In short
The episode argues AI’s biggest near-term impact is on jobs and critical infrastructure, emphasizing “deterministic” robotics and trustworthy data (not hallucinations). It also covers the AI compute race (chip shortages, export controls, and $2.5B “chip heist”/smuggling story), and why enterprises need a hardware-agnostic software layer. It concludes with debate on self-driving progress and whether humanoid/general robots will deliver ROI versus specialized industrial robots.
Guests and backgrounds
- Jake Lusararian, CEO/co-founder of Gecko Robotics; builds purpose-built, mission-critical robots/software for infrastructure health and optimization (started building in college; ~13 years).
- Chris Latner, CEO/co-founder of Modular; builds a software layer to run AI models across multiple hardware types (NVIDIA/AMD/Apple Silicon) to reduce fragmentation/lock-in.
Key claims
- Robots should gather data to predict/prevent catastrophes and enable “fixing,” not just demos.
- AI/robotics value depends on high-fidelity, non-hallucinating datasets.
- CUDA/AMD stacks create lock-in and fragmented developer ecosystems; Modular replaces vendor stacks and supports heterogeneous systems.
- Chip supply is constrained; software portability is the bottleneck.
- Google TPUs may be the “sleeper” competitor; NVIDIA dominance persists due to CUDA community.
Notable examples
- Cantilever robots/software predicting infrastructure failures; optimizing energy efficiency (BTUs), production (barrels/day), and shipbuilding/dry-dock delays.
- Discussion of ship/defense geopolitics, China chip smuggling, and export-control tradeoffs.
- Self-driving: Waymo leads in constrained environments; Tesla scaling depends on permits for autonomy.
- Humanoid robotics demos show actuation/perception, but ROI and repair complexity remain limiting.
Written by AI. May contain mistakes. Listen to the episode to check what was said.
Chapters
Tap a time to open that second in VOThe Impact of AI on Jobs
0:00 to 0:34
Explore how AI is transforming jobs and the importance of upskilling.
“AI, I think, will transform and will continue to push the world forward and it will affect a lot of jobs and people upskill.”
Jake Lusararian and Gecko Robotics
1:07 to 2:10
Learn about Gecko Robotics and their focus on purpose-built AI robots.
“Jake Lusararian, we've had on the program before.”
The Evolution of Robotics
2:10 to 3:46
Discuss the state of robotics and the integration of AI into infrastructure.
“Yeah, I like to put some money into the funds as well for the kids.”
Chris Latner and Modular Technology
3:46 to 5:06
Introduction to Chris Latner's work at Modular and its significance.
“sixes out there, you know, and just all this new Gemini stuff, et cetera.”
The Importance of Hardware Choice
5:06 to 7:30
Explore the need for diverse hardware options in AI deployment.
“I'm sure you have questions for Jake, too.”
Navigating Compatibility in AI Systems
7:30 to 9:57
Understanding the challenges of compatibility in AI hardware and software.
“being very mission focused robotics to help us understand, hey, not all data is important to go get and gather.”
Data Management in Robotics
9:57 to 14:03
Discover how Gecko Robotics manages vast data sets for improved outcomes.
“structural business reasons, but there's also just legacy accents of history reasons.”
Investment Strategies in AI Development
14:03 to 17:09
Explore how companies decide where to invest in AI technologies and data.
“want, good usability, reliability, all the good stuff that you want on NVIDIA is fantastic, but then you can scale off and you can go wherever your business takes you.”
The Future of Robotics in Maintenance
17:10 to 19:13
Learn about the integration of AI and robotics for infrastructure maintenance.
“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.”
Current State of Chip Shortages and Demand
19:14 to 21:36
Understand the dynamics of chip shortages and their impact on AI development.
“I mean, these are incredible amounts of money.”
Show all 39 chapters
Competitive Landscape Among AI Chip Manufacturers
21:37 to 23:56
Analyze how Google, AMD, and Amazon are positioning themselves in the chip market.
“they also don't want to have two different software stacks.”
Challenges Faced by Google in the AI Chip Space
23:57 to 26:36
Delve into the hurdles Google faces in promoting its AI chip offerings.
“I guess the question is, why don't we hear about them?”
The Fallout of Chip Bans in China
26:37 to 28:01
Discuss the implications of chip bans and illicit activities related to chip trade.
“And super confusing to understand like how these companies are related to each other, but Google does everything.”
Product Naming Critique
28:01 to 28:30
Discussing the branding of AI chip products and its creativity.
“I mean, the branding's so like on the nose, but it's Infer...”
Chip Smuggling Incident
28:31 to 29:51
Analyzing the chip smuggling operation involving billions of dollars.
“I don't know if you saw this, Jake, the ban on chips in China.”
National Security and AI
29:52 to 30:58
Exploring the implications of AI and chips on national security.
“I don't know if you want to call it a cold war.”
Government's Role in AI Regulation
30:59 to 32:22
Discussing the need for government involvement and regulation in AI.
“Like we, in UAE in particular, we've like, I can't comment on the sites that have been hit, but just to let you know, like there is, this is all very real for us at Gecko.”
Export Controls and Global Standards
32:23 to 33:58
Debating the strategies behind export controls for AI technologies.
“Is there, is there how much code is being written or being evaluated using these tools?”
China's Competitive Edge in AI
33:59 to 35:29
Examining China's approach to AI development and competition.
“There's a number of different groups there.”
American Capitalism and AI Progress
35:30 to 36:30
Discussing the benefits of a competitive capitalist environment for AI.
“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.”
Self-Driving Technology Update
36:31 to 37:40
Insights on the current state of self-driving technology and its future.
“And so there's like the people are very competitive and they're pushing hard and they're trying to make themselves better.”
Autonomous Vehicles and Permits
37:41 to 39:44
Analyzing the implications of permit filings for autonomous vehicles.
“I asked Jensen last week about the NVIDIA stack.”
China's Advances in Robotics
39:45 to 41:16
Exploring the advancements in robotics and their implications.
“I don't know the time frame, but it does take months to get approval in a place like California.”
Challenges of Robotics in Industry
41:17 to 42:05
Discussing the practicality and ROI of robotics in industrial settings.
“So the walking dog types, these sorts of mobile platforms.”
The Impact of Robots on Labor Markets
42:05 to 43:54
Explore how advanced robotics could transform job markets and economies.
“And then it's got Benioff throwing packages back at it and it's sorting it.”
Private Equity and AI Integration
43:54 to 45:48
Discuss the strategy of private equity in integrating AI into traditional industries.
“I think there is no better decade for private equity than this decade that we're in right now.”
Global Perspectives on Employment Trends
45:48 to 48:05
Examine how outsourcing and AI are reshaping job roles across different regions.
“are the dominant ones because you just have unfair P &Ls as it relates to how you run and manage these things.”
Restructuring Industries for Modern Needs
48:05 to 50:46
Analyze the need for innovation and modernization in traditional industries.
“an incredible amount of talent in the US.”
Challenges and Opportunities in the U.S. Workforce
50:46 to 53:08
Discuss the current state and future of the workforce in relation to AI advancements.
“There's a lot of just like get smart people into the sector, make it cool.”
The Shift in Employment Dynamics
53:08 to 56:01
Understand the changing dynamics of job opportunities and skill requirements.
“I don't I can just pass through my losses down to, you know, to the the single mom is just trying to make it every week to week to week, paycheck to paycheck.”
Job Opportunities and Skills Training
56:01 to 56:49
Discussing the disparity in job opportunities and the potential for skills training in the US.
“Now, people might take offense to my statement and cut out the when compared to the rest of the planet and the rest of humanity.”
Patriotism and Workforce Aspirations
56:50 to 59:00
Exploring American patriotism and the desire for career advancement beyond traditional roles.
“Are there enough electricians in the US?”
The Shift in Labor Dynamics
59:01 to 1:01:59
Analyzing the impact of AI on job roles and the opportunities for professional advancement.
“Vance ran on and that was very successful, that is hitting on a very important part of America, especially in the Midwest.”
Building Opportunities with Technology
1:02:00 to 1:05:36
Discussing the accessibility of technology and the potential for innovative business solutions.
“And I think that's like, that's what I'm trying to, that's a side request, I guess, of like this mission of Gecko.”
Discussion on Robotics and Market Potential
1:07:39 to 1:10:04
Concluding thoughts on the robotics sector and the competition in AI technology.
“I guess this is a new entrance into, Jake, the space going from hardware to LLM as opposed to LLM and then adding hardware.”
Envisioning Future Robotics and Entrepreneurship
1:10:04 to 1:10:30
Exploring the potential for children to innovate with robotics in business.
“I mean, I think the most generous take is what he said.”
Valuation and Competition in AI and Robotics
1:10:31 to 1:11:40
Discussing the valuation of AI companies and their impact on the robotics landscape.
“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.”
Building Unique Value in Business
1:11:41 to 1:12:43
Insights on how to create distinctive value rather than mimicking others.
“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.”
The Importance of Substance Over Hype
1:12:44 to 1:13:52
Understanding the difference between real success and superficial achievements.
“And don't get lost playing games, right?”
Transcript
Automatic transcript. May contain errors.0:00AI, I think, will transform and will 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, 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.
0:33Get 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 paypalopen.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 thisweekina.ai. Thisweekina.ai. There's a sub stack as the number one AI podcast in the world. We've got two all-stars here this week. Jake Lusararian, we've had on the program before.
1:12He'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.
1:51People can visually see them here. and what they're doing. So here we see Cantilever. That's your B2B product. Walk us through it. Yeah, 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 Cantilever. So basically, 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.
2:25There'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 and 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 gathering collect. So gather the information about the health of the built world was the original idea.
2:54Basically build 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 to help to optimize how infrastructure performs, how healthy is it, and help drive things like how do you make kilowatt for less BTUs? How do you produce more barrels per day with less cost? How do you get a ship out of dry dock faster or manufacture a new vessel in quicker times with higher quality and speeds. These are the kinds of things that we build robots for, very specific, mission critical.
3:28And you started this long before the chat GPT moment. When you were doing it, it was machine learning 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 claw at four points sixes out there, you know, and just all this new Gemini stuff, et cetera. Yeah. Back in the day, I mean, we were just using hobbyist motors and gearboxes, planetary gearboxes, and we're trying to ensure that we could build robust systems and building them in the environment when Silicon Valley actually was like, you know, put it in a lab, make it autonomous and then launch it.
4:05And we just didn't believe, agree with that fundamentally back in the YC days in 2016. But now what's happening is you're beginning to get this super, super high focus on what's the pragmatic impact of artificial intelligence, especially for the companies like the energy, oil and 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 we've focused on is building robots that actually affect things today, not painting a vision of five or 10 years.
4:39And the models are putting basically a huge, a huge freaking spotlight on the importance of really important, valuable data sets that don't hallucinate, especially with 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. 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.
5:15Yeah, I was totally going to. Explain to the audience what you're built and why it's important. I was totally going to build Jake, but I'll happily jump in here. No, no, 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. It should be running in massive data centers, also on your wrist, and everywhere in between. I mean, a lot of the world is really consolidated around the NVIDIA platform, which is really amazing and it's very powerful.
5:41But 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 application-specific optimizations and use cases and things like this. I think Jake's probably a leader in the space. And what 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.
6:19What does it feel like to have a 13-year head start? Well, yeah, the party is jam-packed now with so much funding and folks who are jumping into it. Listen, I think it's, I am so thrilled. I mean, it's just incredible. I mean, I am very excited and optimistic about 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 for the world. I mean, it's a very optimistic future. The key is being deterministic, though.
6:57And I think that's maybe where we're like lacking a bit. Determinism as it relates to, you know, making sure that if you cross the bridge it won't collapse or making sure that if you have, you know, right now we have like two, you know, two out of every five ships that are stuck in some dry dock or pier side somewhere, you know, and that's, that really affects like the, the, 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, of energy. I mean, these are all things that robotics deterministically could be focused on improving.
7:28And that's why we built, you know, Gecko itself, being very mission focused robotics to help us understand, hey, not all data is important to go get and gather. Hey, not every action is important to solve for. And then more importantly, when you have that paradigm, being able to put humanoids 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 put coming out with Adams.co. I mean, you know, he's basically the manifesto he wrote is just like, hey, that was my manifesto 13 years ago.
8:02And he'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 Kimi. We've also been testing it in the cloud. but having Kimmy K 2.5, 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?
8:50Is it people trying to run on Mac Silicon, on Intel, on commodity stuff? Where are the combinations showing up? Yeah, well, so I think GPUs have captured the world. And so since the chat GPT moment, GPUs have 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 um it's super funny if you look at the consumer side that you're double clicking on because uh nvidia has the dgx spark uh amd has like the strix halo and other crazy kind of hobbyist pro systems that are that are cool boxes you can buy um but the chips inside of them are all slightly different and so i don't know your experience jason but the uh uh getting stuff set up and actually getting the latest models can actually be a real pain and um have you ever double clicked into why that is?
9:43No, tell us. Yeah, this is a great opportunity, I think, to educate the audience on what the issues here are in terms of compatibility and making this easier for consumers or even prosumers. If you lean in and you really get deep into it, 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, Grok, or lots of other people that go out there and build systems.
10:23So 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. You want to be able to run on, like if you get an NVIDIA box or an AMD box or you get somebody else's chip, you want to be able to run it and um but you have to switch to different software stack and the problem is is that there's never been that unifying layer everybody just builds on top and builds on top and been building up layers and layers and layers of you know cool stuff and very 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 We can interoperate with CUDA if you want to, but our native stack replaces CUDA.
11:11And that's actually a pretty big deal because that means that that entire stack can now move over and is consistent across different hardware. And this is important for the audience to understand. 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 open source or not, but there is a bunch of lock into the NVIDIA chipset if you use CUDA, yeah? It's definitely lock-in, but it's not specific to NVIDIA. AMD has their open source software stack called RockM. We can debate whether it's very good or not compared to NVIDIA's, but it's completely proprietary to AMD chips.
11:49And so it's open source, but that doesn't actually help you because the vendor doesn't want their stuff to run on 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, CUDA, 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 JNI. It's all like C++ 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.
12:22and then we bring a lot of benefits both from technology but also a big open source community and bringing people together and catalyzing 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, 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 him 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?
12:57Yeah, so you can totally run modular on all three of those. And so you can build heterogeneous systems. And so you get software 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 Grok platform that they're coming out with this fall. Vera's a CPU. Grok is a specialized ASIC, a custom accelerator for AI. And then of course they have their GPU. For doing inference, the block pieces 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, right?
13:45So being able to scale across that is a huge benefit. It's also, to your point about lock-in, it gives enterprises choice, right? And so a lot of people are running on NVIDIA, 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 NVIDIA, 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 NVIDIA 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?
14:12Because 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 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 there is an interesting data set that Gecko has amassed, being now, we have like five or 600 ,000 assets inside of cantilever critical glass heads that we have gathered information on using robots and information around those environments as well.
14:51And so there is an interesting data set that no one else does have. But one thing that, you mentioned something, Chris, that was really astute and interesting I'd like to double click on. And that's around hardware companies don't like to play with each other or they have a hard time playing in the sandbox. Now, what's interesting is in the, you know, in the kind of like an 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 sensor 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 to feed into.
15:29You 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 what's out there. And innovation teams do a really bad job, whether it's like a name like them specifically, but like all the top 10 oil and gas companies, right? And they will pick a solution. They will maybe invest into a company through ARM, and then they'll try to leverage and use that. But you end up with a robotics or a hardware company in particular is trying to figure out how do I you know make the big you know return for um for the investments that I'm getting and okay you have to like have some sort of software platform and then there and you end up having like a dozen like software platforms that I'll have to be logged into um and a dozen different like point solutions and that's not actually what the customer wants they just want to be able to make make a barrel you know 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 and 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 have had a hard time um and 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 andro game of like we'll either acquire everybody or like we're gonna put this all under lattice and You know what I mean?
16:54And 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 amassing so much information data. And because that information data is, there is relevance in terms of 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.
17:26And that's where obviously it's all headed. 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 car or something, You know, 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 talk 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 in Star Wars or something?
18:06Yeah, 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 what kind of conditions, how humans the air, all that kind of information is very useful as we begin as the lead towards taking action on how to fix and replace or repair.
18:50I mean, 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 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, an 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 an energy facility. I mean, these are incredible amounts of money. And environmentally, it's horrible.
19:22It's horrible to stop stuff and then turn it back on, just like when you accelerate in a car. That's bad environmentally. And just so many reasons. That's when you typically have things break when you stop and start it. So that's what we're building. And in order to do that, you also need to fix stuff after you find it. And so, yeah, absolutely. And that's even what we're doing on the shipbuilding side right now. Let's talk about the shortage in ships. Chris, is there a shortage like we're hearing about? Is that marketing? Obviously, you have a bunch of players doing custom ASICs. You're having Elon talking about his fab, Amazon making their own, Google making their own, Facebook is going to make their own with Broadcom, I believe.
20:06So there's 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 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 very stocked out for a long time.
20:45You 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 claws, 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 Tranium, 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.
21:14If you're Anthropic or something like that, you have one workload, you can put one workload and dedicate a 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 stalling that, but again, it comes back to the software problem, and people 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 you're struggling with like, okay, well, I get choice, but I get two different stacks.
21:49I 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? 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 these chips? It does seem like Amazon is making quite an investment in chips. Are they going to push the industry towards alternatives? Is it going to be this massive open AI with AMD deal that seemed to have come the week after Sam announced the big open AI NVIDIA deal and then like whatever, 10 days later does an AMD one.
22:27I think Jensen was a little perturbed, maybe would 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, who's going to compete with NVIDIA at scale in 2027, 2028, 2029? 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.
23:04And 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 Fluidstack. And so there's other vendors that are now starting to get access to TPUs.
23:35I 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 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 rent them out through GCP. I guess the question is, why don't we hear about them? Yeah. Why is that? You're saying it's kind of like the sleeper. Why is it the sleeper? Yeah, I think they struggle with two things.
24:08One is GCP. So for a long time, TPUs 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 models. You can't run Kimi K2. You can't run standard models on these devices because two reasons, one of which is that Google has no community.
24:46And so there's no developer community out there that's like using them, no hobbyist community, things like this. But also because Google itself is not investing in 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 not going to open source their high-performance GPU code or TPU code. And so they're not actually set up to actually catalyze their own platform in that way. And this is one where CUDA is pretty amazing.
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25:17This is the NVIDIA software. They've leaned into the community. They've leaned into teaching people. They've leaned into universities. They've really leaned into 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. You can't just run the standard mode of operation 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?
25:53They 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 CPUs 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 Cowork, with the Google suite, with Gemini's products. And Gemini, I suppose is going to have a really good, you know, they're going to, they're really focusing on writing code or code, code co-pilots.
26:33But yeah, this like TPU thing is super interesting. I think who's number two, Greg? It's super funny. Comment 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, that's a big question, right? So I would go, it's either between AMD, who is the, it should be number two in many ways, because they've been working in this space for a long time, they've been competing, or, but it may actually be Amazon.
27:08And so Amazon, AWS is obviously massive, they've been leaning into this. Anthropic, for example, also uses the AWS chip, it's called Tranium. And so they're on their third generation, incredible chip, very big scale. Again, they're not, 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's aware of it, nobody uses it. Software is just a completely different weird world. And they do have software, it does actually work 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.
27:46They'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, Tranium. And is it Infer... I mean, the branding's so like on the nose, but it's Infer... It's overly clever. Inchia? Inferentia? Inferentia, yeah. It's just terrible branding. We get it. It's Inferentia. I mean, did they just ask Chachipiti to name these two products? I feel like they just asked Chachipini, what's a corny name for an inference thing? Inferentiania. It sounds like a spell from Harry Potter or something.
28:29So 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 MicroStrategy CEO was using, I mean, it's from Supermicro's co-founder, rather, not MicroStrategy. supermicro's co-founder smuggling 2.5 billion dollars 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 with the model numbers i mean and 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 That's going to bring this up as it relates to the Department of War.
29:20And I actually think it's astounding to me that our 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 just like you're talking about with, you know, with this story that indicate very clearly that this is an all 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. 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 that we haven't ever seen before.
30:03But this is an example of, look, there is an unleashing and this stuff doesn't get get the light of day unless the, you know, unless the government in China is also allowing it to be exposed. 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 Jensa, 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 a look, there's you cannot you cannot regulate this stuff. I mean, it is going to be just like life will find a way. And just it's NVIDIA chips will find a way is basically like the idea here.
30:39And 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. And so I think what I'm saying - We've fought over oil for 100 years. Oh my gosh, yeah. So now we're fighting over the chips and the oil. Now we have two things to fight over. We got a billion in the Middle East right now. Like we, in UAE in particular, we've like, I can't comment on the sites that have been hit, but just to let you know, like there is, this is all very real for us at Gecko.
31:09Well, 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 in the amount 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 cannot, you know, we cannot over-regulate here that we have in the past.
31:56We 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 just becoming way more self-determined on the government side as relates to leveraging these tools. And, you know, I'd be interested as well, you know, Jason, if you, you should have someone on this podcast talking about how is AI being used in the government?
32:30Is there, is there how much code is being written or being evaluated using these tools? I mean, there's, 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 relates to, you know, how, 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 Emile Michael with that whole kerfluffle, 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.
33:03It's probably the top model right now or the one that's kind of taken a lead all of a sudden leapfrog, Chachapi. 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 the loop there. But Chris, what are your thoughts on just broadly export controls? And do we want to really, are you on the SAC side? Hey, we want to have our standard be the global standard. So we have to let China and other people use it.
33:40So Huawei doesn't beat our standard globally like they did for 5G. or should we just not give them the top ones 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 at it. There's a number of different groups there. They're increasing in sophistication. I kind of agree with Sachs 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 many customers do you have internationally?
34:21And 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.
34:54Like 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 can either be defensive and try to hold things back, or we can be aggressive and lean forward. And I think if you look at OpenAI and Anthropic, for example, both American companies, they're leaning forward. You look at NVIDIA, they're leaning forward. You look at Google, leaning forward. And I think this is the way that you make good progress.
35:22Now, we 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 Morthreads, MetaX, Byron, and Inflame who are doing GPUs locally. This is not Huawei. These are these little ones that are startups there.
36:02And 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 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 priced, right? Like we're seeing with cars right now, I think. Yeah, I think 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.
36:41They're learning, they're studying hard, they're working hard. But then 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. Right. 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.
37:13Like 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 fabs getting 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.
37:43What'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 Jents every weekend just go through all the announcements. Obviously, Uber and NVIDIA have a big relationship. NVIDIA has 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 Noro who use the NVIDIA stack, but then I guess are going head-to-head against the NVIDIA driver, which would be like the Noro or FSD.
38:22So 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, like, 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.
38:59No, 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, again— So that's the thing to watch, is when they file for not a— because right now they filed for ride-sharing. Yeah, so they're Uber. 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 it's going to get real. Yeah. So my understanding, which, again, I'm far from being an expert in any of this stuff, but my understanding is they have single-digit number of cars that are doing anything.
39:40And 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 a company like Tesla or for these other players, like the question is kind of where do they sit on the world stage?
40:15And 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, like at the price of the Kung Fu moves and the Olympics and those kind of things. But what an entire like onstage 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.
40:56The real tricky stuff is the dexterity. I think this is 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. I think the real questions are going to be who's going to buy it? What sorts of ROI is there going to be? We've tried out from Europe, from China, and from the US, 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.
41:36And I've looked and 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 is just too little ROI for the amount of effort that it takes to actually get these systems to be valuable and useful. it's much more i'm 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 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 I guess, or the shipping address face down.
42:22Yeah. 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 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.
43:12And that robot, 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. It's probably millions of jobs. Irregardless of if that robot was teleoperated, if the more complex task of flipping over a more complex, a greater need for a more dexterous robot, It is a fundamental shift in the way that economies can be built and economies can run and unfairly advantage that companies that adopt this sort of technology early and natively will have over the next three to four to five years. I've talked about this publicly.
43:56I think there is no better decade for private equity than this decade that we're in right now. And the reason is because your ability to take and buy especially capital intensive and commoditized infrastructure assets, you know, like, you know, waste, waste, turn energy, you know, from waste into energy or, you know, water treatment facilities or power plants that are old or these sorts of these sorts of investments over 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.
44:37So 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 Thrive Holdings, right? Like with Josh Kushner. So he's buying accounting companies and injecting AI models and stuff. We're still seeing 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.
45:18It's robotics-defined operating platforms that gives us such an advantage. And so I think it's like, look, it could be humanoids. they'll be involved, but you're going to see an extremely high growth of specialized robotics that are very specifically focused on these critical tasks, these 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 which energy, which manufacturing, which mining companies are the dominant ones because you just have unfair P &Ls as it relates to how you run and manage these things.
45:54Well, 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 hardware side. 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 and OpenAI took a stake in this company at Thrive Holdings, which then has this roll-up where they've bought, I 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.
46:45And so those are the two that they've 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, the top 1 % to 5 % of those markets, knowledge workers, are better, more consistent than the average worker in 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 an hour versus$40,$50,$60 an hour in the United States.
47:42So 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 an incredible amount of talent in the US. And so a lot of people are betting big on American talent. AI, I think, will transform and will continue to push the world forward and it will affect a lot of jobs and people will upskill.
48:18The question is, what are they upskilling into? And where does the value accrue? Where does that get captured? Well, yeah, you were sort of talking about like commodity work. And being a CPA, an accountant or a lawyer was considered professional services, not commodity. And here we are in 2026 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 half is going to be harder. I think it's like we're still going to have to see, like, is that strategy pan out like this year, next year? It's still like one of those things.
48:56Also, 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, you know, nuclear reactor parts and like all these like different parts and forges in the U.S. ecosystem, the reindustrialization 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.
49:29You have to understand these sectors have not changed for the most part 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.
50:02And if 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 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, automated inspecting, we're using humanoid here, here and here. But that's like it's going to happen. You need to be forward looking and you need to be as native as you can possibly be.
50:32But I think it's just important to understand this. Like there is like the same sort of principles exist with accounting. There's the same sort of principles exist, you know, in these like sectors that you're seeing this innovation like flooding into. But, you know, in just reality, understand there is a lot of low hang fruit. There's a lot of just like get smart people into the sector, make it cool. And then I think, you know, this, these, the leaders and the CEOs, I, it just boggles my mind and Jason and Chris, like the best recruiting tool in the world is just like, get robots everywhere, get AI everywhere.
51:02Like there is like, that's so exciting. If you're like an energy to your manufacturing, your 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, you know, you want to like reinvigorate, you know, the, 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.
51:30Yeah, 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, right? Just your point, it should be obvious.
52:03It'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. It's happening like the most, by the way, Chris, it's happening in the countries that are most at threat economically. And the hungriest. Yeah, yeah, right. Exactly. It's in the Middle East, 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.
52:41100%. Trying to figure out, like, we have to be technology first. We have to be robotics native, AI native to drive and create a technology company out of these energy companies. And they are doing so 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 the single mom is just trying to make it every week to week to week, paycheck to paycheck.
53:20And, 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 these sectors. is we need to have a reindustrialization and an excitement in these fields because it is going to hit us hard and it's going to hit us 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 finance, 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 uptick in my ticker today.
53:57And 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 when we work more, we're 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. 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, uh, and underwriting. This is the funny thing.
54:37Like, so 10 years ago, people in AI were saying that all radiologists were going to be obsolete. Yeah. How'd that go? Definitely don't go into radiology because you'll never get a job, right? And 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 and our world great.
55:11And so AI is an accelerant. Yeah. And I think that CEOs like me and you, Chris, like we got to be judged more on how quickly can net new people have no idea about the sector use use the technology that we're building for them i mean this is what it's all about i mean how 100 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 and weld inspections and evaluations within three the answer is yes that maybe not all of them have the motivation yeah but when faced hate to be you know um based here but when faced without a job and faced with having to put food on the table, humans, not necessarily the 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.
56:01Now, people might take offense to my statement and cut out the when compared to the rest of the planet and the rest of humanity. We are massively entitled with the job opportunities. If an Uber or 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 trades craft where if you need to put food on the table, you're making$18 an hour in 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.
56:49And obviously you get a token amount of benefits as a contribution. Are there enough electricians in the US? Not even close. Right. Plumbers don't pay one. 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.
57:23Nobody knew how to use any of these tools until, you know, there 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, 10 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.
57:56You 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.K.L., you've had a few assistants, I suspect. And so you know what that's like. 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 your actual life and i think too like we we also like look like you and 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 that's being 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 um you know to be able to not have to do the same job that their father or their mother did.
58:57And if they did, that's great too. But we have to understand that this hillbilly allergy that J.D. Vance ran on and that was 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, how much, like how easy for me to use, how, how like foreign is this?
59:30It'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, you know, maybe just not hiring more developers because the current developers are getting 20 % faster a year. Okay, even if it's just 10, 20 % fast for a year, if you had 100 developers, you needed 10 more.
1:00:03Now you don't need 10 more. You just need to keep paying more and making sure your 100 developers are happy. That's right. 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 massive strategic advantage. And as soon as companies, yeah. I'm sorry to cut you off, but you're hitting it. I'm getting very passionate about this Because 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 these free markets, this capitalism, it's going to make these larger companies larger and larger and larger.
1:00:45I'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 began to get these large Tyson facilities that were making large things. And they were putting a bunch of chemicals into our food and all this 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.
1:01:25There 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 I see what you're talking about. And yes, the small farmers 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. They just have to imagine it. They could be a great writer when they were a terrible writer.
1:01:57They could be a great handyman or whatever the non-gender version of that is. Like 90%. What is it called? Handy person? It sounds so weird. I'm sorry, I'm just going to say handyman and I mean human when I say it handy human I'm just taking out the HU for efficiency it's a non-general term don't cancel that this is where there is a shift that you're all seeing right now as it relates to atoms and I think that is where there is incredible natural resources around the US there is these US steel towns these US manufacturing These are the sorts of like, these are sorts of, you know, 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.
1:02:52You're supposed to build in California. And I think that's like, that's what I'm trying to, 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 in strategically and statistically bad decisions of where to localize. Sure, sure. Places that are not growing. But you can find value in those areas. It's happening in Austin where a group of us saw in Austin, hey, wait a second. You can own a home for 500K, 250K, 750K. You could 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.
1:03:41A white-collar 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 a year 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 and make the same salary in Austin or in Philly or Detroit, this is why these cities, I think, I agree, are going to have a huge comeback.
1:04:22I'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 handyhuman. 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 five hundred dollars a month in tuition six thousand dollars a year in tuition you work at home you do zooms and then maybe you could come and do an intensive for a week or two if you wanted to and pay an extra fee just that job you could go from 20 bucks 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 I do I don't care to build 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 software is faster, cheaper, more accessible than it ever has been anybody can build AI and GPUs these days and GPU software we're seeing people that are taking Python and a lot of people program Python, of course, they're using our stuff to move it to this Mojo language that we're helping build its open source.
1:05:58And you can just take AI tools and say, hey, move this stuff to Mojo. And it goes thousands of times faster. Right. 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 like 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.
1:06:30Yeah. 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 robotics, the one 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.
1:07:02Digital side, I've been using the existing LLM chatbots and have to say they feel incredibly dumb to me. Whoa, disk shot across the bow. So 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.
1:07:38Hark.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? Has there been back channel about it, Jake? No. Or is this 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 tech stack. I don't have too many comments about it. I'm actually kind of interested in Chris's thoughts on it.
1:08:18Yeah, Chris, any thoughts here? I know nothing, right? So this is just me as a tech bro commenting. The curious thing to me is not just the technology, but the product. like how do you actually bring something full pro full featured full product into the market something people were 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 right 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 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 figures philosophy is the exact opposite of our philosophy.
1:08:59And I just don't - Yeah. General purpose robot versus specific ones to the task. Built in a lab, then try to use it in the environment. So I think I'm excited for the attention to the sector. I'm excited for the potential for the products. I'm really excited for the amounts of people that are hitting us up in terms of just applying for jobs because robotics is like cool and it's a second to 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.
1:09:38And, and also like, you know, just like provinces 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 we first created the United States. They should be competing with talent pools, not with tax rates. Exactly. And exactly. And it's like 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 as is like I want my nine year old to be able to create a lawn service business and use robots or.
1:10:15Yeah, for sure. We call that job shepherd. Yeah. Shepherd for robots. I have a cynical take on it. I'm guessing figure. No, no, just on the figure. I mean, I think the most generous take is what he said. Hey, we tried to use these LLMs. It doesn't work for our robots. OK, 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 and neck with OpenAI. 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 robotics group, you know, competing with just Optimus head-to-head and the Chinese companies.
1:11:10I want to be part of the bigger sack. And part of that is, you know, OpenAI 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 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.
1:11:50It might be something for you to think about. Yeah. And also, Jason, there's also other kinds of data sets too as related to this. We are in all these sectors collecting so much information about, and we're basically, in some ways, you can think about the data sets of the YouTube for these industrial sectors as a very valuable data set to be able to train on. I think it's also a a sign that manufacturing is hard. I think it's also a sign there too. Yeah, my take on this is, you know, when you're building a business, when you're building anything of merit, you have to decide what your contribution is.
1:12:21Trying to play other people's playbooks, trying to be the same thing that a relative has already done, trying 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, right? And 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 in an escalating market is people will do unnatural acts. And don't get lost playing games, right?
1:12:50I mean, I think that the creating core value that people are willing to pay for is the recipe, right? And play games, you can get caught up in it. Yeah. And then Chris, I think the thing that's like for the listeners as well, Jason, is like we like to mimic things. From a very Girardian perspective, we like to mimic things. We want to mimic as founders, I want to get as much validation as I possibly can. Look, this person is achieving this valuation. I need to achieve this valuation. I think the lessons that Chris is talking about are only lessons that come from scars, from failures, from understanding the fallacy of pursuing the wrong things and the potential wisdom or lack thereof of folks that seem to have - And what a success.
1:13:35really important. It's like, there's no, there's no replacement for the grit and hard work that, you know, Chris, you know, the people like Chris has, 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 press release needs to compound and propel the product. But if you get confused and you just want to have announcement, announcement, announcement, and 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 another this week in ai is in the books this week in ai.ai to sign up for the newsletter and all the links uh thank you to jake thank you to chris uh they're both hiring go to their websites and uh hardest position to fill jake right now for you uh who do you need robotics engineering perfect robotics engineers if you want to get on the ground floor of a company that's going to go 100x from here.
1:14:34I said that, not him. That's just my professional estimation. And Sidney 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 companydomain.com or.ai. So just, you know, and a lot of times if you build something and share what you built, as opposed to a resume 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.
1:15:08We'll see you all next time. Bye-bye.
From the publisher
This 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.
- Figure's New AI Lab, Hark: Breaking news mid-episode: Brett Adcock announces a new personal intelligence lab.
Learn more about Gecko Robotics: https://www.geckorobotics.com
Learn 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 platform
05:15 Chris Lattner on Modular: replacing Cuda & unifying AI hardware
11:10 Nvidia lock-in, AMD's Rock & why the software stack is broken
19:49 The GPU shortage: how real is it?
22:13 Who challenges Nvidia? Google TPUs, Amazon Trainium & AMD ranked
28:17 China chip smuggling: $2.5B in Nvidia GPUs & the AI cold war
37:43 Self-driving update: Waymo, Tesla's Austin pilot & Chris's Tesla history
42:20 Figure's humanoid package sorting — real or demo magic?
43:47 The best decade for private equity in capital-intensive assets
51:04 Reindustrialization, the trades boom & making manufacturing cool
58:39 Building tech companies outside Silicon Valley
1:06:46 Breaking news: Brett Adcock launches Hark from Figure
1:10:15 Closing thoughts: grit over hype, customers over valuations
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