00:21:58 · Jaimin Rangwalla
[00:21:58] S0: So I think the Open Claw phenomenon is actually really interesting. I think most people maybe don't understand and appreciate it. What OpenCLaw is, it is a form of a harness. Harness is like the fancy word for how a person interacts with a model. Before, you're interacting with a model with just the ChatGPT interface. And then even if you have a terminal, maybe you're interacting in the clawed code terminal. But now a harness allows you to interact. You can be on another computer just typing to your claw and having it control a computer in a different location or a virtual computer and actually taking actions on your behalf. You can WhatsApp message it and say, you know, while I'm in the office, like we have analysts that are using it and testing it for us. He'll have his home open call. He'll message it and say, oh, book me a reservation on Friday at this restaurant, send the calendar invite to Jaemon, and then also make sure that we have a car service set up to take us there and back, and then send him the confirmation email and make a calendar appointment, do all that stuff. It is able to do all of that in the background, and it'll just come back to you with a message and say, okay, I did this and here it is. And so it's almost like the ability to interact has changed with the clause setup. And so now you can use a terminal to interact. You can have it in your pocket like the phone. We have a slide in our deck that just talks about the phone's almost like a remote now. It's a remote for your agents. Which agents do you have working on what? Which agents do you have doing this for you? And you can also launch multiple agents. And so I think that OpenClaw, you're seeing the trajectory, just the number of people that are using it and programming for it and trying to figure out how to incorporate it. Even in China, every one of the big internet companies has their own claw concept. ByteDance has one, Tencent has one, Alibaba has one. It's amazing how quick this has taken off, I don't think people fully appreciate it. But to me, it's just an intermittent state. I don't think that you're going to have it where you've got to go home, you've to hook up all these connections to your cloud, because today you still have to give it access to Gmail and this and that. There's going to be a big opportunity for someone to just say, Oh, here's your phone.
00:23:57 · Jaimin Rangwalla, Molly O'Shea
Here's the app, this is your super app. This now allows you to connect to everything that you have, and you can just ask this app questions and it is going to be the super app for you. [00:24:06] S1: Did you see the clip of Nat Freeman at Stripe sessions? [00:24:10] S0: I did not. [00:24:12] S1: So, he has Open Claw deployed on his phone, think maybe his laptop too, and so his Open Claw saw that he was dehydrated, and so it was like, Oh, go grab a glass of water. So he went to the kitchen, he grabbed a glass of water, he drank it, or maybe it was a bottle, and Open Claw took a picture of him and goes, nice job. And then he was also driving in his car, and they were like, you need magnesium. And so the car then rerouted to Whole Foods to get them magnesium. Was pretty crazy. [00:24:44] S0: Yeah, I mean, we're just at the beginning of what's going to be possible. [00:24:49] S1: So you mentioned that memory per person is exploding. Can you talk through the TAM of that? Yeah.
00:24:56 · Jaimin Rangwalla
[00:24:56] S0: So historically, you think about it, memory was tied to smartphones, memory is tied to computers. Everyone has a smartphone, everyone has a computer, and so you can just say over time, as people started adding more technology devices, individual might have eight gigs of RAM on a computer, you have eight to 16 gigs of RAM on a phone. And so you've seen like a natural growth of that just over time as you've seen penetration of phones, penetration of the computers, and then the density within each device also increases over time. But now if you think about it, if you or me in a year or two, we're going have a claw that's running hundreds of agents at all time. I'm going to have a similar impact at work. I'm going to have hundreds, maybe thousands of agents running at all time. All those agents require CPUs, GPUs, memory. Now it's persistent memory because it's not running twenty four hours a day. Some will run for some amount of time, some are less, you get the kind of a general direction of where this is going, which is your footprint, your like semiconductor or technology footprint as an individual is about to expand by like 10x because you used to have a couple of devices. Maybe you're someone who has an iPad too, you have x, a little more, but like three or four devices is about to go to thousands of virtual devices on top of, and the virtual devices are the agents, and each agent requires, you know, semiconductor content. So it is hard to like fathom a world where like we're all having this like big semiconductor footprint, but that's what's happening underneath the hood, right? And if we're all gonna be users and we're all gonna be using hundreds and thousands of agents at a time, that is where we're going. Like, on our call, we had Boris, Cherny, who's former CodeTwo alum, but also the founder of Claude Code, And he was saying that, you know, he runs, you know, some number of agents during the day, but when he goes home, he's running or on on his way out, he's has a thousands of agents running to kinda do work all through the night before he comes back in the morning. So just imagine, like if we're all going be doing things like that, where we're all going to be having periods where we're running hundreds of agents, and it can be simple tasks.
00:26:55 · Jaimin Rangwalla, Molly O'Shea
It doesn't have to be like, you know, a very complex programming task, but just the footprint of each individual in terms of their semiconductor content, their power content, right? It doesn't just apply to semiconductors, applies to how much power each person consumes, is all going to increase significantly. [00:27:12] S1: Because of those behavioral changes, how is that affecting the architecture of AI?
00:27:17 · Jaimin Rangwalla
[00:27:17] S0: I think that we're now moving to a world where the chatbots, you know, we joke around internally, the chatbots have amnesia, right? Because every time you might give it some files, you give it some medical records, it does a great job of going through and analyzing it. You go back the next day and you give it the same record. You ask a question about those records, it doesn't remember. I don't if you ever watched that movie, fifty First Dates, Bob Sandler, right? Where basically he has to re explain every day what the situation is. It's very similar to that. But what's changing is now you're getting persistent memory with all of the the next evolution of, accelerators. And so I think that you're seeing memory content is increasing. The agent is not gonna have amnesia anymore. The agent is gonna be able to remember. And now because the agents are launching agents and they're doing very complex tasks but also simple tasks, they need offload from CPUs too. Historically, CPUs have done something called serial processing, which is like you just give it a set of instructions and it does one by one by one by one critical instructions, but one in row. And I think that as an agent has some element, which is like, make a reservation, that might just be very serial tasks. It might have something which is like, okay, program something that's super complex and might require parallel tasks. And so I think that that is just creating a massive need for more CPUs and more memory, and we're seeing that. We're actually just at the beginning of that. I think agents is really what is driving that.
00:28:38 · Molly O'Shea
[00:28:38] S1: There was a really interesting slide on that where you're showing the shift of GPUs to CPUs, and it was like a four to one conversion. So how did you kind of model that out, or how are you estimating it?