深入AI数据中心探秘

As we drove through southwest Memphis, KeShaun Pearson told me to keep my window down-our destination was best tasted, not viewed.

当我们驾车驶入孟菲斯西南部时，凯肖恩·皮尔逊嘱咐我把车窗降下来--我们的目的地最好是亲自去感受，只看是不行的。

Along the way, we passed an abandoned coal plant to our right, then an active power plant to our left, equipped with enormous natural-gas turbines.

一路上，我们右边经过一座废弃的煤电厂，左边经过一座正在运营的发电厂，里面配备着巨大的天然气涡轮机。

Pearson, who directs the nonprofit Memphis Community Against Pollution, was bringing me to his hometown's latest industrial megaproject.

皮尔逊是非营利组织“孟菲斯社区反污染组织”的负责人，他正带我去参观他家乡最新的大型工业项目。

Already, the air smelled of soot, gasoline, and asphalt. Then I felt a tickle sliding up my nostrils and down into my throat, like I was getting a cold.

空气中已经弥漫着煤烟、汽油和沥青的味道。 接着，我感觉有东西顺着鼻孔往上爬，然后滑进喉咙，就好像要感冒了一样。

As we approached, I heard the rumble of cranes and trucks, and then from behind a patch of trees emerged a forest of electrical towers.

我们走近时，听到了起重机和卡车的隆隆声， 接着从一片树林后面出现了一片林立的输电塔。

Finally, I saw it-a white-walled hangar, bigger than a dozen football fields, where Elon Musk intends to build a god.

最后，我看到了它——一座白色墙壁的机库， 比十二个足球场还大，埃隆·马斯克打算在这里造出一个"神"。

This is Colossus: a data center that Musk's artificial-intelligence company, xAl, is using as a training ground for Grok, one of the world's most advanced generative-Al models.

这就是"巨像":马斯克的人工智能公司×AI正在把这里当作训练场地的数据中心，用来训练全球最先进的生成式人工智能模型之一"格罗克"。

Training these models takes a staggering amount of energy; if run at full strength for a year, Colossus would use as much electricity as 200,000 American homes.

训练这些模型需要消耗惊人的能量；如果满负荷运行一年，"巨像"所消耗的电量相当于20万个美国家庭的用电量。

When fully operational, Musk has written on X, this facility and two other xAl data centers nearby will require nearly two gigawatts of power.

马斯克在X平台上写道，全面投入运营后，这个设施以及附近的另外两个xAI数据中心将需要近20亿瓦的电力。

Annually, those facilities could consume roughly twice as much electricity as the city of Seattle.

这些设施每年消耗的电量大约是西雅图市的两倍。

To get Colossus up and running fast, xAl built its own power plant, setting up as many as 35 natural-gas turbines-railcar-size engines that can be major sources of smog-according to imagery obtained by the Southern Environmental Law Center.

为了让"巨像"快速启动并运行，xAI公司自建了一座发电厂，根据南方环境法律中心获取的图像，该公司安装了多达35台天然气涡轮机--这些像有轨电车大小的发动机可能是造成雾霾的主要源头。

Pearson coughed as we drove by the facility. The scratch in my throat worsened, and I rolled up my window.

当我们开车经过该设施时，皮尔逊咳嗽起来。 而我喉咙的刺痛感也加剧了，所以我把车窗摇了上去。

xAl's rivals are all building similarly large data centers to develop their most powerful generative-Al models; a metropolis's worth of electricity will surge through facilities that occupy a few city blocks.

×AI的竞争对手们都在建设类似的大型数据中心，以开发其最强大的生成式人工智能模型；这些设施所消耗的电力相当于一座大都市的用电量，而它们所占据的空间只有几个街区大小。

These companies have primarily made their chatbots "smarter" not by writing niftier code but by making them bigger: ramming more data through more powerful computer chips that use more electricity.

这些公司主要让他们的聊天机器人"更智能"， 不是通过编写更精妙的代码，而是通过扩大规模:利用更强大的计算机芯片处理更多数据， 从而消耗更多电力。

OpenAl has announced plans for facilities requiring more than 30 gigawatts of power in total-more than the largest recorded demand for all of New England.

OpenAI已宣布计划建设总需求超过30吉瓦的电力设施--一这超过了新英格兰地区有记录以来的最大电力需求。

Since ChatGPT's launch, in November 2022, the capital expenditures of Amazon, Microsoft, Meta,and Google have exceeded $600 billion, and much of that spending has gone toward data centers-more, even after adjusting for inflation, than the government spent to build the entire interstate-highway system.

自2022年11月ChatGPT发布以来，亚马逊、微软、Meta和谷歌的资本支出已超过6000亿美元，其中大部分资金流向了数据中心——即使经过通胀调整，这一数字也超过了政府建设整个州际公路系统的支出。

"These are the largest single points of consumption of electricity in history," Jesse Jenkins, a climate modeler at Princeton, told me.

普林斯顿大学的气候建模师杰西·詹金斯告诉我:"这些是历史上最大的单一用电点。"

Even conservative analyses forecast that the tech industry will drop the equivalent of roughly 40 Seattles onto America's grid within a decade; aggressive scenarios predict more than 60 in half that time.

即使是保守的预测也表明，未来十年内，科技行业将为美国电网带来相当于40个西雅图市的用电量。而激进的预测则认为，在短短一半时间内，这一数字将超过60个。

According to Siddharth Singh, an energy-investment analyst at the International Energy Agency, by 2030, U.S. data centers will consume more electricity than all of the country's heavy industries-more than the cement, steel, chemical, car, and other industrial facilities put together.

据国际能源署能源投资分析师悉达思·辛格称， 到2030年，美国的数据中心耗电量将超过该国所有重工业的耗电量，比水泥、钢铁、化工、 汽车和其他工业设施的耗电量总和还要多。

Roughly half of that demand will come from data centers equipped for the particular needs of generative Al-programs, such as ChatGPT, that can produce text and images, solve complex math problems, and perhaps one day inform scientific discoveries.

其中大约一半的电力需求将来自为生成式人工智能的特定需求而配备的的数据中心，像ChatGPT这类程序可以生成文本和图像、解决复杂的数学问题，也许有一天还能推动科学发现。

To power Al, energy and tech companies are turning to fossil fuels, which they regard as more reliable and readily available than wind, solar, or nuclear.

为了给人工智能提供动力，能源和科技公司正转向使用化石燃料，他们认为化石燃料比风能、太阳能或核能更可靠且更易获取。

Asked where the energy for data centers should come from, OpenAl CEO Sam Altman has repeatedly said, "Short-term: natural gas."

当被问及数据中心的能源应该从哪里来的时候，OpenAI首席执行官山姆·奥特曼多次表示:"短期内，用天然气。"

A Louisiana utility plans to build three natural-gas plants for a Meta data center that, upon completion, will be among the largest in this hemisphere.

路易斯安那州的一家公用事业公司计划为Meta 的一个数据中心建造三座天然气发电厂，该数据中心建成后将成为西半球最大的数据中心之一。

The lifespans of coal plants, too, are being extended to power new data centers.

为了给新的数据中心供电，一些燃煤电厂的使用寿命也在延长。

And the IEA estimates that data-center emissions could more than double by 2030-becoming one of the fastest-growing sources of greenhouse gases in the world.

国际能源署估计，到2030年，数据中心的排放量可能会增加一倍以上，成为全球增长最快的温室气体排放源之一。

The optimist's case is that, by then, advanced nuclear reactors will obviated many of the new fossil-fuel plants, and Al tools will have invented technologies that can solve the climate crisis.

乐观主义者认为，到那时，先进的核反应堆将使许多新建的化石燃料发电厂变得不再必要， 人工智能工具将发明出能够解决气候危机的技术。

That may well happen. But today, "'the market has converged on Add gas now, and then add nuclear later,"Jenkins said.

这很有可能会实现。但如今，"市场已达成共识，即现在增加天然气，然后再发展核能，"詹金斯说。

In other words, if natural-gas turbines seem to offer the most expedient path to an Al-enhanced future, then clean air may have to wait.

换句话说，如果天然气涡轮机似乎是通往人工智能赋能未来的最便捷途径，那么清洁空气可能就得等一等了。

Adata center is a planet of contradictions: heat without motion, shelter without bodies, light without sky.

数据中心是一个充满矛盾的地方:有热量却无运动，有遮蔽却无人体，有光亮却无天空。

"The lifeblood of the internet is essentially flowing through these sites," Jon Lin, the chief business officer at Equinix, one of the world's largest data-center companies, told me in an Equinix facility in Loudoun County, Virginia.

"互联网的命脉实际上在这些地方流淌，"全球最大的数据中心公司之一--易昆尼克斯的首席商务官乔恩·林在弗吉尼亚州劳登县的一处易昆尼克斯设施中告诉我。

Behind Lin, someone ina green hoodie fiddled with computer chips shelved in a row of humming, refrigerator-size cabinets on the data-center floor.

在林的身后，一个穿着绿色连帽衫的人正在摆弄数据中心地板上一排嗡嗡作响、冰箱大小的机柜里摆放的电脑芯片。

There were no windows, to keep the facility secure and to guard against the sun's heat. As we walked along a corridor of cabinets, motion-activated lights illuminated the way.

这里没有窗户，是为了保证设施安全并阻挡阳光带来的热量。当我们沿着机柜走廊行走时， 感应灯照亮了道路。

Farther ahead, only faint blue lights and blinking computer equipment pierced the darkness

再往前，只有微弱的蓝光和闪烁的电脑设备穿透黑暗。