The Twenty Minute VC (20VC): Venture Capital | Startup Funding | The Pitch
00:19:52 · Chase Lochmiller, Harry Stebbings
He calls it the idiot index in terms of, know, what what is the what is the cost of raw materials, and then what is the end product relative to that cost of, you know, just the raw raw materials going in. By being vertically integrated, we have a perspective on, like, the end to end cost of everything going into building and operating an AI factory. [00:20:10] S1: How much extra margin do you juice out by having that internal build process yourself? Like, is [00:20:16] S0: the idiot index chasm? Look. Electrical manufacturing is not like an ultra high margin business. Like, today, it's actually spreads have gone up quite a bit. Margins have gone up quite a bit just because they're so short on supply. But it's not where like the critical alpha of... It's not the main reason we're doing it. It's like stacking margin. It's more [00:20:35] S1: Availability and getting out.
00:20:35 · Harry Stebbings, Chase Lochmiller
[00:20:35] S1: Availability and getting out. [00:20:36] S0: Availability, being able to deliver on time. And then also, it gives us a critical innovation platform. By being able to, you know, start from first principles and say, okay, we can bring in raw materials and we can build anything we want in the world. What is the thing that we want to build to ultimately serve the workload? And so when you look at the campus in Abilene, the inspiration for that was like, okay, we wanna build a one gigawatt scale computer where you can interconnect a giant cohesive cluster of GPUs that can operate one cohesive workload across the entire campus. And what does it look like to actually build that thing from from the ground up? That's how, you know, the cores are designed. That's how the GPUs are designed. That's... You know, all of it is designed to run on one cohesive RDMA fabric. When we think about scaling of inference, you know, 2026 is really about the scaling of utilization of AI or utilization of LLMs and foundational models for useful tasks. You know, it's been this era of, you know, scaling of agents and and and tokens, token utilization. And, you know, during that moment of scaling infrastructures, people are finding utility in in these AI models, it's driving a lot more demand for inference. It's the era of the agent, the era of of inference. And for that, you don't need a a gigawatt scale computer to serve these models. You can do it with a much smaller cluster. What matters is actually how quickly can I go from not having anything to being able to deliver tokens? Like, so
00:22:00 · Harry Stebbings, Chase Lochmiller
[00:22:00] S1: what is my time to token? I love the analogy you said there of it's like whack a mole. What is the biggest supply constraint that we have today? [00:22:07] S0: Energy is definitely a key constraint. Power that's available for compute is a key bottleneck. Alongside that, labor is a very key bottleneck. There are a finite amount of skilled trade workers, electricians, welders, plumbers, construction workers in The United States. And then when you overlap, trying to find if I have access to energy in this unique place, can I get the labor to that place to actually bring the AI factory to life? You know, that that that is a big challenge. [00:22:37] S1: With the greatest of respect, if power and labor are the two biggest constraints or challenges, The UK is totally fucked. We have energy prices that are four times higher than anyone else, and we don't have labor. And we have humans. They just don't work. You and The US have both, but significantly more expensive than China, if we're honest. Power is not significantly more expensive. Really? No. You don't think that the government is subsidizing data centers in China with much cheaper energy to power that? I'm asking him, not telling. [00:23:07] S0: There are subsidies going in place, but in The United States, we are globally competitive with with power pricing. Labor, I'll give you. Labor in China is far cheaper than United States.
00:23:07 · Chase Lochmiller, Harry Stebbings
[00:23:07] S0: There are subsidies going in place, but in The United States, we are globally competitive with with power pricing. Labor, I'll give you. Labor in China is far cheaper than United States. [00:23:16] S1: What about policy and regulation? Everyone I speak to is like, oh, it's the red tape. It's the policy and regulation that stops us in The US being able to build out. Is that a problem in the way that it's told to me?
00:23:27 · Chase Lochmiller
[00:23:27] S0: I wouldn't classify it as a problem. I would classify it as something that needs navigated. You know, when we think about policies, we want good policies to be in place. We don't want just the Wild West, everybody out doing whatever they want, building whatever they want with no no care for anybody else in the world. You know, these are big investments that are being made. They have to be done thoughtfully. We are supporters of the right policies being in place, but it does cause friction in terms of developing things faster. That's actually one reason we also like the idea of manufacturing infrastructure as opposed to making everything a giant construction project. If I were to put you in charge of policy to enable and encourage this ecosystem to flourish, what would you do? What would you do differently? The thing about policy is it's hyper local. Politics are local. And what people care about is they care about are their jobs being created? Is this gonna drive up my energy costs? Is this gonna take all of my water? Is this gonna pollute the air so that, you know, my my kids get suffer from some disease as a result? Like, you know, care about are the data centers being good stewards and good citizens of the community, and are they actually creating value for the community? And then what are other ways that the data centers are giving back? And so, you know, this comes in the form of things like tax revenues and things like that. So I think one of the challenges for AI data centers broadly right now is that I think there's a lot of misinformation out there about what the impact of a data center is. The number of people that have told me that data centers use all the water in the world is crazy. It's also just false. When you look at all of these modern AI factory designs, they use pretty close to zero water. One of our giant buildings in Abilene, Texas, call it a 140 megawatts of power is like what's budgeted for each of those buildings on the on the first eight buildings. They use about the same water annually as about 10 single family homes. The primary water usage there is like the staff using the bathroom, washing their hands, us watering the plants on the property. It's very it's very de minimis water usage, and there is water in the building. We are using water to cool the GPUs. The critical aspect here is we...
00:25:36 · Chase Lochmiller, Harry Stebbings
We've actually designed a closed loop architecture so the the cold water is entering into the racks, and then it's going out to a chiller outside, and we're sort of exhausting the heat. [00:25:46] S1: So the water requirements argument is just wrong? [00:25:49] S0: The water requirements argument is is just wrong. Yes. Okay. What about energy prices going up? So I think this is an important aspect for the data center industry to get right and to storytell effectively. We like to look at data for these things. When you look at markets where data centers have made investments and have built big data centers, typically energy prices for communities have come down because there... It catalyzes more investment in energy generation technology, in energy generation capacity, and you end up with more megawatts being amortized over the same transmission and distribution infrastructure. And as a result, people's energy costs end up coming down. When you look at some of these big builds that need a lot of net new generation capacity, we are very supportive of, you know, the data center industry helping to bring online new power production in order to support requirements. [00:26:42] S1: So actually, that too is misinformation. Energy prices won't go up for local towns and villages.