I think if you Google Brett Adcock net worth, according to Fortune, you're worth $19 billion. So that's a pretty good swing. How does that make you feel? I don't care about that at all. I give zero shits about that.
Okay, so you, Brett Adcock, the short of it is that you were raised in a rural area of Illinois. You started a company called Vetteri, which we sold for over $100 million. Then you took a company public called Archer, which is unmanned flying planes, I guess, helicopters. And now you have a company called Figure, which is worth, I don't know how much, 40-something, 30-something, 50-something billion dollars. You have another thing called Cover, which stops or aims to stop school shootings. And now you have a new thing called Hark, which you've raised money at in the billions of dollars. And you seem worn out. Feeling great. Feels busy, man.
So you've been on, this is your third time on. I think you've been on one time each year the last three years. You said you were telling a story about how, I think it was right when Figure started. You said, I had, I was worth, I don't know how much, tens of millions of dollars. I put almost all of it into Figure to get started. And at one point you were like, I have a mortgage on my house and the rest of my money is in Figure. And some of the money is in Archer, and that's not doing so great right now. And since then, I think if you Google Brett Adcock net worth, according to Fortune, you're worth $19 billion. So that's a pretty good swing. How does that make you feel?
I don't care about that at all. You have zero shits about that. You're a super competitive guy. I think you said something like, I just want to, you said win a bunch of times. Last time we hung out, it was like, I want to win for these reasons. I'm very competitive. I want to kick ass. I think that you definitely have to care about this a little bit. And you actually have to, I think you care a lot about Figure being the biggest company in the world. You talk about, you definitely have this Napoleon energy of, I want to be the best. I want to conquer.
I think any other way I would characterize it is, we're just now, these companies of mine are just now hitting the inflection point. And they're really early. They can be really big. So if it works, this will hundred-X, thousand-X from here. So most of my energy is, how do I make sure that works? There is no flat line here. It's either it goes down or goes up, right? It's binary. Either the robots go out at scale or they don't go out at scale. So in five years' time, it's either going to be a very big thing or very bad. And so all my energy is going into making this a thousand or a million X from where we're at here. And so the pressure's on to really just deliver.
Where are you now? What's the outlook now for the next five years then? I think last time you were on three years ago, we said that, I think I said it. I was like, you'll probably be in the 40 to $50 million valuation range, which I think you are now. But in terms of, you're still lacking output of robots. We still need that to come. Where are you going to be in five years? What's your prediction? I think at a high level, the AI work that we're seeing now is going to be so much, it's going to be a hundred times bigger than the internet. Everything is just working so well. The system is working well. Deep learning works.
And everything's happening faster than I would think. Having done 15 years of software and internet, nothing was happening faster on a trend line. Here it's happening like that in AI. Can you give an example of something that has happened that's blown you away? We started at, so Hark, I have a new AI lab called Hark. About a year ago, I was very interested in this idea of building this AI-to-human symbiosis digitally. Figure is going to be, I think Figure is going to be the max ceiling of AGI, of being able to put that out. And then there's going to be a version of this in the digital world. A human is going to have this AI pairing.
It's going to have, ultimately, maybe your own AI weights, your own memories, maybe your own hardware. It seemed really close. And fundamental to that thesis was, you've got to figure out how to get AI to use computers for general purpose. You would never hire an assistant that can't use a computer. So you've got to be able to give things out to it so it can do everything you can do. Financial models, book flights, order DoorDash, whatever you need to do. You need to be able to do it all autonomously. But only one in a thousand websites have APIs. Most computers globally are on the internet and browser.
My inclination was that within two or three years, you'd have a system that you'd be able to talk to and say, go do this or do that. And it'd be able to go online and maybe use the internet really well, almost like a robot would, where you can move the mouse and use the keyboard. That's what you have to do to solve general purpose around a computer. You can't rely on API or MCP. You have to figure out how to navigate like a human can. Now at Hark, we just released our first model and research preview last week. It's really hard for us to find something now that we tell it to go do on the internet and it can't do. What did you guys do differently than the others?
Because everyone's trying to do computer use, right? I think Elon's got macro hard and ChatGPT had their computer use thing. Everybody's doing it. You guys feel like you've cracked something. What'd you guys do differently? Okay, there's a couple of things we did a little differently. First is, everybody's tackling this from using APIs and MCPs. The reason why OpenClaw got so great was it could only, it couldn't use the browser. It couldn't go on and use DoorDash end to end because DoorDash has no consumer API. So we tried to figure out how to look at a screen. One is, we spin up a virtual computer for every agent. So they don't need a MacBook or anything.
You can just spin up as many of these environments as you want in the sandboxes. And then you need to give it an ability to look at a screen and move the cursor and use the keyboard. Yeah, but I used ChatGPT's computer use and it was doing that. I was like, hey, book a massage. And it opened up a browser and I saw the mouse going. It was trying to type the thing and it would scroll the results. It was bad. It didn't work well, but it wasn't trying to use APIs or MCP. It was trying to use the internet. Yeah, it's got to work well. I mean, that's the whole point. If it goes somewhere, it fumbles the internet. The whole point is,
So that's what I'm saying. What did you guys do to make it work well? Was it an algorithmic breakthrough? It was in our post-training. We have a reinforcement learning process that we think maybe nobody else in the world has done. Well, let's get some context behind this. Okay, so Figure, that is shockingly easy to understand. Humanoid robots, and that business is going to be massive if it works. If you can crack the code, I think you said there's unbounded demand. Hark, I don't entirely understand what that is. Can you explain like an idiot? Because, Sean, you should see, I got the deck and it was just you talking for an hour in front of a screen.
And then there was a list of a team, and it was like a hundred guys who just moved here from China who had the greatest backgrounds ever. And it seemed like you pretty much just raised money because the team was amazing. And that's all the deck was. It was just you talking in a video. Romeo, that's all we had time for. We started. So, okay. What is Hark? Well, let's get some context behind this. Okay. So Figure, that is shockingly easy to understand. Humanoid robots and that business are going to be massive if it works. If you can crack the code, I think you said there's unbounded demand.
Hark, I don't entirely understand what that is. Can you explain like an idiot? Because, Sean, you should see, I got the deck and it was just you talking for an hour in front of a screen. And then there was a list, there was a list of a team, and it was like a hundred guys who just moved here from China who had the greatest backgrounds ever. And you, it seemed like you pretty much just raised money because the team was amazing. And that's all the deck was. It was just you talking in a video. Romeo, that's all we had time for. We started. So, okay. What is Hark?
I think the best way to become successful is to see how other people did it, whether you're going to copy them or just use it as inspiration, because then now you know what's possible. So starting at the age of 24, I did this relentlessly, and I was very methodical about it. And I created a spreadsheet where I tracked roughly 50 people who were uber successful. And I looked at the year that they were born, the year that they started their apprenticeship, and then the year that they started the first thing that made them successful. Finally, the year that they broke through.
And I aggregated all this data along with the stories of what they did to be an apprentice and what they did to finally break through. And I put it together in a database. And HubSpot went and found this thing that I frankly even forgot about, but it did change my life. And they resurfaced it. They made it even better, and they put it into a thing that you can download for free right now. So if you click the link in the description or click the QR code right here, you can see this database that I made when I was 24, and it changed my life. And so if you're looking to become successful, or you're already successful and just want some more inspiration, check it out.
I strongly believe AI will head in two directions, and then at some point maybe even head together. The first is AI out in the physical world that will do everything in the environment for you, like laundry, dishes, cooking, run the supply chain end to end, be in healthcare. The vessel for that is a humanoid robot. It's just a human form, and it will just go out and do everything. You want one piece of hardware, the hardware capable of doing everything, and you put smart AI into it and it can go off and do everything in the world. That's what Figure's working on.
Separately from that, there's going to be this really close digital AI-to-human symbiosis that forms. You're going to have this very special thing that you can talk to that's with you everywhere you go, that will know all your stuff, have access to all your memories, have access to all your accounts and systems, and be able to actually go do things for you like a superhuman assistant. It'll be maybe the closest thing is Jarvis from Iron Man. And it will be able to do, it'll be superhuman in almost every way. It'll know everything about your life. You'll be able to access it at any moment whenever you need it. It'll be in the background helping you out at all times.
If you're on a flight with a short layover and you miss it, it'll already have backup plans, already help you figure that out. It'll just be something with you everywhere you go. We don't have that. We have really good coding agents. We have really good chatbots. But we don't have something that can go off and be my Jarvis. In order to get there, we need to work on the model side. It's got to be better than text chat. It's got to be able to use computers, have near-perfect memory, be able to talk to you just like a human would back and forth, and we have to have vision in the system. It has to really look at the world, understand what you're seeing with it.
I think, secondly, you need to fix the interface to AI. You have AI over here and a human, and you have an old hardware system in between, like a MacBook or iPhone. They were designed 20 years ago. They're complete rubbish for AI. They're not the right interface. So we went out and we are out there designing what we think comes after the iPhone for AI.
And it's like an upgrade cycle. We see this all the time in startups. You guys see it, right? We're in an upgrade cycle with the computers and phones. They're just going to go away. There are going to be new ones. They're going to be all AI computers and phones and systems. And they're going to be great. They're going to be all real time. You can always access them when you want. They'll always be understanding what's happening. They'll always be able to reference things, what's going on. You'll be able to abstract away most apps. You'll probably not have an app store. You'll probably have an AI operating system. It'll be perfect for you.
You'll ultimately have your own weights on your own devices that you'll own and have with you everywhere you go. It'll be a really great pairing. And we hired an incredible team. The team's maybe like 80 or 90 now. The guy that leads hardware design, ABS, previously designed the last several generations of iPhone, MacBook, MacBook Pro. He's a stud. He's great.
So we're designing what we think are the next generation of AI devices that will kill the phone and computer. And then we're designing the next generation of AI models. The models need to get a lot more multimodal. They need to get a lot more expressive. The text and coding is just not enough for us to really have a real AGI feeling with AI.
So we're working on that. We did our first research preview of our computer-using agent that we came out with last week. I think we were top on some of the leading browser or computer-use benchmarks in the world. And it'll keep getting better. This will keep getting better and better. Every month it'll be better and smarter using a computer and faster.
We're working on a couple other different types of technologies internally on the AI side. And then we'll launch the ability to use Hark on a traditional browser and iPhone and Android in about a month. So you'll be able to start using it. And then we'll have hardware coming. We're working on it now. We actually have hardware in the lab now we're testing. It's crazy shit. The stuff is like sci-fi movie hardware.
What do you think those devices look like? People have been speculating because Jony Ive got his shop acquired by OpenAI. And you've seen the videos of the puck, and then this little puck, and then there's an earring. I don't know if that's real or if that's fake. There was a leaked commercial for the Super Bowl. Again, is that real or is that fake? What's the story of that? And then what do you think these devices end up looking like? Are these watches, glasses, something else altogether?
I think I've really changed my mood on this a lot the last year or so, but we have a really strong opinion here internally. Our opinion is that what sits in the middle is devices that could possibly reach a billion units a year in the world. The only kind of things that we have like that in the world right now are computers and phones. They meet that. We call it mega devices. And then you have things on the ancillary around it, orbiting this big thing, that are like AirPods and a watch or things like this. They don't sell a billion units a year. They're like 3% of Apple's revenue. And they help the ecosystem as a platform.
What we care about at Hark is trying to solve what's in the big middle piece. To solve that, you've got to take down the computer and the phone. There's no way around that. So you have to rebuild a new computer or a new phone that's better and replaces your existing systems end to end. And then what's around there is things that you will have, we will even have at Hark, that help with a family of devices that are not a billion units a year but important for the ecosystem. My understanding, right, you're saying the next device, it might be like a phone. It's just going to be an AI-native-first phone, right? You're not going to try to change the form factor.
No, I'm not saying that at all. They're 3% of Apple's revenue. And they help the ecosystem as a platform. What we care about at Hark is trying to solve what's in the big middle piece. To solve that, you got to take down the computer and the phone. There's no way around that. So you have to rebuild a new computer or a new phone that's better and replaces your existing systems end to end. And then what's around there are things that you will have, we will even have at Hark, that help with a family of devices that are not a billion units a year but are important for the ecosystem. My understanding, you're saying the next device, it might be a phone.
It's just going to be an AI-native-first phone, right? You're not going to try to change the form factor. No, I'm not saying that at all. You're going to want to really radically rethink everything. The first version hardware we have now in our lab is unlike anything I've ever seen in my whole life. Okay. What lives outside of here on the edge are glasses and pendants and wearables and things. They're not the main show. In fact, the Meta Glasses are probably one of the worst products I've ever bought. They're just horrible. They're horrible. I can't even figure out how to use it. It doesn't have its own network. It piggybacks on the iPhone network.
It means your app needs to be open on your phone. The pairing's long. It doesn't work well. I can't think of any reason why I would need this thing strapped to my head for 14 hours a day. It's just the wrong device. It's not. The end state is BCI in the brain. And we're going to have AI language devices for the next 10 years before that. And that's the path. And it's not glasses. Glasses, I think, I don't even know if glasses will make our top 10 list of devices. When you and your team are brainstorming, do you have a framework on how you can think outside of pre-existing norms? Because when you're talking about, I literally can't imagine at all what you're talking about.
Let's get down to the substrate level here. First order, what has changed? What's changed is we have a new type of computer, which is, I think of AI as a new type of computer. New type of automation. That's here. The automation can do a few things that are, when we're designing this, we want to design around key principles that could be 10x better. If it's one or two times better than your phone or computer, you're not going to use it. It's going to be literally 10x better. What are things now that deep learning brings that are 10x better? There's a few of them. One is AI can now think and use computers and systems for you, just like a human can. It can talk to you.
It can see. It has visual understanding. It has real-time speech-to-speech. It can use computers and systems for you as close to as fast or around as fast as a human can. Over time, it'll be just as good as a human and faster in terms of success rate. So you have a system that's almost human-like capabilities. It also can have memory, meaning you can put memory into it and it won't forget anything. You're perfect over time. So you have a system that's almost like a human in a box that has all the same affordances a human has.
And it's almost like the ability of, if you could bring a little human around with a computer on your shoulder everywhere you went, that'd be insane. It was only for Sam, though. Only Sam could see it and only Sam could talk to it. And it only was there to help with Sam. And that was your whole life, and it was getting smarter and better along the way and had perfect memory and could use computers and talk to you and see. You'd be like, damn, that thing would be able to do anything you do on a computer. Okay. So your first step with your team is, let's just get rid of any constraint ever. What would be the coolest magical thing?
If we had a little guy on our shoulder that was AI, all-knowing, and could see and hear everything we see and hear and then give advice to us, what is the thing that's going to bring, that's going to fundamentally reshape all this? Okay. And then from there, we got to design around that system. The competitive advantages here are that it has human-like capabilities and it has almost near-perfect memory. It can go back and reference over time. My phone doesn't have that. I put a contact in my phone last week, and I was busy when I was putting the phone number in. And a day later, somebody's like, hey, did you call that person? I'm like, I don't even know the name.
I forgot. I can't even ask my phone. It's so stupid, the whole system is. And then I go in there, order DoorDash like a monkey every day. Now I'm pushing things. I don't do any of that now with Hark. It does it end to end for me on my drive to work. I just say, order me coffee, and it's done. It does it all for me in the background. I don't have to touch anything. It's all abstracted away. And it's like, if you had that little human with you everywhere you go, it would even predict, probably, Brett, you want coffee today? And I'd be like, eh, yeah, I do. Let's order. But you know what? Make it a double shot today. And route it to the Hark office instead of Figure.
I would just, and done. I got it. Let me take care of it. I'll sit like a monkey on my phone for the next three minutes trying to do checkout DoorDash. It's almost like the phone is a tool, and it's a hammer, right? If you want the hammer to do anything functional, you have to pick up the hammer and start swinging it. Whereas the next generation is basically like having a handyman next to you at all times. And so you just tell them, hey, can you fix that window? Let's go fix the window. You don't have to pick up the hammer and start figuring out how to use it. Start there. And then from there, you got to rapidly prototype.
So when you come over, we have designed everything you could possibly think of. We 3D printed it. What were the designs that didn't work but were kind of cool? What were designs that didn't work that were kind of cool? The thing is, we're building many different devices now that cover a pretty wide area of this. We have some pretty crazy stuff that we were designing. So it's not like you look at that and you're like, that looks like this. And that does well over here. So it's not as easy as drawing those parallels. It's quite radical. But we rapidly prototype all this. We have a fabrication facility that does this stuff.
We have a whole design studio where we work on this. You use this stuff over the coming weeks and months. I'll either carry it around with me, wear it, whatever we end up doing with it. And we'll down-select. We had one of the biggest telecom CEOs in the world here that actually helped with the work with Steve Jobs on iPhone 1. And he was here two weeks ago, and he'd just come from meeting Tim Cook. Tim Cook's on his way out of Apple, but he was over there at Apple and came over here and saw our stuff. And he's just like, holy shit, man. This is the first time I've ever seen anybody that could possibly take out the big guys.
Well, is it true to say that with Archer, Figure, and Hark, the hard problem seems like, can I just mass produce this? The hard problem is not that. We think, we believe now the most important constraint to really solve is building a really intelligent robot system to compare it to the world. There's a bunch of robots you can go buy now. You can buy some from China, and you get them and they're complete crap. They can't do anything. You can enjoy sticking around. That's all you can do. And you hit a button and it waves. It's got no hands. It's got nubs. And you're like, what do I do with this thing? It's a toy. And he's just like, holy shit, man.
This is the first time I've ever seen anybody that could possibly take out the big guys. Well, is it true to say that with Archer, Figure, and Hark, the hard problem seems like, can I just mass produce this? The hard problem is not that. We think, we believe now, the most important constraint to really solve is building a really intelligent robot system to compare it to the world. There's a bunch of robots you can go buy now. You can buy some from China, and you get them, and they're complete crap. They can't do anything. You can enjoy sticking around. That's all you can do. And you hit a button, and it waves. It's got no hands. It's got nubs.
And you're like, what do I do with this thing? It's a toy. It's when I bought a DGI drone years ago, and I was playing around with it. Then a day later, I was like, what do I do with this thing? It was hard to set up. It didn't really work well, whatever. I floated a bunch of trees. It just didn't work. I was like, what am I doing with this thing? Robots are like that now, where we can go manufacture a ton of them, but if they're not really smart, it's not really going to be that helpful. We're trying to crack the true human-level intelligence of Figure. We really want to tackle how we make it so I can put it into any home.
It can do every, every, every job I'd want it to do. That's what we're working on. We think that's the largest gap in the schedule of what we need to go solve for. It's that. Then beyond that, people generally sometimes confuse consumer electronics manufacturing with car manufacturing. There's no big company in the world that would say, I'm scared of manufacturing this consumer electronics at high rate if there's so much demand. This is just possible to go do. You can make them. We make a billion phones almost pseudo by hand in the world, and with some automation. But cars is a different story. Cars, you will die trying to manufacture cars.
There's a lot of companies. It's so... and having seen BMW is a commercial customer of us, I have been to BMW and a few other groups. It's gnarly. The reason why cars are so hard is that you can't hold the part in your hand. Phones, you can just always hold in your hand and go change, or whatever, move and hold. Cars, you can't. You physically can't. So you need robots that literally pass it to other robots that put things on the chassis. And if any of those break across thousands or 800 robots, your whole line's down. And so it's just a huge giant robot you're building that's building the car. And with Figure, you can hold any part in your hand.
So I think if we're between cars and consumer electronics, we're over here, closer to the 40% level over here by cell phones. We just made our 1000s EVT robot for Figure 3 last week or week before that. When you say you made 1000, those are 1000 that go to customers like BMW, or you're making prototypes internally? What does that mean? We have two large customers. We have us as an engineering and AI research org that needs robots here. Every engineer needs a robot. Every lab needs robots. We need to do tons of testing. There's just a lot of work we need to go do internally. We call engineering fleet we need to go to. And the second one is go to customers.
So we have to go into both right now. We've actually shipped out robots to our third customer this week. When they go to customers, what do they do? What can the robot do? What maybe can't it do at this point? We do a lot of logistics stuff right now and packages. We have other stuff we've done in manufacturing. Mostly just manufacturing and logistics is what we've done in the past. But we're also talking to folks about other industries. And at this point, when it goes to a customer and it's doing, I don't know what you said, packaging work, what is that? Sorting or carrying, or what is it doing?
They just did a live YouTube video, and they had hundreds of thousands, maybe millions of views, of people watching this robot sort packages off of a conveyor belt. Yeah, I saw that. So is that the type? Is that, give me an example of one of the jobs. Yeah, that's an example of very close to one of the works we do. Is that customer like, oh, this is awesome because I can't find the labor to do this. It's too expensive to humans. This is way cheaper. Or is it just like, hey, look, today it's not faster, cheaper, or better necessarily, but it's an investment in the future where two years from now that cost curve is going to work and it will be faster, cheaper, whatever?
No, no, no. The pitch is they come to us and they're saying we're dying with labor. We have really high turnover. Some areas have over 100% turnover per year. It's really expensive to find talent. We have a large talent shortfall. The talent's really expensive. Wages are going up, and we don't have a solve for this. We can't figure out how to automate all this work, and we need you to come in and help us. We have an ability to make a lot of good money in our contracts, and the customers make really good ROI on this. You've got to think a robot can do multiple shifts per day, work seven days a week. We can have a lot of time.
The task you saw on the logistics line that we live-streamed was actually a real use case for one of our customers. That needs to be done at three seconds a package, and this needs to be done five hours a day. I think it's five days a week. We did that 200 hours straight at 2.9 seconds a package. So we're already at human speeds. We're already doing this here. Now they're already having ROI, and we're now in the early stages of getting these out to these customers and scaling it up. Over time, it will just put billions out to these groups. Can you help me with the truth versus fiction?
Because one of the weird things is, as an enthusiast or a layperson who's excited about this future, you can't really, it's really expensive or hard to test this, right? So I'll see a Chinese robot, and it's 20 grand if I want to buy this robot. I have no idea really what it can do. I see Elon go out there and say, we're going to build a million of these things in the next year. We're going to ship them. Then you get 1X, and they're showing their hand, and they're like, look at our hand. Look at this. This is the best hand you've ever seen.
And then there's this service in San Francisco where they'll send a robot in to clean your apartment, and they're like, yeah, that works today. So can you help me separate fact from fiction? It seems really hard compared to most categories where I can just try the products quickly online or buy them and test them out. One is the amount of noise in the market for signal is out of control. There's just so much bullshit out there in the market. It's really hard to tell what the hell's going on. So let me summarize what I think is the most important and work backwards.
What I think the most important thing to do is to be able to ship robots autonomously at scale in useful work environments. They can cook you dinner, clean your dishes, make your bed, run the supply chain end to end, work in healthcare, build a building, do logistics, that sort of stuff. That stuff requires fundamentally onboard AI that you can run, so you can do autonomous work. You can't solve it with code. You need to do it autonomously. You need to do it over long periods of time. There's just so much bullshit out there in the market. It's really hard to tell what the hell's going on. So let me summarize what I think is the most important and work backwards.
What I think the most important thing to do is to be able to ship robots autonomously at scale in useful work environments. They can cook you dinner, clean your dishes, make your bed, run the supply chain end to end, work in healthcare, build a building, do logistics, that sort of stuff. That stuff requires fundamentally onboard AI that you can run. So you can do autonomous work. You can't solve it with code. You need to do it autonomously. You need to do it over long periods of time. And you probably need to move around and use something in your hands and move, move, move stuff through the world.
It's like you got to do stuff economically, you got to move electrons around. So I think at a high level, what we care about is not the best robot that's doing backflips and running the fastest mile or dancing or in a parade or running outside in the woods. We don't care about that stuff. Dude, I can't wait till I see a figure on a smoke break at the B&W factory. Like, I could have been great back in high school, but I blew it. Now I'm working at a B&W factory. I've made jokes with you before where I was like, you started with Vetery, which is just a job recruitment thing. Now you're on these world-changing things.
And you were like, well, Vetery actually is world-changing. And here's why. And you gave this pitch. It was very good. You're very good at pitching. You're very good at raising money. You're very good at being charismatic and convincing people of stuff. When you're crafting a pitch to recruit and convince people to change their lives, to uproot their lives and to trust in you and to come and build a company, how do you craft that pitch? And what was that pitch for some of your companies? I mean, most of all these are online. The Figure master plan is on the internet, on the site. Arshers was up for a long time. I posted about it.
I think deep down, I really want to find folks that really care and are obsessed. And I think most of my time is not, I know you want to know about the pitch, most of my time is trying to find those folks. I found that even in the Bay Area, where it is probably the richest AI and engineering folks in the world, 90% of everybody out here is not good at their jobs. How do you tell who's good and who's not? I technically assess them. All of them. Yeah. To do that, does that mean you need to be as good or better than them technically to be able to assess somebody? I need to know certain guiding principles.
For instance, I need to know if you did the work or if you watched somebody do the work. If you've done the work, it's a scar you carry with you. It's dug into you. You know all the details. You can talk about it freely. You don't need to think. You'll understand how to reverse engineer everything you've done and discuss it. The folks that haven't done it can't do that. They can't even go, they get one layer and they just constantly blow up. They can't talk about it. They don't know why.
Out of a hundred candidates who sound good, how many, their resume looks good, the recruiter thinks they're good, out of a hundred candidates, how many would you say actually hit that bar? I'll give you an example. We have a really challenging process to go through to be a mechanical engineer here at Figure. You have to be able to build actuators from scratch. There's bearings and motors, and we have a gearbox. We have other sensors inside the system. It's very compact. It's just a very difficult thing to do, and really hard requirements. We've been doing 10 case studies a week for six months and have not hired anybody. That's insane. It's insane.
But when you do get someone qualified and their competing offers are companies that are larger or more liquid than you, and the offers are, I think they're tens of millions of dollars a year, right? The AI side is certainly like that. The AI side has gotten, and it's mostly all driven from Meta. I've never seen, I thought maybe Meta was paying these people like a year ago and it would go away. They've not stopped. So what are they like? What's a crazy story that you've heard? We gave an offer to somebody that was really senior. They were coming from X at AI. X at AI completely blew up. Everybody just laughed about it six months ago.
It was just like Macro Heart got fully disbanded. Basically, a bunch of stuff happened. We interviewed a pretty senior guy on the AI infra side. It was great. I think I gave him a really good package, like a Series A stock at Hark. And it was, I don't know, 15, $20 million of stock. Over four years? Over, we do five for my companies in the early days. Then we transition to four a little bit later. So we're still at five. And I was like, I think we can 10x Hark here pretty quick. And so I was like, okay, you have 15, 20 million. I think 10x, you have a few hundred million dollars. I mean, 10x more time, you have a few billion dollars. And I think we can do it.
I think we have to, obviously it's going to be hard, but I think we can do it. And he got an offer to go to Meta for 36 million over four years of RSUs. And he was like, it's kind of guaranteed cash. I go there and I have to wait. It's maybe like $200 million at Hark or $20 million or maybe like 36 for sure at Meta. And he left and went to Meta. And they've been doing that. Every candidate we speak to is making some absurd, absurd thing. It just hasn't stopped. They've been at it for like a year, a year, and they've been buying talent. They've been buying their way into the AI race. What do you think of that strategy? Even if you kind of hate it, do you respect it?
Do you just think it's a fool's errand? What do you think of that? I really like it. I think the AI space is, what I found is the folks that really understand how to do language pre-training and mid-training and post-training, especially pre-training, and the infra around supercomputing and data and evals and all the right stuff you need to get put in place to do that right, and the amount of folks that really understand the right kind of recipes that transformers do well in and around MOE or whatever you're going to look at, I think it's really hard to find. It's actually really hard to find the actual folks that know what they're doing.
I think there's probably, my rough calculus now is probably like, or rough back of the envelope, is probably like 20 to 30 people in California who know how to build really good AI models. Wait, but is that trickling down? So you said that there was a senior guy, but are even some of the less-than-senior, the 20-somethings, the young 30-somethings, are they still getting eight figures a year? No, the junior guys, the guys in their 20s, the late 20s or something, are making a few million total. So they're making like 200, 250 in base. They're making another million or whatever in a year in RSUs every year.
And so they're going to pay like 750 to 2 million or so range per year. And that's been driven up by Meta. But then all of the other labs have followed comp. When I asked you, what do you think of that, you said, I like it. So you said that there was a senior guy, but are even some of the less than senior, the 20-somethings, the young 30-somethings, are they still getting eight figures a year? No, the junior guys, the guys in their 20s, the late 20s or something, are making a few million total. So they're making 200, 250 in base. They're making another million or whatever in a year in our shoes every year.
And so they're going to pay a million to 750 to 2 million or so range per year. And that's been driven up by Meta. But then all of the other labs have followed comp. When I asked you, what do you think of that? You said, I like it. Were you being sarcastic, or are you saying, no, actually that is smart given how hard it is to get this talent? I think it was really smart. And I would have done the same thing if I was Mark. I would have bought my way into the race. And I think he's doing that now. I don't think I would have done that. I want to understand it. And I want to first order, find the right folks that really care deeply about this and not hire mercenaries.
And so he hired a bunch of mercenaries. They're just purely money-driven. They came over there. Then nobody wants to go to Meta. They're going there because they're getting paid a guaranteed RSU package by sitting around. And what's happening is you don't need a thousand people or 500 or 300 to design AIM models. You make a really good team of 20 or 30 or 40 people. And you can get there without doing this. And those people probably would care more deeply about the mission and where you're at and be more committed than just to purely throw money at the problem. But I think if I was, I think it was a really good strategy and it's working.
I think hats off, really good execution, their recruiting efforts and how they're structuring this stuff. And I think it's paying off for them. Jury's still out if they can actually ship real products. I think the problem I have with those groups is they've traditionally not been able to do things new well. I think Facebook is probably going to, Meta is going to go down as one of the greatest acquirers of all time. With Instagram and WhatsApp and different ways, they've bought their way into those spaces. But if you look at the Ray-Bans and everything they're doing, it's just not great work. And so I think the question really is, how do you really do great work here?
I think we're even talking, we're using the Hark system right now, and it's so good. It's so much better than anything I use today. You got to send it to us. Yeah, can we use it? Well, yeah, we'll get you guys early on that. Yeah, for sure. It's like research preview. There's 500 PhDs and then me and Sam. Yeah, exactly. No, every other platform, Hark, what's the weather outside? I can answer that. Yeah, no problem. So I think what I'm trying to say is every week there's five or 10 junk AI slop startups or things that are coming out. They're just not very good. This whole space has gotten to a point where there's just not great things coming out the door.
I think the stuff in coding is probably really excellent right now, but everything beyond that is just not great. On January 1st of this year, you made four predictions for the year. I want to check in and see how you think they're going. First one. Number one, humanoid robots will perform unsupervised multi-day tasks in homes they've never seen before, driven entirely by neural networks, long time horizons, going straight from pixels to torques. How are we doing on that one? On track, off track, or done? On track. On track? Yeah, four months. Yeah, I see every day what we're doing. We're on track. The hard part here is we already do pixels to torques.
It just means we're taking camera feeds and we output where to put the motor, put the, we want to tell the motor what to do to get the hand in the right spot or the joints. So we're going to do that. Getting into a new house that's never seen to do work, that's the hard part of this problem. We're working on that. I'm working on that every day. It's where I spend about three, four hours a day, every single day, seven days a week on this problem. So if a figure robot showed up in my house, what would it, what's the bottleneck right now? It wouldn't know what to do. It wouldn't know where to go. It wouldn't be able to fine-tune, handle my dishes. Where would it suck for me?
We can fold laundry as an example, but then going to a new place where we're folding in a different location with different lighting and maybe different table height and different types of laundry and different types of scenarios it's never seen before, the model's out of distribution. It doesn't know what to do. It's like if you removed all the pyramid data from the pre-training of LLMs, they wouldn't know how to talk about pyramids. And we don't have enough of that data out there. It's not on the internet. So you have to go out and collect it.
So what we need to know is how much of that data we have to go sample in the world to be able to train the model to go into your house and say fold clothes, is a good example. Hey, stupid question. Why do all the robot companies care about folding clothes and doing laundry? Wouldn't it be commercially better just to say, hey, we're going to build the best warehouse worker because there's already 20 million of those in the world and that represents this much billions. And of course that buys us the runway to get the robot folding robot done. But why do you care about that at all today?
Why not just industrial work that people don't want to do, companies need done, they're ready to pay? And it's not like my home where there's all these other sensitivities. Why do you guys care about that right now? We didn't care about it in the past. When we first launched, we're like, we're going to basically do the commercial side to pay for the home long term. And that was the strategy. It made a lot of sense. There's, we can charge a lot more in the commercial market. It's much easier to do. It's lower veritability. We're in a little work site. You just work 24-7. Just so much simpler. What I've learned now is that the home is super solvable today.
So we can not go work on that problem and just sit here and work in a warehouse. But me or none of my guys want to solve that problem. We want to solve a robot that can go into any environment just through language and do work. We want to be the first to do that. You can probably do that with 100 robots and a 50-person team. So that company overnight would be a trillion-dollar market cap. That sounds good. Do that. We're doing that. That's what we're doing. We're going to solve that. I think we'll be the first. We call it solving general robotics. And iRobot, don't they attack the humans? I don't remember this movie very well. Yeah, don't worry about that.
Okay, not that part of iRobot. Who could win in a fight right now? Can a human still win? Yeah, a human can still win. Okay. Where are the other predictions? Other prediction. One you had on here. Daily AI usage will shift. People will move beyond text to highly multimodal, voice agents with persistent memory will become common, which will push AI closer to the synthetic human intelligence we've imagined in sci-fi. We're doing that at Hark. We'll ship that in a month, our first version of it. It'll get better and better. I think we're on track for that. Have the labs ever, has ChatGPT or Claude, have they ever released the data on this? I use a ton of the voice things.
Sam, do you use the voice stuff a lot? Yeah, I don't type really at all. Yeah, I wonder. It's probably already a huge percentage. Okay, not that part of iRobot. Who could win in a fight right now? Can a human still win? Yeah, a human can still win. Okay. Where are the other predictions? Other prediction. One you had on here. Daily AI usage will shift. If people will move beyond text to highly multimodal, voice agents with persistent memory will become common, which will push AI closer to the synthetic human intelligence we've imagined in sci-fi. We're doing that at Hark. We'll ship that in a month. And our first version of it. It'll get better and better.
I think we're on track for that. Have the labs ever, has ChatGPT or Claude, have they ever released the data on this? I use a ton of the voice things. Sam, do you use the voice stuff a lot? Yeah, I don't type really at all. Yeah, I wonder. It's probably already a huge percentage. It's gotten to the point where offices need to change. These open-air offices that are popular in startups are kind of whack right now because I want to talk in private. Yeah. Yeah, a lot of engineers have microphones now where they're whispering, and they're just in hushed tones whispering to their computers. Yeah, I was talking last night, and I was like, Claude, why am I so indecisive?
And then my wife was like, gay. She was like, bam, dude, she can hear everything I'm talking to Claude about now. Yeah, no, I talk all the time, but it's embarrassing. Yeah, speech still sucks. It's still not great. It's almost like you have to set up, you have to go there, you have to turn on, it doesn't really remember what you just talked to it about. It can't do tool calling and computer use very well. It's just limited, and you have to use it for a certain session. I don't know if we'll hit it this year, but certainly in 2027, you will hit a full human Turing test with speech.
You'll be able to take a phone call from an AI system on your phone, and it'll be able to fool you guys. I'll be able to have a human call you and a robot call you, and I don't think you guys will be able to tell the difference. That's a 2027 event. I feel pretty strong about it. All right. What's the third and fourth? You had, over the past 10 years, school shootings have increased by 10x. In 2026, the first full scanning system capable of detecting weapons from a 20-foot standoff will be built and beta tested in a K-12 school. Oh, man, we'll have our first, we're building our full-scale system starting in October. And I think we'll bring it up before the year.
I don't know if it'll be at a K-12 school. So we might miss this one by a quarter. Do you have a separate CEO running that one, or are you the CEO also of that company? I'm going to be in market by now, and I pivoted the whole technology system about a year ago. We were building this, I found a way to do everything very cheaply in silicon and chips and reduce the price by 90%, make it much more scalable, make it work better. And we pivoted. The problem was that the fabrication times for designing our own chips and getting them out took about a year. So we just got those chips a couple months ago. And we're testing them, and they're awesome.
Now we need to make more, and there's another six-month lead time to make even more of them. So we're dealing with real silicon, long fabrication of very difficult chips. Lead times now. We'll be out of this at some point, but it's not chips you can go off and buy off a shelf. These are custom-designed cover chips that nobody's really ever designed before. We had a special fabricator in Europe that had to go make them, and it took about a year. Hey, you are firing on all cylinders right now, professionally, it seems. And I actually would like to know, what's the trade-off for the life that you're living right now?
Because you're very optimistic, you seem excited, but what are all the trade-offs? Yeah, about five years ago, having kids and the companies, I had an issue where I think of my life as three pockets. I have work, I care deeply about my family, I have three kids. They're pretty young right now. And then I have the other stuff, where it's like a friend's in town, or you need to go to the annual golf trip, or it's a bachelor party, or it's a wedding in Europe, or whatever it is in this bucket over here. And I felt like I needed to make a decision. If I want to do any of these well, I can't do all three.
And what I wanted to do really well is family, and I want to do business stuff. I want to be A-plus in those areas. And so I basically stopped the third bucket. I don't do anything anymore over here. I had a friend in town from college. It was my freshman roommate. And he was like, I'm in town for 10 days in the Bay Area. I want to meet up. I haven't seen him for a long time. It'd be great to get a coffee. I was just like, oh man, I'm going to be real. I don't have any time. I can't meet you. He's like, I'll make myself available, come to you. I was like, I literally have no time. Every minute I'm away from one of these two is a minute I'm away from my family or work.
And there's almost a limited amount of time I can put in both those buckets. Can I ask you about your workflow? You made a joke. You're like, I don't use Slack. If you're comfortable, could you just hold up your phone right now? What's on the home screen of your phone? What's your app setup? What do you got? All notifications. Oh, well, you got to open it up. Oh, what's my, my. So you have just tons of texts. This is like my, those are all, I think, Slacks and texts. Yes. I mean, I use Slack. I just can't get through it during the day. I have Hark going through it. And then Hark texts me. I think it's important. I need to look at it with a link. So what's your setup like?
What's your day-to-day when you're, do you use a laptop at all? Are you only on the phone? I use a laptop, yes. Laptop a lot. Laptop and phone. I would say I use Hark now for all my AI stuff end to end. Even tracking stuff I'm doing on engineering projects, recruiting, all of it. I do a track, it's in my email. It's in my Slack. What about your to-do list? That's all in Hark. Hark made us all that. So what about before Hark? My to-do list was done in a Google Doc. I had a doc called replanning, and it would constantly keep updating every week. I would come in on Sundays usually and update my plans for the week, and I updated there. And what about health?
Are you doing anything for health? Yeah, I've gotten access to some special doctors and things now where they basically send you through the quarterly blood tests and the whole body scans and the CT scans of the heart, everything. And it's been honestly pretty unbelievable. What was unbelievable about it? The amount of data you get back and the thoroughness of all this. For instance, you can get a CT scan of your heart for like a hundred bucks. I think you can basically prevent heart attacks. You can get a full-body MRI, and I think you can have early cancer detection. A lot of blood work can find some anomalies that you can go fix, and better for your health.
So there's maybe like a dozen of those. Yeah, but the solution to all those things are probably things you're unwilling to do. It's like, you're probably willing to eat whole foods, but it's like get up, go for walks, exercise. And that was outside of your buckets of focus. Yeah. Unfortunately, I haven't been able to have enough time to exercise enough. But, eat right. What was unbelievable about it? The amount of data you get back and the thoroughness of all this. For instance, if you get a CT scan of your heart for a hundred bucks, I think you can prevent heart attacks. You can get a full body MRI, and I think you can have early cancer detection.
A lot of blood work can find some anomalies that you can go fix and better for your health. So there's maybe a dozen of those. Yeah, but the solution to all those things are probably things you're unwilling to do. It's like you're probably willing to eat whole foods, but it's like get up, go for walks, exercise. And that was outside of your buckets of focus. Yeah. Unfortunately, I haven't been able to have enough time to exercise enough. But eat right. I've eaten pretty well now. Yeah. Listen, someone's got to give. I can't sit here all day. I got to go work. I love, I want to go crush these businesses.
When you wrote in our prep doc, you said, I went all in on my first three startups and I pretty much hit rock bottom every year. Can you describe what you mean by rock bottom, and what is your method of dealing with rock bottom? What's the conversation you have with yourself or the entrepreneurial strategy you have when you hit those lows? Yeah. I basically, for 15 years, was always running out of money. At Vetteri, we had a couple of pivots early on. We ended up raising a $500,000 convertible note in 2015. At that point, I think I took out a 50- or 100-thousand-dollar loan. I was not paying myself a salary. I was in New York City. I was so broke. I was in the negative.
We raised the convertible note. It did not look great. And I think it was six months later, we launched the marketplace at Vetteri, and it completely took off. And then a year later, we sold for 110 million. And I think that period from 2012 to 2017 was like, I had basically debt. Things weren't working, and it's hard. And what's the inner monologue? What do you tell yourself? The inner monologue is, this really sucks. Super painful. I think at that point, you just got to go day for day. You just got to make it day. When things get really bad like that, you got to build a punch list, and you just got to get through it. The only way out is through.
So you need to build a punch list, and you need to get to day to day. You got to go day to day. You can't go week to week. Two days. Can't look at Friday. You got to get to the next day. Pile through it. I was training for this ultra marathon, and I hate really long-distance running. And I read this story about this guy who helped me. And he was like, all you got to do is pick something. It doesn't matter if it's a hundred feet or half a mile in the distance. Even though you have 49 miles left to go in the race, just pick something half a mile away and tell yourself once you get there, then you'll consider quitting.
And then you get there and you're like, okay, maybe I have a little bit more. And you pick another thing just 200 yards away. You're like, okay, I'll consider quitting when I get to that. No, I was like, great. I think it's exactly how I thought about it. But it was like, okay. So then I sold Vetteri, and then I was doing Archer. It's like, oh man, it made 110 million. It'd be 12x all the adventure guys. And then I was like, we're going to raise money. It'll be fine. And everybody's like, what are you doing? For Archer? Yeah. Everybody's like, what are you doing? We're not going to fund this. What are you talking about?
How do you fight that inner monologue where everyone says you're stupid and wrong and this is silly. Just go do software. It's coming from a place of conviction. Like I know I'm right because I've done the work. I understand it. I'm on the floor. Yeah, but the odds are still against you, right? But that's the game. When you play this game, 95% of everybody around you will fail. I remember with Vetteri, we started at the NYU incubator. I was so excited. We got in one of the semesters, and there were, I think, 50 companies that were there. We started in Soho. It was great. We had a great time.
I think if you look back, five years later, me and one other guy are the only two people that made greater than $0. One other team. Forty-eight companies went to zero. And I was just like, holy shit. If you're around this game for long enough, everybody dies, and that's everywhere. It's been like that for 20 years. And I've been watching around you. You see all the TechCrunch stuff and things on X about people raising money and all this, and over time, that all just kind of fades away. And it's just really brutal. So I had to, you know, I bought a house, and I had to put all the rest of the money into Archer. And then I had a stock lockup.
So even while I was coming over to Figure, the stock was unlocking. I was funding Figure with stock from Archer because I had no other cash. Stock was coming down. The stock was literally like a falling knife. Well, at that point, it was just like, I think it went from like 10 bucks to like two. And it's since gone up a lot, but I had to take a second mortgage on my house to even fund Figure. We asked you one of your philosophies, and you said, I believe that doing hard things is easier in many ways than doing easier things. Can you explain? Everybody's trying to do easy things. When you work on harder things, you have, generally, first order, less competition.
You have probably, a hard thing probably means it could be a potentially really big TAM, really big exit if it works. You have folks that probably want to work on hard things, probably the best overachievers in the world that want to work there. Generally, hard things have this binary payoff for investors. They really want to fund those things because it could have a 100x return for the portfolio. And I think there's a nonlinear curve to scaling here, of the difficulty here, meaning I think a lot of the hard things are not 10 or a hundred times harder.
I think the hard things sometimes are two or three or four times harder, maybe five times harder, but they're not a hundred times harder. So you might have a hundred times better payoff, but it might be three or four times harder. I'll give you an example in robotics. I think largely building quadruped robots, four-legged dog robots, versus humanoids, probably humanoids are three times harder than that, maybe four. That's it. But there is really no, I don't think there's really a real market for those dogs. I think it's just a niche thing. I don't think there's a real business for it. And I don't know anybody that really at this point wants to spend a lot of time on that.
So you do humanoids, it's like, okay, three times harder, but it's probably a million times higher payoff, probably a million-x or billion-x higher for that. You know what I mean? For investors, for humans that want to work there, get stock, and participate in upside. And for everything else, why would you ever want to work on four-legged dogs? What economic value can a robot dog bring at scale? If you really understand it, I think everybody's trying to do the easy work, and it just becomes really difficult. But there is really no, I don't think there's really a real market for humanoid, like those dogs. I think it's just a niche thing.
I don't think there's a real business for it. And I don't know anybody that really, at this point, really wants to spend a lot of time on that. So you do humanoids, it's okay, three times harder, but it's probably a million times higher payoff, probably a million X or billion X higher for that. For investors, for humans that want to work there, get stock, and participate in upside. And for everything else, why would you ever want to work on four-legged dogs? What economic value can a robot dog bring at scale? If you really understand it, I think everybody's trying to do the easy work, and it just becomes really difficult.
Look at all the AI slop, open claw harnesses out there today. It's all crap. It's all not good. They're all going to go. I don't think any of them will make it long-term. You might have some consolidation here and there for aqua hires and stuff, but that's going to go all the way. Dude, you talk in so many absolutes. Has that not gotten you in trouble ever? I don't know. Mark my words. You think, have you guys even used open claw since then? No, I don't know how to. You use open claw? I never trusted open claw to set it up. I was not going to do it. I used to use it. I don't use it anymore. It's not very good. The wave's over. I don't know.
I'm just trying to say, I think the most important thing you can do as a founder is to think through what you're going to actually go do. Because you're going to spend the next 10, 15 years doing it. And it'll map the whole course, the probability course. It's a probability-weighted decision of potential outcomes. Well, but you're talking about a very particular game. For example, as you've said, you're like, we're going to be a trillion-dollar company or we're going to go bankrupt. It's binary. Most business is not binary. You're playing the game where binary is the outcome, and that's what you like, but it's not like that for a lot of people.
For a lot of people, if they can build a really cool $10 million a year business, that's a massive home run. Is it? If they can do that well. And you look back when you're 70 or 80, would you have asked the same person, hey, you built a really cool $5 or $10 million business. You did it for 30 years. You didn't do anything else. You didn't try anything else while you were doing it. You just worked on that business. Would you have gone back 30 years ago and tried to take a bigger swing? Would you have taken a different swing than Vetteri? Vetteri was like that. Vetteri is my bridge. I sat inside of Vetteri for seven years.
We literally built a marketing automation tool for us internally. And then a year later, I was like, oh man, look at this. It's outreach.io. And it was a billion-dollar company. We built that internally a year or two prior. And then watching all this different stuff happen, I was like, man, we actually did some of this work internally. It's valued less than some other groups out there. This whole decision of what you spend time on is super critical for startups. Assuming there's a, and I do think startups are, I think it is kind of binary.
Even the guys that get the $10 million, there's probably another 90% of those folks that just didn't make it when they were out there trying. So I think it's just hard. And I think, dude, kudos to guys getting five or 10 million in business. That's hard. Especially doing that with maybe a little bit of capital or no capital coming in. Let me ask you real quick about your other stuff you've seen. So I'm sure because you're doing really interesting work, you meet other founders that are doing interesting things in unrelated spaces. So not humanoid robots, but equally cool, interesting peeks at the future.
I think you've probably seen more of the future than us, and definitely more than most of the listeners. Can you give us anything that you've seen or heard or read about, a founder you've met that's doing something that's like, oh yeah, you guys realize, right? The future is actually going to look like this, and it's just not evenly distributed for all the rest of us yet. I like looking at, I like trying to think through this problem of what the world is going to look like in 30 years. Where everything's headed. I think we have an energy problem. Not an energy consumption, a generation problem.
So how do we, maybe both, but ultimately how do we generate more energy as a species? I think there's a secular trend here that you want to go ride and really help. And I think there's a lot of work done correlating this to standards of living for humans. So I think there's a lot of work here. What is that next generation? Is it solar? Is it wind? Is it nuclear? And then there's a bunch of different traits inside of here for fusion and fission and the rest. I think it's a really exciting area. I think it would take a long time, but I think you need really great entrepreneurs solving that stuff.
I think AI is just going to dominate a lot of stuff in the next 10 or 20 years for all of us here. I think it's going to be like a hundred, we all lived through the internet. I think it's going to be a hundred times bigger than the internet. I think it's going to be so, so big. AI is going to eat the whole internet. It's going to eat it all up. And I think it's going to be an extremely large trend, both physically and digitally. Are there any products that you're looking at or companies that you're looking at now that are not already mainstream that you think are good examples of what you're talking about? We're working on this stuff at Hard Configure. It's unclear.
We're still in this spot where it's really not clear who's going to do well here in this stuff, but we're in this foggy area for a lot of this stuff where there's been no breakout here. There's been early wins and early breakouts, but there's a next leg here that we're going to go through. And we're in it now. I think we'll know more in the next year or two what that really looks like. But I've used every AI device out there. Haven't been super thrilled. I don't know if you guys are seeing stuff in the market for these types of things, but I haven't been like, man, this is a crazy great product. I like the small stuff.
Whisper Flow has pretty meaningfully changed how I communicate. That's been pretty cool. I think that's been my big standout the last six months. What about, last question, what about people who inspire you? I think I really admire the folks that are fully dedicated in their craft. You watch the Michael Jordan documentary. He's just like, I just want to be the best in the world at this. I think startups have the same thing too. And I think first and foremost, from what I can read, I'd never met Steve Jobs, but my Lord, stories I've heard and everything else, the guy was just an unbelievable operator and product-led founder. I've also got to know Jeff Bass was pretty well.
He invested in Figure, and he's been here a lot of times. And I think Jeff has been a really good soundboard for a lot of things we've gone through. I had Jensen in here last week again. We are fairly close. What about last question? What about people who inspire you? I think I really admire the folks that are fully dedicated in their craft. You really watch the Michael Jordan documentary. He's just like, he's just like, I just want to be the best in the world at this. I think first startups have the same thing too. And I think first and foremost, what I can read, I'd never met Steve Jobs, but my Lord, stories I've heard and everything else.
The guy was just an unbelievable operator and product-led founder. I've also got to know Jeff Bass pretty well. He invested in Figure, and he's been here a lot of times. And I think Jeff's been a really good soundboard for a lot of things we've gone through. I had Jensen in here last week again. We are fairly close. And I think Jensen's just an unbelievable operator as well. He's very hands-on and has a very unique way of managing NVIDIA and his organization the last 30 years. And I think he's done a lot of really good things. What advice did Jeff give you that was meaningful? Jeff said, well, last time he was here, he's like, listen, you're at a really interesting
period, because you've figured out how to do this somehow. In the next year or two, you're either going to figure out how to break through and really get this working in a bigger way, or you won't. And this is game time for you now. And you gotta just get wired in and figure out how to break out and make this thing work and scale it. And you're at a really interesting point. I don't know how you got here, and I don't know why you got here, but you're here, and you need to figure out how to, your next, you're on the big field now, and your next big push is going to make or break it. So I think he's largely right.
I think we're, we got robots now doing this stuff autonomously with AI models, which is crazy. I think four years ago, you'd been like, I've been like, no way, no way you could. Dude, four years ago, I came to your office and you just had a knee working. And I was like, oh, that's a knee. That's cool. It all was, it was a knee. You had five engineers. You're like, this guy just got done building the Tesla X or Cybertruck or something. This guy did this amazing thing. This guy cured cancer. Look how the knee moves and the ankle has dorsal flexion. And we were just sitting around looking at this knee, and that was the coolest thing.
I know, it's like, and then now we have AI that's working on a humanoid robot. We're taking in cameras, it's doing inference on board. It's operating where all the joints go. It's unbelievable. And it's crazy. It works. And yeah, the next leg up is just making that work at higher scale. So I don't know. It's been great. I think it was, I don't know. I think those are some really good folks to look up to that really love their craft deeply and really care. Well, Brett, I think it's time for you to get back to work, my friend. Great. Thanks, guys. It was good to see you again. Thank you so much, dude. All right. That's it. That's the pop. So congratulations. congratulations
congratulations congratulations congratulations congratulations congratulations congratulations congratulations congratulations congratulations Thank you. So how we, well, maybe both, but like ultimately how do we like generate more energy as like a species? I think there's like, there's like a, there's like a secular trend here that you want to go ride and really help. And I think there's, um, a lot of work done correlating this to like, like standards of living for humans. So I think there's a lot of work here. Like what is that next generation? Is it solar? Is it wind? Is it nuclear? Like, and then there's a bunch of different traits inside of here for fusion and
fission and the rest. Like, I think it's a really exciting area. I think it would take a long time, but you need like, I think you need like really great entrepreneurs like they're solving that stuff. I think AI is just going to dominate a lot of stuff in the next 10 or 20 years for all of us here. I think it's going to be like a hundred, we all live through the internet. Like I think it's going to be a hundred times bigger than internet. I think it's going to be so, so big. It's going to, it's going to, AI is going to eat the whole internet. It's going to eat it all up. And, uh, I think it's going to be an extremely like large trend, both physically and digitally.
What are there any products that you're looking at or companies that you're looking at now that are not already the mainstream that you think are good examples of what you're talking about? I mean, we're working on this stuff at Hard Configure. Um, it's unclear. We're still in this spot where like, it's really not clear who's going to do well here and this stuff, but we're in this like foggy area for a lot of these stuff of like, there's no been no breakout here. Uh, there's been early wins and early breakouts, but there's like a next leg here that we're going to go through. And we're like, we're in it now.
I think we'll know more in the next year or two, what that really looks like. But, um, I mean, I've used like every AI device out there. Haven't been super thrilled. Um, I don't know if you guys are seeing stuff in the market for these types of things, but like, I haven't like, you know, been like, man, this is like a crazy great product. I like the small stuff. Like, I like whisper whisper flow has like pretty meaningfully changed how I communicate. Yeah. Um, that's been pretty cool. I think that's been my big standout the last six months. What about last question? What about, um, people who inspire you?
I think I really admire the folks that are like fully dedicated in their craft. You really watch the Michael Jordan documentary. He's just like, he's just like, I just want to be like the best in the world at this. I think for like first startups have the same thing too. And I think first and foremost, like, you know, what I can read, I'd never met Steve Jobs, but like my Lord, like stories I've heard and everything else. The guy was just like an unbelievable operator and product led founder. Um, I've also got to know Jeff Bass was pretty well. He invested in figure and he's been here a lot of times.
And I think, uh, I think Jeff's has been a really good soundboard for a lot of things we've gone through. Um, I had Jensen in here last week again, like we are fairly close. And I think Jensen's just an unbelievable operator as well. He's very hands-on and has a very unique way of managing NVIDIA and his organization last 30 years. And it's, uh, I think he's like, I think he's done a lot of really good things. What advice did Jeff, uh, give you that was meaningful? Jeff said, well, last time he was here, he's like, listen, you're at a really interesting period. Cause like you've figured out how to do this somehow in the next year or two, you're either
going to figure out how to break through and really get this like working in a bigger way or you won't. And like, this is like your, it's game time for you now. And you gotta just get wired in and like figure out how to break out and make this thing work and scale it. And you're at a really interesting point. I don't know how you got here and I don't know why you got here, but you're here and you need to figure out how to like your next, you know, you're on the big field now and your next big push is going to like make or break it. So I think he's largely right. Like, I think we're like, we got robots now doing this stuff autonomously with AI models, which is crazy.
I think four years ago you'd been like, I've been like, no way, like no way you could. Dude, four years ago, I came to your office and you just had a knee working. And I was like, oh, that's a knee. That's cool. It all was, it was a knee. You had like, there was five engineers. You're like, this guy just got done building the Tesla X or Cybertruck or something. This guy did this amazing thing. This guy cured cancer. Look how the knee moves and the ankle has dorsal flexion. And we were just sitting around looking at this knee and that was like the coolest thing. I know, I mean, it's like, and then now we have like AI that's working on a humanoid robot.
We're taking in cameras, it's doing inference on board. It's operating where all the joints go. You know, it's, it's unbelievable. And it's crazy. It works. And, and yeah, the next leg up is just like making that work at higher scale. So I don't know. It's been great. I think it was, I don't know. I think those are kind of some like, I think really good folks to look up to that really like, like love their craft deeply and really care. Well, Brett, I think it's time for you to get back to work, my friend. Great. Thanks guys. It was good to see you again. Thank you so much, dude. All right. That's it. That's the pop.
So congratulations. congratulations congratulations congratulations congratulations congratulations congratulations congratulations congratulations congratulations Thank you.