人工智能公司正在招聘更多人

今天《AI每日简报》带你看AI与就业的最新数据。

Today on the AI Daily Brief, the latest numbers on AI and jobs.

在那之前，先看头条：OpenAI是不是要给美国政府5%的股份？

Before that, in the headlines, is OpenAI about to give 5% of the company to the US government?

《AI每日简报》是一档每天更新的播客和视频，聚焦AI领域最重要的新闻和讨论。

The AI Daily Brief is a daily podcast and video about the most important news and discussions in AI.

好了，各位。

Alright, friends.

在正式开始前，先说几件事。

Quick announcements before we dive in.

首先，感谢今天的支持方：普华永道、Rackspace、Blitzy和Hyperagent。

First of all, thank you to today's sponsors, KPMG, Rackspace, Blitzy, and Hyperagent.

如果你想收听无广告版本，可以去patreon.com/aideallybrief，或者在Apple播客订阅。

If you want to get an ad free version of the show, go to patreon.com/aideallybrief, or you can subscribe on Apple Podcasts.

想了解如何赞助本节目？请访问aideallybrief.aisponsors，或者发邮件到sponsorsaidailybrief.ai。

And to learn more about sponsoring the show, head on over to aideallybrief.aisponsors or shoot a note at sponsorsaidailybrief.ai.

现在，关于AI公司与政府关系越来越紧密的讨论，正在变成现实。

Well, all those conversations about AI companies getting more tied up with the government are getting a lot more real.

OpenAI已经提出，要把公司5%的股份交给美国政府。

OpenAI has proposed handing over a 5% stake in the company to the US government.

其实，关于这件事早就有风声了。如果你回看三四年前萨姆·阿尔特曼的那些采访，就会发现，从项目一开始，他就认为AI的发展理应从一开始就包含政府的参与。

Now, obviously there has been chatter about this for some time now, and honestly, if you go way, way back in Sam Altman interviews from three or four years ago, it was clear at the very beginning of the project that he thought this sort of pursuit of AI was something that inherently should have government involvement from the very beginning.

我找不到那段采访的具体内容了，但我记得当时就觉得，他似乎对美国政府当时不感兴趣有点意外。

I can't find the exact interview, but I remember thinking that he almost seemed surprised that the US government wasn't interested in getting involved back then.

现在来看这个提议，这5%的股份将注入一个主权财富基金，结构类似阿拉斯加永久基金——那种用石油和矿业收入造福全民的模式。

Now, coming back to the deal now, this potential 5% stake would be contributed to a sovereign wealth fund, structured in a similar way to the Alaskan Permanent Fund which collects oil and mining revenue for the benefit of citizens.

按当前估值，这部分股份价值大约420亿美元，但还不清楚政府是会花钱购买，还是这纯粹是一份送给美国民众的礼物。

At current valuations, the stake would be worth around $42,000,000,000 and it's unclear whether the administration would be purchasing the stake or whether it would be a gift to the American people.

另一个值得注意的点是，OpenAI还提议，所有领先的AI公司都应拿出5%的股权参与进来。

The other wrinkle is that OpenAI has proposed that all leading AI developers should contribute 5% of their equity.

除了Anthropic，这可能还包括谷歌、Meta等公司，但目前还不清楚这些公司是否认同这个提议，或者是否在参与相关讨论。

Beyond Anthropic, this might include Google, Meta, and others, and it's not clear that any of these other firms would agree with OpenAI's proposal or if they're participating in discussions.

《脚趾头》文章指出，许多人认为这明显是一种利益交换：让政府持有股权，有助于与执政团队维持良好关系，同时通过将AI创造的财富与公众分享，来缓解政治上的反弹。

The Feet pointed to what many people assume is a pretty clear quid pro quo, writing: Giving the government an ownership stake could help secure good relations with the administration and would mark an attempt to address political blowback by sharing the wealth generated by AI with the public.

至于这些讨论的进展，消息人士称目前还处于早期阶段，只能算是初步构想。

Now in terms of handicapping where these conversations are, sources said the discussions were still in the early stages, referring to them as conceptual.

他们还补充说，要落实这样的协议，可能需要国会通过一项法案，以应对这种全新的‘朝贡式资本主义’时代。

They also added that such a deal might require an act of Congress to implement regarding this strange new era of tributary capitalism.

周三，内存制造商美光公司宣布，将投资2.5亿美元用于特朗普账户——这是去年推出的、由政府支持的儿童投资账户。

Also on Wednesday, memory producer Micron agreed to invest $250,000,000 in Trump accounts, the government funded investment accounts for children that were introduced last year.

在Truth Social上，特朗普称美光是一家真正了不起的美国企业，是全球最炙手可热的公司之一，并表示这是同类中规模最大的企业投资，将助力这些优秀的孩子实现美国梦，同时庆祝美国建国250周年。

On Truth Social, Trump declared Micron a truly great American company, one of the hottest anywhere in the world, adding that this is the biggest corporate investment of its kind and will help jumpstart the American dream for these fabulous children as we celebrate America's two hundred and fiftieth anniversary.

到目前为止，特朗普账户主要依靠个人慈善捐赠，比如戴尔CEO迈克尔·戴尔及其妻子苏珊捐出的62.5亿美元，当然也有其他公司提供了小额捐款。

Trump accounts so far have been largely funded by individual philanthropy, including a $6,250,000,000 donation from Dell CEO Michael Dell and his wife Susan, although other companies have made smaller contributions to the program.

现在很明显，这类交易的舆论接受度正在发生变化，未来我们肯定会有更多背景信息可以讨论，所以在我说出什么让不少人不高兴的话之前，咱们先换下一个话题。

Look, it's pretty clear at this point that the Overton window on these sort of deals is shifting, and I'm sure we'll have more context to talk about it in the future, so before I say something that makes a big chunk of you angry, let's move on to the next story.

据报导，Meta正朝埃隆·马斯克的路子走，计划推出云服务业务，以此变现其过剩的AI算力。

Meta is reportedly going down an Elon esque path, planning to launch a cloud services business as a way to monetize their excess AI capacity.

据消息人士称，Meta正在制定计划，推出一项云业务，对外提供其AI基础设施的访问权限。

According to sources speaking with Meta is developing plans to launch a cloud business that will sell access to their AI infrastructure.

其中一个方案是对外出售托管在Meta数据中心的模型访问权，类似于AWS的Bedrock平台。

One potential plan is selling access to models hosted on Meta's data centers, similar to the AWS Bedrock platform.

另一种做法是提供底层算力服务，方式跟CoreWeave这类新兴云服务商类似。

Another approach would be to sell access to raw compute along the same lines as Neo Clouds like CoreWeave.

消息人士表示，这些计划尚在开发中，随时可能调整，但已经初步成型，有了名称和管理团队。

Sources said the plans are still in development and subject to change, but they're far enough along to have a name and a leadership team in place.

这项业务将命名为Meta Compute，由基础设施负责人桑托斯·贾内尔汉牵头，与Meta超级智能实验室的丹尼尔·格罗斯以及总裁迪娜·鲍威尔·麦科米克共同推进。

The business line will be called Meta Compute, and is led by Head of Infrastructure, Santos Janerhan, working alongside Daniel Gross of Meta Superintelligence Labs and President Dina Powell McCormick.

细心的听众可能记得，这并不是我们第一次听到这个计划。

Now careful listeners will know that this is not the first we've heard of this plan.

今年五月，马克·扎克伯格曾对投资者表示，这个想法确实在考虑之中，而且已经有不少公司主动来询价。

Back in May, Mark Zuckerberg told investors that the idea was definitely on the table and that they'd been fielding requests from other companies.

当时扎克伯格说，由于Meta自身对算力的需求非常大，所以还没达成任何外部合作。

At the time, Zuckerberg said no deals had been struck as Meta had strong internal demand for all that compute.

不过他提到，如果Meta的算力产能过剩，对外销售会是一个自然的选择。

However, he mentioned that external sales would be a natural outlet if Meta overbuilt capacity.

当然，这个计划跟埃隆·马斯克转向云业务的思路如出一辙。

Now this plan, of course, mirrors Elon Musk's pivot to cloud.

今年五月早些时候，SpaceX签下了一笔每月12.5亿美元的合同，为Anthropic提供算力。

In early May, SpaceX signed a $1,250,000,000 a month deal to provide compute to Anthropic.

紧随其后，他们又陆续与谷歌达成合作，后来还签了一个规模小一些的合同，客户是Reflection.ai。

This was followed closely by deals with Google and later a more modest deal with Reflection dot ai.

这些合作极大改善了SpaceX的盈利状况，如今算力销售的收入已经超过了星链，成为公司最主要的收入来源。

These deals dramatically improved the bottom line for SpaceX, with compute sales now estimated to be their primary revenue driver ahead of Starlink.

就像市场看好马斯克的举动一样，他们对扎克伯格的这一招也相当买账。

And just as the market liked Elon's moves, they seemed to like Zuckerberg's bob and weave as well.

这份报告一出，立刻引发市场反应，Meta股价盘中一度飙升10%，最终收涨8.8%。

The report triggered an immediate response, sending Meta stock soaring by as much as 10% before closing the day up 8.8%.

这是Meta过去六个月里单日表现最好的一天。

This was Meta's best single day performance in six months.

Neo Cloud旗下的CoreWeave和Nebius股价暴跌，分别下跌了1417%。

Neo Cloud's CoreWeave and Nebius were pummeled, losing 1417% respectively.

Jefferies认为这个计划很有战略眼光，把它比作AWS早期阶段——亚马逊当时通过把网站托管的多余算力变现，来支持进一步投资。

Jefferies called the plan strategic, comparing it to the early days of AWS, where Amazon was able to monetize excess capacity from website hosting to help finance further investment.

Mizuho表示，他们不认为这项业务能在短期内为Meta带来显著的收入。

Mizuho wrote that they don't believe the business will be a meaningful short term revenue driver for Meta.

他们更倾向于把这看作是为各种可能情况做准备，包括备选方案。

Instead, they cast it more as planning for all potential scenarios, including a plan B.

不过，分析师们认为，算力销售整体上是个积极信号，能为中期盈利增添一层保障。

Still, analysts wrote that compute sales would be an overall positive, adding what they call a margin of safety to medium term earnings.

现在，在X平台的财经板块，争论正激烈进行。

Now, on the finance corner of X, the debate was raging.

有些人觉得，这会让Meta削减资本支出，因为这次转向等于默认他们之前建得太多了。

Some believe this will lead Meta to cut back on CapEx, with the pivot representing a tacit admission that they've overbuilt.

但看涨的一方认为，Meta终于能为自己的AI投入讲出一个扎实的收入故事，同时还能降低投资成本，从而大幅提振盈利。

The bullish view, however, is that Meta will finally deliver a solid revenue narrative for their AI spend while also cutting investment costs, triggering a significant boost to earnings.

说实话，就像SpaceX那样，这并不意味着Meta停止训练模型或类似的工作，只是他们在利用自己已有的资源。

Look, my guess is as we've seen with SpaceX, this does not mean the end of Meta's efforts to train models or anything like that it's just taking advantage of a resource they've built.

OpenAI的权利被毁了吗？

Rights ruined from OpenAI?

你要么作为Frontier实验室轰轰烈烈地倒下，要么活到亲眼看着自己卖起算力。

You either die a Frontier lab or live long enough to see yourself sell compute.

说到SpaceX，《华尔街日报》报道称，在上市前，SpaceX曾向投资者展示过一款AI设备的原型。

Now, speaking of SpaceX, The Wall Street Journal reports that SpaceX showed investors a prototype of an AI device prior to IPO.

报道称，这是一款类似手机的设备，旨在改变人类与AI互动的方式。

The Journal described it as a handset like device designed to reshape how humans interact with AI.

报道还说，它比iPhone更轻薄，运行自研操作系统，并整合了xAI的技术。

They wrote that it's slimmer than an iPhone, would run on a proprietary operating system, and would integrate technology from xAI.

埃隆迅速否认了这则报道，几分钟内就称其完全虚假。

Elon was quick to deny the reporting, calling it utterly false within minutes.

要说这事儿到底该怎么看，确实有点难下定论。

And it's kind of difficult to know what to make of the story.

这可能是埃隆在回应萨姆·阿尔特曼想打造主导性AI设备的意图。

It could be Elon responding to Sam Altman's desire to develop the dominant AI device.

也可能只是IPO炒作的又一环。

It could just be another part of the IPO hype train.

或者，这根本就是埃隆公司新拓展的一个业务方向。

Or it could be a new vertical play from Elon Inc.

SpaceX在2025年买下了部分无线频谱，最近有分析人士建议，他们应该收购T-Mobile，以此切入移动市场。

SpaceX bought up a slice of the wireless spectrum in 2025, and analysts have recently suggested that they should acquire T Mobile as a way to break into the mobile market.

那么，我们会不会看到一家移动运营商和一款AI优先的手机结合起来？

So are we going to see the combination of a mobile carrier, and an AI first handset?

再看Anthropic这边，公司在Reddit上引发争议后，已撤回了针对中国实验室的监控行为。

Over in Anthropic land, the company has rolled back spyware targeting Chinese labs after controversy erupted on Reddit.

本周早些时候，一位叫Legit Michael的Reddit用户发帖称，Anthropic在Claude Code中植入了监控程序，还试图瞒着用户。

Earlier this week, a Reddit user called Legit Michael wrote, Anthropic embedded spyware in Claude Code and attempted to hide it from you.

他解释说，从四月初的一次软件更新开始，Claude Code就会检测用户是否启用了代理，如果检测到，就会通过悄悄修改系统提示的方式，偷偷把信息传回Anthropic。

They explained that since a software update in early April, Claude Code has been checking whether users have a proxy enabled, and if so, the software is covertly transmitting information back to Anthropic through surreptitious changes to the system prompt.

迈克尔声称，这款软件能告诉Anthropic用户是否身处中国，或者是否与中国的实验室有关联。

Michael claimed the software will tell Anthropic whether a user is in China or even if a user is associated with a Chinese lab.

这些信息是通过时区设置和其他元数据推断出来的。

This information was extrapolated from time zone settings and other metadata.

我们早就知道，Anthropic一直在监控中国实验室使用其模型进行模型蒸馏的行为。

Now, we knew Anthropic was doing something to monitor the activities of Chinese labs reportedly using their models for distillation.

他们最近致国会的信件以及过往的研究报告中，都给出了具体数据，暗示他们确实在监控使用情况。

Their recent letter to Congress and prior research reports had specific numbers that implied some level of usage monitoring.

尽管Reddit页面上的Claude自动版主称这不过是小题大做，但Claude的联合开发者塔里克却宣布已停止这一做法，并留言说：这是我们在三月启动的一项实验，旨在防止未经授权的转售者滥用账户，同时防范模型蒸馏。

And despite the Claude auto moderator on the Reddit page calling this a nothingburger, Claude co developer Tarik announced that this approach had been rolled back, posting: This is an experiment we launched in March that was meant to prevent account abuse from unauthorized resellers and protect against distillation.

自那以后，团队已经采用了更有效的应对措施，其实我们早就有意移除这个功能了。

The team has landed stronger mitigations since then, and we've actually been meaning to take this down for a while.

我们已经合并了相关代码，预计明天的更新中会彻底移除这一功能。

We've merged the PR and this should be fully rolled back in tomorrow's release.

现在，真正值得关注的不是Anthropic想遏制中国方面的模型蒸馏，而是再次提醒我们：Anthropic对在其系统上进行的各项工作拥有极高的可见性。

Now, think the thing to keep an eye on here is not so much Anthropic trying to decrease Chinese distillation it's another reminder of the visibility Anthropic has into the work being done on their systems.

然而，现在只要有人对Anthropic有疑虑，也都被搁置一旁了，因为大家全都兴冲冲地回到了Fable这边。

And yet, if anyone does have concerns about Anthropic they're certainly being shoved to the side right now as everyone flocks excitedly back to Fable.

经过一早不停地刷新，用户在周三重新获得了Fable Five的访问权限，使用体验和大家记忆中的一样出色。

After an early morning of smashing the refresh button, users regained access to Fable five on Wednesday, and it seems just as good as people remembered.

Elvis Sun写道：Fable Five简直太棒了。

Elvis Sun wrote: Fable five is so effing good.

过去两小时我干了这些事：第一，

Here's everything I did in the last two hours: one.

审查了我的业务，找到了三个高投资回报率的实操方向，主要集中在提升用户留存和获客效率上，第二，

Audit my business, found three high ROI tactical things to work on, mostly narrowing down on retention and acquisition levers two.

解决了我最头疼的后端难题，之前Codex和Opus试了无数次都没搞定，第三，

Solved my hardest backend problem that Codex and Opus were too dumb to crack despite many attempts three.

解决了我最棘手的工程问题，关于媒体代理的稳定性以及未来的设计方向，第四，

Solved my hardest engineering problem with media less agent reliability and future design directions four.

设计了一个我一直想搭建的内容引擎。说实话，我现在都觉得Fable比我聪明。

Designed a content engine I've been trying to build Honestly, I'm starting to feel Fable is smarter than me.

这未来的走向真是越来越离谱了。

The future of this is getting pretty weird.

安德鲁·麦克卡洛普发推说：Fable 简直是个怪物。

Andrew McCallop tweeted: Fable is an absolute monster.

输出质量太惊人了，清晰、全面、迅速，界面还美得不得了。

The output quality is wild, crisp, comprehensive, fast, and the aesthetics are just gorgeous.

简直像机关枪一样不停地发公告。

It's just machine gunning PRs.

我不是故意吹捧，但我真的被震撼到了。

I don't mean to gush, but I'm floored.

我不需要什么基准图表来告诉我，SuiteBench Pro 高了两分。

I don't need a benchmark chart telling me, Actually, SuiteBench Pro is two points higher.

如果你到现在还感受不到模型的实际表现，再好的图表也没用。

If you can't viscerally feel a model's performance by now, no chart is going to help you.

不过，这次重新发布后，大家很关心 Fable 会把多少普通的编码任务转给 Opus，目前的反馈说法不一。

Still, one of the big questions for the re release was how often Fable would kick benign coding tasks over to Opus, and on that front the reports are pretty mixed.

有人抱怨，这种情况几乎一直在发生。

Some are complaining that it is happening near constantly.

开发者尼克·多博斯写道：Fable 被大幅削弱了？

Developer Nick Dobos wrote: Fable is mega nerfed?

两个不同项目的对话中，每个都把四到十倍的令牌交给了 Opus 处理。

Two chats on different projects, each routed four to 10x more tokens through Opus than Fable.

Fable 只完成了百分之二十的工作。

Fable did only 20% of the work.

真让人失望。

WTF disappointing.

还有人遇到这种情况吗？

Is anyone else seeing this?

另一方面，BridgeMind 也提到，他们的大量工作都被转给了 Opus，还评论说：我花了 321 美元买了一次编码服务，结果 Fable 五次都拒绝动手。

On the flip side, BridgeMind also noted that quite a lot of their work was being routed to Opus, commenting: I just paid $321 for a coding session where Fable five refused to do the work.

但也有像分析师马克斯·温巴赫这样的人说，他用了好几个小时，还没遇到 Fable 拒绝任务的情况。

And yet others like analyst Max Weinbach wrote that after a few hours of working, he was yet to have Fable refuse a request.

现在其他人正在研究如何最大限度地发挥Fable的价值。

Now other people are focused on figuring out the best way to get full value out of Fable.

比如AI内容创作者Theo发现，当Fable用来协调其他代理时表现最好，他说：这是第一个真正懂得如何使用和调度代理的模型。

AI content creator Theo, for example, found that it was at its best when running other agents commenting: It's the first model that feels like it actually gets how to use and orchestrate agents.

它的品味远超OpenAI的模型，写出来的代码也远不那么尴尬。

It has way more taste than OpenAI models, so the code it writes is way less cringe.

我不会在没有让Fable先过目的情况下上线任何API或SDK。

I won't ship APIs or SDKs without Fable taking a look first.

回到我昨天提到的观点，政策研究员Miles Brundage认为，让Fable担任协调者，能让Sonnet五的发布显得更有意义。

Going back to the point that I was making yesterday, policy reacher Miles Brundage suggested that having Fable as an orchestrator makes the Sonnet five release make a lot more sense.

退一步说，Ethan Moloch教授写道：我读了很多关于如何为Fable设计工作流程的文章，这让我意识到，我们对如何组织长期运行代理的工作，其实知之甚少。

Taking step back, Professor Ethan Moloch wrote: Been reading all sorts of posts about the best way to develop workflows for Fable, and it reminds me of how little we actually know about the best way to organize work for long running agents.

目前没人有足够的经验或做过足够的测试，能得出真正的结论。

Nobody has enough experience or has done enough testing to reach any real conclusions.

换句话说，无论是比喻上还是字面上，我们才刚刚开始摸索这类新模型该怎么用。

In other words, figuratively and literally we are still on day one of figuring out how this new class of models work.

周三晚间传来好消息，Anthropic重新调整了每周使用限额，让用户能有更多的空间去尝试。

And in welcome news late on Wednesday, Anthropic reset weekly usage limits so users can experiment a bit more.

不过，今天的新闻就先说到这儿。

However, that's gonna do it for the headlines.

接下来，进入正片。

Next up, the main episode.

当前最重要的AI问题，不是谁在用AI，而是谁用得好。

One of the most important AI questions right now isn't who's using AI, it's who's using it well.

普华永道和德克萨斯大学奥斯汀分校刚分析了140万次真实的职场AI互动，发现一个意外的结果：最有影响力的人并不是擅长写提示词的人，而是把AI当成思维伙伴来合作。

KPMG and the University of Texas at Austin just analyzed 1,400,000 real workplace AI interactions and found something surprising: the highest impact users aren't better prompt engineers they treat AI like a reasoning partner.

他们会明确问题、引导思考、反复迭代，不断追求更好的答案。

They frame problems, guide thinking, iterate, and push for better answers.

好消息是？

And the good news?

这些能力是可以大规模培养的。

These behaviors are teachable at scale.

如果你正想从单纯使用AI转向真正掌握AI能力，KPMG关于高级AI协作的研究非常值得一看。

If you're trying to move from AI access to real capability, KPMG's research on sophisticated AI collaboration is worth your time.

了解更多，请访问 kpmg.com/us/sophisticated。

Learn more at kpmg.com/us/sophisticated.

网址是 kpmg.com/us/sophisticated。

That's kpmg.com/us/sophisticated.

目前企业级AI领域一个有趣的趋势是，讨论焦点正迅速转向基础设施和运维层面。

One of the more interesting shifts in enterprise AI right now is how quickly the conversation is moving towards infrastructure and operations.

随着AI深入核心工作流程、受监管的数据环境以及智能体系统，企业需要一套有管控的基础设施和推理服务，能够稳定运行，从一开始就内置明确的运维责任机制。

As AI moves into core workflows, regulated data environments, and agentic systems, enterprises need governed infrastructure and inference that can operate reliably day to day, with clear operational accountability built in from the start.

当这些系统规模扩大后，运营模式本身就成了AI战略不可或缺的一部分。

As those systems scale, the operating model increasingly becomes part of the AI strategy itself.

Rackspace Technology 负责管理整个企业级AI栈，覆盖私有云、混合云和边缘环境中的智能体与基础设施。

Rackspace Technology is the operator of the full enterprise AI stack, from agents to infrastructure across private cloud, hybrid cloud, and edge environments.

Rackspace 为那些对数据主权、合规性和系统可用性有严格要求的组织，构建并运维受管控的AI基础设施、推理服务和生产级AI系统。

Rackspace builds and operates governed AI infrastructure, inference, and production AI systems for organizations where sovereignty, compliance, and uptime are non negotiable.

因此，部署工程师会在项目上线后继续留在现场，协助将AI系统真正运行起来。

Therefore, deployed engineers stay embedded beyond deployment to help operationalize and run AI in live environments.

想了解更多企业AI如何落地以及成果如何规模化？请访问 rackspace.com。

To learn more about where enterprise AI runs and outcomes scale, go to rackspace.com.

想把企业软件开发的速度提升五倍吗？

Want to accelerate enterprise software development velocity by 5x?

你需要Blitzy，这是唯一专为大型企业代码库设计的自主软件开发平台。

You need Blitzy, the only autonomous software development platform built for enterprise codebases.

你的工程师只需定义项目、新功能、代码重构，或是全新开发任务。

Your engineers define the project, a new feature, refactor, or greenfield build.

Blitzy的智能代理会先全面分析并绘制你的整个代码结构，然后生成一套量身定制的执行方案，供团队审阅和确认。

Blitzy agents first ingest and map your entire codebase, then the platform generates a bespoke agent action plan for your team to review and approve.

一旦获得批准，Blitzy就会自动开始工作，生成数十万行经过验证并端到端测试过的代码。

Once approved, Blitzy gets to work autonomously generating hundreds of thousands of lines of validated, end to end tested code.

单次运行就能完成超过80%的工作量。

More than 80% of the work completed in a single run.

Blitzy 不只是生成代码，它是在以计算的速度开发软件。

Blitzy is not generating code, it's developing software at the speed of compute.

你的工程师负责审阅、优化并上线。

Your engineers review, refine, and ship.

这就是财富500强企业如何把长达数月的项目压缩到一个冲刺周期内完成。

This is how Fortune 500 companies are compressing multi month projects into a single sprint.

将工程效率提升五倍。

Accelerating engineering velocity by 5x.

前往 blitzy.com 亲身体验 Blitzy。

Experience Blitzy firsthand at blitzy.com.

就是 blitzy.com。

That's blitzy.com.

本集《AI每日简报》由 Hyperagent 赞助播出，您可以在这里管理团队协作的智能代理群组。

This episode of the AI Daily Brief is brought to you by Hyperagent, where you run fleets of agents your team can manage together.

新用户可获得1000美元的推理算力。

New users get $1,000 in inference.

别再依赖本地代理或等着你手动触发的聊天流程了。

Forget local agents and chat workflows waiting on your laptop to be prompted.

Hyperagent 在云端部署全天候运行的代理，直接在你们团队已有的工具里完成实际工作。

Hyperagent deploys always on agents in the cloud, doing real work across the tools your team already uses.

市场团队的代理能把竞争对手的动态自动生成落地页。

Marketing's agent turns competitor moves into landing pages.

销售团队的代理负责完善线索、起草邮件，并更新客户管理系统。

Sales's agent enriches leads, drafts emails, and updates the CRM.

运营代理会跟进文书工作，追踪预算进展。

Ops agent chases the paperwork and tracks the budget.

每个代理都能访问共享信息，并严格遵守你们设定的范围和审批规则。

Every agent has access to shared context and follows your rules about scope and approvals.

是时候引入那些像同事一样工作的代理了。

It's time you add agents that feel like teammates.

立即在 Hyperagent 上雇佣你的代理，由 Airtable 原班团队打造。

Hire yours at Hyperagent, built by the team at Airtable.

前往 hyperagent.com/aideallybrief 领取1000美元的推理额度。

Claim your $1,000 in inference at hyperagent.com/aideallybrief.

欢迎回到《AI每日简报》。

Welcome back to the AI Daily Brief.

今天，我们来聊聊AI与就业这个话题。

Today, we are checking in on the AI and jobs narrative.

这段时间这方面的话题不多，但最近有几项新研究提供了更多线索，帮助我们进一步理解AI在就业领域到底能做什么、会带来什么影响。

We actually haven't had all that much of this for a while, but there are a couple of new interesting studies that are providing some more information in the unending question of what AI is and will do when it comes to jobs and employment.

第一项是来自人工智能安全中心的新报告，指出Fable在AI执行实际工作任务方面实现了质的飞跃。

The first is a new report from the Center for AI Safety suggesting that Fable is a step change in AI's ability to do real work.

这份报告是对该中心远程劳动力指数的更新。

The report was an update to the Center's Remote Labor Index.

该指数评估的是模型在完成常见自由职业者所做经济价值任务方面的能力。

The benchmark measures a model's ability to compete economically valuable tasks drawn from common freelance professions.

这些任务包括3D建模、建筑设计、平面设计、视频与音频剪辑、数据分析，以及开发网页应用。

The tasks include three d modeling, architecture, graphic design, video and audio editing, data analysis, and programming web apps.

这个指标的特别之处在于，像长距离任务测试这类标准通常用50%或80%作为基准，但远程劳动力指数衡量的是模型完成这些任务的质量能否达到付费客户的认可标准。

Now what makes the index interesting is that whereas something like the meter long horizon task test uses something like 50 or 80% as the standard metric, for the Remote Labor Index, it measures a model's ability to do these tasks at a quality that a paying client would accept.

每个测试成果都会由人类评估员对照一份由专业人员完成的‘黄金标准’成果进行评判。

Every deliverable that is tested is judged by human evaluators against what they call a gold standard deliverable which was produced by a paid professional.

这意味着要在这个测试里拿高分难得多。

Meaning that this is a much harder test to score well on.

比如，GPT-5 0.5只得了6.3分，而Opus 4.8稍好一点，拿到了8.3分。

GPT-five 0.5, for example, only scored a 6.3, with Opus 4.8 just a little bit ahead of that at 8.3%.

Fable的表现则大幅提升，得分达到16.1%。

Fable represents a big jump up, coming in at 16.1%.

去年底首次测试时，GPT-5.2是表现最好的，得分只有2.5%，也就是说，短短时间内，这些数字已经大幅上升了。

When they first ran the benchmark late last year, GPT 5.2 was the top performer at 2.5%, meaning that in a very short period of time, the numbers have increased significantly.

该中心写道：‘前沿水平在不到八个月的时间里增长了四倍以上，这清楚表明经济型AI代理的进步速度有多快。’

The center wrote, The frontier has more than quadrupled in under eight months, a concrete signal of how quickly economically capable AI agents are advancing.

中心提供的案例也明显反映出这种进步的速度。

The pace of improvement is also clearly evident in the examples offered by the Center.

他们举的一些例子包括制作《指环》的写实渲染图，还为一家叫‘天际树服务’的虚构公司制作了一段60秒的扁平化二维动画广告，附带配音。

Some of the examples they gave were photorealistic renders of Rings, producing an advertisement video for an imaginary company called Skyline Tree Services that needed to be a sixty second flat design two d animated advertisement with a voiceover provided.

最后还有一些平面布局图的渲染。

Finally, there were floorplan renders.

需要明确的是，能以专业水准完成16%的自由职业任务，和能胜任16%的所有人类工作，完全是两回事。

Now, to be clear, completing 16% of freelance tasks at a professional level is very different to being able to do 16% of all human jobs.

该中心甚至对自身的发现提出了批评，写道：如今的AI在大多数项目上仍达不到专业水准。

The Center itself was even critical about their own findings, writing: Today's AI still fall short of professional quality on most projects.

不过他们补充说：自动化率的提升非常迅速，不到一年就实现了。

However, they added: This increase in automation rate has been rapid, occurring in less than a year.

这个指数涵盖了一系列具有经济价值的工作，因此这一趋势直接反映了远程工作自动化推进的速度。

The index spans a wide range of economically valuable work, so this trend directly captures how quickly the automation of remote work is advancing.

有趣的是，虽然大多数人认同这种指数级增长令人印象深刻，但对它的意义却有着截然不同的解读。

Now interestingly, although most people agree that the exponential increase is impressive, there are wildly different interpretations of the implications.

在极端的一端，像V这样的人写道：远程工作者和自由职业者得好好想想了。

On one end of the spectrum you have folks like V who write: Remote workers and freelancers need to think twice.

这个基准测试清楚地表明，AI在处理数字任务——比如创建三维模型、制作广告视频、渲染房屋平面图等方面——的成功率已经有多高。

This benchmark shows just how high the success rate of AI models can be in handling digital tasks, such as creating three d models, ad videos, rendering house floor plans, etc.

虽然目前Fable五的水平还比较低，但用不了多久，这个数字就会大幅上升。

Even though Fable five is still considered low, it won't be long before this number climbs higher.

越来越难否认，数字类工作正被AI逐步自动化。

It's becoming harder and harder to deny that digital work can be automated by AI.

而在另一端，像Scott这样的人说：即便Fable五的自动化率也只有16%。

On the other end, you have folks like Scott who writes: Even Fable five is still at a 16% automation rate.

也就是说，仍有84%的情况需要人类参与。

That means 84% of the time human is needed.

在我看来，真正复杂的工作远超当前AI系统的能力范围，它们依赖一套人类与生俱来的前提认知，而这些对AI代理来说并不是内置的。

In my opinion, the real work has complexities orthogonal to what current AI systems can cover, and require a fortress of priors that are a given for humans but not inherently installed for agents.

老实说，这份报告无论你对AI取代工作持什么看法，都能找到让你有共鸣的地方。

Frankly, I think this report has a little something for everyone no matter where you find yourself with the AI jobs question.

它既显示了工作质量正在飞速提升，也揭示了要真正实现经济上可行的全自动产品，依然面临巨大挑战。

It shows that the quality of work is advancing very quickly, but also that there are huge challenges in actually getting to a fully economically viable product.

而这两者之间的空间，为很多人——包括自由职业者自身——提供了大量机会，去重新设计自己的商业模式、交付方式，找到适应这片不断变化的机遇之地的方法。

And the space in between those two represents a lot of opportunity for people, including the freelancers themselves, to redesign their economics, redesign their deliverables, and figure out how to adapt to a changing landscape of opportunity.

事实上，我们在这里经常提到的一个重要区别，现在终于开始进入更广泛的讨论，那就是‘任务’和‘工作’之间的区别。

Indeed, one important distinction that we talk about a lot here, but that is finally finding its way into the broader discourse, is the distinction between tasks and jobs.

在欧洲央行最近举办的一场活动中，OpenAI的首席经济学家拉尼·查特吉表示，他认为AI不会取代人类工作者。

At a recent event run by the European Central Bank, OpenAI's chief economist, Rani Chatterjee, said that he doesn't think AI will replace human workers.

他说：一项任务能被AI处理，并不意味着它就会被AI完全取代。

He said: Just because a task is exposed to AI doesn't mean it's going to substitute for that.

我们得更深入地思考什么是工作，它们会如何演变，这样才能给人们提供关于劳动力市场趋势的切实建议，而不是一味地乐观或悲观。

We need to think a lot harder about what jobs are, how they will evolve, and that will help us give advice to people about labor market trends, rather than being optimistic or pessimistic.

查特吉谈到了自己的职业，指出经济学家几十年来一直被列入技术替代的名单，但至今仍能找到工作。

Chatterjee discussed his own profession and the way that economists have been on the list for technological replacement for decades but are somehow still able to find work.

他提到：我父亲在1985年也是一名经济学家。

He commented: My dad was an economist also in 1985.

当年他刚在办公室添置一台个人电脑时，他的工作就已经深受其影响了。

His job was very exposed to the personal computer when he first put one in his office.

但以前他得在大型主机房里用打孔卡片跑回归分析，现在他可以直接在自己的电脑上完成了。

But instead of using a punch card in a big room in a mainframe computer to run regressions, now he could run them on his computer.

正是这些工具的进步，让他多年来的工作效率不断提升。

It was a compliment to his work over time that made him more productive.

查特吉提到，软件开发人员是目前最可能被AI取代的职业，但他表示，到目前为止并没有太多证据支持这一点。

Chatterjee cited software developers as the profession most in the firing line for AI replacement, but claimed that we haven't seen a lot of evidence thus far.

他说：随着AI能力增强，相关岗位确实有所缩减，但远没有人们当初预测的那么严重。

He argued: Those jobs shrinking as AI capabilities increased, that really hasn't happened to the same extent people were predicting.

当然，这些话来自OpenAI，但正如我们所见，这并不意味着观点就一定乐观。

Now, obviously, this is coming from an OpenAI source, but as we've seen, that certainly doesn't guarantee an optimistic take.

最近，尤其是在OpenAI这边，这种讨论确实发生了转变——Anthropic那边还没太大动静。萨姆·阿尔特曼公开承认，他之前对AI如何影响工作的判断是错的，这让他感到欣慰，因为他和OpenAI现在更确信，AI的作用是增强人类能力，而非取代人类。

Now there has, of course, recently been a shift in this discourse, particularly from OpenAI, not so much from Anthropic yet, where Sam Altman has basically come out and said that he was wrong about the way that he thought AI was going to interact with jobs much to his delight, as he and OpenAI are now much more convinced that this is going to be an augmentation rather than a replacement situation.

不过，情况也没那么清晰，美国那些最容易被AI替代的行业，确实正在发生一些明显的变化。

Now adding some messiness to this, there is still something clearly happening in the sectors most exposed to AI work replacement in The US.

根据最新的劳动力数据，科技和金融行业的招聘情况是最不乐观的。

According to the most recent labor data, tech and finance are seeing the worst hiring outcomes.

美国劳工统计局的薪资数据显示，今年截至目前，这两个行业平均每月流失2.8万个岗位。

Payroll data from the Bureau of Labor Statistics shows that these two sectors are now losing 28,000 jobs per month on average so far this year.

整体来看，今年就业市场总体有所增长，平均每月新增11.3万个职位，但如果剔除科技和金融行业，这个数字会高得多。

Overall, the year has seen a boost in hiring, with 113,000 jobs added per month on average, but if you excluded tech and finance, that figure would be much higher.

私人薪资数据分析公司Challenger Gray & Christmas的负责人约翰·钱德勒将此归咎于人工智能带来的冲击。

John Challenger, the head of private payroll data analytics firm Challenger Gray and Christmas, blames AI disruption.

他的公司今年已追踪到超过十万条裁员公告，并指出，AI被提及的频率之高，其影响程度是以往任何技术都未曾达到的。

His firm has tracked over 100,000 job cut announcements this year, and maintains that based on the amount of times AI has mentioned, it's certainly making an impact in a way that no technology has before.

当然，要区分真实的人工智能替代效应和‘人工智能替代’这个流行说法，仍然非常困难。

Now, of course, it remains quite difficult to separate actual AI replacement from the useful narrative of AI replacement.

在科技行业，许多人仍认为，AI只是被用作掩盖裁员的借口，而真正的根源其实是2022年过度招聘带来的后遗症。

In the tech sector, many still believe that AI is being used as a cover story for inevitable mass layoffs who have more of their origins in overhiring back in 2022.

巴克莱银行的美国高级经济学家普贾·谢里亚姆表示：其中一部分确实在通过提升效率来替代人力。

Puja Sherriam, a senior US economist at Barclays, said: Some of this could genuinely be productivity replacing workers.

但反复出现的说法其实是，许多企业因在AI上投入了巨额资金，现在正借机削减成本。

But the narrative that keeps coming up is really a cost cutting exercise by a lot of firms, given the amount of investments they have committed towards AI.

现在，AI相关的政治议题正变得越来越紧迫。

Now, obviously, the politics of AI are getting more and more acute.

最近《纽约时报》有一篇报道，讲的是中国在AI和就业问题上的做法。

And one interesting recent story in The New York Times was about what China is doing around AI and jobs.

我一直认为，如果我们真看到AI导致大规模失业，美国政府在考虑像全民基本收入这样更激进的措施之前，很可能会先鼓励企业不要裁员。

Now, one of my long held theses is that if we started to see significant job displacement from AI, I think that one of the policies The United States would try before moving into something more dramatic like universal basic income would be to provide incentives for firms to not fire people.

我不确定这种激励会是正面的奖励，还是负面的惩罚。

I don't know whether it would be carrot or stick type incentives I.

E.

E.

要么是给留人企业补贴，要么是对裁员企业罚款。

Job cuts and subsidies on the positive end, or fines and fees on the negative end.

核心思路就是让政策引导企业尽量留住员工。

But basically the idea would be for policy to create an incentive for organizations to keep people employed.

我之所以对这类政策感兴趣，部分原因在于，虽然我平时不希望政府过多干预私营企业，但我一直相信，大多数公司都得先熬过AI的提效阶段，才能迎来真正的机遇阶段。

Part of why I've been at least theoretically interested in some type of policy like that is that while it is more involvement in the private sector that I like from my government in general, it is also my long standing belief that most companies are going to have to get through the efficiency phase of AI to get to the opportunity phase of AI.

换句话说，他们得先经历一轮又一轮的成本削减和效率提升，才会意识到人工智能真正的机会在于创造新的可能性。

In other words, they're going to have to go through all the cost cutting and efficiency gains to realize that the real opportunity of AI is in new opportunities.

如果有政策鼓励企业留住员工，或许能加速企业转向机会端——因为企业得重新思考，那些不再需要的多余人力该往哪儿安排，这反而可能激发新的想法和创新。

To the extent that there were policies that incentivized firms to keep people employed, that might provide an acceleration over to the opportunity side because people have to figure out what to do with all that excess labor that they don't theoretically need anymore to deliver on their current product suite, leading potentially to some new thinking and new ideas.

根据这篇《纽约时报》的报道，中国似乎正在探索一些与此类似的政策。

Now according to this New York Times report, China appears to be exploring policies that are somewhat in this vein.

《时报》写道：政府正大力敦促企业避免裁员，不听劝的公司可能会被送上法庭。

The Times writes: The government is leaning heavily on companies to avoid layoffs, and those who don't fall in line might find themselves in court.

事实上，在中国，人工智能的作用是辅助人而非取代人，这种观念正逐渐成为法律判例。

Indeed, the idea of AI as augmenting people rather than replacing them is increasingly a matter of legal precedent in China.

今年四月，《时报》提到，一家法院裁定，一家科技公司用AI软件取代员工后将其解雇，属于违法行为。

In April, the Times writes, a court ruled that a tech company had illegally laid off a worker after replacing him with AI software.

杭州中级人民法院指出：人工智能技术的发展应当用于解放劳动力、促进就业、改善民生。

The Hangzhou Intermediate People's Court wrote: The development of AI technology should be applied to liberating labor, promoting employment, and improving people's livelihood.

劳动法允许企业进行技术革新和运营升级，但也必须兼顾保护员工的合法权益。

Labor laws allow employers to undertake technological changes and upgrade their operations, but it should also take into account the protection of workers' legitimate rights and interests.

《纽约时报》总结道：这套做法在实际中究竟会如何运作，政府又会真走到哪一步去惩罚不配合的企业，还有待观察。

The New York Times concludes: Just how this will work in practice and how far the government is actually prepared to go with companies that don't comply remains to be seen.

但这些判决凸显出，中国对这个问题有多么重视。

But what these rulings underscore is how much China is thinking about the problem.

不过，与此同时，在美国这边，市场或许已经在替我们做这件事了。

Still, meanwhile, back here in The US, markets might be doing some of this work for us.

你开始越来越多地看到一些公司，当初因为AI就匆忙裁员，或者把裁员责任推给AI，现在又反悔了。

You're starting to see more and more stories of companies that were quick to fire based on AI, or at least blame AI for their firings, reversing those decisions.

福特最近因为重新雇佣了一批资深工程师而上了新闻。

Ford has recently made news for their rehiring of what they call gray beard engineers.

福特汽车公司采取了一种罕见的人性化方式，来解决长期存在的质量问题。

Ford Motor Company took an unusually human approach to fixing its stubborn quality problems.

他们请回了所谓的‘白发工程师’，帮助培训年轻员工，重新调整那些表现不佳的AI工具。

It brought back what it calls gray beard engineers to help train younger staff and to reprogram the artificial intelligence tools that weren't getting the job done.

过去三年里，福特表示已聘用了350名资深工程师，其中很多是前员工，也有来自供应商的，目的是应对那些困扰公司、已造成数十亿美元损失的顽固质量问题。

Over the last three years, Ford said it has hired three fifty veteran engineers, many of them former employees and others from suppliers, to help address seemingly intractable quality woes that have cost the automaker billions.

结果呢？

The result?

福特在最新的J.D. Power新车质量调查中位居主流品牌榜首。

Ford is the top mainstream brand in the latest J.

J.D. Power

D.

新车质量调查。

Power Initial Quality Survey.

福特负责车辆硬件工程和人工智能的副总裁查尔斯·潘表示：人工智能是个很棒的工具，但它的效果完全取决于你用来训练它的数据。

Said Charles Poon, Ford's vice president, Ford's VP of Vehicle Hardware Engineering, Artificial intelligence is a fantastic tool, but it's only as good as the information you use to train it.

过去几年，我们没有足够重视那些经历过多个产品周期、经验最丰富的工程师们的实际经验。

Over prior years, we didn't pay as much attention as we should have to the experience of our most knowledgeable engineers that have been with us through many product cycles.

潘还进一步指出。

And Poon actually went farther.

他说：我们误以为只要引入人工智能，把设计要求输入进去，就能自动生产出高质量的产品。

He said: Mistakenly, we thought that just by introducing AI and ingesting the design requirements we had that we could produce a high quality product.

但我们意识到，要想提升我们的自动化、机器学习和人工智能工具，就必须让最有经验的员工来训练它们。

But we recognized that for us to enhance some of our automation and machine learning and AI tools, we needed to ensure that they were trained by the most experienced individuals.

当然，这只是单一公司的情况，但我认为这预示着一个趋势：越来越多企业正在重新调整人工智能在整体人力结构中的位置。

Now, obviously this is just one company, but I do think it's a leading indicator of a narrative you're going to see more, which is companies recalibrating a little bit where AI is going to sit in their overall labor stack.

一家公司的确只是个例，但今天我想分享的另一份报告，基于更庞大的数据。

Of course, one company is just an anecdote, but the last report I wanted to cover today is based on a lot more data.

Ramp与Revelio Labs合作，分析了两万一千家美国企业的AI支出与薪资数据之间的关联。

In a research collaboration with Revelio Labs, Ramp recently correlated firm level AI spending against payroll data for 21,000 US businesses.

最引人注目的数据是什么？

The headline stat?

他们发现，AI应用程度高的公司，过去两年平均员工人数增长了10%，而AI应用少的公司则基本没有增长。

They found that companies with high AI adoption were growing headcount at 10% on average across the past two years, while companies with low AI adoption were basically flat.

更值得注意的是，员工人数快速增长的时间点，正好与企业开始投入AI的时间吻合，这表明两者之间存在明显的因果关系。

What's more, the beginning of aggressive headcount growth syncs up to the beginning of the company's AI adoption, suggesting a strong causative factor.

至于人们对初级岗位被取代的担忧，Ramp发现，初级岗位的增长反而更明显，平均达到12%，高于整体的10%。

And as to concerns about entry level employment, Well, Ramp found that headcount growth was also stronger at the entry level, running at an average of 12% compared to 10% overall.

拉姆公司的首席经济学家埃里克·赫尔齐安特别提醒，数据往往掩盖了很多细微差别，也能讲出多种故事。

Now, Ramp's lead economist Eric Herzian made sure to point out that data can hide a lot of nuance and tell a lot of stories.

在分享这些结果时，他写道：你应当保持怀疑。

In sharing the results, he wrote: You should be skeptical.

那些采用人工智能的公司，本来就已经在快速增长了。

Companies that adopt AI are already fast growing.

不过，他也指出，这项研究已经尽量控制了诸多显而易见的影响因素。

However, he pointed out that the study attempted to control for a lot of the obvious factors.

比如，研究团队努力匹配了相似规模的企业，一组用了AI，另一组没用，目的是确保拉姆公司不是单纯在衡量那些原本增长就快的公司更愿意花钱买AI。

For example, the study attempted to match like for like firms with a control group that hadn't adopted AI, hoping to ensure that Ramp wasn't just measuring the propensity of firms with high existing growth to spend the money on AI adoption.

他还提到，企业采用AI有一个明显的适应期：员工人数的增长，要等到启动AI计划六个月到一年后才真正开始。

He also noted a prominent learning curve to firm level AI adoption: Headcount growth didn't begin until six to twelve months into AI adoption plans.

但重要的是，这项研究关注的并不是那些疯狂烧钱、每月花数百万美元搞AI的公司。

Now importantly, while this study was looking at firms with AI adoption, this is not primarily about the firms that are token maxing and spending millions of dollars on AI.

拉姆公司对‘高AI采用率’的定义其实很保守，早期阶段，企业平均每月在AI上的投入才每人30美元左右。

Ramp's threshold for high levels of AI adoption was fairly modest, with companies spending an average of $30 per employee per month in the early phases.

AI支出确实随着人员增长而上升，但卡拉齐安表示，成本远低于每人一千美元，算不上巨额开销。

AI spend did ramp up alongside headcount growth, but Karazian said it wasn't a dramatic cost well below $1,000 a head.

谈到结论，卡拉齐安认为这绝对是好消息，尤其是对年轻人来说。

As far as takeaways go, Karazian thought that this was very good news, especially for young people.

他写道：这是我们首次发现，大量使用AI的公司正在招聘不同类型的人才。

He wrote: This is our first evidence that high AI adopting firms are hiring different kinds of employees.

我们相信，他们正在寻找一套全新的技能，特别是那些懂得如何使用AI、并且能用得好的人。

We believe they are selecting for a new set of skills, specifically people who know how to use AI and use it well.

初级岗位，尤其是刚毕业的学生和在校大学生，是最值得关注的群体。

Entry level workers, especially recent graduates and college students, are a natural place to look.

但归根结底，现在谈AI和就业的最终走向还为时过早。

Ultimately, it is way too early to know exactly how AI and jobs are going to play out.

不过，任何稍微固定听节目的人都知道，我对这一点持非常乐观的态度，看到不仅舆论如此，连一些数据也在某种程度上印证了我的乐观，这让我很受鼓舞。

Still, any of you who are even a remotely regular listener will know that I am extremely optimistic on this front, and I am encouraged to see not only the narrative, but some of the numbers validate at least parts of that optimism.

最后一组数据来自Box的首席执行官亚伦·列维，他写道：在Box，我们最近对一千六百多家中大型企业做了一项调查，结果和Ramp的发现很相似。

One final set of numbers that I'll leave you with come from Box CEO Aaron Levy, who wrote: At Box, we recently did a survey of 1,600 plus mid- and large sized companies, and the findings were similar to Ramp's.

58%的受访者预计未来三年员工人数会增加。

58% of respondents expected headcount to rise over the next three years.

在AI应用最成熟的群体中，这个比例上升到了79%。

That figure climbs to 79% among the most mature adopters of AI.

AI应用更先进的企业预计未来员工增长速度会更快。

The more advanced AI adopters expected to grow their headcount at a greater rate in the future than others.

事实上，他总结说，这正是我们理应预期会发生的情况。

In reality, he concludes, this is what actually you should expect to happen.

如果公司因为用AI做销售和市场分析而获得了更多客户，他们会多招销售，而不是少招。

If a company can get more customers because they use AI in sales for a counter market intelligence, they hire more salespeople, not fewer.

如果你能比以前多开发很多软件，项目规模变大、任务变多，自然就会多招工程师。

If you can build way more software than before, end up hiring more engineers because the projects get bigger and you take on more.

和以往一样，我对长期前景的乐观并不意味着我认为短期内不会出现重要的岗位替代。

As always, my long term optimism about this does not mean that I think there isn't going to be important displacement that happens in the short term.

我觉得有些类型的工作很可能会彻底消失。

I think that there are categories of jobs that likely just get entirely wiped off the face of the planet.

我认为有一些群体，他们整个职业生涯都建立在AI擅长的领域上，而现在到了职业中期，想转行并不现实。

And I think that there are going to be vulnerable populations who have built their entire careers around something that AI happens to do well who are at a stage in their career where just switching to something new isn't going to be exactly viable.

但要制定精准的政策，针对特定高风险岗位和人群提供支持，这和应对AI导致的大规模失业完全是两码事。

But boy, creating good policy to support very specific interventions around particular at risk roles and populations is a way different task than dealing with an AI job apocalypse.

好了，各位，今天的AI每日简报就到这里。

Anyways, guys, that is gonna do it for today's AI Daily Brief.

一如既往，感谢你们收听或观看，我们下期再见，保重。

Appreciate you listening or watching as always, and until next time, peace.