Fruitfly Hard Takeoff, Washington on AI Risk, 𝕏 Timeline Reactions | Thijs Simonian, Alex Heath & Guy Oseary, Mitesh Agrawal

29:45So lots of different groups around the table that need to be brought on board to this movement. The discourse truly is fascinating. Let me tell you about console. Console built AI agents that automate 70 % of IT, HR, and finance support, giving employees instant resolution for access requests and passports. That's a new approach. Okay. So what is Tyler Cowen calling for? He is banging the table saying, bet on this. Tyler Cosgrove. Are you named after Tyler Cowen? Is that your namesake? Tyler Cowen says, if you have very pessimistic fears or predictions about AI, name the market prices that will support or confirm them.

30:31This is what taking this seriously means. And I love Tyler Cowen. I'm not sure this matters because you're not going to be around to collect it. Yeah, this is what Deep Dish employer says. Tyler, why would short-term existential risk affect market prices in any meaningful way? Spell out the exact mechanism. Contracts that pay out if everyone dies aren't worth anything to me. Yeah, I don't know. Yeah, I think he's just calling for like, you know, he wants people to like make a falsifiable claim. Like, is this, am I able to tell if your claim is like true or false? And so it's like very hard with these scenarios.

31:08Isn't it an unfalcible claim, though, just by definition? And, like, you just have to, like, accept that and move on? Yeah, but then it's, like, so hard to have any, like, real discussion. Was nuclear any different? Like, the threat of nuclear apocalypse, the threat of World War III, this was a very motivating factor for decades, most of the 20th century. People made real decisions based on it, based on where to do business and where the conflicts were going to be and the motivation for nuclear treaties and nonproliferation. You can make financial decisions like thinking about nuclear war, right?

31:49You have a bunker. That's like a decision you make. Bunky? Is anyone making like AI bunkers? No, because they think it's going to be so totalizing that the bunker actually doesn't do anything. Exactly. Yeah. So if you think it's so totalizing, then you don't make the bunker. And so saying, hey, you don't have a bunker is not proof that the person doesn't believe what they're saying. Yeah. I don't know the answer to this question either. That's odd. It seems like, I don't know, maybe there's some question you can ask that is falsifiable. I don't know. I don't know. I think you just got to believe this crew that that's what they believe and they believe it.

32:26There is the other side of this, which is Paul Cristiano, who has been worried about risk. He recently just joined the board of OpenAI. And Tyler Cowen has this quote, if you're a doomer, why aren't you short the market? And Paul Cristiano is 2x levered long, and he's short the bond market or U.S. treasuries, right? So he has 5 % of his net worth in Tesla, 90 % of his net worth in AI bets, and 100 % of his net worth in normal investments. No Tesla options. That sounds like a scary place with lottery ticket biases and the crazy Tesla investors. And then Eliezer Yudikowsky says, am I correctly understanding?

33:13You're 2x levered. And Paul Christiano says, yeah. And so he says he's personally short the U.S. 30-year debt. I think that just means you have a mortgage. I'm pretty sure that's like if you have a mortgage, you are effectively short the U.S. 30 year because you have you have sold that debt and you got the cash effectively. That's how that works. But still, it makes sense because if you have enough money, you could pay off your mortgage, go long that debt and short the market on a relative basis. But but again, that's not this doesn't seem like a doom based bet. This seems like this bet also pays out in just like the good ending and like AI is real and delivers value.

33:58So your AI bets perform well, the market performs well, and money slides from U.S. debt to data centers and AI build out debt or something like that. So he is putting his money where his mouth is, but it doesn't feel like a representation of like doom by any means. Anyway, let me tell you about Shopify. Shopify is a commerce platform that grows your business, lets you sell in seconds, online, in store, on mobile, on social. on marketplaces and now with AI agents. Speaking of AI agents, people have been creating AI agents of fruit flies. Have you seen this? Yes. Okay, so where should we start? Because I want to set the table on what is actually going on.

34:40Tyler, do you understand this? Break down what people are cooking. We've seen this before. We've talked about this before. But what's actually going on with the fruit fly? because now people are taking the fruit fly all over the place. Yes. My understanding is Google basically mapped out all of the neurons in a fruit fly. Fruit fly. So they probably took a deceased fruit fly and put it in a mass spectrometer or something that can investigate the brain at a high-powered microscope effectively. Yeah, like the entire nervous system. In 3D, they got the entire structure, and now people have been able to recreate that in software in a simulation.

35:22Yes. I think in theory you can like replicate all of the flies like decisions or whatever. It's like movements. Yes. And this is notable because many people have said I have the mind of a fruit fly. They've said I have the intellect of a... Yeah. So now they're going to put it to the test to see which performs better, the simulated fruit fly or just Jordy Hayes who we got right here. This is organic, farm-to-table, Jordy Hayes. So now that this is out and the code is out and you can run this fruit fly-in simulation however you want, people are having, they're doing all sorts of experimentation.

35:59So Kevin said he trapped the fruit fly in his rabbit, R1. When he shakes it, he can see its brain's escape circuit light up. By the way, our consciousness is physically defined, which is why our physical things like drugs, neurotransmitters, or events alter or initiate or end our consciousness. And things like sleep, hallucination, waking, or death, computer simulations are also physically defined representations. Yeah, I think what ends up being unsettling and weird about this is if it just purely you being human and doing this is probably not good for your own soul. And imagine you have a fruit fly in a box and you're shaking it and you're like, look, it wants to escape, right?

36:52Totally. I'm not a huge fan of small insects. I don't really want them around that much. But when they're in my house, I try to, you know, if a spider's in my house, even if I know it might want to take a nice bite of me, I'm still going to try to transport it out of my house and put it back into the world. I think it's not good for your soul to be a merchant of death in that situation. And yet, if you're playing a real-time strategy game and you highlight a bunch of soldiers in this simulation and you send them on a charge that will result in their virtual death, you might not feel... But those soldiers opted in to riding and dying with me.

37:39Okay, okay. Right? Okay, what about... This fruit fly is just sitting there, John. So they made the fruit fly play Doom. What about if you play Doom, you are killing a demon who's simulated? Is that immoral? Well, is that demon trying to kill you? A lot of it comes down to the fact that it's simulating the actual representation of the fly makes it a lot more concrete than just, oh, yeah, it's a 3D model in a Python script that just says if you see a character shoot at them in the simulation. But we're clearly starting to grapple with these odd moral questions of if you're simulating something, then the next step is a couple of order of magnitude.

38:22But you get there and you can simulate a human and you could talk to that human and it would do everything the human does. Does that human have rights and agency as an ethical moral agent? Or is it merely just a simulated, just a really good computer simulation? it's just existing on transistors so you don't need to feel any moral weight about anything that you do to it uh i agree with the just the vibes based analysis that like torturing a real fly torturing a virtual fly probably just don't be in the business of torturing anything you don't need to overthink it but people are the the real debate here is like the question of you know are Are LLMs sentient?

39:04Are they moral? Is there a moral weight to synthetic intelligence, to artificial intelligence? That's what people are debating here. And I'm sure the debate will continue. Who knows if it will ever be ended. But they did teach it how to parallel park, which I think is cool. Interestingly, last night I had Astra use computer use to play a video game that I very much enjoy playing called Blatro. It's sort of like a modified poker game. and I don't feel like I was torturing the LLM by that. I feel like I was giving it a treat. I was like, hey, instead of doing my taxes, you get to just chill and play a video game.

39:40It did very well. It won. Seoul was not able to win. And it was really fun because I would, like, pop in while it was using the computer and kind of armchair quarterback and be like, hmm, is it making the right decision right now? It felt like a coach coaching, like, a kid on the soccer pitch or something. I had a funny moment last night. I was on my racing simulator comparing, asking Chachi Biti to compare my times at Laguna to just other, you know, what would best in class be like, what's beginner like, et cetera. And it said, if you want, I can help you, you know, cut some seconds off of this time.

40:26and it was like, why don't you take a video of a full lap and I'll analyze it for you. And I was like, yeah, dude, I bet you'd love to just hang out and watch track footage. Pretty soon it's going to be like, you want me to just get in the seat? You want me to just take over? Yeah, no, computer use in iRacing is something I'm going to experiment with this weekend. I'm down. I'm down. Take half my quota, my monthly quota. Just play games. chill, do whatever. It's a nice treat. I've got some banked resets that I'll put to work. Yeah. Anyway, we have our first guest. I don't want to mispronounce.

41:04Tyler, how do we pronounce his name? Teese. Teese? Let's bring him in. How do you pronounce your first name? It's Tice. Tice. Like nice. That's right. Like nice. Well, welcome to the show. Thank you so much for taking the time. Great to have you. Tell us about your role in robotics and also some of your recent work hooking these models up to robotic tools and infrastructure. It feels like we're going to be entering a boom of like people they ordered the Mac Mini recently people are going to be ordering 3D printers and robotic arms and doing hack projects super excited for like the DIY world to explode over the next couple months but let's start with just like your most interesting projects recently.

41:50Yeah I'm incredibly excited for that. And that world's definitely just around the corner. So I'm super excited about that. Yeah, I work here on the robotics team at OpenAI. I'm an intern and have been doing lots of exploratory projects. And this is just one of the projects I basically noticed that our models are really good at painting and doing various computer use tasks in software, like you were just talking about, and learned a lot that you could actually basically connect these into physical robots in the real world and wanted to see how they would do that sort of drawing and tasks like that as well.

42:25Yeah. If you can, if you can paint in Google calendar with calendar invites, you can probably translate that, uh, to, to the real world. Yeah. It's really like everyone is doing everything. Like I've seen people paint the Mona Lisa in Microsoft Excel or Google sheets, and then you take it back and you can do Excel in MS Paint now, if you want, with computers. And it's like everything becomes everything. What is actually the important precursors to a good experience? We were talking to a YC founder who built a humanoid robot with some basic claws for under$2 ,000. And it feels like there's an importance of some on-device API or some on-device models in some case doing some slam on-device.

43:12But then there's also just tools that give you a very primitive interface that might be kind of clunky, but it doesn't really matter because you can just vibe code your correct interface. But what have you liked? What are you excited to put in the repertoire of tools? Like within robotics? Yeah, within robotics. Yeah. I think that, of course, like a lot of these demos and stuff is very early. I think the whole space and exact modeling and methods are still definitely being figured out. But I did really like the fact that you're sort of able to hook in the intelligence of what the models are able to do, as you can see with all that painting stuff, and plug it into something physical in the real world and get it to do things.

43:55There's probably going to need to be some combo right now. Basically, my experiment here is plugged right into Codex, and that's, of course, probably quite expensive. Definitely pretty slow. I think these paintings took between one hour and like two hours, depending on the methods exactly that the model chose to use here. But yeah, there's definitely a lot of improvements to make, but it's quite cool to see what you're able to do already. Yeah. How are you balancing tradeoffs between speed and reasoning effort? I've been testing computer use on a bunch of video games that I just mentioned. And part of what the feel the AGI moment is, is when the cursor is moving at at least near human speed.

44:43But then also you don't want to be making a bunch of mistakes. So this balancing act is really key. Did you try multiple reasoning effort levels across different paintings and see noticeable results? Can you see qualitative differences in speed and quality based on models that you pick? Yeah, there's a lot of different ways to go about doing this. I initially started out these experiments by just telling the model, like here, as you can see, I actually have the bot behind me. Over here, it's currently painting a TBPN logo. Oh, cool. That's amazing. I love it. But it's doing its best. There you go.

45:23Good start. We got basically this camera up here that the model, which is connected right into the codecs over here, is connected to. And the biggest challenge is that images are quite large to process, especially for the model. There are a lot of tokens. And the loop of taking an image, taking an action, taking another image, taking an action, that's the thing that has taken a lot of time. So what I ended up doing, it's not directly doing image, one small movement, image, one small movement. And I think that would probably result in the best performance for general robotic tasks and stuff. But at the moment, it's basically taking an image, writing a plan in code of what it should do and where it should go next.

46:07After it has done a lot of the calibrations, maybe a slower sort of methods at first. And then after it has that plan, it executes it and then monitors it in the background. taking images every second or few seconds and watching to make sure things are going well and making small adjustments to the plan throughout. And I found that has been a good balance of speed here. Have you been thinking about compression on the input? You mentioned that the images are lots of tokens. I have this monitor that renders at 5K resolution, and I was like, this is probably going to be really slow for computer use.

46:40I should run this game in a window and give it a 720p input because that's probably enough information. But I'm wondering how important the resolution to speed and quality is that you've seen. Yeah, I think it's very important. In this case, for a lot of the early demos, I was using 512p, just compressing it, just to make sure. Because I think the model has pretty much solved a lot of the perception challenges here. So it's really good at understanding what's going on, even with a lower quality photo here. But in this case, with the longer planning and sort of like a minute of action out, it's less important.

47:20The specific resolution probably. But yeah, as we go to more like faster, much more smaller loops of like control, it's definitely going to be important. Jordan? I'm super excited about this project, mainly because it feels like we're right on the precipice of sort of like, what I think is going to be a big breakthrough is sort of a deep research moment for robotics, like simple robotics use cases where deep research for so many people was their first time using agents and the idea that you could type out a prompt and then get back what would have been maybe at least hours of human work, right?

48:00Somebody reading all these different sources and combining that information into a document that's that has a consistent and narrative and understands the right information. That was just such a big moment because a lot of people were saying, wow, I can't believe that the AI was able to do something that would have otherwise I would have had to hire somebody to do or just taken a bunch of time. But there's very simple tasks that I feel like you could probably start working on sooner than later, which is like an example, at least for me, would be like if I could just take all the mail I get and dump it in front of a robot like that and have the robot sort it, you know, take all the, you know, 50 % of everything I get is probably some sort of advertisement.

48:42So, like, figure out what's an ad and shred that. And then actually, you know, basically, like, photograph and respond to if I have, like, a utility bill or any number of things that I actually need to respond to. Theoretically, you could close that sort of, like, IRL to digital loop where the agent would actually get a task from the real world and then close that loop online with just normal computer use. That's the kind of thing that you don't need. You don't need a $50 ,000 humanoid robot. You theoretically could have an actual desktop robot that was able to do this thing that otherwise takes me...

49:18I dread going and like, okay, I have to sort through all this mail and figure out what's important and make sure I don't miss things. But I feel like there's a bunch of other use cases like that where people are like, okay, I didn't just generate a pretty picture or answer some question that I had, I actually saved myself. You want an IRL spam filter. Yeah, an IRL spam filter. The spam filter robot. Yeah, I think there's two really, really cool things about this project, which sort of shows that direction that things are going. One is that this arm, I don't know if you know too much about the prices of classic robotics equipment.

49:52It's like thousands and thousands of dollars at the moment. And this arm that I'm using here, right behind me, This is a Hugging Face SO100 robot, which is open source, fully 3D printable. You just need to get the actuators, which are much cheaper. I think at the moment, which is more expensive just because of supply chain issues, it's around$200 or so. But that's incredibly cheap for robotic equipment and what you're able to do with it. So I can see a world quite soon where similar to, and someone put this really well on Twitter, similar to how there's this whole 3D printing craze where everyone went and bought 3D printers and ran software.

50:27where everyone's going to buy these cheap, before we get really industrial equipment, for personal use and personal product, buy these plastic, cheaper robot arms that you can just clip onto a table and just put stuff in front of and plug them into agents that you can already do things with that are already out there. Astra is something that people can just pull up codecs and start controlling robots with right now, which is super sick. And we've also been seeing, at least on Twitter, I've noticed a lot of academic researchers at different institutions start to realize that you can do this with these models and start doing initial explorations and things with it, which is super sick to see.

51:08And there's so much more to explore in this space. There was a YC company on the show yesterday that has managed to build a humanoid robot for under$2 ,000. Oh, my gosh. And that feels like a price point that people would experiment with. So if I know I can get a robot for like two grand and connect it to Codex and then tell it, like it basically lowers the stakes a lot where I can be like, hey, go every weed like this that you can find in my yard, go like pluck it out and try to put it in a bag or whatever. and like that that's basically like the gardening robot and it could like flounder and fail but i have like pretty high confidence that even right now astra would be able to identify like hundreds of like a specific type of of of weed and probably and there's of course like safety safety concerns with that but yeah yeah the nat friedman like leaf robot like that feels like we're here the models can do it it it's not it's not cheap but uh we're what is uh what is the next medium that you want to explore are you going to get into whittling ceramics i want to see you whittle a bench as a benchmark whittle bench that's really good but whittling a spoon or something i don't know it just feels like 3d is the next thing you really want to give the robot john wants to give the robot a knife i don't think that's i don't think read the room john read the room okay okay maybe we'll stick to uh to enter open ai intern gives robot a pocket a knife.

52:38We'll do some ceramics, maybe get it on the pottery wheel, make a nice vase, something like that. But I mean, is there anything where you're like, oh yeah, okay, this is where this goes next. I think I was having the exact same thought, which is like giving a robot a knife is like probably a very bad idea. Um, but I, I do want to like sort of see if it can help do like cooking tasks or do a various tasks that are like things that you do in your life. That'd be really sick if you could have a robot help you out here and there. Yeah, yeah, that's interesting. Yeah, I'm so interested to see, because there's a whole class of tasks where you can't wait a full minute.

53:14I was testing on a real-time strategy game, and you can pause the game, but if you're not moving at a certain APM, even on easy mode, you will just get smoked. And so, but it feels like with new chips and Cerebris and Spark models and stuff, like the speed up is going to come, but it's just, and that's going to unlock a whole new host of capabilities. What advice do you have for young people that want to get into DIY, you know, like this type of work? I mean, you mentioned that one hugging face device that you have behind you. Are there any other devices or tools, toolkits that you recommend as places to get started?

53:57Yeah, I think that the Hugging Face robot is an incredible tool. You can also 3D print completely new embodiments and stuff. There's lots of open source projects online where people have changed around to get better grippers and things you can do with that. Also, just don't give up after the first attempt. This was the very first painting at the row. That's upside down, even. I couldn't even tell. You can see the Golden Gate Bridge here. You can kind of see the ground it was trying to do. And just like if you keep going and you can sort of see the progression as it improves. Wow, that's amazing.

54:29Yeah, you need to frame those next to each other. That's incredible. Yeah, I think you're putting all five of the progression in like a frame and calling it self-improvement. Because, yeah, the model, this was a thread. The model just was able to figure things out with a few pointers here and there how to get better and better at painting. who's who's going to sign it is it you do you have codex sign it astra sign it well who i've also given the robot i've given the robot a pen and it's going to try i don't know how well it's going to do but we'll see an axe or something uh well thank you so much for coming on the show so cool very cool come back on soon yeah yeah i'm feeling i'm feeling the physical agi for sure for sure very cool have a great rest of your day goodbye cheers let me tell you about public.com investing for those who take it seriously.

55:16They got stocks, options, bonds, crypto, treasuries, and more with great customer service. And let me also tell you about Cisco, critical infrastructure for the AI era. Unlock seamless real-time experiences and new value with Cisco. We have two guests with us in the TVP and UltraDome. How are you guys doing? We're good. Welcome to the show. Partners. Yes. Thanks for having us. Yeah, welcome. Great to have you. Introduce yourselves. Introduce yourselves. My name's Guy Osiri from Maverick and also Sound Ventures. Yeah, welcome. And I'm Alex. Yeah. Now with Sound. Yeah. Also running Sources still.

55:52Okay. Very excited. Yeah. It's been a big week. No hat on your head. No hat at all. No hat right now. We were debating. Are you taking it off? Yeah, every time for the last year, every time I've seen you have the Capital J Journalism hat on. It's off. But it's off now. It's off. Okay. Yeah. But getting him here, guys. How long were you a Capital J Journalist? 10 years? 10 years. 15? Okay. Started around in high school. Yeah. And then now, capital V venture capital. Capital V. Right? Capital I investor? Yeah. It feels we're aligned on the vision and really excited to get started. This guy's a force, but also a talent.

56:35Yeah. Like you guys. I mean, you guys understand how to work with people and talk to people and help them tell their story. And I think it's so aligned with what I've been doing my whole life as well, which is helping people tell their story. And so when we got together, it was just magical. Yeah. Yeah. It's awesome. What are you interested in investing in? We're spending a lot of time on different things. Personal agent space, very interested in. It's very hot, obviously. Are you a daily driver of anything yet? I'm using everything. Everything. Yeah. What's the last agentic thing you did? Did you book a flight?

57:13Did you email the CEO of Walmart for a refund on$5 at Raspberries? Did you hear about this? No. Oh, yeah. Some of these agents are very persistent. There's very persistent personal agents where – one of the seemingly now very obvious use cases of agents is just like, hey, do a bunch of things that would take me a lot of time that could maybe save me some money. And when you're using a free agent, You don't care if it's spinning its wheels for 24 hours to get you a$10 refund if it's not costing you anything. So apparently somebody was trying to get a refund on a$5 pack of blueberries they got at Walmart.

57:50It was raspberries. Raspberries, raspberries. And the agent actually reached out to the EA of the CEO of Walmart. That was the last place to escalate. It was like, I got to take this right to the top. These agents are getting crazy. They're getting crazy. They're swarming. But I guess like re, yeah, rewinding a little bit, Guy, you invested in OpenAI and Anthropic like years ago. And Hugging Face. Wow. And Hugging Face. I didn't know that. Yeah. Nice. And so in some ways, like you probably the last few years have been just sitting back in awe, I'll just basically just getting to like getting to experience your own conviction and watching the space evolve.

58:36But I think like everyone has got to the point in the last or at least has consistently been feeling like nothing is like settled yet. We have these new kinds of businesses, labs. Some of the labs are making products, but there's still tons of room for other players to come in and make things. So are you feeling like renewed excitement around early stage? When we did Anthropic and OpenAI, I think we were the only fund that went in so deep back then. And it was confusing to some people, but to us it felt like this was it. This was the time. These were the companies. These were going to be longstanding foundational platforms.

59:20And today it's a lot more confusing. There's so much going on. And every single week, every single day, you guys are announcing people's raises. They're raising now. They're raising now. They're raising now. And it's hard to tell. It's not as easy as it was for us to really decipher these are going to be the things people use in 10 years. And now it feels like there's so much going on. But I'm also as excited. I'm also as inspired. I want to be part of these exciting companies. we just have to pick right um i'm i'm meeting with some really incredible founders and visionaries it feels really exciting and so it's like when it's starting in the music business it's like the early days where i got going and you're just getting demos everywhere you know you're walking out of a club you're like hey yeah you're the guy at the here's the demo here's my demo here's my demo is my demo how can i tell which one of these artists but if you just if you put enough work in enough time in and you're diligent they start to like they start to become a little more obvious.

1:00:25And there wasn't. Initially, I had 100 demos. I literally was like 17 years old with 100 demos. But as you listen to 100, my first three demos. At 17, they were 100 people that I would give them to you. Yeah, people that I would go out and go, let me hear your music, let me hear your music. And the first three demos I had, I had my favorite one, my favorite two, my favorite, like in order, but 100 in, those three are not even in the top 20, right? So you have to just, you have to, you know, pattern recognition. You have to do a lot of work. You have to listen. You have to meet a lot of people.

1:00:58And then through this crazy time, it's pretty freaking crazy. I think the right things appear. And then you just have to be there to be part of that. And so I'm still as excited. Yeah, we have been able to sit back a little bit and watch our, you know, we've also, we didn't just invest in those companies. We also invested on the way up. So that also keeps you busy. We put a lot of money into Anthropic on the way up. We put a lot of money into OpenAI on the way up. And I think we have close to a billion dollars worth of money invested into those two companies. And so we're not just like laying back, you know, but it is a lot harder today to decipher between what is real and what is not real.

1:01:40I think when you have two effectively recent investments that are now two of the most important companies in the world, I do feel like the bar goes up on other investments because it suddenly is as thrilling to invest in a company that can only be a$10 billion company. Right. When when and when. A lot of VCs were very excited to underwrite a company to$10 billion six years ago, even during the period that you were making those two investments. Yeah, I think about it differently. I have heard some people say, hey, zero to 100, that's not a big deal anymore.

1:02:24I've always been attracted to talent and visionaries. So I don't start with, okay, we're fortunate to be in these two incredible companies. But there's a lot in between, and there's a lot that's to come. And I just love sitting with a founder and problem-solving and figuring out how we're going to get from A to B. And sometimes it's where you get in. I saw a lot of people, you know, John from Betaworks did really well on Hugging Face. We came in. We did well. But he came in at Seed. So you did really well. And sometimes it depends where you get in as well. But for me, what excites me is the same thing.

1:03:09It's been constant my whole life, which is surround yourself with really, really incredible, brilliant people who are trying to change the world. How does identifying creative or musical talent differ from startup entrepreneurial talent? because I'm sure there's some common threads. But whereas in music, you might back a musician that has like, you maybe know they have a drug problem and that's part of the music. But in startups, a founder that has like some crazy, crazy, crazy stuff going on in their personal life, maybe it's like, hey, you should figure that out before you build a massive team and you're managing people and stuff like that.

1:03:53but there has to be like a bunch of common common ground between the two well i was able to transition seamlessly because of music my job was to identify artists before anyone had heard of them and to sign them very quickly and to then help them reach an audience so when i meet a founder i i i actually feels the same i always say founders are the rocks are the rock stars too because when they walk in and they also have their music that they want to share with the world. So I have to identify that founder, same way I used to identify music artists. And then go, this guy has, or she or whoever have music that is so good.

1:04:38Oh, I love that course. That's a great idea. You mean a car shows up and it picks you up and it takes you, or you mean an apartment people could share and you're like, oh, wow, that's a hit song. So I always listen to every pitch like it's a song or an album or a music artist. And I just go, that guy's got the talent. He's a rock star. We just need to make sure the world knows it. We need to make sure that people are aware of what he's building. Let's go get a base. Let's go create, find that audience first and tell this story. So for me, I feel like I've been doing the same job since I was a teenager, which is identifying talent and helping them reach an audience.

1:05:19But music is the constant. I'm always listening for the chorus. And if I don't hear the chorus, I'm like, I'm not sure about the song. Or the performance of the song. I don't think this one works. So it always comes from that. The DNA is being around music artists. is that in tech world, you see entrepreneurs that are truly visionaries, and they're seeing opportunities before they are obvious and pursuing those, and they have an idea of the way that the world should be, and they're trying to sort of mold the world into that state. And then you have actually the majority of entrepreneurs, which are just like they don't know something's an opportunity until they see someone else pursuing it, And they're like, that seems like a good idea.

1:06:08I'm going to do that. It's the same thing in music where you have somebody that has truly a new sound and they have a life experience that they're trying to – they feel like they need to create art out of. And then there's the follow-on of like, oh, yeah, country. You want to back a cover band entrepreneur? Yeah, a cover band entrepreneur. That might be a good – When we started the record label, you had Jimmy Iovine here the other day. when we started the record label it was just like four of us small company, it was Madonna's company so that's cool but it was still there was just no one knew what to make of it and Jimmy was on fire, Interscope Records was on fire and I was always thinking if I don't act quickly he's just going to pay them more and get them so and we were competing with big labels Jimmy was the guy who I always looked at like hey He can just come in here and just wow them and get them.

1:07:05So not only do I have to hear your song and decide right then and there, I want to do it. I don't have any background. I don't have, oh, my biggest successes were always the things no one else wanted. But Alanis Morissette, I mean, she tells the story where every single label passed. I didn't have any of that history. She came in. She was in my office with her producer, Glenn Ballard. They played me one song, which is called Perfect. And within 30 seconds or 40 seconds, I think I was like, I'm in. And so that news, you know, the band from England, they came to L.A. I flew them in because I like their demo.

1:07:50They did one. They were there to perform a few songs. After the first song, I stopped them. I said, we're ready to go. And they're like, we flew all the way from London. Can we just play out the next few songs? I'm like, of course, but I just want you to know. So I developed that act-quick intuition, and it really just came from I had to, or else someone else would just figure it out and overpay, and then I couldn't do the deal. Well, there's so many of the market dynamics that you see in music. A friend of mine, Zach Bia, was telling me about some of the process of signing the artists that he works with, where these artists are like, you know, the same thing that happens on, on, like with, in tech where like some X account pops up and maybe there's like a team attached to it.

1:08:35There's no launch video yet, but you see a bunch of people following this person. And then you hear that they're meeting with this firm and this firm and that firm and, and, and the whispers start going around. Same thing in music where like an artist might one day have no followers on Instagram, be totally, totally under the radar, living like in their parents' basement, but they have some little bit of magic. And then soon enough, they're like doing a roadshow basically with different labels. And then you as a label need to be like, well, how much can we invest in this person? How big do we want to bet?

1:09:10We need to get to them first. And then you're also sometimes competing on price, but other times you're just competing on like well how how great a partner can i be to this to this artist so like i can see how music translates just so well into venture because the exact same thing venture is not a game once somebody's talented and they're known it's like very obvious obviously you want to be it's harder to get in then yeah and it's the same with i have competed when things are big i remember when prodigy everyone wanted them and i flew to london like twice in four days to try to get that, and I got it.

1:09:47Yeah, and every VCU will have a story like that where they're like, I had floated this backwater place. We have those. We have all of those. But, you know, you look at when we did Anthropic, when we did SPBs in Anthropic, we couldn't, a lot of people were not, hey, you guys. Tough to fill. Yeah, tough to fill. A few times people didn't get it. Of course now, you know, We're begging to get more of it. So I just, again, I always go back to don't listen to anybody. You know, you talked about, I think the other day also, you talked about blinders. Did you talk about blinders or something on the show?

1:10:26Yeah, Jimmy Iovine has that concept. Yeah, so that. Horse blinders. So we have a mutual friend, and he's my mentor. His name is David Geffen. Yeah. And David said to me when I was like 21, he told me that story. I didn't know this. He said, you know, guy, you need to be a racehorse. and I was like he goes you know what race horses do and I go yeah they race I had no idea and he goes no no they wear blinders and so just race your own race because if you don't wear your blinders if horses don't wear blinders they could literally they could kill they could die they could trip over their they look over and they could trip over they could break their legs and so I really stuck with me that you guys talked about it that concept stuck with me and I really try to just not pay attention.

1:11:13When we did Anthropic and OpenAI, a lot of people doubted it. We didn't have any doubt. We were determined to do it. I want to stick with... We're really trying to continually connect to that approach of not listening to all the noise. Of course, data is important and we want to get more details and more information and we're structured. but that gut that has gotten me here, I need to continually respect. Alex, on your side, you've spent, how is it? 15 years, a decade, 15 years-ish. Did it take, do you feel like it took a few sort of cycles to hone your intuition around companies? Because in our first conversations, I was always impressed with your ability to just see directly through the marketing on so many different companies.

1:12:12Like some people, like marketing just works on them. Marketing works on all of us. Advertising just works, period. But like marketing works, marketing and good comms work like too well on us at times. Or there's some people that are just like, this is a good story, so I'm chasing it from the capital. But for you, you'd be like, we would be talking about something and you would be aware of like a dynamic around a company that no other journalists had talked about. And at times like you would be like, yeah, the story is not for me. But you were like clued in on a story and you knew exactly what was going on with the company.

1:12:45And then in the example I'm thinking of, I won't name the company, only six months later has it even started percolating up that that dynamic is going on. And so I feel like for me, and at least personally, I had to see the cycle of company starts, gets hot, attracts a bunch of capital. But sometimes you have this intuition around the company where something doesn't really feel right about this company, even though it has a lot of momentum. Yeah. I don't know where that comes from, except that I've been fortunate to spend time with a lot of the best founders in the world. I mean, I just had Zach on the podcast, Sam on the before that.

1:13:26incredible lineup coming up. And I've gotten to know these people over years and years and years. So when you see like the people at the Apex who are crushing it and who are at high integrity, are beasts at the game, on the field, you can quickly see when someone is pretending. And I just try to stay really close to like what's actually happening and ask around, do my diligence, leave no stone unturned. And that's gotten me well so far. But like the thing you said about like six months later, you saw it. I have that a lot where I'm like, oh, this seems really interesting. This seems like everyone's going to be talking about this.

1:14:05And then it happens. And it's happened enough in times to where I'm like, okay. I've got to figure out a way to make some money on it. Well, yeah. And like what Guy was saying about his gut, and this is where I think we really hit it off is, yeah, you have to trust your gut. Like if you can get enough pattern matching recognition in, it's just instinctual. how do you think the podcast will evolve in this new role it's going full tilt i mean uh first two episodes again were were sam and mark uh i can't share the names but um it's it's going it's amazing like like there's there's interesting ways when you have position in a company the the critiques i was gonna be like they're only having them on the show because they have a bag or whatever but when I look at like what Dworkash has done with Maddox and Rainer, like explaining his expertise, it doesn't feel like a sales pitch for that company at all.

1:14:57It's actually just tapping the network at a deeper level. And at the same time, if I'm a founder and you're the place that I go to hear Mark Zuckerberg talk about his vision, that adds value and attracts, even if it's not a company that you're actively investing in because you're not doing Publix. So I'm wondering if there will be more like less like this person's on the funding track or more like 360 views do you want to climb the mountain and do all the mag seven ceos is that the goal or is it more like go deeper with certain experts build this community of people with particular philosophy there's like a whole bunch of different ways i could see it evolving and i'm wondering if you have any particular direction the mag seven i feel pretty good about yeah uh you're on that track for sure Yeah, I feel great about it.

1:15:46I always love the like – I love putting the people at the top with the people who are up-and-comers. Okay, yeah, yeah. So I've got to and from base 10 on next week. Amazing. Legend. Legend, incredible company. He's incredible. And he's obviously crushing. He's huge. Yeah, yeah. But like he's not Zuck yet. Yeah. But I want to bridge that world because like this is all one world we're in. And, like, everyone talks, like, the Zucks want to know what the Tuins think, vice versa. They want to learn from each other. So I like building that cinematic universe. Sure. And it's, like, my taste. It's, like, I wanted to have that convo with Tuin, which is coming out next week, because, like, inference is just so important right now.

1:16:28Yeah, yeah. And it's, like, everyone's trying to figure it out. Yeah. And so you're also getting my POV of what I think is interesting with my guests, and I'm booking everything myself. Sure. and I think that's only going to get better because again like sources is separate I mean obviously I'm with guy and I'm with sound but you know we'll have I'll have people on the pod that you know are we're not investors in I'll have competitors I'll have other vcs on of course um it's about the ecosystem sure um and I think the brand is important like I want to invest in the brand what's the future of the writing newsletter I imagine that you're not gonna be able to put the pen down forever.

1:17:05Well, yeah, it's interesting. There's gonna be times when you just want to get something out. Yeah. I think, I think, you know, I want to use the newsletter, which has just an incredible audience to, to share what I'm seeing. And it's really like, you're getting like an even deeper sense of what I'm seeing because now I'm like in the room in a way that I was kind of in, but I was always like, when you're a journalist and you're in the room, you like get brought into the room and then escorted right back out. And now it's like, I get to hang out in the room. And so you're, I'm like, I'm sitting with it and I'm marinating on it.

1:17:35And so when I write like a, a piece, like I'm thinking on something on personal agents actually right now, it's informed by a lot of conversations. I'm not going to share all those, right? Like obviously confidentiality is very important, but I think it's going to make the perspectives I'm sharing a lot better. But look, I, you, you started this, like hanging up the, the capital J journalism hat, right? There is a sense of like journalism in the traditional sense of the, and we were talking about this when I was on the show before, like the leaks and all the things that I've been known for over the years.

1:18:03Like, obviously I'm not going to do that. Yeah. But, but you know what? Like I've done that for 10 years. If you have a, like, I'm very excited to read this take on personal agents. I think a lot of people have been thinking about the way this category evolves. Do you have any interest in turning that into a video essay, direct to camera, talking to the camera, putting it on the same feeds, like what Dwarkech does when he writes an essay, he also has a video version. Yeah. Could just be a good product, but also reach more people. People have asked me to do that. Yeah. I have another job. I don't know if that makes sense for like other reports where it's like, here's the, here's some facts.

1:18:39Yeah. It's more of a quick hit. Yeah. But if I'm like getting like a quarterly thesis from you, like maybe it's a 20 minute video. I would watch that. Well, and it just gives me more optionality to like, I can browse it in the email. I can, like with Dworkhush, I get his emails. I also see him on YouTube and then I get it in the podcast feed. And sometimes I'll be in the video mood sometimes. and I'm multi-platform with a lot of these creators. I need AI to help me with this, guys. I'm going to be honest. Yeah. But you want the rawness of the person, which, of course, but I think the pod is conversations for now.

1:19:11Yeah. Maybe I branch it out. Maybe it's more things. I just think a lot of the platforms are very receptive to multi-product feeds, like having multiple media products within a feed. I've thought a lot about this. I've been surprised that we've been able to do it with a 20-minute version of the show and a three-hour version of the show dropping in the same feed every single day. Yeah. And it hasn't been bad. People don't care. No. People just pick whatever they want. And then if there's a hero interview, we get a big interview with someone, that goes out as another one. Yeah. And that's its own thing.

1:19:39This is maybe a phase two thing. I mean, I have eight incredible guests lined up on the podcast over the next few weeks. So it's like I got to get those out. That's great. I'm an SF guy next week doing some. I'm doing four next week. So I want to get all those out. And then, yeah, maybe like the personal agents thing. Maybe that's like a thing to carry on. Has the lens changed when, if you think about a Mag7 CEO, there's the getting the scoop in the interview, the capital J journalist interview in that conversation. And I think that you can, there's a bunch of different ways to do that. But then there's also the, you know, what is, what will the next generation of great founders get out of this particular conversation with this Mag7 CEO?

1:20:23Are you starting to put on that hat of like? I don't really think of it that way. I think about like, what do I want to know? And, and I really care about strategy. I really care about connecting the dots, like getting them to say something they've never said, which you saw with, you know, the last two pods. And that's still going to be the thing. And that's, that is journalism. Like that, that, you know, you're getting interesting and facts out in the world. It's just good content. Yeah. And like, you know, these people are, are doing a lot. And so it's They're out there, but I don't know. I think I get a lot out of my conversations with them.

1:20:59I don't think I'm going to change much. I think the only thing is, yeah, I'm not going to be leaking memos anymore. I used to do leaks about companies worrying about leaks, and that was one of my favorite kinds of stories. I'm not going to do that anymore. I'm not going to do that anymore. Just one more leak in 2027, you get a good one. No, a decade of that, and I'm good. You're hanging it up. is the is now a good time to become the next alex heath somebody's like 20 20 22 i think that's great yeah i mean i think i think it's really hard right now if you're early because um it's just the media the traditional media environment is so challenged structurally and uh places are doing really well i feel like i feel like the the the ads product the sponsorship product He's saying traditional.

1:21:47No, I'm saying traditional. Yeah. Oh, okay. So next hour, he would start in the newsroom. How would you start? How would you, you know, I've been fortunate people care because I've broken a lot of big stories. And I've gotten a lot of big interviews. And I came up in an environment where, like, I was in a newsroom learning from incredible people who've gone on to do incredible things and run now in many of these newsrooms. So I don't know how you do that now. Like, a lot of places aren't hiring. Their traffic's declining. They haven't made the pivot to, like, what we're doing, this direct thing.

1:22:15like subscriptions, like streaming. It's really tough. I've thought about it. I don't know how you would break out right now unless you just kind of are like - Are you going to start? You maniacally focus on one thing and become the best in the world at that, which is how I started, which is like I'm going to be the best in the world at social media covering Snap back in the day during the IPO. And then I was breaking a ton of news on Snap. And then I got noticed. And then I was like, oh, I can shift this into other companies and keep shifting it and shifting it. So I would still say that's it.

1:22:42You have to maniacally focus on one thing that matters. But it's the intersection of niche and matters. It can't be. Yeah, of course. What do you think about the possibility of Instinct having a bigger valuation than Snap? I think, I mean, I wouldn't be surprised. It's crazy out there, guys. It's also a new category. What do you guys think about Instinct? I think that they're in a unique position because they're a startup so they can – like if there's like rough edges, like those can get ironed out and there's more forgiveness I think as opposed to – Yeah, fair startup. Yeah, as opposed to like the muse agent is going to be like congressional hearing if something goes poorly.

1:23:29Whereas Instinct is going to be like, look, it's a startup. You knew you were an early adopter. Let's give them the benefit of the doubt here. Yeah, to me, the most interesting dynamic right now is because of the people's fear around AI, there's like way greater willingness to try new products because you don't want to be left behind. right and so you may somebody may have been trying and being a daily active user of a variety of ai products for years now and still they're like they want to try the new thing because one the space is progressing there's so much room for new products and new categories but then there's also this fear in the back of your mind of like if i don't try the new thing then like you know the permanent underclass meme.

1:24:16And that's just consistently created this sort of second mover advantage, third mover advantage. And then AI brands, once they're big, they accumulate, they've been accumulating baggage, right? And so people are like, you know, maybe they have some, maybe they're just like, they're excited to share and talk about the new thing in a way that, that they wouldn't be even products that they're using day to day. So I think it creates a big opportunity for startups, but I think that I'm very interested to see how the personal agents market ends up comparing to just like the frontier model inference market, because it seems like every company is going to build a personal agent.

1:24:59Many of them already have, especially if you count LLMs, which do have agentic, or just like chat apps, which do have agentic capabilities, but it's going to be an absolute it's going to be an absolute bloodbath network effect and you get to some sort of take rate on agentic commerce like you buy your car through it and they make 500 bucks like that's a very very good which zack told me will be the business for muse is that's what he's trying to do and he has the network effect to bring to it so yeah instinct certainly there are i'm really interested in the idea of network effects with agents yeah and since instinct's doing it talent is doing it yep uh met is going to do it yep uh and maybe that is the At the same time, it's tricky if you can point an agent and say, like, get me off of this thing.

1:25:41Right. Well, they're not people. So it's like, do you care? Do you care if your agents are in a network? But if you're like, this one is the one that's never had a leak or never had a crash or never had a hack, then you do stick around. In theory, like the time to build a new social network would be today because you could say, like, go open up my Snap account or LinkedIn and scrape out every single person I have. They don't get a say in it. And go at them on this new network. Right. Because like that, that was like export. The contact book was like arbitrage that closed. Yeah. And it's kind of opening back up.

1:26:15You think? I think so. I'm, I'm waiting for, you know, the, the criticism of social media was always like, we created social media to be social and it's made us less social than ever. And with personal agents, it's like, it's like less, well, less like personal. Like we don't have, we're not going to have personal relationships with like service providers and, and variety of things because it's like even, even people, some of these new functionalities, which is like, sorry, grandma, I don't want to talk about the road trip that we're going on. Just talk to my agent, you know? And, and, and so the new criticism will be like, we're no, we're no one's talking to each other.

1:26:51It's only agents talking, you know, we're communicating through like, uh, you know, can on a string or whatever. Yeah. we, we, we got to hop on with the test from positron. Uh, we should, this was great. I'm super excited for you guys. Thank you. I'm a big fan of both of you. We'll let you hop in. Yeah, sounds good. You guys are going to absolutely cook together. Thank you. Thank you. Thanks so much. Let me tell you about MongoDB. What's the only thing faster than the AI market? Your business on MongoDB. Don't just build AI. Own the data platform that powers it. And let me also tell you about CrowdStrike.

1:27:25Your business is AI. Their business is securing it. CrowdStrike secures AI and stops breaches. We are joined by Mitesh Agarwal from Positron AI, building a new chip for the AI era. Welcome. What's going on? How are you doing? Hey, John Doherty. Pretty good. How are you guys? Thanks so much for hopping on the show. Pretty good. Great to have you here.

1:27:45Mitesh Agrawal:I just want to start by saying I've been in the background of Stephen doing this multiple times. Oh, yeah. And Stephen Balaban from Lambda. That's right. He loves you guys. So this is my first time on. So thanks for having me. Yeah. How direct is the lineage from Lambda? you're working at effectively NeoCloud, you see the problem, you go solve the problem externally with a new startup. Is the story that simple? Yeah, fairly. I mean, for me, I mean, like, look, I didn't found Positron, right? Positron was co-founded by Thomas Summers and Edward Komet. Sure. Another lineage, Grok lineage from before, and they designed the actual Silicon and the system setup, and part of it is just great luck.

1:28:28Mitesh Agrawal:I've known both Steven and Thomas for over a decade. I've been close friends with both of them. I've worked with them, been roommates, everything, all of those things. And Thomas has been wanting me to join Positron since day one, since he started the company in 2023. But Lambda was just starting on its hokistic growth then. And I was like, look, I'm not leaving Lambda. Started the company with Steven there and Lambda Cloud. But early 2025, like late 24, reasoning models had come out. O1 just started to get in the zeitgeist. and then video generation. Sora, first Sora came out. Not a lot of people saw it, but I got to see a little bit behind the scenes on the video generation models, the amount of memory.

1:29:08Mitesh Agrawal:I remember looking at the Google video model back then. It needed four H100s to run a 10-second clip. It was completely memory-bound on bandwidth and capacity. And I knew what Thomas was building. I was like, this is actually very interesting. Memory is going to get a big part of the story very poor inference. Someone is building something about it. Let me go get and work at actually the fundamental technology there. Like Lambda builds technology on the cloud and services. And I'm chemical engineering, studied fabrication, never used it ever. So I was like, all right, I'm going to go back a little bit to my roots and come back to it.

1:29:48Amazing. How much is AI actually accelerating semiconductor design, semiconductor fabrication? Uh, we saw one of your investors, Dylan Patel, semi-analysis talking about the, the opening of jalapeno chips seemed like ahead of schedule or very, very quick. Uh, for a long time, we've been hearing, oh, new chip, that's three years. That's five years. Feels like it's 18 months now. What are you actually feeling? What are you seeing?

1:30:17Mitesh Agrawal:Yeah. To start from it, it was like to answer your last part about it. Like, man, new chip every 12 months. NVIDIA is the absolute king. and if they're coming out with a new silicon every 12 months, you better get in that game or don't even be part of the conversation kind of thing, right? So that's for sure. In terms of utilization of AI, I mean look, I'll just focus on Positron itself, right? We're a small team I mean, we got to, right just now I mean, just yesterday or today, crossed 100 people but over 50 of that is over the last three months. So we got our first gen product out with less than 20 people and that's built on FPGA so it's already pre-taped out silicon and we're deploying and implementing our architecture and our second gen Those are the 50 Atlas racks you have at Oracle?

1:31:04Okay, so those are FPGAs

1:31:06Mitesh Agrawal:Yeah, those are FPGAs and it's kind of like harking back to a little bit of previous times when you used to design and build silicon you would actually test it on FPGA before going into the tape out kind of thing so we just wanted to get a product out as quickly as possible, like that was the whole thing It's like, you know, from the start of the company, we got our first shipment to a customer in 15 months. And it was built on FPGAs, obviously, but to get the full, you know, bit file ready, getting it deployed, getting models running on it, it was all done in the first 15 months and then over the last 10 minutes killed it out.

1:31:40Mitesh Agrawal:But yeah, I mean, like, look, we have to use a lot of the AI toolkit, especially on verification. design less so I would say I mean look obviously we use a lot to kind of interact with like now Astra for example this phenomenon right you know to interact with it but you're still not going there and saying hey come up with this new design yet although like you know Anas and others they're obviously built out and they raised a big ground for that as well right so it's going to come you know you're going to see very soon it's like one person and Astra or one person and Astra's kid taped out a chip kind of thing.

1:32:16Mitesh Agrawal:But we have to use it a lot. I mean, if you think about 100 people or, you know, very recently, very recently, 50 people. For a company that is targeting tape out end of this year to do with like 50, 60 people, it's a very tiny amount in the Silicon world. What is the demand side of the equation work? You're already working with Jump Trading, i3d.net. Is this something where you, like, if you can get capacity, if you can get performance, some solid benchmarks, you think that sales isn't going to be a problem? Or are you going to have to find and work very closely with a customer to sort of co-design a solution for a particular problem within the AI stack?

1:32:58Mitesh Agrawal:Yeah. I don't want to trivialize or make it sound simple like that. Your sales guys might be listening and they're like, we work very hard, okay? Shut up. Well, we only have one. Everyone is a salesperson. We only have one salesperson. You know, like in that way, right? But the point I will make is really around the way we think about the demand curve is you're kind of hitting the nail on the head in saying that, like, look, if you can make your silicon work, show the performance is comparable, especially in the current ecosystem, even within the niche of doing this ag or something like that. But especially if you can make the entire inference kind of workflow, have a good TCO and or, and generally people always assume it's an or that you have a good TCO or you have a great interactivity curve.

1:33:48Mitesh Agrawal:But if you can do and or, you know, you're going to bound to have get demand. More importantly, you know, when you step into the rooms of like not only just jump trading or, you know, hedge funds or kind of inference service providers, but like really the big labs, the hyperscalers. kind of two questions that it boils down to is like, hey, like, look, guys, can you fabricate this in enough quantities? Like, you know, is your supply chain and the way that you are using the technology components, is it robust enough that you can fabricate it, that we can be interested in it? And then the second thing they're asking is, can we deploy it?

1:34:17Mitesh Agrawal:You know, is your power source, like, you know, do you need this kind of liquid cool setup? And if so, then, you know, we might not have a data center because we've already allocated it to GPUs or TPUs. Or can you do something else? So the questions you can see there they are asking is not that, hey, we will see, we're not sure of the demand curve. So from that angle, you are kind of spot on that, look, if you can make the frontier models run, you're bound to find kind of adoption into this market. And that is a really great, I mean, I'm so lucky, as Positive, we are so lucky to be building silicon in this environment.

1:34:52Mitesh Agrawal:And that's kind of what you're seeing for the silicon companies is raising rounds right now. Yeah, I think$9 billion has flowed into silicon companies over just the last 12 months. Yeah, which we were talking yesterday, which feels incredibly low relative to the annual spending category. Gavin Baker, another one of your investors, has this quote where he says, I see it as 1 % market share is$100 billion opportunity. And that sounds like a crazy bull take. And then you realize, wait, no, NVIDIA is a$5 trillion company. It's going to be a$10 trillion market any day now. And so, yeah, actually 1 % should equal$100 billion.

1:35:35But yeah, anything else?

1:35:37Mitesh Agrawal:He said that in a board meeting to me, I don't even know, like a year ago or something. It's basically like, yeah, look guys, like Mateusz Thomas, just 1 % of the market, $100 billion enterprise value, just focus on your architecture where you can do well. you know like one of the things like you know people always like whenever a new new chip company raises around the headline and luckily you guys don't have that which is like oh to rival nvidia it's like guys like no no no one is rivaling nvidia like get to at least 10 of their revenue before before putting the tagline on right but uh but like the point there is just like look nvidia is everywhere you got to work in that ecosystem uh to to both work with them but also like having a product that is differentiated enough like you have to have technical innovation obviously to stand out and then show your performance TCOs and interactivity.

1:36:26Mitesh Agrawal:But then you also got to prove that like, look, in the world of HPM CoVos constraint, like for us, our big stories are, you know, like, look, HPM and then CoVos, bottlenecked, you have NVIDIA, TPUs, AMDs ahead of you in that line. You know, how do you get around that? Well, again, you say, okay, we are using commodity memory. Well, pro and con, no free lunch in Silicon land. Like, you know, commodity memory is slow. How do you solve that? That's where the technical innovation comes in. And then second thing is like, okay, it's still not trivial to get commodity memory. It's not like I can just show up to Samsung or Micron and be like, hey, can you give me LPDDR5X?

1:36:59Mitesh Agrawal:You have to still figure out how to get that and plan it. But it is more feasible to get it. And that becomes a story that the company can then scale out and saying, not only are we going to have a product, but we're going to have a product that will scale with the requirements of hyperscalers and kind of the frontier. Yeah, how do these customers think about the minimum scale when they're working with you and they're looking at making orders that will be delivered in, let's say, 2028, 2029, right? You need to be able to – and during that same time period, right? We saw Microsoft yesterday wants to add an extra 10 gigawatts, right?

1:37:3426 gigawatts.

1:37:36Mitesh Agrawal:Yeah, 26. They want to get to 38 gigawatts by 2032. Yeah, so you're sitting there and it's like to really be worth a company at that scale's time, you need to be thinking about it's almost like, hey, the orders we want delivered in 2029 are like a proof of concept for the 2032 order, which will be at some scale to actually impact and be able to scale the fleet in a meaningful way. But how are you thinking about, that feels like the biggest challenge is minimum viable deployment. I mean, literally you kind of circle back on, as I said, when we walk in these meetings, And like, look, the scale depends on, like if you're going into hyperscalers and frontier labs, and I said, the first question they ask is like, guys, can you fabricate like this?

1:38:21Mitesh Agrawal:Like in enough, and the question there is like, in enough quantities that it's like worthwhile to us. And that answer for hyperscalers and frontier labs, like honestly, they will literally say gigawatt plus, like come up to us with a proposal of a gigawatt plus, which is kind of insane, right? Like a gigawatt, like even at a video scale, you're talking about$40 billion,$35 billion worth of revenue for them, right? Even, you know, assume ASIC, cheaper, blah, blah, blah, all those things, you're still talking about tens of billions of dollars, right? But like, at least you have to show a plan of like, how do you get to hundreds of megawatts in, you know, to use your, like, your specific year, 2028, you know, for us, we're taping out this year, production kind of ramped up in second half of 2027.

1:39:00Mitesh Agrawal:In 2028, we better have a plan of how do we get to like hundreds, and I don't want to just say, cop out by saying hundreds as in just 100 megawatts. hundreds means truly like three, four, five and above for those. Yeah, so that by the next scale up, you're in that gigawatt range. Yeah, exactly. But also I also don't want to discount the fact that you have other customers like you have inferences service providers, obviously sovereign AI clouds, quantitative finance, quant finance kind of spectrum. And so they have different magnitudes of kind of requirements that come through with it. So, you know, although we do internally use kind of go big or go home as a thing.

1:39:38Mitesh Agrawal:Like we have to attract one of these large customers to really be a long-term viable company. You know, I don't want to just like discount the fact that like, look, you can grow the company through the ranks as well. Like you can grow the company, you know, get 200 million revenue for 250 million, a billion, 2 billion through this other kind of channels as well, right? I think that becomes a big part of it. But yeah, like if you really want to get to like the frontier labs and hyperscalers, you're really talking about hundreds of megawatts. And that's why like, you know, Like, look, when we, you know, we have VentureTech Alliance on our kind of cap table.

1:40:10Mitesh Agrawal:And when we speak with TSMC for fab capacity, they are also wanting to know kind of like, can you scale? Like, you know, do you have the balance sheet to do that? Like one of the reasons we raised, you know,$875 million is not like we need$875 million to spend tomorrow or even in the next six months. I mean, look, we raised$230 million in Series B in February of this year. Untouched, right? We still have all that capital. Part of it is because we have been making revenue this year. but we do have plans to spend that very quickly. Thank you. That was actually the job. I was wondering what you were doing.

1:40:42Mitesh Agrawal:Untouched. Untouched. Untouched. Because we're making revenue. Yes. The main point that is there though is like, look, they want to know, like if you actually get a customer, you have the capital. And even that capital, that is not enough equity capital to scale out to even 200 megawatt, right? Then you have to go to the black students of the world and figure out how to finance that deal. kind of what Lambda has done, right? What's the software side of the equation? You're coming for NVIDIA. You're challenging them. You're going to drive their market cap to zero. You have to drive that end. Obviously, this is a market that can sustain multiple players, and there's different tools for the job.

1:41:23But interoperability is important. And I'm interested in terms of software development. Are you going to lean more open source with the software side of the business or more integration with just a few buyers and co-design on the software side to make sure the integration is really seamless? Is there even, do we even need to be having a software conversation in an era where AI agents can write code?

1:41:53Mitesh Agrawal:Yeah, I mean, you definitely need the software conversation because you have to plan around how people want to use it and people want to use it how they're currently using it and going to continue to use it, which is based on NVIDIA stack, but also primarily based on PyTorch and then your VLL, MSG, Lang, and I'm specifically focused on inference elements. Like, look, training, that's such a harder challenge. Like what Jensen says, like true mode around scale out and everything, right? That's the only reason you have probably only TPU as a potential kind of only other silicon that can be used for training, right?

1:42:28Mitesh Agrawal:Sure, sure, sure. But on the inference side of things, for sure, you have to have the conversation. I will say this, in the era of agentic kind of software development, the worries around like, hey, you know, model drops, if you don't have access to it, it takes you days, weeks, months to bring it up. It's going away. Like, you know, we had Muse Glimmer Drop and within our team, you know, on our ad, let's first-gen could get it up and run it within hours, right? And yeah, exactly. Like, I had the same reaction internally when we had that. And people are making it even faster and more automated too.

1:43:02Mitesh Agrawal:Like, you don't even have to interact. Model Drops comes in, can probably do it. And that's a very near future of it. But to that point, it doesn't give you the right-of-way, the efficiency, the optimizations. Like, you know, you want to extract every dollar off it. So to your question around, you know, when the customer is large enough, you want to work closely with them to like literally extract every single dollar. And also, like, I'll be very frank, like Anthropic, OpenAI, this Frontier Labs, Hyperscorders, they are so sophisticated. They kind of want to come in and be like, look, guys, even if you don't want it, we are working with you to make sure that this is kind of like, you know, this is optimized to the fullest, right?

1:43:37Mitesh Agrawal:So the answer, as always, in this scenario, is all of the, you know, even though it might sound like, oh, it's a very cliched answer, but it really is that way. Sounds like the mafia coming in. Oh, your software stack is an open source, so you're about to open it for me. I'm going to make some changes if I need them. The software stack is going to be built on open source, in the sense of, if you want to make every company to use us for inference, you have to build it on SG Lang and VLM kind of setup, right? But, you know, it's like when you're talking to SpaceX or Anthropic or OpenAI, they're not using the generic SG-Lang or BLM.

1:44:12Mitesh Agrawal:They have all their optimizations built in, and they're going to help you do that. Then, obviously, there's DISAG. Then within DISAG, there's all the different domains that they do. And they're going to figure out, it's like, oh, Jalapeno is good for this. Positron AI, you're good for this. And then they're going to say, okay, that's how we're going to use you guys. Amazing. Well, exciting times. I want to hit the gong for you. You raised$875 million. That was a solid one. Thank you. Congratulations. Thank you so much. Great stuff. Great to meet you. Keep an eye out on Instagram because we're definitely dropping a NVIDIA Challenger slide later today.

1:44:50Please do not associate my photo with that.

1:44:52Mitesh Agrawal:But yes. Well, have a great rest of your day. Looking forward to the next appearance. Have a good one. Great to hang. Goodbye. Cheers. Let me tell you about Railway. Railway is the all-in-one intelligent cloud provider. Use your favorite agent to deploy web app servers, databases, and more while Railway automatically takes care of scaling, monitoring, and security. And lastly, the New York Stock Exchange. Want to change the world? Raise capital at the New York Stock Exchange. You can see Positron over there pretty soon. Pretty soon. Picking up some fresh ones. Wonderful week. Wonderful week. Short week.

1:45:27Monday. Yeah. Monday, 11 a.m. Do us a favor and go ahead and have the best weekend of your entire life. Have the best weekend of your entire life. Let's do it. Put the pieces together. Make it happen. We'll see you on Monday. Leave us five stars on Apple Podcasts and Spotify. Sign up for our newsletter, tbpn.com. Goodbye.