🔮 The curious economics of a $6 AI agent #597|$6 AI agent 的奇特经济学|英文原文 + 中文翻译

🔮 The curious economics of a $6 AI agent #597|$6 AI agent 的奇特经济学|英文原文 + 中文翻译

Exponential View #597 从 RMA 每天 6 美元的成本审计写起,延伸到 AI 支出分化、数据中心的地方财政代价与一组值得继续追踪的短讯息;本文保留公开英文原文及对应中文翻译。

原文信息

  • 作者:Azeem Azhar、Marija Gavrilov
  • 发布时间:2026 年 8 月 16 日 13:39(北京时间)。1
  • 访问状态:公开可读。以下保留官方详情页可读取的文章正文、章节、引语、数据和来源链接;赞助商广告与站点页脚不属于文章正文,因此不纳入双语内容。2

English original

Good morning from London.
We are looking for an outstanding economist to join us as an AI Economy Research Fellow. If you know someone we should speak to, send them our way.
Cheers

The AI spend of your nightmares

Amazon spent some $1.8 million on a Claude project that ran for five months. A senior employee said: "It’s difficult to figure out how much anything [AI-related] costs". 2
We had a similar experience with R Mini Arnold, my OpenClaw agent. Its costs have run up as it has grown in complexity, and it takes time to switch it to progressively cheaper models. It becomes hard to keep track of exactly what is running efficiently and what isn’t. Nathan Warren called out an outrageous few days when the bot blew through $500 a day. 2
The subsequent tedious audit was worth it. Many processes were running older, higher-tier models, like Opus 4.5, which are more expensive than smaller, newer models like Sonnet 5 or a slew of open-weight models. The price war that has broken out between Anthropic and OpenAI in response to Chinese advances has helped even more. 2
Financial Times chart comparing daily spending on closed and open models per million inference tokens
Original chart: daily spending per million inference tokens for closed and open models. The page attributes the data to SiliconData and links the recent drop in closed-model prices to cheaper offerings from OpenAI. 2
By default, RMA now uses my token allowance on OpenAI Codex, which is already paid for in my $200-a-month subscription. It will fall back to DeepSeek v4 Flash or Pro if OpenAI is unavailable. For harder tasks, it can jump to 5.6 Sol, OpenAI’s top model, through the same subscription or Kimi K3 or Anthropic’s Fable (both of which I pay for by the token). The net result is $6 a day, lower than it has been for months. 2
The funny thing is that RMA is cheaper than it ever has been and yet more capable than ever. It plugs into the Manus API for some types of work; Claude Code and Codex for coding tasks; Prism (our internal research graph, which is more powerful than ever); and other resources like Elicit for academic papers. 2
It’s a microcosm of the big question in the industry. Has $494 a day just disappeared from genAI revenue? In some sense, yes, but that was really an anomaly. RMA had typically cost me $50 to $60 a day before it went wild. Even at $6 a day, it runs to $2k per year from me alone, which is reasonably substantial for someone who isn’t writing code. I expect spending to spike as I move back into book-writing terrain and need more research done. 2
I’m curious whether readers have had similar experiences.
See also:
US companies are continuing to spend on AI. Ramp reports that "in July, the top 1% of businesses spent a median $7,400 per employee on AI. The top 10% spent $650. The median firm spent $11.95 per employee." 2
Ramp chart showing monthly AI spend per employee for the top 1%, top 10%, and median business
Original Ramp chart: monthly AI spend per employee from January 2024 through July 2026, split across the top 1%, top 10%, and median business. 3

Who really pays for data centers?

The cost of building data centers spills over on neighboring towns — in some cases disproportionately so. Each additional data center within 25 miles raises a neighboring town’s bond spread by about 10 basis points. The effect fades with distance — roughly 4 basis points at 75 miles. Neighbors also borrow more. A town with the average number of nearby data centers issues about $34 million more in debt over the following year. The effect roughly doubles between six and thirty-six months. In states with tax breaks, the bill goes through schools. After a state adopts a data center incentive, state transfers to school districts fall by roughly $673 per student. 2
Explained simply, the towns nearby get the strain but no bargaining chips, so when they need to borrow money for a school or a road, lenders charge them more. And if the state gave the company a tax break to show up, the money the state didn’t collect comes out of the school budget. 2
Addressing these types of issues is going to become a priority as data centers become about as popular as lead in petrol. 2
Jasmine Sun’s extraordinary reporting from the frontlines of data center backlash is more than worth your time.
See also:
Aerial concept rendering of a green, regenerative data center integrated into a wooded landscape
Original "See also" image: a regenerative data center concept based on biomimicry, shown as a landscaped campus integrated with trees and water. 4

Short morsels to appear smart at dinner parties

Researchers built protein logic gates that can trigger cancer cells’ self-destruction.
A hidden prompt injection in a court filing asked AI to side with the plaintiff in case the court used LLMs.
Batteries deployed in 2026 could move more than one-third of new solar generation into the evening hours to replace fossil fuels. 2
Chart showing the share of new daily solar generation that new battery storage can shift into evening hours
Original chart: the share of new daily solar generation that new battery capacity can theoretically shift into the evening, rising to 34% in 2026 year-to-date. 2
💪🏼 France’s solar panel recycling sector hit scale in 2025, up 40% from 2024.
An AI designed 16 entirely new synthetic viruses from scratch that were better at killing E. coli than the natural counterparts.
👀 Anthropic is hiring a chip design team.
AI is a decent financial advisor, but it tends to be too patient and sensitive to your prompting.
👾 Fun game: run the AI lab from 2017 and race to recursive self-improvement takeoff.
Over 150 years and despite major electoral reforms, Congress has consistently been dominated by “fortunate sons”.
Thanks for reading!

中文翻译

早上好,伦敦来信。
我们正在寻找一位出色的经济学家,加入我们担任 AI Economy Research Fellow(AI 经济学研究员)。如果你认识我们应该联系的人,请把他们推荐给我们。2
祝好。

让人做噩梦的 AI 支出

Amazon 曾在一个运行了五个月、却一直没有被发现的 Claude 项目上花掉约 180 万美元。一名高级员工:「很难弄清楚任何与 AI 有关的东西究竟要花多少钱。」2
我的 OpenClaw agent,也就是 R Mini Arnold(RMA),也经历过类似的情况。随着它变得更复杂,成本一路上涨;要把它切换到更便宜的模型,也需要时间。于是,很难持续掌握究竟哪些任务运行得高效,哪些没有。Nathan Warren 指出,有几天这个机器人每天烧掉了 500 多美元,情况相当离谱。2
之后那场枯燥的审计证明值得一做。很多流程仍在使用较旧、级别较高的模型,例如 Opus 4.5;它们比更小、更新的 Sonnet 5,以及一系列开放权重模型更贵。Anthropic 和 OpenAI 因中国同行的进展而展开的价格战,又进一步压低了成本。2
RMA 现在默认使用我在 OpenAI Codex 上的 token 配额;这部分费用已经包含在我每月 200 美元的订阅里。OpenAI 不可用时,它会退回到 DeepSeek v4 Flash 或 Pro。遇到更难的任务,它可以通过同一订阅切换到 OpenAI 的顶级模型 5.6 Sol,也可以切换到 Kimi K3 或 Anthropic 的 Fable;后两者我按 token(模型处理文本时使用的计量单位)付费。结果是每天 6 美元,比过去几个月低。2
有意思的是,RMA 的成本比过去任何时候都低,能力却比过去任何时候都强。它会把 Manus API 接入某些类型的工作;编程任务则调用 Claude Code 和 Codex;它还接入 Prism,也就是作者团队内部的研究图谱,如今这个图谱比过去更强大;学术论文等工作则会调用 Elicit 等其他资源。2
这件小事折射出行业里的大问题:每天 494 美元是否就这样从生成式 AI 收入中消失了?某种意义上是的,但那本来就是异常值。RMA 在失控前通常每天花费 50 至 60 美元。即使现在每天只花 6 美元,单是作者一人使用,一年也要花约 2,000 美元;对于一个不写代码的人来说,这笔钱并不算小。作者预计,等自己重新进入写书阶段、需要更多研究时,支出还会猛增。2
作者想知道,读者是否也遇到过类似的情况。
另见:
美国企业仍在继续增加 AI 支出。Ramp 报告称:「7 月,支出最高的 1% 企业平均每名员工在 AI 上花费 7,400 美元;前 10% 企业为 650 美元;中位数企业为每名员工 11.95 美元。」2

谁真正为数据中心买单?

建设数据中心的成本会外溢到邻近城镇,而且在某些情况下,这种影响并不成比例。每增加一个方圆 25 英里内的数据中心,邻近城镇的债券利差就会上升约 10 个基点。距离拉开后,影响会减弱:到了 75 英里,大约还剩 4 个基点。邻近城镇的借款也会增加。附近数据中心数量处于平均水平的城镇,在接下来一年发行的债务大约会多出 3,400 万美元。这种影响在 6 至 36 个月之间大约会翻倍。在提供税收优惠的州,账单会通过学校系统体现出来:州政府采用数据中心激励政策后,拨给学区的转移支付每名学生大约减少 673 美元。2
简单说,附近城镇承受了压力,却没有多少谈判筹码。于是,当这些城镇需要为学校或道路借钱时,贷款方会收取更高利率;如果州政府为了吸引企业到来而给了税收优惠,政府少收的那部分钱就会从学校预算里扣掉。2
随着数据中心变得像含铅汽油一样不受欢迎,处理这类问题会成为优先事项。2
Jasmine Sun 从数据中心反弹前线发回的报道非常出色,值得一读。
另见:

晚宴上显得见多识广的短讯息

研究人员制造出了蛋白质逻辑门,可以触发癌细胞自我毁灭。
一份法院文件里藏着提示注入:如果法院使用大语言模型,它就要求 AI 站在原告一边。
2026 年部署的电池,可能把新建太阳能发电量中超过三分之一转移到傍晚时段,用来替代化石燃料。2
2025 年,法国太阳能电池板回收行业开始形成规模,较 2024 年增长 40%
AI 从头设计出了 16 种全新的合成病毒,它们杀死大肠杆菌的效果比天然病毒更好。
👀 Anthropic 正在招聘芯片设计团队。
AI 是一个还不错的财务顾问,但它往往过于有耐心,也太容易受提示方式影响
👾 一个有趣的游戏:从 2017 年的 AI 实验室起步,竞速走向递归式自我改进的起飞点。
150 多年来,尽管经历了多次选举改革,美国国会始终被「幸运之子」占据主导地位。
感谢阅读!

References

  1. 1
    Exponential View 官方 RSSexponentialview.co
  2. 2
  3. 3
  4. 4
    The regenerative data center discussioninnovatingoutloud.substack.com
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Exponential View 双语追踪

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