This Week in Startups - $2.5B Chip Heist, The Future of American AI, and Purpose-Built Robots | This Week in AI Ep 6

Episode Date: March 25, 2026

This Week in AI sneak peak! If you enjoy the episode find us on Spotify, Apple podcasts and YouTube by looking up "This Week in AI" or by going to thisweekinai.aiThis week Jason sat down with Jake Loosararian and Chris Lattner on Episode 6 of This Week in AI. Jake is the CEO and co-founder of Gecko Robotics, a company deploying purpose-built robots and AI for mission-critical infrastructure inspection across energy, defense, and manufacturing. Chris is the CEO and co-founder of Modular, building a universal software layer that lets developers run AI models across Nvidia, AMD, and Apple silicon without being locked into any single hardware vendor.We explore the GPU shortage, why China's chip smuggling reveals the stakes of the AI cold war, how purpose-built robotics are beating humanoids on ROI, the case for American reindustrialization, and why the next decade could be the best ever for private equity in capital-intensive industries.Purpose-Built Robots vs. Humanoids: Jake has been building mission-critical robots for 13 years. He explains why general-purpose humanoids still have too little ROI for industrial use, and why specialized robots that find and fix problems are winning in the field.The GPU Shortage Is Real: Chris breaks down why you can't just go buy 100 Blackwell chips today, why Nvidia's Cuda creates massive lock-in, and how Modular is building a unified software layer across all major chip architectures.Google TPUs Are the Sleeper: Chris ranks Google as the number one threat to Nvidia's dominance, ahead of Amazon's Trainium and AMD.China's Chip Smuggling & the AI Cold War: A Supermicro co-founder allegedly smuggled $2.5B in Nvidia chips to China using fake serial numbers and a hairdryer. The Best Decade for Private Equity: Jake makes the case that capital-intensive, commoditized infrastructure assets: waste-to-energy, water treatment, old power plants will all generate incredible returns.Self-Driving State of Play: Chris, a former Tesla Autopilot lead, gives his read on Waymo's lead, Tesla's small Austin pilot, and why the real signal is when Tesla starts filing for fully autonomous permits in California.Learn more about Gecko Robotics: https://www.geckorobotics.comLearn more about Modular: https://www.modular.com/This Week In AI is made possible by:*PayPalOpen* - One Platform for all Business: paypalopen.com*Timestamps:*00:00 Welcome & intro to Jake Lu (Gecko Robotics) and Chris Lattner (Modular)01:34 Gecko's 13-year journey & the Cantilever platform05:15 Chris Lattner on Modular: replacing Cuda & unifying AI hardware11:10 Nvidia lock-in, AMD's Rock & why the software stack is broken19:49 The GPU shortage: how real is it?22:13 Who challenges Nvidia? Google TPUs, Amazon Trainium & AMD ranked28:17 China chip smuggling: $2.5B in Nvidia GPUs & the AI cold war37:43 Self-driving update: Waymo, Tesla's Austin pilot & Chris's Tesla history42:20 Figure's humanoid package sorting — real or demo magic?43:47 The best decade for private equity in capital-intensive assets51:04 Reindustrialization, the trades boom & making manufacturing cool58:39 Building tech companies outside Silicon Valley1:06:46 Breaking news: Brett Adcock launches Hark from Figure1:10:15 Closing thoughts: grit over hype, customers over valuationsSubscribe to This Week in AI on Apple: https://thisweekinai.ai/spotifySubscribe to This Week in AI on Spotify: https://thisweekinai.ai/appleThanks for watching!🤖 If you want to stay ahead of the curve on all things AI, make sure to join our community across all platforms:📩 Get the Weekly Newsletter: https://thisweekinai.ai/📺 Subscribe on YouTube: https://www.youtube.com/@ThisWeekinAIPodcast📸 Instagram: https://www.instagram.com/thisweekinaipodcast📱 TikTok: https://www.tiktok.com/@thisweekinaipodcast✖️X: https://x.com/ThisWeeknAIFollow Jason:X: https://twitter.com/JasonFollow Oliver:https://x.com/oliverkorzen

Hey, it's Oliver from This Weekin AI, the brand new podcast from the team at Twist. We're dropping a sneak peek right here in your feed to show you what we've been building. If you enjoy it, join the community at thisweekinA.i.com, or find us on Spotify, Apple Podcasts, or YouTube. AI, I think we'll transform and we'll continue to push the world forward, and it will affect a lot of jobs and people upskill. The question is, what are they upskilling into? Being a CPA and an accountant or a lawyer was considered professional services, not commodity. And here we are in 2026 and we're like the bottom 50% of those jobs are chores that machines can do easily. When you see technology companies saying they're taking on manufacturing in the kind of ways that you see.

You have to understand these sectors have not changed for the most part in the past 40, 50, 60 years. Get robots everywhere. Get AI everywhere. Thanks to our friends at PayPal, the exclusive sponsor for this week in AI. Try the payment and growth platform that's trusted by millions of customers worldwide. PayPal Open. Start growing today at PayPalopoopen.com. All right, everybody, welcome back. It's episode six of This Week in AI. We decided to start a dedicated show just for AI. It's how I meet the smartest people in the world. You can subscribe to this podcast at this week in AI.com. This

week in AI.com. There's a substack as the number one AI podcast in the world. We've got two all-stars here this week. Jake Lucerarian, we've had on the program before. He's a friend of this week in startups and all in. He's the CEO and co-founder of Gecko Robotics. They deploy robots for very specific mission-critical infrastructure products. They're not humanoid robotics, which have become very in vogue all of a sudden, Jake. No, you've been working on purpose-built AI robots for, is it seven or eight years now? If you count the college years, it's been 13 years. But Gecko Robotics is more of a seven, eight-year story, if I'm remembering correct? Yeah, that's about right. And so what's the state of the art now?

Give people an example, or maybe my team can pull up a video from your YouTube channel of how these robots work. People can visually see them here and what they're doing. So here we see Cantilever. That's your B2B product. Walk us through it. That's a software. So basically, actually it's actually been 13 years. I started building this in the college dorm, Jason, which it's been a long time.

You and Michael Dell. I know, I guess so. Hopefully the same outcome. Yeah, hopefully. Yeah, I like to put some money into the funds as well for the kids. But yeah, what you're seeing here is Canyliever. So basically, you know, 13 years ago when I was in college, I thought to myself, man, there has been so many deaths of robotics companies in the world. There's so many important jobs for robots to be able to help out with and solve for. And so, you know, what's this delta? And the base of the delta that I figured out back in

college was this idea of gathering information data, using robotics to help drive better outcomes. It's this whole idea, if you're building robots just to build robots and scaling those, there leads to a commoditized future. And in reality, you're not really delivering on the value that the robots are able to actually gather and collect. So gather the information about the health of the built world was the original idea. Basically, the minority report, but for physical structures and be able to predict a catastrophe before it happens. And then that's begun to build now into this software now that all these robots are feeding information data into the help to optimize how infrastructure performs, how healthy is it, and help drive things like,

how do you make a kilowatt for less BTUs? How do you produce more bills per day with less cost? How do you get a ship at a dry dock faster or manufacture a new vessel in quicker times with higher value, with higher quality and speeds? These are the kind of things that we build robots for. Very specific mission critical. And you started this long before the chat GPT moment. When you were doing it, it was machine learning, you know, on the margins. for this robotics company. So you were predating large language models hitting the fidelity they have now. How has that impacted the business now to have the clawed 4.6s out there, you know, and just all this new Gemini stuff, etc. Yeah, back in the day, I mean, we were just using hobbies, motors and gearboxes, planetary gearboxes. And we were trying to ensure that like we could build robust systems and building them in the environment. And so when Silicon Valley actually was like, you know, put it in a lab, make it autonomous and then launch it. And we just didn't believe, agree with that.

that fundamentally back in the YC days in 2016. But now what's happening is you're beginning to get this super high focus on what's the pragmatic impact of artificial intelligence, especially for the companies like the energy, oiling gas companies, the power companies, the manufacturing companies, the defense and now Department of War are completely looking at how impactful can robotics and information data sets be to actually drive better decisions, outcomes, et cetera. And so what you're, you know, what we've focused on is building robots that actually affect things today, not a painting a vision of five or ten years. And the models are putting a, basically

a huge, a huge, frequent spotlight on the importance of really important, valuable data sets that don't hallucinate, especially with, you know, things that if they do hallucinate, it could cause an explosion and kill people. Yeah, and maintenance is one of those crazy things that people ignore, but have massive impact. All right. And our second guest is Chris Latner. He is the CEO and co-founder of Modular. That you guys build, Chris, a layer that will let you. deploy models on different types of hardware. And that's important why. Maybe explain to the audience. I'm sure you have questions for Jake, too. Yeah, I was totally going to explain to the audience what you're built. I'll happily jump into. No, no, sure. In about one minute after the audience understands

what you do. Totally cool. Yeah, so we're building a software layer that enables people access to lots of hardware. So the obvious problem that we all face is that AI is everywhere, should be running in massive data centers, also on your wrist and everywhere in between. A lot of the world is really consolidated around the InVideo platform, which is really amazing and it's very powerful. But there's a lot of chips from other players too. And what we want is we want more people involved in the ecosystem. We want to make it easier to adopt this technology. We want more hardware vendors in the space.

We want people to have choice. And so that's a deep tech problem. But it really comes between, you know, like enable developers that, you know, are typically thinking about CPUs to get into the GPU era, get into AI that's more customized, build more applications. specific optimizations and use cases and things like this. I think Jake's probably a leader in the space. And why I was going to ask Jake is I was going to ask him, you know, so as, you know, the whole world is discovering robotics. You've been at this for 13 years.

What does it feel like to have a 13 year head start? Well, yeah, the party, the party is jam-packed now with so much funding and folks who are, who are jumping into it. Listen, I think, I think it's, I am so thrilled. I mean, it's just incredible. I mean, I am very excited and optimistic about, you know, what the future will be with robotics and how, in particular, it makes us all focus on the first principles here. The first principles of artificial intelligence, the first principles of how do you actually

build an economy and create this incredible growth and prosperity, you know, for the world. I mean, there's a very optimistic future. The key is being deterministic, though. And I think that's maybe where we're lacking a bit. Determinism as it relates to, you know, making sure that if you cross the bridge and won't collapse or making sure that if you have, you know, you know, right now we have like two, you know, two every five ships are stuck in some dry dock or pierced somewhere, you know, and that's, that really affects like the deterrence and the geopolitics around the world.

Or you have, you know, refineries that are shut down for, you know, months at a time and, and you just have increased costs of energy. I mean, these are all things that robotics deterministically could be focused on improving. And that's why we built, you know, Gecko itself, being very mission-focused robotics to help. help us understand, hey, not all data is important to go gather, hey, not every action is important to solve for. And then more importantly, when you have that paradigm, being able to put human rights to work in high ROI use cases, this is the key. And I think that that's underlying infrastructure on the software side to help guide where is how do you employ robots. And I think

that you see this with, you know, Travis, Travis coming out with Adams.com. I mean, you know, he's basically the manifesto he wrote is just like, hey, that was my manifesto 13 years ago. And he's, That's absolutely right. Chris, when we think about your product, what are the hardware and language model combinations that are emerging this year? We bought a Mac studio, and we've been testing Kimmy. We've also been testing it in the cloud. But having Kimmy K2.5, I guess, is the latest version. We're running that at Apple Silicon with, I don't know if we have 128 gig or 256 gig.

And it's reasonably good. It's not Claude. It's six months, 12 months. behind it. But it is free, essentially. So that's kind of the right price. Claude is expensive at scale with lots of open claw agents. And so what are the combinations that you see most often? Is it people trying to run on Mac Silicon, on Intel, you know, on commodity stuff? Where are the combinations showing up? Yeah, well, so I think GPs have captured the world. And so since the chat GPD moment, GPU has really taken off.

The inference side of it is huge. We currently support Nvidia, AMD, and Apple Silicon. And so those are the three that we currently support and can scale across a number of different variants of those. It's super funny if you look at the consumer side that you're double-clicking on because

Nvidia has the DGX Spark. AMD has like the Strix Halo and other crazy kind of hobbyist pro systems that are cool boxes you can buy. But the chips inside of them are all slightly different. And so I don't know, experience, Jason, but the, uh, getting the stuff set up and actually getting the latest

models can actually be a real pain. And, um, have you ever double-click into why that is? And no, tell us. Yeah. It's a great opportunity, I think, to educate the audience on what the issues here are in terms of compatibility and, and making this easier for consumers or even prosumers. If you lean in and you really get deep into it, um, there's both structural business reasons, but there's also just legacy accents of history reasons. And so the structural business reasons are that it turns out hardware companies don't get along with each other. They all care about their products. Apple, for example, they make great systems.

I'm a veteran. I'm a huge fan of what they do. They don't really get along with Nvidia or AMD or whoever GROC or lots of other people that go out there and build systems. So, of course, they build software for their chips. What that does is that then fragments the entire world on top of it. But developers all want choice. Like you want to be able to run on, like if you get a, Nvidia box or an AMD box or you get somebody else's chip,

you want to be able to run it. But you have to switch to different software stack. And the problem is that there's never been that unifying layer. Everybody just builds on top and builds on top and building up layers and layers of, you know, cool stuff and very interesting capabilities. But it's all kind of duct tape and bailing wire. And so if you could change anything, it breaks.

And so our approach on that is go burn it all down. Go build software that goes and, replaces the software that the hardware vendor uses. And so we love CUDA, for example. We can interoperate with CUDA if you want to, but our native stack replaces CUDA. And that's actually a pretty big deal, because that means that entire stack can now move over and is consistent across different hardware. And this is important for the audience to understand if, you know, CUDA is a language created by Nvidia many years ago. And it kind of creates lock-in, right? I don't know if it's starting as open-source or not. but there is a bunch of lock into the Invidia chip set

if you use Kuda, yeah? It's definitely lock-in. But it's not specific to NVIDIA. AMD has their open-source software stack called Rock M. We can debate whether it's very good or not compared to NVIDs, but it's completely proprietary to AMD chips. And so it's open source, but that doesn't actually help you because the vendor doesn't want their stuff around somebody else's chips.

And the other big problem with all this stuff is that it's not actually that good. I mean, if you go look at this, Kuta, for example, is a shining star of system software for GPUs, but it's 20 years old. Like the entire world has changed five times in that time, right? And so really, this stuff isn't really designed for the modern systems, not designed for Gen. I, it's all like C++ plus and it's not Python.

And so it's like it's coming from a different world. And so what we're doing is we're investing in really rebooting that. And then we bring a lot of benefits both from technology, but also a big open source community and bringing people together and capitalizing new use cases and all this kind of stuff. That's why it's fun. When you're building on modular,

as opposed to using CUDA or the AMD stack, which is rock M? Yeah. Can you attract multiple hardwares on modular? In other words, could I have like an AMD and Nvidia and an Apple hardware and some sort of cluster? All talking to each other? Yeah, all talking to and modular being the layer above it?

Or is it just, hey, use modular and then you could swap it out one for one type situation? Yeah, so you can totally run modular on all three of those. And so you can build heterogeneous systems. And so you get hardware with different kinds that are all talking to each other. This is actually super powerful. If you look at what Nvidia announced last week, so they announced their Vera Rubin-Groch platform

that they're coming out with this fall. Vera is a CPU. GROC is a specialized ASIC, a custom accelerator for AI, and then, of course, they have their GPU. For doing inference, the GROC piece is for doing inference. Your query goes in, yeah. Yeah, exactly. And so the key thing about today's compute, but also very much more the future of compute,

is you get these heterogeneous systems where you have different architectures that are all talking to each other. And you don't want to have to rewrite all your code or your model or your ecosystem every time you want to try something. So being able to scale across that is a huge benefit. It's also, to your point about locking, it gives enterprises choice. Right. And so a lot of people are running on in video, which is fantastic. They have great flops. But they also want choice to be able to adopt other systems as well.

And so even if you're staying on in video, having an amazing experience and good performance and all the things that you want good usability, reliability, all the good stuff that you want on video is fantastic. But then you can scale off and you can go wherever your business takes you. Jake, how do you think about this at Gecko? Because certainly you're going to be facing this increasingly of where you put your investment. Now, you're not building a large language model, I don't think, but you're probably building a lot of proprietary, you know, you certainly have a lot of proprietary important information. so you probably have to be careful where you put it, yeah? 100%. Yes. And I think that, like, there is interesting data set that Gecko has amassed, like being now, like, you know, we have like five or 600,000 assets instead of candle lever critical assets that we have gathered information on using robots and, like, information around those environments as well.

And so there is an interesting data set that no one else does have. But one thing that, you know, you mentioned something, Chris, that was a really astute and interesting. I'd like to double click on. And that's around, you know, hardware companies don't like to play with each other or like they have a hard time playing in the sandbox. Now what's interesting is in the, you know,

in the kind of like industrial or like, you know, let's talk about energy for a second. On the energy sector, you have, you know, typically would have a lot of like point solutions on the hardware side, IoT center companies. You'd have maybe like robotics, drone companies or, you know, you have a, and then you have kind of like a different kinds of awful infrastructure and software that also feed into.

You have, you know, digital officers. You have, you know, very like software focused. And I imagine you have a lot of standards that connect these components. That's correct. And one of the things that's hard for these companies is to understand, like, what's out there. And innovation teams do a really bad job, you know, whether it's like a, you know, the name like them specifically, but like all the top 10, only gas companies, right? And they will pick a solution.

They will maybe invest into a company, you know, through an arm. and then they'll try to leverage and use that. But you'd end up with a robotics or a hardware company in particular is trying to figure out how do I make the big return for the investments that I'm getting. And okay, you have to have some sort of software platform. And then you end up having like a dozen software platforms that all have to be logged into and a dozen different point solutions. And that's not actually what the customer wants.

They just want to be able to make a barrel for less amount. or make more of it for binary. And so, like, it ends up being like, hey, is there, like, something that can just bring solutions and help me be able to evaluate, like, what's actually valuable or not? And so, you know, you kind of have, like, this, like, almost, you know, this environment has been the reason why robotics, hardware companies in particular, I've had a hard time. And then you just don't get, like, the power law returns if you have 10 companies all trying to approach this.

So you have to kind of, like, play this, like, and real game of, like, we'll either acquire everybody or, like, we're going to put this all under lattice. And you know what I mean? And you can only have that happen a few times. Well, but so I mean, when you're building your robots, I assume you have a bunch of AI running locally on the robot. Yeah. Where do you source your chips from?

What does that look like? What are the pain points that you hit? We're processing at the edge. But we're also then just like a massive source information data. And because that information data is, there's relevance in terms of the localization in real time, but there's also like a post processing of the data sets that we're okay doing in the cloud. It doesn't have to be instantaneous.

That's going to become more and more edge forward, especially as we, do more of the not just finding it but fixing it side of this. And that's where obviously it's all headed. Yeah. So the future is you have chips. Right now you have some chips on the edge. I would assume like giving the robot, letting it make decisions in the field. But you can do the review later. Like if you're doing a giant Navy ship, some aircraft carrier or something, you don't, they don't need that information in real time. But if they were going for maintenance where, hey, there's a problem and we want the robot to actually fix it, which I've never heard you're talking about, but is the plan for you to have robots identify a crack or something and then go

weld it as well, like a maintenance droid and stalwart or something? Yeah, you're exactly right. I mean, it's always kind of been for me, there's a, you know, atoms to bits. We hear that talked about a lot. Yeah. But then there's actually a back to atoms. And that's really where the impact comes from. And the large unlock, too.

I mean, it's, you know, you want to be able to be the best in the world at understanding material science and the physics behind that, you know, as a data collector of all this, you know, all this critical infrastructure data and material data and physics data. And then it's just like, okay, now that I understand all these different use cases, materials, environments, metadata around like what kind of conditions, you know, how much so, how much, you know, how humans the air, like all that kind of information is very useful as it begins to lead towards taking action on how to fix and replace repair. we want to live in a world where infrastructure that we rely on every single day is not down unless you absolutely need it and want it to be we shouldn't have a maintenance cycles that should not be a thing like there should just be like I'm down like every once in a while I fix the stuff I need to fix but that's like you don't need like a outage twice a year if you're like a thermal facility you don't need like you know these turnarounds that occur multiple times at energy facility I mean these are incredible amounts of money and environmentally, it's horrible. It's horrible to stop stuff

and then turn it back on, just like when you accelerate in a car. It's like bad, that's bad environmentally. And just like, just so many reasons. Bad for the, you know, that's when like you typically have like things breaks when you stop and start it. So that's, that's what we're building. And in order to do that, you also need to fix stuff, you know, after you find it. And so, yeah, absolutely. And that's, that's even what we're doing on the shipbuilding side right now. Let's talk about the shortage in chips. Chris, is there a shortage like we're hearing about? Is that marketing?

Obviously, you have a bunch of players doing custom A6. You're having, you know, Elon talking about his fab, Amazon making their own, Google making their own. Facebook is going to make their own with Broadcom, I believe. So there's like Broadcom as this provider to help people build their own. But those people are obviously, I interviewed Jensen last week on All In. they're obviously trying to keep up. They're making this, you know, complete solution with multiple types of compute on one product. But tell me about the shortage, how real is it, and then about all these new competitors to Nvidia coming to market when they'll land

and what impact they'll have. Yeah. I mean, if you snapshot today, just you go out and try to buy 100 black hole nodes. It's very difficult. There's no supply out there. It's, It's very stocked out for a long time. You have to get many of your commits. They're installing a tremendous amount of compute, but unless you're one of the biggest players, building your own data centers, it's very hard to actually get access to the number of flops

that a lot of people want. Meanwhile, AI is exploding. The agents, all the different, the clause, like all the different use cases are happening. And so everybody wants choice. Now, to your point, there's lots of chips out there. There's the Traneum, there's the Google TPUs. There's lots and lots and lots of chips

from lots of different vendors. But people generally, don't use them. If you're anthropic or something like that, you have one workload. You can put one workload and dedicated team to it, but other people generally haven't done that. Even AMD, it's pretty close architecturally to an Nvidia, but it doesn't have the adoption and the penetration that Nvidia is seeing. Lots of people are building and installing that, but again, it comes back to this software problem. And people want, they want choice, but they also don't want to have two different software stacks. And so if you end up running with a big chunk on Nvidia like

Jake, you guys are. You may want choice, but now are you struggling with like, okay, well, I get choice, but I get two different stacks. I get two different sets of bugs. And my software team has to be twice as big. And how am I going to go manage that? And what if my models change, right? And so this is what we're trying to help with. Who's going to make the biggest dent in Nvidia's dominance? Is it going to be AMD? Is it going to be Google or Amazon making this chips? It does seem like Amazon is making quite an investment in chips. Are they going to? push the industry towards our alternatives? Is it going to be this massive open AI with AMD deal that seemed to have come the week after he Sam announced the big open AI Nvidia deal? And then like,

whatever 10 days later does an AMD one. I think Jensen was a little, um, uh, perturbed, maybe be the right word by that. And so like, yeah, we have the opportunity to invest in open AI. We'll see if we take it. So there's a little bit of back and forth there. But if you had to rank one, two, three, Chris, knowing what you know. Yeah. Who's going to compete with Nvidia? at scale in 2027, 2028, 29. I think the biggest player that most people are still not paying enough attention to is Google. Google is not an AI startup chip company.

They have been building TPUs for seven generations. They are really good at it. They have better scale out than Nvidia does. And so in some dimensions, they're way better already. And they're used at scale, tremendous amount of flops that are available out there. And so they just need to decide what they're doing with their business. And I think Google has an opportunity to add a couple trillion dollars more to its market cap.

So that's Google. And the idea would be they would offer it through GCP as cloud computing resources. Or do you think they eventually sell the TPUs? They're getting more ambitious. And so they're selling it, I think, through fluid stack. And so there's other vendors that are now starting get access to TPUs. I don't know their business strategy, obviously. But if I were at Google, I'd be advocating very strongly for, yeah, let's lean in and let's

make a gigantic business. This is a huge opportunity for them. And they've, you know, earned the right by being years ahead, building the transformer and all these other things, to really lean into that and make that happen. Now, I don't know how that factors into their cloud business. I mean, they sell, rent them out through GCP, but I guess the question is like, why don't we hear about them? Yeah. You know, like, why is that not, you're saying it's kind of like the sleeper. Why is it the sleeper? Yeah, I think they struggle with two things. One is GCP. So for a long time, MTPs were GCP only, and so that just kind of segmented off the market share that they had into GCP.

Now, GCP is doing better, so that's a good thing, and now they're breaking past GCP. And so I think that's a big, bold move for Google, and I think that's huge. The other is that basically nobody can use them. If you're a big lab and you've got a team of 50 people to throw at it, you can use it. But if you're not, then you can't run open source model. You can't run Kimmy K2. You can't run standard models on these devices because two reasons, one of which is that Google has no community. And so there's no developer community out there that's like using them or no hobbyist community, things like this.

But also because Google itself is not investing and building into that. And so they like many of the different massive players in the space, they're building amazing things. I think Gemini is amazing, amazing, amazing. But it's all proprietary. They're not incentivized to actually share anything. they're going to open source their high-performance GPU code or TPU code. And so, like, they're not actually set up to actually catalyze their own platform in that way. And this is one where Kudah is pretty amazing.

This is the NVIDIA software. They've leaned into the community. They've leaned in teaching people. They've leaned into universities. They've really leaned in to getting the technology out there. And that's a huge advantage that NVIDIA has going forward. So this is a huge opportunity, I think, for the whole industry to figure this out. But you have to change the playbook a little bit.

He can't just run the standard mode of operations they've been doing before, and they have to decide is allowing the hardware to sing actually worth doing new things. And I think they'll probably say yes. The thing that's interesting about all this, Jake, is Anthropic, which is a major competitor to Gemini, right? They are the big first, my understanding, and Chris, you would know better, but Anthropic is, I don't want to say, all in on these tensors from these T's, from Google, but they have a significant footprint. And then Google, I believe, is like a quiet shareholder in Anthropic as well. So in typical Silicon Valley fashion, no conflict, no interest.

Like, they're competing with Claude Code, with Claude Co-work, with the Google suite, with Gemini's products. And Gemini, I suppose, is going to have a really good, you know, they're really focusing on writing code or code co-pilots. But yeah, this like TPU thing is super interesting, I think. Who's number two? It's super funny. It's been common on that, yeah.

Yeah, super funny and super confusing to understand like how these companies are related to each other. But Google does everything. Like it makes LLMs, it makes autonomous cars. It makes search and ads. It makes obviously TPUs. It's crazy. And who's number two? Yeah.

So number two, that's a big question. Right. So I would go, it's either between AMD, who is the, it should be number two. too in many ways because they've been working the space for a long time. They've been competing, but it may actually be Amazon. And so Amazon, AWS is obviously massive. They've been leaning into this. Anthropic, for example, also uses the AWS chip. It's called Traneum. And so they're on their third generation. Incredible chip, very big scale. Again, it's not the first chip they're building. And so they've done some iteration. They've optimized

and gotten progress on it. I think, again, just nobody, nobody's aware of it. Nobody uses it. software is just a completely different weird world. And it does, they do have software. It does actually work if you, if you can figure it out. But it's just such a different universe. And again, the customers, they're not going to open source anything. They're the biggest companies in the world. They're all competing with each other. And so the ecosystem is just tiny. And this is, I think, a huge thing holding people back. So Google TPU number one, AMD number two, Amazon, Traneum. And is it infer, I mean, the branding. so like on the nose, but it's infer. It's overly clever. Enfrancia. Inferentialia, yeah.

It's just terrible branding. We get it. It's an infringement. I mean, did they just ask Chachypita name these two products? Like, I feel like they just asked Chachapida, what's a corny name for an inference thing? Inferentia. It sounds like a spell from Harry Potter or something. So what do we think of the ban? I don't know if you saw this, Jake, the ban on chips in China. And then the micro strategy CEO was using, I mean, it's from Super Micro Micro's co-founder, rather, not Micro Strategy, super micros co-founder smuggling $2.5 billion worth of Nvidia chips to China through a middleman. and then they were doing like fake paperwork and using a hair dryer to take off the serial numbers

and replace them or the model numbers. I mean, and then talking about it on social media, there was a video going around where he was talking about it. Any take on the brazen insanity of this, Jake? And people are talking about it in the group chats, obviously. I was actually going to bring this up as a relation to the Department of War. And like, I actually think there's, it's astounding to me that are. budget on the defense bill or the amount of budget going from trying to go from a trillion a year

to 1.5, I'm actually surprised it's not way higher that we're not trying to make it way higher. And why I'm saying this is, you know, it's like little insights like you're just like you're talking about with a, you know, with this story that indicate very clearly that this is an owl out sprint. It's an all out. I don't know if you want to call it a cold war. It is a cold war. it is a cold war, that's what it is. And it's a war that's not exactly that cold either. It's being fought in a lot of different ways than we haven't never seen before.

But this is an example of, look, there is an unleashing, and this stuff doesn't get the light of day unless the government in China is also allowing it, you know, to be exposed to. I think it's kind of just like a, look, we can break the rules, we can go around things. And also, like, you interviewed with Jensen, I mean, you know, it's opening back up

and there's a lot of folks that are looking to buy this. I think there's like, look, you cannot, you cannot regulate this stuff. I mean, it is going to be, you know, just like, just like life will find a way. And like just, it's, you know, Nvidia chips will find a way. It's basically like the idea here. And the A infrastructure is an all-out race. It is a matter of national security. Energy is a matter of national security.

These, like, sectors and industries wars are being fought like around these assets in particular. So I think what I'm saying. We've fought over oil for a hundred years. Oh, my gosh. Yeah. I mean, like, we're fighting. over the chips and the oil. Now we have two things to... We got a few years in the Middle East right now. Like we, we, we, uh, in, in, in UAE in particular, we've, like, I can't comment on the,

the sites that been hit, but just to let you know, like there is, this is all very real for us, I get go. Well, if you, yeah, if you do share it, the UAE government's like, please don't share pictures of Dubai getting hit, a little sensitive to it, which I understand. But what I'm saying from all this is basically just like there needs to be, government needs to be getting way more involved, both in the amount of both the amounts of spend that they have on ships themselves, the amount of independence they have on the compute. This is why I think Chris is probably right as it relates to Amazon over AMD, by the way. I just think there's going to be, you know, there just needs to be a much more aggressive amount of spend, both from a deterrence, but also as it relates to, you know,

if you want to actually supercharge, you know, these companies and not stifle growth, you can, We cannot over-regulate here that we have in the past. We take too much of a historical perspective on regulating these sectors and industries. In reality, all of this is very different. There are not a bunch of historical precedents for what we're seeing right now. And we need to be unleashing and unlocking and having more primes emerge, having more integrations between old primes and new ones that are trying to emerge. And also is becoming way more, you know, way more self-determined on the government side as

Related to leveraging these tools. And I'd be interested as well, Jason, if you, you should have someone on this podcast talking about, how is AI being used in the government? Is there, how much code is being written or being evaluated using these tools? I mean, there's test procedures. These are like, these are like great applications.

I'd love to hear, you know, from the horse's mouth as we allege to, you know, how much impact the tools that we're talking about here are being used with our most important, you know. Apparently, like when we had a. Neil Michael, with that whole kerfuffle, Chris, on All In. I don't know if you saw that interview. Claude was, you know, like a leading provider, and Claude is a leading provider to Palantir, so it's integrated. It's probably the top model right now, or the one that's kind of taken a lead,

all of a sudden leapfrog, Chachypee. So it's definitely being used. I didn't believe the reports that they would use it to pick the targets without a human in the loop. I mean, it could evaluate targets, I guess. I think that would be a fine use of it. Probably a good use, but you would definitely want a human in a loop there. But Chris, what are your thoughts on just broadly export controls? And do we want to really in... Are you on the SAC side? Hey, we want to have our standard be the global standard. So we have to let China, other people use it. So while way doesn't beat our standard globally like they did for 5G, where do you, or should we just, you know, not give them the top ones? you know, and let them suffer with the previous ones.

I'm not the expert on geopolitics here, but the thing I'll point out is that China's building their own chips. We know this. They're quite good. Huawei, yeah. Yeah, and so there's a number of different groups there. They're increasing in sophistication. I kind of agree with sex.

If you hold yourself back, then it feels like a short-term win, but long-term you end up kind of losing. And so I can see definite advantages for short-term tactics. And Chris, how much of, I mean, How many customers do you have internationally? What does your customer base look like? Yeah, we're global. And so we both have a big commercial base,

but we also have a big open source community. And so with open source, you don't know where any of your bits go. And so I'm sure there's folks in China that are playing with things and doing things. But honestly, what I love is I love people coming together. I love the developers building new things. I love people and the ideas getting out there. And this is where, again, with AI,

there's a, I think, fair argument to make that AI moving faster is just good for everybody. And so it does not know any walls. Like the Chinese models, the open source Chinese models are really good. The Kimi K2s and all this kind of stuff are actually quite good. And we're benefiting a tremendous amount. We as America are benefiting from their work on that stuff. And yeah, they also benefit from our work. And so we could either be defensive and try to hold things back or we could be aggressive and lean forward. And I think if you look at Open Eye Anthropic, for example, both American companies, they're leaning forward. You look at

In video, they're leaning forward. You look at Google, leaning forward, and I think this is the way that you make good progress. Now, it could be that, you know, try to put up walls around everything and play defense. Again, maybe if there's a short-term strategy that you're trying to, like, make work, that can work. But I think that leaning forward and driving the status quo is driving the standards, being the platform, being the leaders is really what winning looks like. Yeah, and they're making bets. There's this concept term. I heard four little dragons. I don't know if Chris, you've heard that one before. But this is for more threads, MetaX, Byron, and Inflame, who are doing GPUs locally.

This is not Huawei. These are these little ones that are startups there. And that's typically how China does it. They create, underwrite, you know, pick, they don't pick the champion. They kind of let 20 champions bloom and then narrow it down to the. the two or three big winners and have this like more constrained version of capitalism with the goal of, of course, flooding the market with things that are, you know, under, under price, right? Like we're seeing with cars right now. Yeah, I think the best example.

The thing I respect about the Chinese system is it's very competitive, right? And so there's like the people are very competitive and they're pushing hard and they're trying to make themselves better. They're learning. They're studying hard. They're working hard. the provinces within China are all competing against each other. And so they're all trying to build and one up each other. A lot of this nature, a lot of this mindset is really what's driving the

open source AI movement coming out of China. And they're trying to one up each other, trying to do better things. And when I look back on what made America great, it was really about that capitalistic competition of companies trying to outdo the other and capture value and deliver value. And so I think that, again, this is where progress comes from. Like, we shouldn't be playing defense. We should be leaning into building a bigger, better, faster moving flywheel and be able to capitalize that and be able to drive that up into our products. And I think we're seeing that.

And if you look at the American economy over the last year plus, it's been just on fire. And a lot of that's been because of the transformations, people have been able to roll out because of the increased value being delivered. And yes, all the fab's being built, too. That doesn't hurt. Let's pivot a little bit here and talk about self-driving. Chris, you were involved a little bit in the self-driving space. What's your assessment of it today?

I asked Jensen last week about the Nvidia stack. There's been a lot of talk about this. There's a really good podcast, The Road to Autonomy, with a couple of Jens every weekend, just go through all the announcements. Obviously, Uber and NVIDIA have a big relationship. NVIDIA's got a giant relationship now with, I think, 18 different OEM, yeah, original,

I guess they're the OEM to the car companies. then you have people making their own software like Nuro who use the NVIDIA stack, but then I guess are going head to head against the NVIDIA driver, which would be like the Nuro or FSD. So your assessment of this now, Chris, and your history in it? So, I mean, I haven't worked in the space for nine years, but I led the autopilot team at Tesla and helped convert them from hardware one to hardware two and a bunch of technology ecosystem improvements back then.

Are you curious about who's going to win? Are you curious about what it looks like in this new future? Are you curious about... I guess your assessment... Because Waymo's obviously in the lead. Yeah, Waymo has the most miles, most rides. It works in a constrained environment. Then I guess you have Tesla going for this incredible vision.

No, Tesla's not a realistic player. They're not filing the permits to have actually autonomous cars, and they still have humans in their car. But I think that in China... So that's the thing to watch is when they file for not a, because right now they filed for ride chairing. Yeah. And they're doing, yeah, like Uber, but they're using the software under supervision. So you think that's the tell.

When they start filing to be autonomous, that's when, you know, it's going to get real. Yeah. So my understanding, which again, I'm far from being an expert in any of the stuff. But my understanding is they have single digit number of cars that are, doing anything and they're in one geo area in Austin or something like that. And so it's a very small, small, small program. I don't know the time frame, but it does take months to get approval in a place like California. And so when they start applying for those permits and going, then you can see that as a lean forward of when they're going to scale. Yeah. Again, if you look at China,

China has amazing humanoid robotics. Jake, I'd love your take on this. They have amazing autonomous cars that are pretty widely available as well. And so this is one where, for company like Tesla or for these other players, like the question is kind of where do they sit on the world stage? And I think this is a huge question. Jake, I'd love to know what you're seeing from the China Robots world. And I see these videos on YouTube of the humanoid acrobatics almost. It's pretty crazy.

Is it real? Yeah, yeah. I mean, like it's demos can be written and can be executed in the kind of way that you saw, I guess they got the, you probably saw the Kung Fu moves. and the Olympics and those kind of things. But what entire on stage shows with like 30 robots and humans and robots all dancing together doing crazy stuff? What it shows off is like the actuation.

It shows off the perception. It shows off a lot of those things. The real tricky stuff is a dexterity. I think this is the stuff that probably Elon talks about with the Optimus 3. I mean, Jason, you've probably seen the Optimus 3. Yeah, I got to see it early. It's super, super. Incredible.

Yeah. I think like, you know, the real questions are going to be, you know, who's going to buy it? What sorts of like ROI is there going to be? We've tried out from Europe, from China, and from the U.S., the best mobile platforms. So the walking dog types, these sorts of mobile platforms. What I have been able to determine is that there's very little value that the data sets and the actions that can be taken from the mobile robots actually have. And I've looked and tried. And I've looked and tried. tried my hardest because it's so cool, right? It's like so cool to be an implementer of that on the cantilever stack. But what I've determined is that there's just too little ROI for the amount of effort that it takes to actually get these systems to be valuable and useful. I'm curious on that because it's also, it's not just about having a general robot, which you might want for a consumer product. It's also about being efficient, good reliability, what does the repair look like?

More complexity is actually just worse for operating at scale in an industrial setting, I would think. Jake, here's the figure robot with, I believe this is Mark Benioff messing with it. It's sorting packages just putting the barcode face down,

I guess, or the shipping address face down. Yeah. And then it's got Benioff throwing packages back at it and it's sorting it. You see something like this, Jake. I mean, what is this? You know, we were talking about demos

you know, being faked or, you know, perfect conditions or even self-driving demos, Chris, in your day, you know, five years ago, a lot of times the self-driving demos were very canned, I would say. I wouldn't say, you know, they weren't fake, but they were produced in a way for a limited, you know, space, you know, so they, you know, didn't have the edge cases, let's say. But that video right there, that looks like a general purpose. robot doing a general purpose task that humans are doing right now for 20 bucks an hour, 24 bucks an hour. And that robot, you know, if it doesn't break down and it has decent fidelity, could be sorting packages 24 hours a day at a factory. That's hundreds of thousands of jobs.

Yeah. It's probably millions of jobs. Yeah. Regardless of the if that robot was teleoperated, if the more complex task of flipping over a more complex, more necessary, like, like a greater need for a more dexterous robot. It is a fundamental shift in the way that economies can be built and economists can run and unfairly advantaged that companies that adopt this sort of technology early and natively will have of the next three to four to five years. Like I've talked about this publicly. I think like there is no better decade for private equity than this decade that we're in right now.

And the reason for us because your ability. to take and buy, especially capital-intensive and commoditized infrastructure, assets, you know, like waste, return energy, you know, from waste into energy, or, you know, or water treatment facilities or power plants that are old, or these sorts of, these sorts of investments of the next decade are going to be incredibly high return because you can be able to, you can be able to turn these assets into more and more autonomous assets, you can be able to self-insure more and more. So reducing the amount of risk, taking on more risk itself with tools and technologies where you can understand the health of these assets.

Because the management team's not going to do that, but this might be what we're seeing with these open AI and private equity deals they're doing. And they're going to buy legacy businesses and then AI them. You see like Thrive Holdings, right, like with Josh Kushner. So he's buying accounting companies and injecting AI models and stuff. Like we're still seeing like how much return there is with that strategy, but you can see the strategy being implemented. I think it should be way more money, but basically he's doing that for manufacturing because he's seen the impact that millions of robots have for his distribution centers and helping two-day shipping. You know, it's a robotics defined operating platforms that gives us such an

advantage. And so I think it's like, look, it could be humanoid, they'll be involved, but you're going to see an extremely high growth of specialized robotics that are very specifically focused on, you know, these like critical, critical tasks, critical data sets that help to unfairly run large pieces of infrastructure over the next decade. And then I'm going to think you're going to see a consolidation of, you know, which energy, which manufacturing, which, you know, mining companies are the dominant ones because you just have unfair, you know, unfair P&Ls as relates to how you want to manage these

things. Well, and J-Cal also knows, and has talked about quite a lot, as the cost of software goes to zero, it's not just the harbor side, right? So the transformations are going to accelerate. Here's the story. Hold on, let me just share this. Here's your New York Times story. So Thrive, and this is Josh Kushner, Jared Kushner's brother.

Jared's making peace in the Middle East right now, or attempting to, his brother, Josh, I guess Sam Altman in opening, I took a stake in this company at Thrive Holdings, which then has this roll-up where they've bought, I think, think 20 or 50 accounting firms. And so it's called Crete C-R-E-T-E Professional Alliance and the IT service provider, shield technology partners. And so those are the two that they put together. They've committed 500 million to Crete, which the trade publication accounting today described this year as one of the fastest growing accounting firms in the United States. So the idea here, buy up all the accounting firms. A lot of those already have.

offshore and that's always my little tell to figure this out the step before AI automation was move the work to the Philippines move the work to India you know the top one to five percent of those markets knowledge workers are better more consistent than the average worker in American America which is to say the averages are not the same but the elite in India the elite in Philippines are going to be better than the average in America, and they're going to cost, in my experience, 4, 5, 6, 7, 8 bucks an hour versus 40, 50, 60 bucks an hour in the United States. So that's an interesting kind of wrinkle here. Yeah. Well, if you look at that analogy, I think that analogy may also be

comparable to the AI replacement cycle, right, where the lower value jobs get replaced. The higher value jobs don't, right? For the same reason that people have been out offshoring and getting lower-cost labor and other geos, but there's still an incredible amount of engineering and an incredible amount of talent in the U.S. And so a lot of people are betting big on American talent. AI, I think, will transform and we'll continue to push the world forward and it will affect a lot of jobs and people upskill. The question is, what are they upskilling into? And where does the value accrue? Where does that get captured? Well, yeah, and you were sort of talking about like commodity work. And being a CPA and an accountant or a lawyer was considered professional services, not

commodity. And here we are in 2006 and we're like, well, obviously that's a commodity job. Like, you know, the bottom 50% of those jobs are chores that machines can do easily. Maybe the top has going to be harder.

I think it's like we're still going to see like is that strategy pan out like this year, next year. It's just like one of those things. Also, as it relates to manufacturing, there is just like, listen, like there are single points of failure in so many supply chains, whether it's turbines and generators and nuclear reactor parts and like all these

like different like parts of and forges in the U.S. ecosystem, the re-industrialization that's happening right now. One thing that's important to understand is that there's also, when you see technology companies, you know, saying they're taking on manufacturing in the kind of ways that you see or you see empty materials, you know, taking on a mine and making it more effective and efficient, you have to understand these sectors have not changed for the most point. in the past 40, 50, 60 years. And so there's actually not a lot. Look, technology is like there's low-hanging fruit.

There's low-hanging fruit. Like, there is just like, hey, look, we're still using clipboards, guys. Or like, we just, like, don't know how to hire because, like, no one wants to come work in these sectors and industries anymore. Like, there are 200, you know, folks who graduate with mining degrees every single year in the U.S. Like, look, let's just make this sexy

and just, like, first and foremost, just try to get, you know, the low-hanging fruit to be wins. and you want to masquerade them as technology advancements and improvements, great. I mean, I guess that's like fine. I don't love it from a, I don't love it as a trying to tell the truth in the matter and understanding of the truth. But I also don't, I also really want there to be a resurgence into the sector. And technology advancements are going to come. You're going to see contracts being won by companies that are able to show like, look,

we're using automated welding, autoimmune inspecting, we're using humanoid here, here, here and here. But that's like, it's going to happen. You need to be forward looking and need to be as native as you can pop. be, but I think it's just important to understand. There's like, there is, like, the same sort of principles exist with accounting. There's the same sort of principles exist, you know, in these, in these, like, sectors that you're seeing this innovation, like, flooding into. But, you know, industry reality, understand there's a lot of low-hanging fruit.

There's a lot of just, like, get smart people into the sector, make it cool. And then I think, you know, these leaders and the CEOs, it just boggles my mind in Jason and Chris, like, the best recruiting tool in the world is just, like, get robots everywhere. Get AI everywhere. Like that's so exciting if you're like in energy, you're manufacturing or mining, whatever it is. It's like, make it cool. And like the folks in these communities will run towards these jobs.

Otherwise, they should run somewhere else, right? And so you want to re, you want to re-invigorate, you know, the working class. You want to reinvigorate these towns and these, you know, these places around the U.S. where you just have so much dissipation, people moving away from these cities and towns. Like, that's beautiful. That's America.

We want there to be a research. Yeah, it's super. It's super hard to do that. I mean, Jake, I'll give you one example from my little world is I'm trying to get software engineers who are one of the biggest groups of people that are under threat from this AI tooling explosion that's going on. And all these folks, depending on who they are, have like this existential dread of what does it mean for my job. Or if you're a college kid, you're entering the workforce. Am I going to get a job? What are people hiring?

What does it all mean? But there's this amazing platform out there of GPUs. And there's this amazing thing happening, AI. Just to your point, it should be obvious. Everybody, it's happening, right? But what I see is that, you know, some people do adapt and adopt and jump in and upskill and then differentiate themselves. And some people do that. But a lot of people are just kind of following the university playbook.

The university playbook is a few years out of days. You know what is happening like the most, by the way, Chris? It's happening in the countries that are most at threat economically. Yeah. And the hungriest. Yeah, yeah. Right. Exactly.

It's in the middle of the least. Jason, you know this well, whether it's in Saudi or it's in the UAE or it's in Israel. There is threat to the economy that is causing these leaders to be big, bold as it relates to how they are adopting technology, trying to be. 100%, yeah. Trying to figure out, like, we have to be technology first. If you have to be robotics native, AI native, to drive and create a technology company out of these energy companies.

And they are doing so, you know, because they understand that survival is the most important thing whereas in the U.S. we've been very accustomed to peacetime, very accustomed to, you know, we all get this percentage of the energy market and, you know, we're all, you know, we have utilities that have 30-year power purchase agreements. I don't, I can just pass through my losses down to, you know, to the single mom who's just trying to make it every, you know, week to week to week, paycheck to paycheck. And, you know, this is, this is why, like, we're spending time out in these regions. But it's, my goodness, like, the U.S. needs to wake up as it relates to these sectors, we need to have a re-industrialization and an excitement in these fields

because it is going to be, it's going to hit us hard and it's going to hit as fast as it relates to how vulnerable we are because there's just not enough people in these sectors using and trying to adopt big, bold visions from these CEOs. And these CEOs, most of them are financed, you know, were CFOs before that. And so their minds are not focused on vision and ambition. They're focused on how am I going to get an extra couple cents, you know, up, uh, taking my, my, in my ticker today. And my goodness, that is not what America needs. We need a complete change in that approach. And so that's the CEOs that I look for. You know, we work more looking to do big deals. And yeah, very clear, we're going to need a lot more tradespeople. We have, even before the AI boom,

needed more plumbers, electricians, teachers, nurses, doctors. Like, there's a whole group of jobs that have been desperate and literally bringing in people, you know, essentially importing talent, you know, whether it's Jamaica, you know, or India or the Philippines to find nurses, to find doctors and underwriting. This is the funny thing. Like, so 10 years ago, people in AI were saying that all radiologists were going to be obsolete. Yeah, how that goes?

Definitely don't go into radiology because you'll never get a job, right? Here we are, 10 years later, and there's not enough radiologists. AI is definitely being used, but we have so much demand. And I think this is the thing that everybody kind of forgets about is that the market, the economy, the capabilities are expanding. As you get more creation, you get more products, you get more customer experiences, you get more opportunity. Like this virtuous flywheel is what has made our ecosystem and our community in our world great. And so AI is an accelerant. Yeah.

And I think that CEOs like me and you, Chris, like we've got to be judged more on how quickly can net new people have no idea about this sector use the technology that we're building for them. I mean, this is what it's all about. I mean, how fast, you know, for me, it's just like, can I get a McDonald's employee or Home Depot employee to be, you know, an expert in weld inspections and evaluations within three months? The answer is yes. That needs to be. Maybe not all of them have the motivation. Yeah.

But when faced, hate to be, you know, based here, but when faced without a job and faced with having to put food on the table, humans, not necessarily the intent. Entitled humans we've had in America who have had massive abundance and an incredibly low unemployment rate and incredible wages when compared to the globe Yeah, now they people might take offense to my statement and cut out the when compared to the rest of the planet and in the rest of humanity. We are massively entitled with the job opportunities if an Uber or you know being a greeter at Walmart existed in the Philippines or in India or other places with high unemployment the Middle East China if those jobs actually exist people would be racing to them and be thrilled with them, let alone a tradescraft where, you know, if you need to put food on the table, you're making $18 an hour and fast food or $25 an hour being a gig worker. I think actually if you presented the path, here's the training, here's what it costs to get trained, and on the other side is $45 an hour, you're going to make twice as much money and

benefits, which I'm guessing McDonald's doesn't pay benefits. And obviously, you get a token amount of benefits as a contribution. Are there enough electricians in the U.S.? Not even close. Right. So there's so many opportunities. Yeah. It's an unbelievable amount of opportunities.

And yet we are incredibly pessimistic. And I also find it, I don't know if you guys find it offensive, but when like rich people or powerful people, successful people are like, yeah, but poor people, they're just not capable of learning a new skill. And you're like, are you not paying attention to humanity? Like, humanity learns new skills as a group. like nobody knew how to use a laptop, a phone. Nobody knew how to use, you know, any of these tools until, you know,

they might be laggards in terms of the technology adoption cycle. It's not an insult. This is one of the reasons I see everything accelerating, right? Because it feels like things are accelerating. I think we can all feel that right now. And it used to be, you go back five, ten years ago, it was YouTube, right? And you could learn anything off YouTube. And before there was, you know, you could not learn how to, you know, fix your car or

whatever it is, but now with YouTube, you could do that. Today we have AI. Now everybody has assistance, you have infinite knowledge, you have problem solving, you have reasoning, you have all kinds of different capabilities that people haven't had before. And so we talk about the open clause, right? People get personal assistance. And J. Kell, you've had a few assistants, I suspect, and so you know what that's like. Yeah. But for somebody that's never had one, having to deal with the inconsequential details of everyday life is a huge drag that prevents you from investing and upskilling and doing whatever it is that you want to do with your actual life. I think, too, like, we also, like, look, like, you guys all know, like, and you've talked to so many

people, there is such patriotism in this country, like real patriotism about, like, really, really proud, I mean, you might not agree with every decision to be made by the administration, whichever administration it is. There's patriotic Americans, and for the most part, I grew up in a small little Maryland town, like, people don't typically leave, and they want the ability to be able to, you know, to, you know, to be able to, you know, not have to do the same job that, you know, their, like, father or their mother, like, did. And if they did, they, that, that's great, too. But we have to understand that, like, this, this, this, this, this, this, this, this, this, this, this, this, this, this, this, this, this, this is a very successful.

That is hitting on a very important part of America, especially in the Midwest. This is where Pittsburgh is a very interesting vantage point. People don't want to leave. They want to be able to be, they want to be able to be in technology companies to invest in them, to be able to bring them along for people who are building products to build products for them that are oriented towards how much, like how easy for me to use? How like foreign is this? It's so, this is such an opportunity, Jake, is I think what you're framing here. And if you were to just think for a moment, like from first principles, as all these jobs are getting cut, you know, square obviously. And people are saying, hey, you know, maybe they're using

AI to make a bloated job cut or whatever. Okay, fair enough. But there are definitely AI cuts happening in customer support, in product management, and maybe just not hiring more developers because the current developers are getting 20% faster a year. Okay, even if it's just 10, 20% faster a year, if you had 100 developers, you need 10 more. Now you don't need 10 more. You just need to keep paying more and making sure your 100 developers are happy. But what an amazing opportunity for professional development. And if these big companies don't see that opportunity, well, then they're missing what I think would be a massive strategic advantage. It's not just not a specific advantage. I'm sorry to cut you off, but you're hitting it. I'm getting very passionate about this because like

the same, like if we have just a few companies that are all benefiting from the big wave we have right now, which by the way is the natural progression of free, of like these like free markets, this capitalism. It's like it's going to, it's going to make it, it's going to make these like, like larger companies, larger and larger and larger. I'm telling you, there is going to be a degrading of democracy that will happen as that continues to happen. Just like with the farming industry, you had small local farms that would create food for the local villages, the local cities. And then as free markets and capitalism went on, you begin to get these large, like, Tyson facilities that were making, you know, large things. And they were putting a bunch of chemicals into our food and all those kind of stuff was happening.

But Jake, let me... And so we really, really what we need to do is have... There needs to be these, like, robots, this AI. There needs to be a, you know, government and capitalism. There needs to be a, you know, how can we create, like, these small energy facilities that are creating small data centers instead of like these, like big, like... Your reaction, Chris.

Yeah, so Jake, Jake, Jake, I hear you. I see what you're talking about. And yes, the small farmer is having a bad day. How do you square that with the power? that every person has in AI. People can build things like they've never been able to build before. They could become a software developer.

They could build apps for the app store. They can do anything, right? They just have to imagine it. They could be a great writer when they were a terrible writer. They could be a great handyman or whatever the non-gender version of that is. Like 90% was it called? Handy person?

It sounds weird. I'm sorry, I'm just going to say Handyman. And I mean, Human. when I say it, and d-human. I'm just taking out the H.U. for efficiency. It's a non-gener term. Don't cancel that.

Yeah, how does it say it? This is where, like, there is a shift that you're all seeing right now as it relates to Adams. And I think that's where, you know, there is, there is, there is, uh, there's incredible natural resources around the U.S. Um, there is, there is like these, you know, these like U.S. steel towns, these like, um, these are the sorts of like, these are sorts of, and, um, you know, when I, when I, when I, when I, when I, when I, when I, when I,

talk when I talk about like, you know, why we're in Pittsburgh, like, I want to be in Pittsburgh because you're not supposed to build a billion dollar, you know, multi-billion dollar technology company in Pittsburgh. You're supposed to build in California. And, and I think that's like, that's what I'm trying to, in that's a side request, I guess, of like this mission of Gecko. It's like, I want to be able to show that you can build these kinds of companies, you know, in, in, you know, strategically, like, strategically, um, and statistically, um, um, bad areas, like decisions of like where to look. Sure, sure.

Places that are not growing. And I think that AI and robots. Like, it's happening in Austin where we, we, a group of us saw in Austin, hey, wait a second, you can own a home for 500K, 250K,000, 750K,000, you could, uh, save 14% on your taxes from California. Your 1,000 employees could be happy. They could be happy and be able to hire a nanny, like a white college. couple with dual income in San Francisco can't hire a nanny because the nannies in San

Francisco. I hate to blow people's brains who are not from the Bay Area. They're getting paid $100,000 a year to be a nanny, $125,000 to be a nanny, to be a housekeeper. I know this sounds insane to people, but $40, $50 an hour for a domestic staff is the standard in the Bay Area because the cost of living is so high. It's no dig. But then when you could hire a nanny for $50K for $25 an hour or something like that. like that in the in and make the same salary in austin or in philly or detroit like this is why these cities i think i agree are going to have a huge comeback i'd love to invest in a company i just had a company idea so if anybody's listening who wants to start a company a company that was a bridge

between gig workers you know and the lowest end of knowledge workers you know fast food workers and then doing handyman services and by the way handyman is handy human, the HU is silent. I just learned. The HU is silent. Imagine just that, handyman, people who can fix things around the house. Then handyman to junior plumber, electrician, HVAC. Just a company that just does that from home for but $500 a month in tuition, $6,000 a year in tuition. You work at home, you do zooms, and then maybe you could come and do an intensive or for a week or two if you wanted to and pay an extra fee. Just that job.

You could go from $20 an hour to $50 overnight. Overnight. Somebody build that company. I will incubate it. As the resident software guy, sometimes I joke, I just turn zeros into ones and ones into zeros. That's all they do. I don't get to build cool things like Jake does.

But in this world, it turns out there's a huge amount of opportunity, right? And it turns out that building softers, faster, cheaper, more accessible than it ever has been. Anybody can build AI and GPUs these days in GPU software. We're seeing people that are taking Python, and a lot of people program Python, of course, are using our stuff to move it to this Mojo language that we're helping build its open source.

And you can just take AI tools and say, hey, move this stuff to Mojo, and it goes thousands of times faster. And so what this means is that there's a huge amount of opportunity out there in the world. And what we need is we need people with imaginations. We need people that are willing to put themselves out there. We need people that are willing to try.

And I think this is where, again, it doesn't matter if you're in Pittsburgh or if you're in the Bay Area or wherever you are. It's really about your mental mindset. It's about what you want to achieve, like your ambition and drive. And I think that if we can catalyze that, then everything else flows from that. Yeah. Here's something interesting, breaking news. I'll just get your final comments here as we wrap. Brett Adcock from figure robotics, which we just talked about earlier, making humanoid robots.

robotics, the ones sorting the packages. Today I'm excited to introduce Hark, a new artificial intelligence lab building the most advanced personal intelligence in the world. We've been in stealth for eight months, assembling one of the greatest AI and hardware teams on the planet. I want to explain why I started Hank, blah, blah, blah, spent the last three years working on the hardest AI challenge, AI humanoid body. Digital side, I've been using the existing LLM chat bots and have to say they feel incredibly dumb to me. Whoa, dis, shot across the bow. AGI, quote, in the limit, should feel like a sci-fi movie. It should be able to listen and talk.

It should have persistent memory and be highly personalized. It should see and touch the world. But we're far from this today. We're crafting a new interface to AGI intelligence that lets you offload your mental workload into a system that begins to think like you and sometimes ahead of you. Build the world's most advanced personal intelligence paired with next generation hardware. Hark.com. This is breaking news, folks.

This just happened. I guess this is a new entrance into, Jake, the space going from hardware to LLM as opposed to LLM and then adding hardware. Your reaction, did you know about this project? Have you, as there has been back channel about it, Jake? No. There's just breaking news to you as well. I don't, I mean, like, I don't really follow figure all that closely.

Yeah. But, yeah, I think it's, you know, there's a rising amount. of attention like in this particular text text. I don't have too many comments, but I'm actually because I interested in Chris's thoughts on it. Yeah, Chris, any thoughts here? I know nothing, right? So this is just my, me as a tech bro commenting, I, the curious thing to me is not just the technology, but the product. Like, how do you actually bring something full, full featured full product into the market, something people willing to pay for, right? And I think, Jake, like you've shown, I mean, you've learned, it's really hard to do that.

Getting some of the technology components there is one thing, but getting it to scale, shipping the thing, having people actually use it and then breaking it in the field and then trying to fix it. Like all this stuff's really hard. Yeah,

I think like the reason I don't pay attention to figure is like figure's philosophy is the exact opposite of our philosophy. And I just, I just don't. They're general purpose robot versus specific ones to the task. Built in a lab,

then like tried to use it in the environment. So I think like, like I think I am excited for for the attention to the sector. I'm excited for the potential for the products. I'm really excited for, you know, the, the amount of people that are hitting us up in terms of just like applying for jobs because robotics is like cool and it's a sector doesn't create death much. And so it's like that's great.

And I think like one thing I was going to say on the last like part, Jason, just to finish up my thought is like democratizing the amounts of ability to create prosperity across the country and also like you know just like provinces are are competing against each other in China states should be competing against each other kind of like they were like 100 years ago 50 years ago when you know when we first created the United States they should be competing with talent pools not with tax rates exactly and exactly and and it's like we we like the whole game of politics like just doesn't reinforce this like fierce amount of like competition amongst the districts and states but I think like the vision of the future we have to like

be really excited about and striving for it, helping to create as well. It's like, I want my nine-year-old to be able to create a lawn service business and use robots or be able to, yeah, for sure. We call that job Shepard. Yeah,

shepherd for robots. I have a cynical take on it. I'm guessing figure. No, no, just on the figure in it. Oh, figure something. I mean, I think the most generous take is what he said, hey, we try to use these LMs

that doesn't work for our robots. Okay, fair enough. You make your own. cynical take, which would be, hey, the valuations of Open AI, the valuation of Claude, you know, getting to $800 billion, $400 billion. I'm sure Claude's next valuation will go from $350 billion to $800 and be neck-in-neck with open AIs. I believe they'll probably be similarly valued.

So if they're going to be worth $900 billion and XAI as part of SpaceX is worth $2 trillion, I need to be in that group, not in the role. robotics group, you know, competing with just Optimus head-to-head and the Chinese companies, I want to be part of the bigger sack. And part of that is, you know, Open AI and Claude will get into robotics. So we need to get into their business now and just, you know, kind of put us in that competitive set. A lot of times founders and CEOs and boards will be like, hey, wait a second, let's rewrite the

rules here. Let's be in that set. Actually, Jake, for you, with your robotics company, if you said, hey, we have a have our own proprietary LLM just for maintenance, it would increase your valuation. It would be another asset. I would look at it as an investor or a board member or just a market participant as, oh, wow, they're going to power other robots with their underlying technology. It might be something for you to think about it. Yeah. And also, Jason, there's also other kinds of data sets, too, as you're just like, we are in all these sectors collecting

so much information about, and we're basically, in some ways, like, you can think about, like, the data sets of, like, the YouTube for these industrial sectors is a very valuable about data sets we have trained on. Last word, Chris. I think it's also a sign that manufacturing is hard. I think it's also a sign there too. Yeah, my take on this is that, you know, when you're building a business, when you're building anything of merit, you have to decide what your contribution is, trying to play

other people's playbooks, trying to be the same thing that our routes has already done, trying to try to just like, you know, appeal to the investor isn't really actually a great strategy because you get too diffused. You don't achieve things. You can't differentiate. you become mediocre at a bunch of different things instead of exceptional at one. So I think this is the challenge.

The North Star should be the customers and the value providing to them. And then what happens in a hot market and an escalating market is people will do unnatural acts. And don't get lost playing games, right? I mean, I think that creating core value that people are willing to pay for is the recipe, right? I think games you can get caught up in it.

Yeah, and then Chris, but I think the thing that's like for the listeners as well, Jason, is like, We like to mimic things, like from a very Gerardian perspective. Like, we like to mimic things. And we see, we want to mimic as founders. Like, I want to get as much validation as I possibly can. Look, this person is achieving like this valuation. I need to achieve this valuation.

I think the lessons that Chris are talking about are only lessons that come from scars, from failures, from understanding the, you know, the fallacy of pursuing the wrong things. and the potential wisdom or lack thereof of folks that seem to have been. And what is success? It's really important boundaries. It's like there's no replacement for the grit and hard work that, you know, Chris, you know, the people like Chris has, you know, his wisdom right now is like, it's so important to just really rock and, and like, success will come if you adopt those principles.

Yeah, success is not the press release. Success is the product. The pressure release needs to compound and propel the product. But if you get confused and you just want to have. announcement announcement announcement there's nothing of substance behind it then you're not winning even though it feels like it in the moment bingo short-term gain versus long-term gain and the long-term gain takes a lot of pain and another this week in AI is in the books this week in a.i.coma.com to sign up for the newsletter and all the links thank you to Jake, thank you to

Chris. They're both hiring go to their websites and hardest position to fill Jake right now for you Who do you need? Robotics engineering. Perfect. Robotics engineers, if you want to get in on the ground floor of a company that's going to go 100x from here. I said that, not him. That's just my professional estimation. And Sydney with Chris, what are you hiring for Chris?

Cloud platform, GPU programmers, AI software professionals of all sorts. Little tip here. Sometimes the CEO or founder gets their first name at company domain.com or dot AI. So just, you know, and a lot of times if you build something and share what you built as opposed to a businessman and begging for a job and promising things. Sometimes you build something dope. You send it to a CEO. Sometimes they'll click the link and see what you built. Just a little professional tip there from your boy, Jake. We'll see you all next time. Bye-bye.