Limitless: An AI Podcast - Robot Olympics 2026: China's Robots Just Broke Human World Records

Episode Date: August 26, 2026

We discuss the World Humanoid Olympics in China, where humanoid robots competed in human-style events and set new performance marks. We also cover autonomy, reward-based training, and the comparison between China and the U.S. in robotics and AI.------🔒 Check Out Our Sponsor: LEDGER AGENT STACK 🔒https://developers.ledger.com/docs/ai-tools/overview/?utm_source=Audio&utm_medium=Podcasts&utm_campaign=Limitless------🌌 LIMITLESS HQ ⬇️NEWSLETTER:    https://limitlessft.substack.com/FOLLOW ON X:   https://x.com/LimitlessFTSPOTIFY:             https://open.spotify.com/show/5oV29YUL8AzzwXkxEXlRMQAPPLE:                 https://podcasts.apple.com/us/podcast/limitless-podcast/id1813210890RSS FEED:           https://limitlessft.substack.com/------TIMESTAMPS0:00 Robot Olympics1:45 Record-Breaking8:07 How Robots Learned9:30 China’s AI Advantage13:17 Tiangong Takes Lead16:03 Subsidies and Scale20:11 Tesla vs China24:57 Real Benchmark26:29 Closing------RESOURCESJosh: https://x.com/JoshKaleEjaaz: https://x.com/cryptopunk7213------Not financial or tax advice. See our investment disclosures here:https://www.bankless.com/disclosures⁠Josh works with Anthropic as a contractor. All views expressed are his own and do not represent Anthropic, its leadership, or its affiliates. Nothing in this episode is investment advice.

26 years ago, a human athlete ran the 1,500 meter race in 3 minutes and 26 seconds. And ever since then, the record had never been beaten. We've had seven Olympics, the latest Nike running shoes, and no one has been able to beat it. But over the weekend, a humanoid robot out of China crushed it in 2 minutes and 21 seconds. This was the World Humanoid Olympics that was hosted in China over five days, and these robots are crushing human-based Olympic events. They ran a faster 100 meter than Usain Bolt. They jumped higher than the Olympic record,

and they broke 1,500 meter and the 400-meter racers. We're talking about 2,000 robots from over 16 countries that competed in 55 Olympic events. These are the same events that humans compete every four years. And the contrast between last year's Robot Olympics and this year's is vastly different. And we're going to get into all of that on today's episode. This is a visual episode where like, if you're not watching, you're probably going to want to watch these videos because they're insane.

This is also a funny episode because one year ago, we actually filmed the first annual Robot Olympics. We were here now for our second annual, pretty much any event on the show. You're around the sun. To talk about this, I mean, dude, just look at the visual of this on screen. This looks like it's AI generated, but it is not AI generated. What we're seeing run across the screen is an army of robots that are perfectly in sync. For this event, the scale is huge. I think the total amount of robots competing is up 300% year over year, and the amount of teams

is up like 200% year over year. And the most interesting statistic is 96% of all the robots that competed in this Olympics are all Chinese made. This is the China event. And it's kind of sad because I was looking at humanoid robots from the US and I was like, oh boy, we might just be cooked. So for the records, I'm just going to just list off a couple that are kind of unbelievable. And then we'll get into the videos of how they actually did it.

The first is the 100 meter gold. That is like the flagship race that everyone kind of denominates in. And that is the one where Usain Bolt famously is the human world record. He ran it in 9.58 seconds. The robot ran it in 9.39 seconds. And oh my God, look at this video. It's terrifying. Could you imagine a robot running at you that fast?

No. And also look how tall these things are. I could have sworn that these robots are meant to be like waist height. They were certainly like last year when they were competing. This thing is like six foot three. to six foot five. These things are huge. Oh, you see the crash pad over here as well where they just kind of like slat into it.

I find it funny how, yeah, they crash and they just die. Like they just turn off and then they have to get dragged off in cards. They're coming carsy, one and done. It's nuts. The next one that was kind of crazy is the standing high jump, which was above the human record. They cleared 2.8 meters, 2.88 meters, almost 9 meters. The 1,500 meter race, the Tianangang Ultra is what they call it, was 2 minutes and 21 seconds.

against a human world record of three minutes and 26 seconds, which was untouched since 1998. And the robot, most interestingly, these aren't human controlled. It ran fully autonomously with zero human intervention. So I think all of these things, as we go through the videos from this event, yeah, here's the robot running 14.5 miles per hour just running into the barricade. It's the first time that feels scary. And I remember we did this episode a year ago. And I was like, okay, robots are kind of a joke. Like they don't actually look like they are doing anything effective.

They're not running that fast. They're kind of falling apart and collapsing. Similar things were happening this year, but we're seeing some serious upgrades year every year. And if we continue this trajectory, even one year in the future, that leaves us with a pretty unnerving reality with how capable these robots are going to be.

Yeah, I mean, I remember last year's Olympics and just so that you guys have an understanding in how advanced these robots have become in a very short period of time, specifically in China. last year, the 100 meter time, the winning robot ran it in 21.5 seconds. That's like more than double the world record that Usain Bolt held. And now in less than a year, because it has been less than a year, they crushed Usain Bolt's record. So what's that going to be next year when these robots' arms aren't flailing in a crazy way

and they're way more dynamically efficient, they're going to crush it even more. And so I think the realization that struck to me is, this is, to your point, no longer a joke. the Chinese are very advanced in hardware. We were talking about this before we started recording, but hardware and manufacturing has been their kind of mecca over the last couple of decades at this point, and they have completely beaten the US. When I'm looking at the figure robots in the US

or any kind of robots, Amazon delivery robots, I'm just like China is way more advanced. And for humanoid specifically, because this is the other thing, right? It's like, why would these events kind of like matter to us at all? It's because they're human-looking, robots competing in human-based events. Like, look, and we're not just talking about, you know, track and field events. We're talking about, like, football. We're talking about, like, tennis. Like, I think in this one, there's a crazy penalty. Josh, I want to show you this in one second.

So a yellow card on the robot, and again, if you're not watching this, I urge you to. And so he lines up for a peno. Drain's it. Absolutely drains it. So the point is, these robots are no longer toys and we saw the famous Chinese robot lab Unitree IPO last week and their stock is up 650 and that wasn't like a pump or dump, it's still up around 4 to 500%. So there's obviously a demand for these robots. These robots are very much at the research phase until this event, which tied in with a very important conference, I think it was like the World Robotics Conference or something like that, where the pitch was essentially, these robots are now physically able to do a lot of complex things that humans are able to do and you can now apply this to various

different industries and the sports and athletics feed is just one example of that. There's one thing that I wanted to highlight that I found extremely interesting from this because one of the new rules that happened this year is that if it's a flat event, meaning like if the robot is on a flat surface, it must be fully autonomous. And this is true for the relay races, this is true for anything on these flat surfaces. And what we noticed this year was a property that a lot of people laughed at, which is this robot, you doesn't know you saw it running with its arms, waving, like, flailing crazy. And this is the best of this robot.

We have a video that we could show them. Of course. So look at that robot. Look at how they're running with their arms flailing side to side. And I thought this was funny and goofy until I realized that this was actually an emergent property of machine learning. And this was not trained into the robot. This was understood and emerged from what yielded the best results.

And it turns out that the robots are getting smart enough where they can kind of self-recursively loop themselves and come to terms with the idea that this is the optimal strategy. And when I look at this, I'm laughing because this is kind of what evolution developed as a tail for a lot of animals that were running around. Like a lot of these large animals that run fast, they need a tail as a counterbalance. They don't fall over. These humanoid robots now are running with their arms flowing back and forth as a mechanism for balancing. And I wonder, I wonder, if this is some sort of Move 37 from Go, if you remember, there was like Google's deep mind computer, it was competing against a human. And on Move 37, it did this like crazy, unbelievable move that no one

expected, no one understood why, but it turned out to be genius because it was thinking so far in advance. I wonder what types of emergent properties will get and we'll learn about the human body through this. Like, perhaps what if Usain Bolt spent his whole life training to run and training to run like this instead of with his arm straight forward? Like, would that turn into a superhuman runner that's even faster? I don't know, but I find this really fascinating that humans are kind of, or humanoid robots are kind of relearning human movement principles from first principles. And the results of that are going to be pretty interesting as we continue to watch these evolve. Like, how are they going to move in a different way than us? If so, and this is one of

the examples I thought it was like super interesting, really bizarre and funny. But on the inside, like very technically interesting. It's like, oh, they created their own tail. That's kind of cool. When I look at this, it seems like it's in a perpetual state of falling. Like, it's about to stumble, but it just gets in front of it just at the right time. Now, the story behind this is actually interesting. Just kind of like unpack it a bit more. The makers of this robot in particular that crushed the 400-meter record, a human record, is called Tian Gong. And the engineers actually had no idea how to teach this robot to run fast.

So they started off with the human movement, which is we swing our arms back and forth, right? It propels us forward. And so they built a robot that did exactly that. And they realized that this was incredibly inefficient for their robot. Its rotator cuff, its shoulder started getting really heated, and it ended up exploding. So its arms would literally fall off in the test case when they had a robot that would run like a human. So they didn't know they was crushing their heads. They were like, how on earth do we figure out how to make this robot run super fast autonomously?

And so it just gave the robot model that was in its brain the task and said, I will give you more rewards if you figure out how to run faster. Your goal is to get to the finish line as quick as you can. And the robot started doing this. It started swinging its arm from side to side, which basically makes. mimicked the swinging your arms back and forth forwards as you're running normally like a human, but it had less resistance on the shoulder rotator cuff. So it figured it out on itself independently, and this might be a more uniform way of running. I can't speak on behalf of humans, but certainly for robots, it ran the fastest time it has ever run. Now, I saw another stat that

was super interesting. 70% of AI tokens that are used in China are apparently used for video models specifically. And a large chunk of that is for robot models. So when we look at this and we're wondering, how on earth is China, like, you know, usurp the US? How have they, like, become so advanced in such a short amount of time? It's because they're spent the majority of their AI tokens and research development on video models specifically. And we see this with, like, the text of video models that we've seen outside of this that we've talked about on the show on various other episodes. They are far superior than the US-based labs. And so this makes sense, like when it comes to the world of world models and robotic brains. It just has, they have a, they have us on visual intelligence

is what I'm realizing as I'm watching more and more of these videos. One thing that I did want to show I just sent you a post if you don't mind pulling it up. Yes. Because I thought this was so funny too. This is what an earlier version of this emergence of understanding human movement looked like. This was an early Google deep mind project. And what they did is they gave this like figure human properties, but didn't teach it how to walk. And you can see it slowly learning over time how to move its joints and its body to figure out how to actually get from point A to point B, using a reward system that you just described, which is like, if you can get to this place, you will be rewarded to figure out how to get there. And you see it like really, really like weird because it is

like a humanoid looking thing. And what we're seeing today is not only the evolution of this early technology that we saw at Google DeepMind, but the iterative improvement so much so that it actually has a physical body to live with it. When I think about the next evolution of, or the next phase of this like general evolution, as we get. greater intelligence, naturally the hope is to embody that intelligence, to put it into these physical objects that are going to be moving physical atoms around. This is the next thing. It's much more difficult because we have to manufacture things. We're not the best of manufacturing things. But in the case that we are competing head to head with China on manufacturing things

and applying AI to it, I see no world in which we stand a chance. And that's a kind of scary place to be because like 96% of these robots that competed are Chinese. And when I look at American They're different. They're different. They're more general purpose. It's much more technically challenging. They suck. But they currently do suck.

Like, it's funny, I was scrolling my feet. We were talking about this yesterday. Look, even this robot's head is down. Look at this, Josh. Like at the start, look at the start. Look at it. It's just so sad. He watched the robot Olympics.

So I'm scrolling my feet. I'm seeing these robots doing like backflips. They're running 20 miles an hour. They're like doing high jumps. They're doing these unbelievable things. And then Brett Adcock from Figer, who is a humanoid robot maker. He's sharing like just robots kind of walking around campus slowly.

And he shared a video of like a robot slowly walking up a staircase. Yeah, this one. He's like, look, guys, he climbed like 15 feet of stairs. And I'm like, man, I understand these are different robots. I understand this is a general purpose robot that can do a lot of things. But just on a purely optical basis, when you look at the videos from the Olympics versus when you're looking at the videos from this, you're like, man, we got a long way to go. And not only that, but we have what, two, maybe three companies here in the U.S. that are doing it. We have figure. We have Tesla. Maybe there's like Boston Dynamics. China, everyone's doing this.

There is like no specific company that is taking the lead. Everyone's building these unbelievable robots. Assuming that this progress continues, next year is going to look freaking crazy. Like I cannot imagine they're probably going to need a bigger arena because I'm sure the robots are going to very quickly outgrow this like small confined space originally meant for humans. This was taking place in the Olympic Stadium that is used for humans traditionally. I think it's like the 200 meter lap race or whatever it is. But really like unbelievable rate of progress and like kind of a scary thing. to see knowing that none of those robots belong to us.

So what I'm looking at this, I'm thinking, okay, we know China is obviously very advanced compared to the US, but which companies in particular in China? Are they private? Are they public? Like, what's so special about them? What are the name brands that we need to kind of like bring ourselves to be aware of? The winner, the winning brand is this company called Tian Gong. I don't know if I'm pronouncing that correctly, but Tian Gong.

And it's basically a startup from Beijing, China. And no one kind of like knew about their name very well. outside of China at least. I think the name brand was basically Unitary, which placed second across all the medals that were won so far. Remember, it's still going on as you're listening to this right now. You can probably catch the live stream. But Tian Gong, it's a small startup, and they crushed it at the 400 meter, as well as a number of other track events. And the reason why they're getting a lot of the glory right now is, to your earlier point, any kind of flat surface events had to be completely autonomous. So there was no human controller at all. So it's a much harder feat to teach or

train an AI robot to basically run around a track or kind of like maneuver around a various different obstacle courses. And Tian Gong had the best AI model paired with their hardware, right? So it was very kind of like pliable. Now, when you look at Unitri, Unitri is the name brand that I mentioned earlier. That IPO last week and their stock is up like something like 600%. And I think they're valued at like $55 billion, where they initially IPOed at like $2 billion. So you're seeing these crazy multiple returns in China as a recent.

And it's not just in robotics. It's happening in the semiconductor space with memory stuff. I think they have the CXMT, IPO. China's having a bit of a moment with their AI models and with their robotic side of things. And I just want to spend a quick moment kind of describing what those conjectures sort of look like. On the AI model side of things, they have kept up in open source. And now they're kind of putting out models that are competing on the frontier. There's this model. I don't know if you've seen it being tested recently, Josh. It's called Ox Alpha, and many people think that it's meant to be GLM's next model, 5.3, and it's a flash model. Stay tuned for that episode once we know. It's going to be a banging episode, hopefully, once they officially release it.

But that is competing at the level of a Fable 5 or a GPD 5.16 salt, and it's a hell of a lot cheaper. So somehow Chinese have been able to keep up on the software model side, but if you flip over to the hardware side, which it is my strong belief, is going to be the next kind of phase of frontier of AI. We're talking about world models, visual intelligence, all that kind of stuff. We see a flow where China actually might have the more advanced models and advanced hardware and the scale to pump these robots out. Remember, China has, I think, something ridiculous, like five times more robots. Oh, they produced five times more robots than the US did in all of 2025. And that's scaling on an exponential curve where the US just can't compete.

Right now, it's just like two startups. So China's having a bit of a moment, and it's something that we need to keep an eye on, both from an investment perspective, but also from, like, protecting the frontier if the West wants to stay ahead of, you know, they made adversaries. And it also feels like it's private industry versus the government in the U.S. versus China. Like, this is interesting. Yeah.

The Beijing government, they poured $20 billion in subsidies into the sector over just the last year alone. And reportedly is planning a one trillion yuan fund. I'm not sure exactly what that translates to. But that is like a tremendous amount of money that they're putting towards these companies to push the frontier forward. And this is, in a way, China's advantage where they are able to just force progress by any means necessary. We've seen this many instances with frontier AI labs where they will just subsidize price, or even prior to AI, if there is a competing product from China and a competing product from the United States, what they would do is the Chinese government

would step in. They're going to say, hey, we're going to subsidize you. We're going to make the cost lower so that you can outcompete everyone else. The entire market will go to you. And then we'll gradually raise the prices up. But they're willing to step in and put their hand on the scale to make meaningful change in the progress of a specific division. And it's very clear that robots is one of their top priorities. And this is interesting. It's happened in the past around manufacturing. I know China has this like requirement for a lot of ships where when they're made, they must be made to a size in which you could fit a tank on top of them. Like you need to be able to roll a tank on top of your boat for it to be classified as a specific type of boat that

you could then go off and build and use and get permits for because they they're thinking in this like almost military sense and they have the control over everyone where they can do that. So I think it's really interesting to see the dynamics of kind of like private government versus public industry at play here in the US versus China. And so far like capitalism kicking ass. But man, like China with their subsidies and their ability to manufacture things at scale, it seems like a legitimate concern. And sure, a lot of this is staged. A lot of the software is like like pre-coded, but the robots are real. Like, those things are real.

They're produced at scale. They're doing the flips. They're running the things. And they're getting better much faster. So if we gauge this on a rate of progress, which is all we can ever do, year over year, I'd say they're up like, what is this? A 10x? I remember last year, as we were sitting here talking about this, it was mostly a joke.

We were just kind of laughing like, how look at that robot like falling, sparks flying everywhere, just like dropping dead and totally blanking out. But this year, it is a very different story. And like next year, man, you've got to imagine it's just going to be even more. slightly deranged than this. I'm not even sure how much of this year's robots were hard-coded. Like when I look at that 400-meter race and that robot kind of developed that weird sideways swinging movement by itself, I think like, wow, okay, so next year's robots are probably going to come up with completely new performance ways that humans probably could learn from at the actual human Olympics.

So I'm curious how that develops. But your point around kind of like having a nation-state influence and dictate how a certain technology progresses, in this case, robotics. It has had meaningful impact. And listen, like on the West, when I compare it, right, we are arguing to ban data centers almost everywhere, in every single state in the US at least, right? And that is going to hinder progress in massive ways. And listen, some of the reasoning is very valid around electricity concerns,

but I know that a lot of the AI labs are taking very meaningful steps to subsidize that and also pay a much larger tax so that it goes to the local community so they can get much more benefits from this kind of stuff. But there's a lot of pushback. The general feel and vibe in the Western front,

or I'll speak for the US, is AI is bad. It consumes a lot of water. It is bad for humans. It is taking our jobs. It is replacing us. And I'm not saying that's right or wrong, but when you compare that to China,

which is so AI forward, it's just so robotics forward, they are obviously going to get the leap on us. The US government comparatively is like, hmm, should we ban open models? Should we ban some of these other front tier AI models in China. Meanwhile, is like, we're going to do anything and everything to get ahead of this space because we know it's going to be incredibly transformative technology and we'll make it safe when we can.

I don't know what the right path is forwards, but we are going to see a stark contrast over the next year, is my guess, if the two countries don't change their kind of ideological views on how this pans out. What I would like to see, Josh, next year, is Tesla Optimus compete in this. I'm sure, or I know. Oh, this is so sick. Elon Musk is looking at this and thinking, I think I have a card up my sleeve and I can do this. So I'm hoping that the Chinese Olympics, robot Olympics will be open to taking a Tesla Optimus because I kind of want to see how badass it is compared to it. Now, China, granted, has all the data and information

that is required to train frontier robotics. If you look at any of the hardware components, like the actuators, rotator cuffs, they produce the majority of it. I think actually Tesla Optimus sources are bunch of this from China. But I want to see the Western Front kind of like compete on this because right now, this feels like the GPT3 moment, where China had nothing and American had all the frontier AI models, but swapped the other way around.

As you're saying that, I'm like, man, why is it China versus Elon? Why is it not China versus US? Why do we only have Elon and Optimus to put up against him? Maybe the figure robots. It is also important to note to play both sides of the coin here that the United States is trying very different strategies than China in the most cases. Like Optimus and the figure robots are general purpose, humanoid robots that are met for very different use cases than the ones that we're watching

on screen today. The ones on screen today are very narrow purpose. They're built for a singular specific thing, whether it be racing. All these things are within a closed loop system. So we're seeing pickleball so crazy too. How long do you think, uh, or is this tennis? I can't even. That's tennis. How long do you think until a robot can like, you just, I know you play a paddle all the time? Yes. What would you give the overrun, like say two years before a robot can kick your Well, I mean, I would probably give it two, maybe three years. That seems fair. Look at how, okay, right now, this is like the equivalent of me laughing at this, right?

Because it looks like there's a young kid playing tennis over here. But I said that last year for all the track events. And now they've beaten the world record. So if I assume in a year's time, this is going to beat like, say, Carlos Alcaraz or Djokovic, then, yeah, actually, maybe even a year. It could happen. It could happen. It could happen.

And the thing with these systems is, like, humanoids that we're trying to build at Tesla or figure, those need to work for the real world. Those need to be trained on everything because they need to be prepared for the unknown variables that occur on a day-to-day basis that no computer can really predict. What these are doing is they're being trained on very narrow focused versions of that. So, like, this is a ping-pong trained robot. This ping-pong robot cannot go and play tennis. It cannot go run the 100-meter dash and win gold. It is specific for this one use case. and it's very cool to see, but it is just a totally different strategy.

And when I think about where value is going to be derived from humanoid, it's certainly across, or from just like robots in general, it's certainly across the stack. But a general purpose humanoid who can do useful productive tasks is going to generally be more productive than a humanoid that can like kick. Oh my God. Did you see that? Do you see that?

That's great. Can you really? Let me rewind that for everyone. Yeah, for those of you listening, this is like a full 360 round has to kick and kicked the robot's head off. This is not. AI. This is completely real. Imagine you're like walking out, you're like walking out of a bar or something and a robot starts picking a fight with you. And then hitting the emotes. The full night emotes? Look at this.

It's so insane. I do appreciate that they're having fun with it. Yeah. But yeah, like that that's it. That's happening. Like that is the robot Olympics summed up is like it's scary. Like robots don't suck anymore. Robots are clearly the future. They're clearly being produced at scale and they're clearly finding these emergent properties of human beings that we have not even considered to try yet. And like, this is so cool. If anything, just a really fun visual event, I really enjoyed scrolling this weekend, seeing all the videos from it and just kind of watching in awe at how much progress they've made just in the last 12 months. It's pretty sick. And what's also sick is agents, because if you are not fully operating humanoid robots, chances are you're running agentic robots.

And security is a fairly big concern when you're working with agents. And we have a solution for that, which comes in the form of ledger, our friends and sponsor of the show. If you are building with AI agents, you are probably worried about security. Ledger has an agent stack that fixes this. It does it in three steps. The agent proposes, the humans approve, the Ledger signer enforces. And it comes with this entire stack of software that's open source, fully available, and helpful for you to navigate your security concerns as it relates to engaging with agents.

It works with Cloud Code, Codex, cursor, basically anywhere that you integrate and work with AI, and it's fully open source and linked in the description below. So if you are in need of security for agents, go check out Ledger. And thank you to Ledger for sponsoring this part of the episode. And with that, I think we have described the Robot Olympics. The great part about just seeing these robots perform, like, people might think this is, like, novel and, like, kind of stupid. But it is sort of a real physical benchmark. Like, you can't game this benchmark.

This isn't, like, an AI model that kind of, like, fakes its scores and kind of, like, scores really well against some kind of, like, arbitrary exam. Where you can kind of see the answer sheet. This is, if a robot can jump high enough, you're going to be able to see it. If he can kick a free throw or penalty and hit a sue afterwards, hell yeah, it can do that as well. Like, the point is, I like that with robots in particular, there is no kind of like hidden in plain sight type of thing. If a robot is good, you'll be able to see it performing as well as it can. And I think China right now, if I was to summarize, is taking the number one spot from the US and it's the US position to respond to. And two, it's broken a number of the human Olympic records.

Again, just to recap, 1500 meter record is now owned by a humanoid robot. The 100 meter record, you say, Oh, sorry, goodbye, mate. Like, it's owned by Tian Gong, right? 400 meter, sorry, it's owned by a robot that runs like this with its arm swinging side to side. They're taking over, man.

But they're taking over, right? Now, imagine if you retrofit a robot that is as agile as this to your manufacturing plant or to a factory or to any kind of manual labor job. If it can do this, It can probably do some simple kind of movement, such as packaging and stuff like that. And my expectation is this is just the chaser. This is the advertising to say, hey, don't you think we're cool?

Like, now let's have a serious business chat around like, oh, these robots can do for you. And so, yeah, it's fun and novel, but I think we're going to see some real progress in robotics going forward. And I am pumped to see it. So if you have listened to this episode, that is the robotics download. There's anything and everything you need to know in the last year. China is winning very effectively. If you're listening to this on YouTube, Spotify,

or wherever you're listening to, please give us a thumbs up, leave us a comment. It helps us out massively. We read every single comment. There are a lot of newbies, Josh. I think there's like 1,500 over the last couple of weeks. Welcome to the party.

It is lovely to have you here. We post around four times a week. We love talking about AI robotics and any kind of frontier tech. If there's anything that we've missed over the last couple of weeks that you think we should include, let us know, reach out to us on our personal profiles.

Josh, any final concluding thoughts? Yeah, don't forget to share with a friend who you want to terrify. Like, share, you know what? You know who you could share it with is like, there's a lot of people who, like, they kind of still use AI as like a Google search and they're not really sure about what's going on. Just send him a video from the Humanoid Olympics. Be like, listen, this is where we're at.

It's a lot farther along than you think. And maybe he'll give him a little scare before the end of day. But yeah, it's nuts. It's nuts. So we're going to be following along with that as well as all of the other fun and exciting topics on the frontier of technology. AI and thank you just so much for being here with us for the journey. So with that, we'll see you guys on the next one.