AI基础设施公司Runware在Sonic Information Pod揭幕几个月后，又再次发布新闻，Sonic Information Pod是一家工厂建造的模块数据中心，被运往客户准备安装。 现在公司有更大的计划。 它告诉TechCrunch它想建造一个工厂，在生产线上组装这些吊舱，就像汽车一样。
这个想法并不是全新的。 Crusoe和Schneider Electric等公司也出售预制吊舱，但Runware 称可以更快地运送吊舱。
Runware的联合创始人兼首席执行官Flaviu Radulescu告诉TechCrunch，该公司计划在2028年之前将设在罗马尼亚的工厂的产量扩大到每天30兆瓦的数据中心容量，即每月近1千兆瓦。 如此之快的一年里，Runware的产量大约相当于全美国今年预计的数据中心功率，大约10千兆瓦。 但这也反映出整个行业都希望更快地部署数据中心。
Nvidia 宣布，例如今年早些时候的Vera Rubin AI工厂和DSX POD. 两者也都是为了让公司更快和更容易地建立自己的AI数据中心。 然而，与Runware的区别在于，它实际上已经建造了一个工厂，而不是仅仅设计了让其他人建造的基础设施。
称雷达 runware将于明年开始逐渐增加产量，它已经拥有两家工厂——一家已经用了几年时间来建造吊舱，另一家也在今年早些时候开始建造。 二期预计数月内完成，明年初上线。
运行软件将在装配线上制造模块数据中心。 客户可以提供自己的站点来组装它们，或者Runware可以为它们找到一个。 雷达Scu 称 Runware的目标是在48小时内把舱上线。 时间包括安装和设置时间，而不是建设时间。 一个吊舱曾经花了三个星期才建成但不久后它就会用一天时间加速生产称公司如果部件失效，运行软件将提供零件。 客户还可以从Runware租借计算或提供自己的GPU，并每月支付客舱和业务费。 电源和互联网是分开收费的，He 称。
客舱也可以按照顾客的喜好定制，he 称。 客舱有标准设计，但可以配置以满足客户要求和最新的GPU芯片。 芯片在订购后需要很长时间才能到达，“我们的舱载时间也比目前的GPU周转时间短，“对于新的GPU世代来说，我们内部的硬件团队可以设计、建造和测试组件本身，使我们能够迅速适应。”
现在，这些都是计划——执行是考验。 工厂需要大量人员，库存，供应链物流，以及金钱。 有一些关于重塑制造业的警告性故事，特别是电动车辆起动器，它曾经价值超过130亿美元，与传统工厂相比，它难以以成本效益高的方式生产大量电动车辆。 称计划募集B系列，但是现在它正在完成，发布工厂去年12月的5000万美元A系列，融资。
Radulescu 称解释Runware如何设法避免抵达的命运。 他接着说，“我们确实有人口和材料成本。” “但相对于部署人工智能计算的价值而言，我们的工厂工作人员具有成本效益。” 他还认为，设计自己的系统并购买广泛可用的、负担得起的零件有助于降低成本。 我们从汽车工业引进了一位经验丰富的工厂经理
采购组件也可能是一项挑战。 虽然Runware 称它设计和建造了自己的冷却系统和其他带有标准组件的吊舱系统，但一些零件，如泵和风扇，来自德国，它仍然依赖于Nvidia进行联网。 但Runware 声称自一个月前开始向客户以外的地方提供Sonic吊顶以来
美国和国外的数据中心因消耗了多少能源以及这对电网和其他资源有何影响而遭到炮火袭击。 Radulescu 称公司只需要电力和互联网连接。 他们将使用闭路液冷却系统，称提到其计划选址清单，并补充说，该公司在比Amazon、Microsoft、Google等超标器使用的选址上部署模块化数据中心。
他继续说，这些网站通常已经拥有电源，吊舱还“完全无声，温度达华氏86度。 我们尽可能使用可再生能源，”他继续说。 “我们正在积极努力扩大我们的能源供应者和场址网络。 我们的目标是把可再生能源作为我们的主要能源。
接下来，Runware将于明年初将其新工厂上线，然后扩展到美国和世界其他区域。 模块系统是未来，不久将成为“大规模部署AI的标准”,Radulescu 称。
他补充说，“客户应该能够从一开始就规划一个在工厂建造的吊舱周围的超规模数据中心，并让它在几个月而不是几年内运作”。
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AI infrastructure company Runware is making news again, just months after unveiling the Sonic Inference Pod, a modular data center built in a factory and shipped to customers ready to install. Now the company has bigger plans. It told TechCrunch it wants to build a factory that assembles these pods on a production line, as if they were cars.
The idea isn’t entirely new. Companies like Crusoe and Schneider Electric also sell prefabricated pods, but Runware says it can ship its pods faster.
Flaviu Radulescu, co-founder and CEO of Runware, told TechCrunch that the company plans to scale production at its Romania-based factory to 30 megawatts of data center capacity per day by 2028, or nearly 1 gigawatt per month. That’s a whole lot of capacity: at that pace, Runware would produce roughly as much in a year as the entire U.S. was expected to add in data center power this year, about 10 gigawatts. But it also reflects an industry-wide push to deploy data centers faster more efficiently.
Nvidia announced, for example, the Vera Rubin AI factories and the DSX POD earlier this year. Both are also meant to make it faster and easier for companies to build their own AI data centers. The difference with Runware, though, is that it says it has actually built a factory rather than just designed the infrastructure that would let others build one.
Radulescu said Runware will gradually increase production starting next year and that it already has two factories — one it has used for a few years to build the pods, and a second it started building earlier this year. The second is expected to be finished within months and go online early next year.
Runware will manufacture the modular data centers on an assembly line. Customers can provide their own site to assemble them, or Runware can find one for them. Radulescu said Runware aims to bring the pods online within 48 hours. That time covers installation and set-up time, not build time. A pod once took three weeks to build but it will soon take one day as it ramps up production, says the company. Runware will provide spare parts if components fail. Customers can also rent compute from Runware or supply their own GPUs and pay a monthly fee for the pods and operations. Power and internet are charged separately, he said.
The pods can also be customized to customer preferences, he said. The pods have a standard design, but can be configured to meet customer requirements and the latest GPU chips. Chips can take a long time to arrive after they’re ordered, which works in Runware’s favor. “Our pod delivery times are also shorter than current GPU lead times, giving us time to adapt the infrastructure to the hardware being ordered,” he said. “For new GPU generations, our in-house hardware team can design, build, and test components itself, allowing us to adapt quickly.”
Right now, these are all plans — execution is the test. The factory will need a lot of people, inventory, supply chain logistics, and money. There are cautionary tales about reinventing manufacturing, notably the electric vehicle startup Arrival, once valued at over $13 billion, which struggled to mass-produce electric vehicles cost-effectively compared with traditional plants. Runware, which has raised more than $60 million to date, said it plans to raise a Series B, but for now it is finishing and launching the factory with the $50 million Series A it raised last December.
“Our cost structure is very different,” Radulescu said, explaining how Runware seeks to avoid Arrival’s fate. “We do have headcount and materials cost,” he continued. “But our factory staff is cost-effective relative to the value of deploying compute for AI.” He also said that designing its own systems and buying widely available, affordable parts helps keep costs low. “We’ve brought in a highly experienced plant manager from the automotive industry to work alongside our chief of hardware and help us get that execution right.”
Sourcing components could also be a challenge. Though Runware says it designs and builds its own cooling and other pod systems with standard components, some parts, such as pumps and fans, come from Germany, and it still depends on Nvidia for networking. Still, Runware claims it has received $1 billion in committed interest for its Sonic pods since it began offering them to outside customers a month ago, “representing over 20 megawatts, which we’re now working to deliver,” Radulescu said.
Data centers in the U.S. and abroad have come under fire for how much energy they consume and how that affects the grid and other resources. When pressed, Radulescu said his company’s pods only need power and an internet connection. They’ll use a closed-loop liquid cooling system with air-cooled radiators to release heat, so they don’t really need a water connection. “We’re working with power providers on a site pipeline covering 397 megawatts, with potential to expand to 1.2 gigawatts,” he said, referring to its list of planned sites and adding that the company is deploying its modular data centers on sites that are much smaller than those used by hyperscalers like Amazon, Microsoft, and Google.
The sites, he continued, typically already have power, so they shouldn’t further strain the grid or disrupt the community. The pods also run “completely silent up to temperatures of 86 degrees Fahrenheit. We use energy from renewable sources whenever possible,” he continued. “We are actively working on expanding our network of energy providers and sites. We’re aiming to have renewables as our main energy source.”
Next, Runware will bring its new factory online early next year, then expand to the U.S. and other regions worldwide. Modular systems are the future and will soon become “the standard for large AI deployment,” Radulescu said.
“Customers should be able to plan a hyperscale data center around factory-built pods from the beginning and have it working in months instead of years,” he added.
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