技术英语精读 · 句式篇
📖 Generative AI Is an Engineering Disaster（生成式 AI 是一场工程灾难） 来源：The Atlantic — https://www.theatlantic.com/technology/2026/07/generative-ai-engineering-disaster/687901/
✍️ 句式拆解：
“Large language models such as ChatGPT and Claude are so resource-hungry that tech companies may be purchasing 70 percent of the world’s supply of high-end computer memory, causing a shortage.”
🔍 结构：
- 主句：
Large language models such as ChatGPT and Claude are so resource-hungry— 主语Large language models+such as举例插入 + 系表结构are resource-hungry（主系表，形容词短语作表语），前置程度副词so为后文铺垫。 - 结果状语从句：
that tech companies may be purchasing 70 percent of the world's supply of high-end computer memory—so...that...结构中的 that 从句，may be purchasing用进行时 + 情态动词表达「正在发生且尚在持续」的推断。 - 现在分词短语作结果状语：
causing a shortage— 悬挂在从句之后，用分词把前因进一步收紧成一个「短缺」的结果。
💡 亮点：
- 一句话装下「程度 → 因果 → 结果」三级递进：
so...that...本身自带因果关系，句末的现在分词causing a shortage又追加一层结果，整句像多米诺骨牌一样顺势倒下，读起来一气呵成。 - 具体数字让抽象变可感：
70 percent和high-end（高端内存）两个词，把「AI 很耗资源」这种空洞的说法钉死在可量化的事实上——这正是技术写作里「show, don’t tell」的体现。 - 分词收尾比另起一句更锋利：如果写成 “This causes a shortage.” 要另起一句、多一个主语；用
causing a shortage收尾，省掉冗余的this，节奏更紧凑、更有冲击力。
🧩 段落精读：
“As they scramble to keep their systems online, AI companies are making things expensive for the rest of us. Large language models such as ChatGPT and Claude are so resource-hungry that tech companies may be purchasing 70 percent of the world’s supply of high-end computer memory, causing a shortage. As a result, the prices of computer memory and storage are skyrocketing: Hard drives that I bought for my reporting two years ago for 800 when I checked two weeks ago, and are now out of stock.”
🔗 逻辑：
- 论点（第 1 句）：
As they scramble...用现在分词引导的时间状语开场，先给读者一个「手忙脚乱」的画面，再抛出核心主张——AI 公司正在让「其他人」的日子变贵（the rest of us划出对立阵营）。 - 论证（第 2 句）：给出原因链条——LLM 太耗资源 → 买走全球 70% 高端内存 → 造成短缺。用
so...that...+ 分词把整条因果链压缩进一句。 - 结论（第 3 句）：
As a result承接，落点到「价格飞涨」，随后用冒号 + 个人亲历数据（硬盘 800 → 断货）作为最具体、最可信的证据收束。
📌 连接词：As they scramble / As a result / （冒号引出例证）
🎯 模仿练习：用类似结构写一句技术表达
“Microservices such as payment and checkout are so chatty that a single user action may be triggering hundreds of internal RPC calls, driving up tail latency.”
（套用「主语 such as 举例 + so…that… 因果 + 现在分词结果」结构，把「架构低效」用一个可量化的因果链说清楚。）
📎 备注：本文是《大西洋月刊》“AI Watchdog” 系列调查，作者 Alex Reisner。开头段是新闻特写的经典「漏斗式」结构：先给画面（scramble），再给原因（resource-hungry → 70% 内存），最后落到具体可感的后果（硬盘价格翻倍、断货）。学这类技术评论时，重点看作者如何用情态动词（may be purchasing 表达推断而非断言）和具体数字（800）维持客观与可信度，而不是一味堆形容词。