robots and I think this is a conservative estimate by the way. Um, this is this is one I I'd be would be willing to to put serious money betting on. Um, that there will be at least a billion robots in 10 years and that those robots will be at least five times the output of a human. Meaning the the billion humanoid robots will will um be more productive than all humans combined.
9:12Wow. Um, shifting gears just a little bit to to to a question that's kind of facing the US today. um you know, data centers have been a big political issue over the over the last um 6 to8 months here in the United States. And I think there's a general understanding that um in order to to drive and power the the the AI revolution that's coming, we need to have the the electricity um and the data center uh compute capacity um to to do the training and the inference of of
9:41all this AI. Um you know, how how do how do you think about this particular issue? um where where are we on the on the curve of of kind of how much we built versus how much we need? And as government leaders here think about how to prepare their economies and and build the right power and data infrastructure, how should they be thinking about where sort of compute and power needs are going to be in the in the next few years?
10:04Well, there actually is a quite a crisis of power. So the this this is a in fact this is something if if you um just if you just sort of follow the AI topic on the X platform um which by the way is is where almost all of the AI discourse takes place. Um you you I think you get a very good sense for where things are headed. Um so that's how that's how I get my news and it's it's incredibly good. Everyone who's
10:34anyone in AI posts on X. Um so so so that's why I'd recommend like just just just go on the AI AI AI topic on X and you'll you'll understand all these these things and get a a day dayby-day account of things. The the uh and and and what the consensus is at this point is that the there will be a significant power shortfall uh uh next year. So not like distant future. uh there's expected to be I believe I believe the the consensus
11:02estimate among analysts that uh follows the AI space very closely is that there will be at least a a 15 gawatt uh shortfall of power uh in 2027 for AI chips. So this is perhaps um an obvious uh thing that one would expect to occur because the rate at which AI chips is being produced is is uh has been rising incredibly rapidly. They're sort of rising on the order of 40 40 to 50% a
11:32year. But the but the power available outside of China has been rising at like 10 to 20% a year. So obviously the the faster rising thing will will eventually overwhelm the slower rising thing. And so um the in fact even I'd say at this point there there there are challenges with power even before next year which is why uh Google and Anthropic and many other companies are actually leasing compute from SpaceX
12:00um because we've been able to turn on um AI better than anyone else so far but this is by by constructing our own power plants is the only way we were able to do it. Um so now now China does have a tremendous amount of electricity but but but uh due to GPU export bands one cannot uh you know establish data centers with the latest chips in China.
12:24So so but so really the consideration is what what sort of electricity growth is there outside of China. Um and that is a currently a significant shortfall relative to AI chip production. So there is this this creates an opportunity I think for countries around the world to to to save to to to sort of if they're interested in AI data centers um to to to construct uh a lot of power um and uh
12:53and offer that to uh AI companies um and in exchange of course the these AI data centers would be would be taxed and and have to pay you know reasonable fees and stuff. Uh but it does create an opportunity for for a lot of countries.
13:08Absolutely. Well, thank you so much for your time. It meant a lot that you could join us here and uh really appreciate it. Thank you so much.
13:15You're most welcome. Thank you.