
据水基金会(Water Foundation)称,美国数据中心每年使用170亿至190亿加仑水来冷却发热的芯片——这一数字预计在未来五年内将翻三倍。
US data centers use 17 to 19 billion gallons of water to cool their hot-running chips each year — and that number is expected to to triple in the next five years, according to the Water Foundation.
对于投入数十亿美元推动AI扩张的投资者来说,这是一项昂贵且政治棘手的举措。减少用水的一种方法是更好地监测冷却液,而目前这项工作需要将样本送往实验室进行测试,整个过程需数天。
That’s an expensive and politically tricky proposition for investors throwing billions of dollars at the challenge of scaling up AI. One way to use less water is to do a better job monitoring the cooling fluids, a task that currently involves sending samples away to a laboratory for tests in a multi-day process.
Omen AI成立于2024年,旨在解决这一问题。该公司正在研发一种实时传感器,用于判断阀门是否失效,或系统中的细菌生长是否威胁要堵塞水流。在6月完成3100万美元A轮融资后,Omen目前正以1600万美元的现金与股票交易收购竞争对手Aquatic Labs。
Omen AI was founded in 2024 to solve that problem. The company is building a real-time sensor to determine whether valves were failing, or if bacteria growth in the system threatened to choke off water flow. After raising a $31 million Series A in June, Omen is now acquiring competitor Aquatic Labs in a $16 million cash-and-stock deal.
这笔交易的达成,源于Omen创始人扎克·拉贝尔格(Zach Laberge)通过一位过滤领域投资人结识了Aquatic Labs首席执行官艾伦·亚当斯(Allan Adams)。两家初创公司都在研发实时水传感器,技术互补:Omen的传感器检测水中的元素,而Aquatic Labs的传感器检测水的碱度。
The deal came together after Omen founder Zach Laberge was introduced to Aquatic Labs’ CEO Allan Adams by an investor in the filtration space. Both startups were building real-time water sensors with complementary technology: Omen’s sensors looked for elements in the water, while the Aquatic Labs sensor tests its alkalinity.
将这两种技术整合到同一个传感器中,能够形成“关于水和流体的更丰富图景”,亚当斯对TechCrunch表示,同时也统一了他们自动化此前缓慢、手动流程的愿景。
Putting those two technologies in the same sensor creates a “much richer picture of the water and the fluid,” Adams told TechCrunch, while uniting their vision of automating what had previously been a slow, manual process.
这次合并汇集了两种典型的创始人类型:拉贝尔格辍学创办了他的第一家公司,该公司为依赖液压系统的大型建筑机械进行类似的流体分析。亚当斯是一名学者,受过物理学家训练,在创办公司之前,大部分职业生涯都在麻省理工学院(MIT)担任教授、在伍兹霍尔海洋研究所(Woods Hole Oceanographic Institute)担任研究员,致力于开发先进的海洋感知技术。
The combination unites two classic species of founder: Laberge dropped out of college to pursue his first company, which did similar fluid analysis for large construction machines that depend on hydraulics. Adams was an academic, trained as a physicist, who spent much of his career developing advanced ocean sensing technology as an MIT professor and Woods Hole Oceanographic Institute researcher before starting his company.
现在,亚当斯担任该公司首席科学官,合并后的团队正致力于将两种技术整合到一个传感器中,预计明年初将其推向市场。拉贝尔告诉TechCrunch,Omen最初的传感器将是监控芯片,到今年底耗电量将达到250至300兆瓦,价值约50亿至70亿美元,并希望到2027年底安装相当于1吉瓦芯片的数量。
Now, with Adams as the company’s chief science officer, the combined teams are working to integrate both technologies into one sensor, which they expect to have on the market by early next year. Omen’s initial sensors will be monitoring chips pulling in 250 to 300 MW of power by the end of the year, worth about $5 to $7 billion, Laberge told TechCrunch, with the hope of being installed on the equivalent of 1 GW of chips by the end of 2027.
附加价值在于正常运行时间:如果流体系统出现故障,数据中心运营商通常会选择排掉水,而不是冒昂贵设备受损的风险。这意味着要停止运营,直到流体系统恢复,这将花费大量资金。监控可以让数据中心运营商更长时间地使用相同的流体,并最大限度地降低清理成本。
The added value is in uptime: If the fluid system gets out of whack, data center operators typically choose to dump the water rather than risk damage to their expensive equipment. That means shutting down operations until the fluid system is restored, which costs a lot of money. Monitoring lets data center operators use the same fluid for longer, and minimize the costs of a clean up.
亚当斯希望他们的技术在数据中心之外也能产生影响,他告诉TechCrunch说:“水进入数据中心,然后流出并被倾倒到市政用水中,你希望整个过程尽可能安全、负责任地进行——这意味着你必须进行测量。”AI公司曾估计到2030年将在AI基础设施上花费高达4万亿美元,但一些投资者对建设持怀疑态度,导致超大规模云服务商股价近日暴跌。不过,Omen团队并不担心情绪转变,因为他们的工作是在数据中心建成之后进行的。
Adams hopes to see their technologies have an impact outside of data centers as well, telling TechCrunch that “water goes into data centers, and then it comes out and gets dumped into municipal water, and you want that whole process to happen in a way that’s as safe and responsible as possible — and that means you got to measure stuff.”AI companies once estimated as much as $4 trillion would be spent on AI infrastructure by 2030, but some investors have grown skeptical of the buildout, sending hyperscaler stocks plummeting in recent days. Omen’s team isn’t worried about shifting sentiment though, since their work comes after a data center has been built.
“我们正在与客户合作,针对他们今天正在建设或已经建成的项目,所以这对我们影响不大,因为所有这些项目都是12个月前融资的,”拉贝尔说。“我们的观点是,即使市场缩水一半,这仍将是人类历史上最大的市场。”
“We’re working customers on stuff they’re building today or have already built, and so it doesn’t really affect us because all of those projects were financed 12 months ago,” Laberge said. “Our view is, if there’s tightness, this is still going to be the biggest market in human history, even if you sliced it in half.”